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precinct analysis

Precinct analysis: Congress, part 2

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020
State Senate district comparisons
State House districts 2020, part 1
State House districts 2020, part 2
Median districts
State House district changes by demography
State House district changes by county
SBOE
Congress, part 1

I didn’t want to leave the Congressional district analysis without looking at some downballot races, since I mentioned them in the first part. To keep this simple, I’m just going to compare 2020 to 2012, to give a bookends look at things. I’ve got the Senate race (there was no Senate race in 2016, another reason to skip that year), the Railroad Commissioner race, and the Supreme Court race with Nathan Hecht.


Dist   Hegar   Cornyn  Hegar% Cornyn%
=====================================
01    79,626  217,942  26.30%  71.90%
02   157,925  180,504  45.50%  52.00%
03   188,092  224,921  44.50%  53.20%
04    79,672  256,262  23.20%  74.70%
05   101,483  173,929  36.00%  61.70%
06   155,022  178,305  45.30%  52.10%
07   154,670  152,741  49.20%  48.60%
08   100,868  275,150  26.20%  71.50%
09   168,796   54,801  73.50%  23.90%
10   191,097  215,665  45.90%  51.80%
11    54,619  232,946  18.60%  79.20%
12   129,679  228,676  35.20%  62.00%
13    50,271  217,949  18.30%  79.40%
14   117,954  185,119  38.00%  59.60%
15   110,141  111,211  48.10%  48.60%
16   148,484   73,923  63.10%  31.40%
17   127,560  174,677  41.00%  56.20%
18   178,680   60,111  72.60%  24.40%
19    65,163  194,783  24.40%  73.00%
20   163,219   99,791  60.10%  36.80%
21   203,090  242,567  44.50%  53.10%
22   188,906  214,386  45.80%  52.00%
23   135,518  150,254  46.10%  51.10%
24   165,218  171,828  47.80%  49.70%
25   165,657  222,422  41.70%  56.00%
26   168,527  256,618  38.60%  58.70%
27    98,760  169,539  35.90%  61.70%
28   118,063  107,547  50.60%  46.10%
29    99,415   51,044  64.00%  32.80%
30   203,821   53,551  77.00%  20.20%
31   178,949  206,577  45.20%  52.20%
32   170,654  165,157  49.60%  48.00%
33   111,620   41,936  70.40%  26.50%
34   101,691   93,313  50.60%  46.50%
35   175,861   87,121  64.50%  32.00%
36    78,544  218,377  25.90%  71.90%


Dist   Casta   Wright  Casta% Wright%
=====================================
01    75,893  217,287  25.20%  72.20%
02   153,630  176,484  44.90%  51.60%
03   181,303  220,004  43.70%  53.00%
04    76,281  254,688  22.50%  75.00%
05   100,275  171,307  35.80%  61.20%
06   151,372  176,517  44.60%  52.00%
07   149,853  149,114  48.50%  48.20%
08    97,062  271,212  25.60%  71.40%
09   168,747   51,862  74.10%  22.80%
10   184,189  211,020  44.90%  51.40%
11    53,303  230,719  18.30%  79.10%
12   123,767  227,786  33.90%  62.50%
13    47,748  215,948  17.60%  79.50%
14   114,873  182,101  37.40%  59.40%
15   113,540  103,715  50.50%  46.10%
16   144,436   75,345  62.30%  32.50%
17   121,338  171,677  39.70%  56.20%
18   177,020   57,783  72.60%  23.70%
19    62,123  192,844  23.60%  73.20%
20   165,617   93,296  61.40%  34.60%
21   197,266  234,785  43.90%  52.30%
22   184,521  209,495  45.50%  51.60%
23   136,789  144,156  47.10%  49.60%
24   160,511  167,885  47.10%  49.20%
25   157,323  218,711  40.30%  56.00%
26   160,007  251,763  37.30%  58.70%
27    97,797  165,135  36.00%  60.80%
28   121,898  100,306  52.90%  43.60%
29   102,354   46,954  66.30%  30.40%
30   204,615   50,268  77.60%  19.10%
31   169,256  203,981  43.40%  52.30%
32   168,807  160,201  49.60%  47.10%
33   111,727   40,264  71.10%  25.60%
34   105,427   86,391  53.30%  43.70%
35   173,994   82,414  64.70%  30.60%
36    76,511  216,585  25.40%  72.00%


Dist Meachum    HechtMeachum%  Hecht%
=====================================
01    79,995  215,240  26.60%  71.50%
02   154,787  179,887  45.20%  52.50%
03   185,076  220,662  44.60%  53.10%
04    79,667  253,119  23.50%  74.50%
05   101,813  172,186  36.40%  61.50%
06   155,372  175,793  45.80%  51.80%
07   149,348  154,058  48.20%  49.70%
08    99,434  272,277  26.20%  71.60%
09   170,611   52,213  75.00%  22.90%
10   188,253  212,284  45.80%  51.60%
11    56,146  228,708  19.30%  78.50%
12   129,478  225,206  35.50%  61.80%
13    51,303  214,434  18.90%  78.90%
14   118,324  181,521  38.50%  59.10%
15   115,046  103,787  51.20%  46.20%
16   149,828   73,267  64.20%  31.40%
17   126,952  170,378  41.50%  55.70%
18   179,178   58,684  73.50%  24.10%
19    66,333  190,784  25.20%  72.30%
20   166,733   93,546  62.00%  34.80%
21   200,216  237,189  44.50%  52.80%
22   188,187  210,138  46.30%  51.70%
23   138,391  143,522  47.70%  49.50%
24   164,386  168,747  48.10%  49.40%
25   162,591  218,370  41.60%  55.80%
26   168,621  251,426  39.10%  58.30%
27   100,675  164,273  37.10%  60.50%
28   122,263   99,666  53.50%  43.60%
29   101,662   48,349  66.00%  31.40%
30   207,327   50,760  78.50%  19.20%
31   172,531  198,717  45.00%  51.80%
32   169,325  163,993  49.60%  48.10%
33   112,876   40,077  71.80%  25.50%
34   104,142   84,361  53.80%  43.50%
35   177,097   82,098  66.00%  30.60%
36    78,170  216,153  26.00%  71.90%

	
Dist  Sadler     Cruz Sadler%   Cruz%
=====================================
01    76,441  169,490  30.55%  67.74%
02    84,949  155,605  34.35%  62.92%
03    88,929  168,511  33.52%  63.52%
04    69,154  174,833  27.60%  69.79%
05    73,712  130,916  35.14%  62.41%
06   100,573  143,297  40.12%  57.16%
07    89,471  141,393  37.73%  59.63%
08    55,146  190,627  21.88%  75.64%
09   140,231   40,235  76.35%  21.91%
10   103,526  154,293  38.76%  57.76%
11    45,258  175,607  19.93%  77.32%
12    77,255  162,670  31.22%  65.74%
13    43,022  175,896  19.12%  78.17%
14    97,493  142,172  39.77%  58.00%
15    79,486   62,277  54.55%  42.74%
16    91,289   56,636  59.66%  37.02%
17    82,118  130,507  37.31%  59.30%
18   145,099   45,871  74.37%  23.51%
19    52,070  155,195  24.37%  72.65%
20   106,970   73,209  57.47%  39.33%
21   115,768  181,094  37.32%  58.38%
22    90,475  157,006  35.74%  62.02%
23    86,229   98,379  45.28%  51.66%
24    90,672  147,419  36.88%  59.97%
25   101,059  155,304  37.79%  58.07%
26    77,304  173,933  29.66%  66.74%
27    81,169  125,913  38.11%  59.12%
28    90,481   68,096  55.14%  41.50%
29    71,504   38,959  63.27%  34.47%
30   168,805   44,782  77.58%  20.58%
31    89,486  138,886  37.46%  58.13%
32   103,610  141,469  41.03%  56.03%
33    81,568   33,956  68.96%  28.71%
34    79,622   60,126  55.23%  41.71%
35   101,470   56,450  61.37%  34.14%
36    63,070  168,072  26.66%  71.04%


Dist   Henry    Cradd  Henry%  Cradd%
=====================================
01    67,992  170,189  27.73%  69.41%	
02    78,359  155,155  32.30%  63.95%	
03    80,078  167,247  31.02%  64.80%	
04    64,908  170,969  26.53%  69.87%	
05    69,401  129,245  33.75%  62.86%	
06    96,386  141,220  39.03%  57.18%	
07    80,266  143,409  34.60%  61.81%	
08    51,716  188,005  20.83%  75.74%	
09   138,893   39,120  76.19%  21.46%	
10    94,282  153,321  36.00%  58.54%	
11    44,310  171,250  19.77%  76.42%	
12    72,582  160,255  29.85%  65.90%	
13    42,402  171,310  19.15%  77.36%	
14    96,221  137,169  39.91%  56.89%	
15    81,120   56,697  56.51%  39.50%	
16    90,256   49,563  60.67%  33.31%	
17    77,899  126,329  36.20%  58.70%	
18   142,749   44,416  73.97%  23.01%	
19    50,735  150,643  24.17%  71.76%	
20   102,998   72,019  56.19%  39.29%	
21   103,442  181,345  34.03%  59.66%	
22    85,869  155,271  34.42%  62.24%	
23    85,204   92,976  45.63%  49.79%	
24    83,119  146,534  34.52%  60.85%	
25    92,074  153,051  35.16%  58.44%	
26    71,177  172,026  27.82%  67.24%	
27    79,313  120,235  38.16%  57.84%	
28    94,545   59,311  58.53%  36.72%	
29    72,681   35,059  65.14%  31.42%	
30   166,852   43,206  77.43%  20.05%	
31    82,045  136,810  35.10%  58.52%	
32    92,896  143,313  37.69%  58.15%	
33    81,885   30,941  69.96%  26.43%	
34    82,924   50,769  58.78%  35.99%	
35    97,431   55,398  59.79%  34.00%	
36    62,309  161,751  26.88%  69.79%


Dist   Petty    Hecht  Petty%  Hecht%
=====================================
01    71,467  163,306  29.37%  67.11%
02    84,472  147,576  35.05%  61.23%
03    85,368  161,072  33.16%  62.56%
04    68,551  163,313  28.26%  67.31%
05    72,559  123,012  35.59%  60.34%
06   101,437  133,905  41.29%  54.51%
07    86,596  135,562  37.63%  58.90%
08    55,495  181,582  22.47%  73.53%
09   141,509   36,555  77.91%  20.13%
10   100,998  146,370  38.76%  56.17%
11    47,657  163,669  21.49%  73.81%
12    76,959  153,820  31.79%  63.53%
13    46,099  162,448  21.01%  74.02%
14   100,566  131,348  41.86%  54.67%
15    83,009   53,962  58.27%  37.88%
16    93,997   46,517  63.26%  31.31%
17    82,692  120,206  38.64%  56.16%
18   145,329   41,564  75.56%  21.61%
19    54,458  143,426  26.12%  68.80%
20   109,712   66,441  59.93%  36.29%
21   112,633  172,657  37.12%  56.90%
22    91,252  149,320  36.71%  60.06%
23    90,554   87,003  48.74%  46.83%
24    89,019  139,910  37.09%  58.29%
25    98,663  145,549  37.88%  55.87%
26    76,953  165,377  30.12%  64.73%
27    83,222  114,299  40.30%  55.36%
28    97,850   55,633  60.91%  34.63%
29    74,382   33,124  66.97%  29.82%
30   169,799   39,877  78.96%  18.54%
31    89,084  128,420  38.24%  55.13%
32    97,997  137,060  39.92%  55.84%
33    84,095   28,859  72.01%  24.71%
34    85,950   47,645  61.27%  33.96%
35   102,646   51,225  63.03%  31.46%
36    66,497  154,956  28.85%  67.24%

There are two things that jump out at me when I look over these numbers. The first actually has to do with the statewide totals. Joe Biden cut the deficit at the Presidential level nearly in half from 2012 – where Barack Obama trailed Mitt Romney by 1.26 million votes, Biden trailed Trump by 631K. The gains were not as dramatic in the Senate and RRC races, but there was progress. Ted Cruz beat Paul Sadler by 1.246 million votes, while John Cornyn beat MJ Hegar by 1.074 million; for RRC, Christi Craddock topped Dale Henry by 1.279 million and Jim Wright bested Chrysta Castaneda by 1.039 million. Not nearly as much progress, but we’re going in the right direction. At the judicial level, however, that progress wasn’t there. Nathan Hecht, then running for Supreme Court Place 6, won in 2012 by 908K votes, and he won in 2020 by 934K. That’s a little misleading, because in the only other contested statewide judicial race in 2012, Sharon Keller beat Keith Hampton for CCA by 1.094 million votes, and five out of the seven Dems running in 2020 did better than that. Still, the point remains, the judicial races were our weakest spot. If we really want to turn Texas blue, we will need more of an investment in these races as well.

One explanation for this is that Dem statewide judicial candidates didn’t do as well in at least some of the trending-blue places. Hegar and Castaneda both carried CD07, but only two of the Dem judicial candidates did, Staci Williams and Tina Clinton. All of them carried CD32, but none of them by more than two points, while Biden took it by ten; to be fair, Hegar won it by less than two, and Castaneda had the best performance with a 2.6 point margin. Maybe these folks were motivated by Trump more than anything else, and they didn’t see the judicial races in those terms. I have noted before that Dem judicial candidates did better in CD07 in 2018 than in 2020, so maybe the higher turnout included more less-likely Republicans than one might have expected. Or maybe these folks are in the process of becoming Democratic, but aren’t all the way there yet. Just something to think about.

On the flip side of that, while Hegar underperformed in the three closer-than-expected Latino Democratic districts CD15, CD28, and CD34 – Cornyn actually carried CD15 by a smidge – everyone else did better, and indeed outperformed Biden in those districts. The judicial candidates all carried CDs 28 and 34 by at least six points, with most in the 8-9 range and a couple topping ten, and all but two carried CD15 by a wider margin that Biden’s 1.9 points, with them in the three-to-five range. Still a disconcerting step back from 2012 and 2016, but at least for CDs 28 and 34 it’s still a reasonably comfortable margin. Maye this is the mirror image of the results in CDs 07 and 32, where the Presidential race was the main motivator and people were more likely to fall back on old patterns elsewhere. As with CDs 07 and 32, we’ll have to see where those trends go from here.

After however many entries in this series, I don’t have a whole lot more to say. We’ll be getting new maps soon, and we’ll have a better idea of what the immediate future looks like. I think the last two decades has shown us that there’s only so far out in the future that redistricting will be predictive in such a dynamic and growing state as Texas, but we have seen the winds shift more than once, so let’s not get too comfortable with any one idea. Whatever we get in this session is not etched in stone, and we still have some hope for federal legislation. For now, this is what we’re up against.

Precinct analysis: Congress, part 1

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020
State Senate district comparisons
State House districts 2020, part 1
State House districts 2020, part 2
Median districts
State House district changes by demography
State House district changes by county
SBOE

In addition to the SBOE data, we finally have 2020 election results for the Congressional districts as well. With the redistricting special session about to start, let’s look at where things were in the last election.


Dist   Biden    Trump  Biden%  Trump%
=====================================
01    83,221  218,689   27.2%   71.5%
02   170,430  174,980   48.6%   49.9%
03   209,859  214,359   48.6%   49.6%
04    84,582  258,314   24.3%   74.3%
05   107,494  172,395   37.9%   60.8%
06   164,746  175,101   47.8%   50.8%
07   170,060  143,176   53.6%   45.1%
08   109,291  274,224   28.1%   70.5%
09   178,908   54,944   75.7%   23.2%
10   203,937  210,734   48.4%   50.0%
11    58,585  235,797   19.7%   79.1%
12   140,683  224,490   37.9%   60.4%
13    54,001  219,885   19.4%   79.1%
14   124,630  185,961   39.5%   59.0%
15   119,785  115,317   50.4%   48.5%
16   160,809   77,473   66.4%   32.0%
17   137,632  172,338   43.5%   54.5%
18   189,823   57,669   75.7%   23.0%
19    71,238  195,512   26.3%   72.2%
20   177,167   96,672   63.7%   34.7%
21   220,439  232,935   47.8%   50.5%
22   206,114  210,011   48.8%   49.7%
23   146,619  151,914   48.5%   50.2%
24   180,609  161,671   51.9%   46.5%
25   177,801  216,143   44.3%   53.9%
26   185,956  248,196   42.1%   56.2%
27   104,511  170,800   37.4%   61.1%
28   125,628  115,109   51.6%   47.2%
29   106,229   52,937   65.9%   32.9%
30   212,373   50,270   79.8%   18.9%
31   191,113  202,934   47.4%   50.3%
32   187,919  151,944   54.4%   44.0%
33   117,340   41,209   73.0%   25.6%
34   106,837   98,533   51.5%   47.5%
35   188,138   84,796   67.6%   30.5%
36    82,872  221,600   26.9%   71.9%

Joe Biden carried 14 of the 36 Congressional districts, the 13 that Democratic candidates won plus CD24. He came close in a lot of others – within two points in CDs 02, 03, 10, 22, and 23, and within five in CDs 06, 21, and 31 – but the Congressional map gets the award for most effecting gerrymandering, as the Presidential results most closely matched the number of districts won.

Generally speaking, Biden did a little worse than Beto in 2018, which isn’t a big surprise given that Beto lost by two and a half points while Biden lost by five and a half. Among the competitive districts, Biden topped Beto in CDs 03 (48.6 to 47.9), 07 (53.6 to 53.3), and 24 (51.9 to 51.6), and fell short elsewhere. He lost the most ground compared to Beto in the Latino districts, which is a subject we have covered in much detail. I only focused on the closer districts in my 2018 analysis, but you can see the full 2018 data here. Biden’s numbers are far more comparable to Hillary Clinton’s in 2016 – I’ll get into that in more detail in a subsequent post.

As we have also seen elsewhere, Biden’s underperformance in the Latino districts – specifically, CDs 15, 28, and 34 – was generally not replicated by other candidates down the ballot. Again, I’ll get to this in more detail later, but with the exception of John Cornyn nipping MJ Hegar in CD15, Democrats other than Biden generally carried those districts by five to ten points, still closer than in 2016 but not as dire looking as they were at the top. Interestingly, where Biden really overperformed compared to the rest of the Democratic ticket was with the judicial races – Republicans carried all but one of the statewide judicial races in CD07, for example. We discussed that way back when in the earlier analyses, but it’s been awhile so this is a reminder. That’s also not too surprising given the wider spread in the judicial races than the Presidential race, and it’s also a place where one can be optimistic (we still have room to grow!) or pessimistic (we’re farther away than we thought!) as one sees fit.

I don’t have a lot more to say here that I haven’t already said in one or more ways before. The main thing to think about is that redistricting is necessarily different for the Congressional map simply because there will be two more districts. (We should think about adding legislative districts, especially Senate districts, but that’s a whole ‘nother thing.) I have to assume that Republicans will try to give themselves two more districts, one way or another, but I suppose it’s possible they could just seek to hold serve, if going for the gusto means cutting it too close in too many places. I figure we’ll see a starter map pretty soon, and from there it will be a matter of what alternate realities get proposed and by whom. For sure, the future plaintiffs in redistricting litigation will have their own maps to show off.

For comparison, as I did in other posts, here are the Congressional numbers from 2016 and 2012:


Dist Clinton    TrumpClinton%  Trump%
=====================================
1     66,389  189,596  25.09%  71.67%
2    119,659  145,530  42.75%  52.00%
3    129,384  174,561  39.90%  53.83%
4     60,799  210,448  21.63%  74.86%
5     79,759  145,846  34.18%  62.50%
6    115,272  148,945  41.62%  53.78%
7    124,722  121,204  48.16%  46.81%
8     70,520  214,567  23.64%  71.93%
9    151,559   34,447  79.14%  17.99%
10   135,967  164,817  42.82%  51.90%
11    47,470  193,619  19.01%  77.55%
12    92,549  177,939  32.47%  62.43%
13    40,237  190,779  16.78%  79.54%
14   101,228  153,191  38.29%  57.95%
15   104,454   73,689  56.21%  39.66%
16   130,784   52,334  67.21%  26.89%
17    96,155  139,411  38.43%  55.72%
18   157,117   41,011  76.22%  19.90%
19    53,512  165,280  23.31%  71.99%
20   132,453   74,479  60.21%  33.86%
21   152,515  188,277  42.05%  51.91%
22   135,525  159,717  43.91%  51.75%
23   115,133  107,058  49.38%  45.92%
24   122,878  140,129  44.28%  50.50%
25   125,947  172,462  39.94%  54.69%
26   109,530  194,032  34.01%  60.25%
27    85,589  140,787  36.36%  59.81%
28   109,973   72,479  57.81%  38.10%
29    95,027   34,011  70.95%  25.39%
30   174,528   40,333  79.08%  18.27%
31   117,181  153,823  40.07%  52.60%
32   134,895  129,701  48.44%  46.58%
33    94,513   30,787  72.78%  23.71%
34   101,704   64,716  59.07%  37.59%
35   128,482   61,139  63.59%  30.26%
36    64,217  183,144  25.13%  71.68%

Dist   Obama   Romney  Obama% Romney%
=====================================
01    69,857  181,833  27.47%  71.49%
02    88,751  157,094  35.55%  62.93%
03    93,290  175,383  34.13%  64.16%
04    63,521  189,455  24.79%  73.95%
05    73,085  137,239  34.35%  64.49%
06   103,444  146,985  40.72%  57.87%
07    92,499  143,631  38.57%  59.89%
08    55,271  195,735  21.74%  76.97%
09   145,332   39,392  78.01%  21.15%
10   104,839  159,714  38.77%  59.06%
11    45,081  182,403  19.55%  79.10%
12    79,147  166,992  31.65%  66.77%
13    42,518  184,090  18.51%  80.16%
14    97,824  147,151  39.44%  59.32%
15    86,940   62,883  57.35%  41.48%
16   100,993   54,315  64.03%  34.44%
17    84,243  134,521  37.76%  60.29%
18   150,129   44,991  76.11%  22.81%
19    54,451  160,060  25.02%  73.55%
20   110,663   74,540  58.77%  39.59%
21   119,220  188,240  37.85%  59.76%
22    93,582  158,452  36.68%  62.11%
23    94,386   99,654  47.99%  50.67%
24    94,634  150,547  37.98%  60.42%
25   102,433  162,278  37.80%  59.89%
26    80,828  177,941  30.70%  67.59%
27    83,156  131,800  38.15%  60.46%
28   101,843   65,372  60.21%  38.65%
29    75,720   37,909  65.89%  32.99%
30   175,637   43,333  79.61%  19.64%
31    92,842  144,634  38.11%  59.36%
32   106,563  146,420  41.46%  56.97%
33    86,686   32,641  71.93%  27.09%
34    90,885   57,303  60.71%  38.28%
35   105,550   58,007  62.94%  34.59%
36    61,766  175,850  25.66%  73.05%

Looking at the 2016 numbers, you can begin to see the outlines of future competitiveness. That’s more a function of Trump’s weak showing in the familiar places than anything else, but Democrats got their numbers up enough to make it a reality. Looking back at 2012 and you’re reminded again of just how far we’ve come. Maybe we’ll reset to that kind of position in 2022, I don’t know, but that’s a little harder to imagine when you remember that Mitt Romney won the state by ten more points than Trump did. We’ll be going down that rabbit hole soon enough. As always, let me know what you think.

Precinct analysis: SBOE

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020
State Senate district comparisons
State House districts 2020, part 1
State House districts 2020, part 2
Median districts
State House district changes by demography
State House district changes by county

Hey, guess what? The 2020 election data is finally on the Texas Redistricting page for Congress and the State Board of Education. It had been there for awhile for the State House and State Senate, which is why I was able to do those most recent Precinct Analysis piece. Now I can fill in the missing pieces, and I will start here with the State Board of Education, which has a current composition of nine Republicans and six Democrats following the Dem flip in SBOE5. Here’s what the 2020 results looked like for these districts:


Dist   Biden    Trump  Biden%  Trump%
=====================================
01   288,864  245,645   53.3%   45.3%
02   259,587  281,363   47.4%   51.4%
03   361,827  238,999   59.4%   39.2%
04   388,518  117,290   75.9%   22.9%
05   554,766  475,249   52.9%   45.3%
06   391,913  371,101   50.6%   47.9%
07   351,218  509,642   40.2%   58.4%
08   307,826  526,425   36.3%   62.2%
09   196,720  577,419   25.1%   73.7%
10   440,594  445,355   48.7%   49.3%
11   383,185  472,594   44.1%   54.3%
12   469,730  429,676   51.3%   47.0%
13   401,190  128,910   74.7%   24.0%
14   310,738  570,422   34.7%   63.7%
15   150,843  498,932   22.9%   75.6%

Before we dive into the numbers, you’re probably wondering where these districts are. I know I don’t have a mental map of the SBOE like I do for the legislative districts. Here is the SBOE statewide map, and the District Viewer, which you can zoom in on to the street level. That will be your best friend for when the new maps are coming out.

So the numbers. As you can see, Joe Biden carried seven of the fifteen districts, falling just short in district 10 for a majority but carrying Republican-held districts 6 and 12. The bad news is that he did not carry district 2, which is a Democratic district held by Ruben Cortez, who was not on the ballot after winning re-election in 2018 by seven points. District 2 has been purple through the decade but it was on the blue side of purple before 2020. Beto carried SBOE2 in 2018, but only by 4.5 points; Greg Abbott won it by a wider margin, with Glenn Hegar and George P Bush also carrying it. Based on this I think Cortez would have held it had it been on the ballot last year, but I feel confident they’ll make a stronger push for it next year.

Here’s my look at the 2018 results for these districts, for which Beto won nine districts, carrying SBOE2 and 10 where Biden fell short. As you know, District 5 has been on my radar since 2016 when Hillary Clinton carried it, and it came through as I expected. District 10 was the longest-shot of the potential takeovers, with districts 12 and 6 being in between. If we went into the 2022 elections with the same districts, I’d feel like Democratic SBOE candidates would win between five and seven districts (remember, everyone is on the ballot in the first post-redistricting year), with 2 and 12 being the main variables. I see 6 and 10 as tougher nuts to crack, with 10 having more Republican turf in it, and 6 starting from a redder place and thus just taking longer to get where I think it would be going.

Obviously, all of this will be affected by redistricting, and not only is there a greater degree of freedom for the GOP given the small number of districts, there’s been little to no attention paid to SBOE districts. The SBOE map was never part of any voting rights litigation in the 2011 cycle. I have no idea how much attention it will get this time, but as SBOE5 was one of the few Democratic pickups from 2020, I have to think that people will care a little more about it, on both sides.

As we know, Biden tended to run ahead of the rest of the Democratic ticket. It’s pretty straightforward here, in that the rest of the ticket carried five districts, with everyone winning SBOE5 but falling short in 2, 6, 10, and 12. Consistent with what we have seen in the House and Senate districts, Biden’s number in SBOE2 was about the same as everyone else’s, which you can interpret optimistically (it didn’t get any worse!) or pessimistically (Republicans overall improved, it wasn’t just Trump!) as you see fit.

For comparison, here are the numbers from 2016 and 2012:


Dist Clinton    TrumpClinton%  Trump%
=====================================
01   255,909  169,214   57.4%   37.9%
02   234,172  204,262   51.4%   44.9%
03   282,715  163,940   60.2%   34.9%
04   333,156   76,478   78.7%   18.1%
05   377,928  376,417   47.0%   46.8%
06   286,931  301,142   46.3%   48.6%
07   255,474  407,386   37.1%   59.2%
08   205,760  416,239   31.5%   63.7%
09   148,687  486,392   22.7%   74.1%
10   287,936  346,670   42.5%   51.2%
11   257,515  397,155   37.3%   57.6%
12   315,973  356,576   44.4%   50.1%
13   324,952  102,622   73.5%   23.2%
14   195,965  453,354   28.8%   66.5%
15   114,553  426,441   20.3%   75.5%

Dist   Obama   Romney  Obama% Romney%
=====================================
01   213,132  161,807   56.1%   42.6%
02   209,020  187,147   52.1%   46.7%
03   247,020  149,659   61.4%   37.2%
04   311,236   84,036   78.0%   21.1%
05   294,887  375,942   42.9%   54.7%
06   215,839  332,415   38.8%   59.7%
07   215,952  390,808   35.2%   63.6%
08   160,372  398,664   28.3%   70.3%
09   156,833  449,301   25.6%   73.3%
10   235,591  331,022   40.5%   57.0%
11   210,974  396,329   34.2%   64.3%
12   242,306  373,920   38.7%   59.7%
13   314,630  110,615   73.3%   25.8%
14   163,020  413,181   27.9%   70.6%
15   116,797  413,942   21.7%   76.9%

As noted, Hillary Clinton carried six districts, while Barack Obama carried five. The thing that always interests me is the shift over time, and you can see how dramatic it was in the districts that we’ve been talking about. Mitt Romney won districts 5, 6, 10, and 12 by double digits, with 6 and 12 being 20-point wins for him. Again, we have seen this in the previous posts, these districts are anchored in the big urban and suburban districts that have trended hard blue recently, this is just another way of looking at it. I like having the different views, you can always pick up some nuances when you have different angles.

I’m working on the Congressional data next. As always, let me know what you think.

A look ahead to Commissioners Court redistricting

As we know, the Census redistricting data is out, and that means a whole lot of map-drawing is in our future. The main focus on this will be in Austin where the Congressional and legislative maps are re-drawn, but those are not the only entities that have this job to do. Harris County will be redrawing its Commissioners Court map, and this time for the first time in decades it will be done with a Democratic majority on the Court. What might be in store? Benjamin Chou with the Texas Signal provides an advance look at the possibilities.

Over the course of the last decade, population in Harris County boomed, growing by over 630,000 residents from 4.1 million in 2010 to 4.7 million today. Most of the population growth occurred in Precincts 3 and 4, which are also the same precincts currently held by the two Republicans.

In this round of redistricting, the Court will need to tweak the districts so that the four precincts have relatively similar population numbers. For this year’s sake, that means increasing the population in Precinct 2 and decreasing the population in Precincts 3 and 4. To do so, the Democratic-majority can attempt a range of actions that can be simplified into 3 main results: maintain the same 3–2 Democratic majority or increase their majority to 4–1.

The current Commissioners Court map was drawn a decade ago, by the then 4–1 Republican majority. At that time, Republicans held Precincts 2, 3, 4 and the county judge position. The map was drawn with the intent to solidify the Republican 4–1 majority by increasing Republican voters in those three precincts, particularly Precinct 2. The court did so by replacing Hispanic Democratic voters with Anglo Republicans.

They were successful through much of the decade. In the high-Republican turnout year of 2014, Republicans crushed Democrats. Republican Governor Greg Abbott won Precinct 2 by more than 16% of votes and Precincts 3 and 4 by more than 20% each. Even in 2018, when Beto O’Rourke lifted Democratic performance to its most competitive level in a generation, the Republican majority barely crumbled. County Judge Hidalgo, the only one of the five members of the court to be elected county-wide, won by less than 2%. Commissioner Garcia won Precinct 2 by 1%. Last year, when Democrats had a chance to flip Precinct 3, the Democratic candidate lost by 5%.

When considering how to redraw the map, the new Democratic majority will likely keep Precinct 1 solidly Democratic while shoring up Precinct 2 for Commissioner Garcia. The question is whether the court makes Precincts 3, 4, or neither more Democratic so a future challenger has a better chance of ousting the Republican incumbents.

The problem with choosing neither means the Republicans have a chance of flipping the current Democratic 3–2 majority in the event Democrats lose the County Judge position. Similarly, if the Court decides to make only Precinct 3 more Democratic, there remains a risk that Republicans win control because Precinct 3 is not up for election until 2024. Because Precinct 4 is up for election in 2022, the safest bet for Democrats to retain uninterrupted control will be to redraw Precinct 4 more Democratic.

Chou goes on to draw three potential new maps, one that just makes Precinct 2 more Democratic, which would end up with the same Court if Judge Hidalgo wins re-election, and one that shores up Precinct 2 while also turning a radically redrawn Precinct 4 Democratic as well. I’ll let you have a look and see what you think. You can also review this tweet from Hector DeLeon to see the Census population figures for each of the four precincts.

It’s a good writeup, and it captures the choices well. A couple of things that were not directly addressed: One, the Latino drift towards Trump in 2020, which we have discussed before multiple times. We saw that manifest here, though perhaps not as much as in South Texas, but in areas that would affect Precinct 2. Biden carried Precinct 2 in 2020 by a tiny margin, while other Dems generally fell short; in 2018 Beto won Precinct 2 by seven points, while other Dems generally carried it by four or five. For a variety of reasons we don’t know how this will play out in 2022, but we should start with the assumption that Latino voters are a little softer than we’d like, so that we don’t overestimate our position.

Two, we can’t just shove Anglo Republicans into Precinct 1 as a way to aid Precinct 2, because the Voting Rights Act is still more or less in effect, and retrogressing its Black population would be a violation of the VRA. Yes, the thought of a Republican plaintiff filing a VRA lawsuit over this is ironic to the point of causing nosebleeds, but care must still be taken.

Three, as Harris County continues to grow and change demographically, Precinct 3 as it is now will likely become more Democratic in time for the 2024 election without much else being done. Betting on that does entail the risk that the Court could swing Republican in 2022, either via Commissioner Garcia losing or Judge Hidalgo losing. I’m less worried about the latter, and the former can certainly be mitigated against, but this would allow for the possibility of getting to 4-1 without a complete redesign of the county map, which might be controversial politically in ways that are not currently apparent.

It should also be noted that redrawing the Commissioners Court map does the same for the HCDE Trustees map. As it happens, due to resignations and appointments, Dems have a 6-1 majority on that body right now, with all three At Large seats plus the Precincts 1, 2, and 3 positions in their column. I’m certain this will be a lower priority for consideration by the mapmakers, but it is worth keeping in mind.

Beyond that, we’ll see. Commissioners Court is under the same time constraints as the Lege, in that they need to get a new map in place in time for the 2022 primaries, whenever they wind up being. Assuming that will take place in May, and the filing period will be pushed back commensurately, they have a couple of months. Expect to see some action soon – if this is like last time, they’ll hire a consultant to do the actual work, with their specifications, and they will formally approve it once it suits their needs and the public has a chance to weigh in. I will of course be keeping an eye out for this.

Precinct analysis: State House district changes by county

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020
State Senate district comparisons
State House districts 2020, part 1
State House districts 2020, part 2
Median districts
State House district changes by demography

One more look at how state house districts have changed over the decade. For this exercise, I’m going to look at some key counties and the State Rep districts within them.

Bexar:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
122   -1,304  10,628  12,204  21,091  10,900  31,719  20,819
121   -4,020   6,534   6,059  15,078   2,039  21,612  19,573
116     -583   6,014   3,546  10,281   2,963  16,295  13,332
117    4,532   8,828  14,927  22,921  19,459  31,749  12,290
123   -1,427   5,225   3,742   9,272   2,315  14,497  12,182
124      330   5,077   5,877  11,756   6,207  16,833  10,626
125   -1,081   4,378   4,753   9,350   3,672  13,728  10,056
120     -184     863   4,503  10,856   4,319  11,719   7,400
119    1,062   3,428   6,041  10,507   7,103  13,935   6,832
118    1,391   3,719   6,633   7,790   8,024  11,509   3,485

Bexar County doesn’t get the props it deserves for contributing to the Democratic cause. Each of its ten districts became more Democratic in each of the two Presidential cycles. Where Bexar had gone 51.56% to 47.04% in 2012 for Obama, it went 58.20% to 40.05% for Biden. Obama had a net 23K votes in Bexar, while it was +140K votes for Biden. The two districts that shifted the most heavily towards Dems are the two Republican districts (HD117 went Republican in 2014, then flipped back in 2016), with Biden carrying HD121 as Beto had done in 2018, and HD122 coming into focus as a potential long-term pickup (modulo redistricting, of course). Both HDs 121 and 122 were over 60% for Romney, with HD122 at almost 68% for him. Both can and surely will be shored up in the next round of mapmaking, but the long term trends don’t look good for the Republicans holding them both.

Tarrant:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
092   -1,102   3,986   4,166  13,144   3,064  17,130  14,066
094   -3,344   2,238   2,655  10,231    -689  12,469  13,158
096      821   4,468   6,527  15,522   7,348  19,990  12,642
098     -489   6,891   8,798  13,948   8,309  20,839  12,530
097   -3,267   3,654   6,147  11,472   2,880  15,126  12,246
101     -734   3,487   4,523   9,808   3,789  13,295   9,506
093    2,751   5,180   9,984  15,697  12,735  20,877   8,142
091      401   2,489   5,437   8,897   5,838  11,386   5,548
090     -180   2,391   3,170   5,496   2,990   7,887   4,897
095     -613  -2,745   2,727   7,752   2,114   5,007   2,893
099    2,757   3,282   9,686  11,208  12,443  14,490   2,047

I know everyone sees Tarrant County as a disappointment in 2020. Beto broke through in 2018, we had a bunch of close districts to target, and the Republicans held them all even as Biden also carried Tarrant. The point here is that Democrats made progress in every district, in each cycle (the dip in predominantly Black and heavily Democratic HD95 in 2016 notwithstanding). That includes the strong Republican districts (HDs 91, 98, and 99), the strong D districts (HDs 90, 95, and 101), and the five swing districts. Tarrant will be another challenge for Republicans in redistricting because like in Harris they have mostly lost their deep red reserves. HD98 went from being a 75% Romney district to a 62% Trump district last year. They can spread things out a bit, but remember what happened in Dallas County in the 2010s when they got too aggressive. I’m not saying that’s what will happen in Tarrant, but you can see where the numbers are.

Collin:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
067   -3,022   8,595   6,135  19,411   3,113  28,006  24,893
066   -4,911   8,517   4,001  14,432    -910  22,949  23,859
089    1,038   6,667   9,980  17,338  11,018  24,005  12,987
033    4,656   8,268  18,234  20,233  22,890  28,501   5,611
070    7,648   8,675  21,284  25,686  28,932  34,361   5,429

Denton:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
065   -1,378   6,440   6,048  16,110   4,670  22,550  17,880
106    8,757  11,138  21,190  29,280  29,947  40,418  10,471
064    3,003   6,205   8,257  15,136  11,260  21,341  10,081
063    2,642   6,129  16,382  17,279  19,024  23,408   4,384

I’m grouping these two together because they have a lot in common. Both shifted hugely Democratic over the decade, in each case across all their districts. Both contain a district that was added to their county in the 2011 redistricting. HDs 33 (72-26 for Romney in 2012, 60-38 for Trump in 2020) and 106 (68-31 for Romney in 2012, 54-45 for Trump in 2020) were supposed to be super-red, but didn’t stay that way. I might have thought that the southernmost districts in each county – i.e., the ones closest to Dallas and Tarrant – would be the bluest, but that is not quite the case. HD65 is in southeast Denton, where it is almost entirely adjacent to HD115, but HD63 is the reddest district in Denton (61-37 Trump) and it is the other district on Denton’s south border, though it aligns almost perfectly with HD98, the reddest district in Tarrant. HD64 is the next most Dem district in Denton, and it’s in the northwest quadrant, catty-corner to HD65. I have to assume this is a function of development more than who its closest neighbors are; I’m sure someone who knows Denton better than I can comment on that.

In Collin, HDs 66 and 67 are on the southern end of that county, but so is HD89, where it abuts Rockwall County more than it does Dallas. HD70 is north of 67 and 89, and HD33 (which contains all of Rockwall County) is the outer edge of the county to the west, north, and east, dipping down into Rockwall from there. Both counties continue their massive growth, and I expect them to have at least one more district in them next decade. Republicans have more room to slosh voters around, but as above, the trends are not in their favor.

There are of course other counties that are growing a lot and not in a way that favors Republicans. Here are two more of them.

Williamson:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
136       52  10,901   7,842  22,330   7,894  33,231  25,337
052    2,422   8,335  11,479  22,872  13,901  31,207  17,306
020    7,373   2,895  20,820  14,926  28,193  17,821 -10,372

Fort Bend:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
026   -4,573   9,082   7,327  13,556   2,754  22,638  19,884
028    4,053  14,090  19,260  24,010  23,313  38,100  14,787
027     -461   4,708   6,324  13,724   5,863  18,432  12,569
085    2,908   5,495  10,258  10,161  13,166  15,656   2,490

HD20 also includes Milam and Burnet counties, and I suspect that’s where most of the Republican growth is. HD85 also includes Jackson and Wharton counties. The previous version of HD52 had flipped Dem in 2008, the first such incursion into the formerly all-red suburbs, before flipping back in 2010, but neither it (55-42 for Romney) nor the newcomer HD136 (55-41 Romney) were ever all that red. There were some maps drawn in the 2011 redistricting process (not by Republicans, of course) that carved HD26 out as a heavily Asian swing district (it went 63-36 for Romney as drawn), but it just needed time for the “swing” part to happen. Of the various targets from 2018 and 2020, it’s one that I feel got away, and I wish I understood that better.

Brazoria:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
029      496   8,084  10,828  15,387  11,324  23,471  12,147
025    1,759     215   8,293   3,874  10,052   4,089  -5,963

Galveston:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
024    2,403   3,959  13,045   8,928  15,448  12,887  -2,561
023    3,847     346  11,123   7,296  14,970   7,642  -7,328

Montgomery:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
015   -1,563   7,905  13,226  15,512  11,663  23,417  11,754
016    7,437   2,437  16,088   7,160  23,525   9,597 -13,928
003    7,758   1,807  17,456   8,286  25,214  10,093 -15,121

We’ve looked at these counties before, this is just a more fine-grained approach. Note that HD03 includes all of Waller County, HD25 includes all of Matagorda County, and HD23 includes all of Chambers County. HD23 was already Republican in 2012 when Craig Eiland still held it (Romney carried it 54.6 to 44.2) and while it has gotten more so since then (Trump won it 57.5 to 41.0), that has mostly been fueled by the Republican growth in Chambers. I did a quick calculation on the data from the Galveston County election results page, and Biden carried the Galveston part of HD23 by a slim margin, 29,019 to 28,896. (Republican rep Mayes Middleton won that part of the district 29,497 to 27,632, so this tracks.) The rest of Galveston, the northern part that’s all Houston suburb, is much more Republican, but like with these other two counties one can see a path forward from here. What to do about the likes of Chambers County, that’s another question.

HD29 in Brazoria should have been a target in 2018 but the Dem who won the primary dropped out of the race, and there was no traction that I could see there in 2020. I expect that district to get a little redder, but the same story as elsewhere applies in that the geographic trends are a force that won’t be stopped by boundary lines. As for Montgomery, there are your signs of progress right there. HD15 is still very red, but as I’ve said before, the first goal is to bend the curve, and we’re on the right track there. HD15 is basically the Woodlands and Shenandoah, just north of HD150, while HD03 wraps around it and HD16 is the north end of the county.

Lubbock:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
084     -474     873   4,124   6,975   3,650   7,848   4,198
083    3,359     242  12,224   5,141  15,583   5,383 -10,200

Smith:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
006       67     938   6,922   6,208   6,989   7,146     157
005    4,565  -1,293   9,646   2,832  14,211   1,539 -12,672

These two districts, on opposite ends of the state, may seem odd to be paired together, but they have a couple of things in common. Both contain one district that is entirely within its borders (HD06 in Smith, HD84 in Lubbock) and one district that contains the rest of their population plus several smaller neighboring counties (HD05 also contains Wood and Rains counties, while HD83 contains six other counties). Both have a city that is the bulk of of its population (the city of Lubbock has over 90% of the population of Lubbock County, while a bit less than half of Smith County is in the city of Tyler). And both provide a bit of evidence for my oft-stated thesis that these smaller cities in Texas, which are often in otherwise fairly rural and very Republican areas, provide the same kind of growth opportunity for Democrats that the bigger cities have provided.

Both HDs 06 and 84 were less red than Smith and Lubbock counties overall: Smith County was 69-30 for Trump, HD06 was 68-32 for Matt Schaefer; Lubbock County was 65-33 for Trump, and HD84 was 61-39 for John Frullo. I didn’t go into the precinct details to calculate the Trump/Biden numbers in those districts, but given everything we’ve seen I’d say we could add another point or two into the Dem column for each. HD84 shows a clear Democratic trend while HD06 is more of a mixed bag, but it’s still a slight net positive over the decade and a damn sight better than HD05. HD06 is not close to being competitive while HD84 is on the far outer fringes, but that’s not the main point. It’s the potential for Democratic growth, for which we will need every little contribution we can get, that I want to shout from the rooftops. The big cities and big growing suburbs are our top tier, but we’d be fools to ignore the places like Lubbock and Tyler.

Precinct analysis: State House district changes by demography

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020
State Senate district comparisons
State House districts 2020, part 1
State House districts 2020, part 2
Median districts

I return once again to doing cycle-over-cycle comparisons in vote turnout, in this case for State House districts. There are a lot of them, and I’m not going to do them all but I am going to do enough of them that I will split this into two parts. Part One, this post, will group districts by demographic groups. Part Two, to come later, will be to group them by counties of interest.

First up, just to ease ourselves in, are the four big urban districts that are Anglo, wealthy, highly college-educated, and swung hard towards the Democrats since 2012:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
134  -10,943  15,312   6,540  17,771  -4,403  33,083  37,486
047   -2,005  14,218  13,145  27,678  11,140  41,896  30,756
108   -5,942  12,553   8,628  17,929   2,686  30,482  27,796
121   -4,020   6,534   6,059  15,078   2,039  21,612  19,573

As discussed before, the columns represent the difference in vote total for the given period and party, so “1216” means 2012 to 2016, “1620” means 2016 to 2020, and “1220” means 2012 to 2020. Each column has a D or an R in it, so “1216R” means the difference between 2016 Donald Trump and 2012 Mitt Romney for the Presidential table, and so forth. In each case, I subtract the earlier year’s total from the later year’s total, so the “-9,951” for SD114 in the “1216R” column means that Donald Trump got 9,951 fewer votes in 2016 in SD14 than Mitt Romney got, and the “56,887” for SD14 in the “1216D” column means that Hillary Clinton got 56,887 more votes than Barack Obama got. “Dem net” at the end just subtracts the “1220R” total from the “1220D” total, which is the total number of votes that Biden netted over Obama. Got it? Good.

Despite the large swings, only the top two are now Dem-held. HD108 managed to remain in the hands of Rep. Morgan Meyer despite being carried by statewide Dems all the way down the ballot, while HD121 still remains somewhat Republican-leaning. I don’t know what magic Republicans have in mind for redistricting, but their hold on these voters is slipping away rapidly. I can’t emphasize enough that Mitt Romney got 60% of the vote in HD134 in 2012, and look at where it is now.

I’ve written plenty about these districts, and I could have included more of them in this table. Most of those you will see later. There’s not much to add except to say that this particular demographic shift has been a huge driver in the overall blue-ing of Texas, and especially of its most populated areas. I don’t know what the future holds, but I don’t see that changing in the near term.

When I mentioned that this post was a look at the districts by demographic groups, I assume your first thought was that I’d take a closer look at Latino districts. Well, here you go:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
051      425  10,783   4,422  19,073   4,847  29,856  25,009
102   -4,430   5,333   2,511  10,832  -1,919  16,165  18,084
148   -1,481   8,555   5,598  10,113   4,117  18,668  14,551
107   -3,023   4,566     718   7,532  -2,305  12,098  14,403
103      -96   7,314   3,535  10,357   3,439  17,671  14,232
116     -583   6,014   3,546  10,281   2,963  16,295  13,332
117    4,532   8,828  14,927  22,921  19,459  31,749  12,290
105   -2,249   4,377   2,900   8,547     651  12,924  12,273
078   -1,129   6,723   6,731   9,618   5,602  16,341  10,739
124      330   5,077   5,877  11,756   6,207  16,833  10,626
125   -1,081   4,378   4,753   9,350   3,672  13,728  10,056
079     -453   7,038   4,976   6,495   4,523  13,533   9,010
075    1,734  11,011   9,747   8,599  11,481  19,610   8,129
104     -777   3,881   2,743   6,042   1,966   9,923   7,957
077   -1,530   5,080   3,539   3,936   2,009   9,016   7,007
119    1,062   3,428   6,041  10,507   7,103  13,935   6,832
145   -1,306   5,575   5,291   5,038   3,985  10,613   6,628
090     -180   2,391   3,170   5,496   2,990   7,887   4,897
118    1,391   3,719   6,633   7,790   8,024  11,509   3,485
076     -260   5,039   3,826   1,635   3,566   6,674   3,108
140     -733   4,433   4,140   1,810   3,407   6,243   2,836
144   -1,051   3,577   4,044   1,480   2,993   5,057   2,064
041    1,664   6,820   8,617   5,201  10,281  12,021   1,740
143   -1,038   3,244   4,483   1,446   3,445   4,690   1,245
022   -1,261  -2,280   1,510   2,254     249     -26    -275
034      620     799   6,012   3,759   6,632   4,558  -2,074
038    1,533   4,706   9,344   2,945  10,877   7,651  -3,226
040    2,384   3,753   8,981   3,433  11,365   7,186  -4,179
037      969   3,764   7,324      36   8,293   3,800  -4,493
036    1,482   5,527   9,847    -480  11,329   5,047  -6,282
039    2,071   3,256   8,411     836  10,482   4,092  -6,390
035    2,007   2,358   8,961   2,163  10,968   4,521  -6,447
042      882   2,195   7,908    -323   8,790   1,872  -6,918
043    2,532     162   8,001   1,059  10,533   1,221  -9,312
080    1,959   1,789   9,567     127  11,526   1,916  -9,610
074    1,127   2,708   9,454  -2,185  10,581     523 -10,058
031    3,017  -1,816  13,479    -412  16,496  -2,228 -18,724

A couple of notes here. Defining “Latino district” is subjective, and I make no claim that my way is optimal. What you see above is almost all of the districts that are represented by a Latino member, plus HD80, which despite being majority Latino is still represented by Democrat Tracy King. I skipped HDs 49 (Gina Hinojosa) and 50 (Celia Israel) because the’re much more Anglo than Latino. HDs 102, 105, and 107 were held by non-Latino Republicans before being flipped by Democrats in 2016 and 2018. HD43 is held by the one Latino Republican in the House, JM Lozano, who won originally as a Democrat in 2008 and then changed parties after the 2010 election. HDs 79 and 90 were held by Anglo Democrats in 2012; Lon Burnam was primaried out by Rep. Ramon Romero in 2014, and Joe Pickett resigned following the 2018 election due to health challenges.

There’s a lot of data here, and I’ll try to keep this manageable. All the districts that showed a net gain for Dems over both elections are in Bexar, Dallas, El Paso, Harris, Travis (HD51), and Tarrant (HD90), plus HD41 in Hidalgo County. In Bexar, Dallas, and Tarrant, there were net gains in each cycle. In El Paso, there were big gains in 2016 and more modest gains in 2020, with the exception of HD75, which had a slight gain for Republicans in 2020. HD75 is the easternmost and thus most rural of the El Paso districts. It also still voted 66.5% to 31.9% for Biden in 2020, just for some perspective.

In Harris, all five districts gained in 2016, but only HD148 also gained in 2020. HD145 came close to breaking even, while HDs 140, 143, and 144 all moved towards Republicans; we saw this when we looked at the Harris County Senate districts and talked about SD06. This is the first of several places where I will shrug my shoulders and say “we’ll see what happens in 2022”. Honestly, I don’t know what to expect. We’ve discussed this topic numerous times, and as there are forces moving urban and college-educated voters towards Democrats, the same forces are moving rural and non-college voters towards Republicans. The biggest of those forces is Donald Trump, whose presence on the ballot helped Republicans in 2016 and 2020 but whose absence hurt them in 2018. We just don’t know yet what 2022 will bring.

Of the districts that had net Republican gains, HD22 is in Jefferson County (basically, it’s Beaumont; Dade Phelan’s HD21 has the rest of JeffCo plus Orange County) and HD34 is in Nueces County. Jefferson County has been slowly losing population over time, and I think that was a big driver of what happened with HD22. It’s also much more Black than Latino, and thus maybe is a better fit with the next data set, but it has long been represented by Rep. Joe Deshtotel, and this is the decision I made. Nueces County also has the Republican-held HD32 in it, and it showed a net Democratic gain of 1,576 votes over the two cycles, with most of that in 2016 but still a small Dem net in 2020. Its Latino voting age population is about 46%, nearly identical to its Anglo VAP. HD34 was one of the tighter districts even before 2020, and I figure it’s on the target list for Republicans in redistricting.

Most of the other districts are in Cameron, Hidalgo, and Webb counties, and while 2020 was a better year for Republicans in all of them, I don’t think that will necessarily be the case in 2022, a belief driven in part by the incumbency theory and in part by my own wishfulness. That said, as noted before the shifts were more muted downballot, with Trump outperforming other Republicans in those districts. I had my doubts about the durability of Democratic gains in 2016 because of the disparity between the Hillary numbers and the rest of the numbers, and I think it’s fair to have those same doubts here. We do know how it went in 2018, but as before Trump is not on the ballot in 2022. Which force is stronger? Have the underlying conditions changed? I don’t know and neither does anyone else at this time.

HDs 31, 74, and 80 are all cobbled out of smaller counties, and I have much less hope for them, but who knows what the combined effects of the freeze and the Abbott Wall will have. The main thing I took away from analyzing this data is that there was already a Republican shift in 31 and 74 in 2016 with a near miss in 80, though they all rebounded in a Democratic direction in 2018. How much of this was caused by new voters, and how much by swapping allegiances, those are big questions to ponder.

Let’s move on. These are the predominantly Black districts:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
046     -331   7,462   4,363  20,080   4,032  27,542  23,510
027     -461   4,708   6,324  13,724   5,863  18,432  12,569
147   -1,282   3,575   4,571   9,831   3,289  13,406  10,117
109     -914    -500   1,853  11,161     939  10,661   9,722
111   -1,449  -1,155   1,627   8,981     178   7,826   7,648
120     -184     863   4,503  10,856   4,319  11,719   7,400
100     -840    -537   2,107   7,799   1,267   7,262   5,995
142      294   2,093   4,685   8,804   4,979  10,897   5,918
131     -642   2,681   4,289   6,642   3,647   9,323   5,676
146   -1,653    -923   2,438   6,798     785   5,875   5,090
139   -1,290   1,216   4,826   6,786   3,536   8,002   4,466
095     -613  -2,745   2,727   7,752   2,114   5,007   2,893
141      218    -721   2,594   4,405   2,812   3,684     872
110     -101  -3,010   1,820   3,362   1,719     352  -1,367

HD27 is in Fort Bend, HD46 is in Travis (it’s also much more Latino than Black but has long been represented by a Black legislator, with Dawnna Dukes preceding Sheryl Cole; it is the inverse of HD22 in that way), HD95 is in Tarrant, and HD120 is in Bexar. HD101 in Tarrant County has a higher Black percentage of its population than either HDs 46 or 120, but it’s held by the Anglo Dem Chris Turner, so I skipped it. All the rest are in Harris and Dallas. The range of outcomes here is fascinating. I think what we see in the 2016 results, at least in some of these districts, is a bit of a letdown in enthusiasm from Obama to Clinton, with perhaps a bit of the campaign to dampen turnout among Black Democrats finding some success. Some districts in Harris County like HD141 have had pretty modest growth in population and voter registration as well. I don’t know what the story may have been in HD110, but if one of my Dallas readers would like to offer a few words, I’d be interested in hearing them.

There was some evidence around the country of Trump making modest gains with Black voters, mostly Black men, in 2020. I do see a case for that here, because even as Dems had net gains in 2020 – significant gains, in some of these districts – their share of the total new turnout is smaller than you’d otherwise expect. For example, HD131 voted 80.6% to 18.5% for Biden, but only 60.8% of the extra voters in 2020 voted for Biden. HD131 had voted 84.1% to 13.3% for Hillary in 2016, meaning that Trump cut almost ten points off of his deficit from 2016. This is your reminder that a shift in vote share towards one party is not the same as a shift in total votes towards one party. We’ve had this conversation about Democrats making percentage point gains in some heavily Republican areas while still falling farther behind, and this is that same conversation from the other side.

Finally, here are the four districts represented by Asian American legislators:


Dist  12-16R  12-16D  16-20R  16-20D  12-20R  12-20D Dem net
============================================================
026   -4,573   9,082   7,327  13,556   2,754  22,638  19,884
112   -2,140   4,427   5,086  10,634   2,946  15,061  12,115
137     -848   2,147   2,435   4,099   1,587   6,246   4,659
149   -2,592   3,504   8,134   4,645   5,542   8,149   2,607

This grouping is even more tenuous than the Latino districts, mostly because there’s no such thing as a plurality Asian district. Indeed, only HDs 26 and 149, which are the two most Asian districts in the state, are in the top five; HDs 66, 28, and 67 are the next three in line. They will all be covered in the next post in this series. HD137 is mostly Latino and HD112 is mostly Anglo. Like I said, these are the decisions I made. HD26 is in Fort Bend and was won in 2020 by Republican Jacey Jetton, after years of being held by Rick Miller. It was carried by Biden in 2020 and as you can see it has moved pretty heavily Democratic, but it was still Republican enough to be held by them in an open seat race. HD112 is in Dallas and is held by Angie Chen Button, and like HD108 it was otherwise Democratic in 2020. Good luck with redistricting, that’s all I can say. The other two are in Harris County, with HD137 being held by Gene Wu since 2012. It was 63-34 for Obama in 2012 and 67-31 for Biden in 2020. The most curious case for me is HD149, which as you can see followed a pattern similar to the Latino districts in Harris County; I noted this before when I did the Harris County numbers way back when. I’m not quite sure what to make of those totals, but they don’t keep me awake at night. As with the rest, we’ll see what 2022 has in store for us.

Next time, a closer look at some counties of interest. Let me know what you think.

Precinct analysis: The median districts

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020
State Senate district comparisons
State House districts 2020, part 1
State House districts 2020, part 2

This is a straightforward post, with a simple answer to an important question. We know that Joe Biden carried 74 State House districts and 15 State Senate districts. How much better did he need to do to get a majority in each chamber? Daily Kos calls this the “median district”. In this context, that means the data for the 76th-most Democratic House district, and the 16th-most Democratic Senate district. The idea is to see how far off the Dems were from being able to win those districts and thus claim a majority in each chamber.

We’ll start with the State House. The table below gives the data for the median district in each of the last three Presidential elections for the Presidential race, the Senate race (2012 and 2020 only), and the Railroad Commissioner race:


Year    Dist      Dem      GOP   Tot D
======================================
2012   HD138   39.29%   59.16%      54
2016    HD54   43.58%   50.50%      65
2020    HD54   48.85%   48.98%      74
				
2012    HD97   38.35%   58.88%      54
2020    HD92   46.04%   51.12%      68

2012    HD97   36.16%   59.58%      54
2016    HD66   37.77%   54.46%      56
2020    HD31   46.52%   50.55%      68

In 2012, the 76th-most Democratic district was HD138, in which Barack Obama received 39.29% of the vote to Mitt Romney’s 59.16%. This is a polite way of saying that the 2011 gerrymander was super effective, and the Democrats weren’t within hailing distance of winning half the chamber. The last column shows the total number of districts carried by the Democratic Presidential candidate. In 2012, this closely mirrored the total number of seats that the Dems actually won, which was 55. One Democratic-held seat was carried by Romney – HD23, the Galveston-based district won that year (and for the final time, as he declined to run again) by Craig Eiland. As you may recall from previous analyses, that district has trended away from the Dems ever since – in 2016, it was won 56-41 by Trump, and in 2020 it was 57-41 for Trump. Obama carried zero Republican-won seats – the closest he came was a 52-47 loss in HD43, another district that has moved farther away from Dems over the decade. He came within six points in three Dallas districts that Democrats now hold – HDs 113, 107, and 105. Like I said, an extremely effective gerrymander. Also a consistent one, as Paul Sadler and Dale Henry won the same districts Obama did, no more and no less.

Until it wasn’t, of course. The cracks began to show in 2016, when Hillary Clinton carried 65 districts, though Dems still only won 55 of them overall. HD23 fell to the Republicans in 2014, but Dems earned their first flip of the decade (*) by taking HD107, which as noted above was one of the closer misses in 2012. The nine GOP-won districts that Hillary Clinton carried were HDs 113, 105, 115, 102, 112, 114, 138, 134, and 108. Seven of those are now Democratic districts, with six flipping in 2018 and one (HD134) flipping in 2020.

Note how Clinton ran ahead of other Dems as well. Perennial candidate Grady Yarbrough picked up only HD105, and that by a 45.9 to 44.6 margin (there was a lot of third-party voting in that extremely unappealing race), and it was the same at the judicial level. You may recall this is why I was more guarded in my optimism about 2018 initially – I had some doubts about what the Clinton/GOP voters would do their next time out.

We know how that turned out, and we know how Biden did, as well as how MJ Hegar and Chrysta Castaneda did in 2020. Look at how the median district shifted over time. In 2012, the 76th district was more Republican than the Presidential race was, at each level. In 2016, the median district looked a lot like the Presidential race, and to be honest a lot like the RRC race as well; Wayne Christian defeated Grady Yarbrough 53.1 to 38.4, a bit closer than the median but not far off. In 2020, at all levels, the median district was closer than the statewide race was. Republicans outperformed their baseline in the House, and they needed to because by this point their vaunted gerrymander had completely failed them. I have to think this is something they’re giving serious thought to for this time around.

Here’s the same data for the State Senate districts:


Year    Dist      Dem      GOP   Tot D
======================================
2012    SD08   36.60%   61.67%      11
2016    SD09   41.75%   53.09%      12
2020    SD09   48.30%   50.00%      15

2012    SD08   35.94%   61.05%      11
2020    SD09   45.40%   51.70%      13

2012    SD08   33.34%   62.19%      11
2016    SD08   36.19%   55.94%      11
2020    SD09   44.60%   51.60%      13

It’s a similar pattern as above. In 2012, Mitt Romney carried SD10, which Wendy Davis won in a hard-fought race. In 2016, Hillary Clinton carried SD16 by a 49.9 to 45.3 margin, and just missed in SD10, losing it 47.9 to 47.3; she also came within a point of SD17. The median district was a little friendlier to the GOP in 2016, but in 2020 as with the House it was closer than the corresponding statewide race. Again, the once-solid gerrymander buckled at the knees, aided in large part by the suburban shift. Dems also managed to hold onto all of the red-shifting Latino districts, while Biden dropped two of them in the House.

What does any of this mean going forward? I have no idea. I’m seeing map proposals for Congress that are pretty brutal, but who knows what we’ll get in 2022, and who knows how population growth and the shifts in suburban and (mostly rural) Latino areas will affect things. Texas is a more challenging state than the likes of Wisconsin or Michigan to control over an entire decade precisely because it changes so much in that time. Republicans will have some opportunities for gain in 2022, but they also have a lot of vulnerabilities, and their best defense may be to just try to shore up everything they now have. The choices they make, based to some degree on their level of risk tolerance, will be fascinating to see.

Precinct analysis: State House districts 2020, part 2

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020
State Senate district comparisons
State House districts 2020, part 1

Today’s post is going to be an analysis of the State House districts from the perspective of the US Senate and Railroad Commissioner races. We have already observed in other contexts how Joe Biden outran the rest of the Democratic ticket, and we will see that here as well. But it’s a little more nuanced than that, because of the Latino vote and the Trump shift, which we have characterized as being mostly about Trump. The Texas Signal boiled down one piece of research on that as follows:

In an interview with Texas Signal, the Executive Director of Cambio Texas, Abel Prado, walked us through some of the big takeaways from their post-election report. One of his first points from the report was that many of the voters who came out in the Rio Grande Valley were specifically Donald Trump voters, and not necessarily Republican voters.

Many of Trump’s traits, including his brashness, a self-styled Hollywood pedigree, his experience as a businessman, and his billionaire status, resonated with many voters in the Rio Grande Valley. “The increase in Republican vote share were Donald Trump votes, not conservative votes, and there’s a difference,” said Prado.

Hold that thought, we’ll get to it in a bit. I’m going to present the data here in the same order as I did in the previous post, with the results from the Senate race (MJ Hegar versus John Cornyn) and the RRC race (Chrysta Castaneda versus Jim Wright) grouped together. We will start with the Republican districts that Biden carried:


Dist    Hegar   Cornyn   Hegar%  Cornyn%
========================================
026    40,478   43,650    47.1%    50.8%
066    42,688   42,768    48.9%    49.0%
067    47,484   46,775    49.2%    48.5%
096    42,210   44,471    47.5%    50.0%
108    50,639   49,689    49.4%    48.5%
112    34,800   32,591    50.2%    47.0%
121    44,062   49,365    46.0%    51.2%
132    48,460   50,865    47.5%    49.8%
134    61,018   48,629    54.7%    43.6%
138    31,508   31,993    48.3%    49.1%

Dist    Casta   Wright   Casta%  Wright%
========================================
026    39,238   42,818    46.5%    50.8%
066    41,139   41,650    48.1%    48.7%
067    45,970   45,494    48.6%    48.1%
096    41,135   44,103    46.7%    50.1%
108    49,347   48,118    48.8%    47.6%
112    34,635   31,768    50.3%    46.2%
121    43,992   46,975    46.6%    49.8%
132    47,483   49,947    47.0%    49.4%
134    57,940   47,504    53.2%    43.6%
138    30,796   31,201    47.9%    48.6%

You don’t need to review the previous post to see that Hegar and Castaneda fell short of the standard Biden set. Still, they carried 70 House districts, three more than were won by the Dems, and came within a point of two more. What we see here is the same thing we saw when we looked at these races in Harris County, which is not only that Joe Biden got more votes than these two Democrats, but John Cornyn and Jim Wright outperformed Donald Trump. These are your crossover voters, and the big question going into 2022 is what potential exists to swing them again, and in which races. Dems still fell short statewide in 2020 even with all those voters, but the hill is less steep with them than without them.

UPDATE: Correction – Hegar and Castaneda carried 68 House districts, one more than the total won by Dems. They carried GOP-won HDs 67, 108, and 112 and lost Dem-won HDs 31 and 74, for a net increase of one. I managed to confuse myself with the math by basing the calculation on that table above. They were still within a point of two other districts as shown above.

Here are the near-miss and reach districts for Biden:


Dist    Hegar   Cornyn   Hegar%  Cornyn%
========================================
014    27,435   35,269    42.2%    54.3%
028    54,571   65,387    44.6%    53.4%
029    43,327   52,292    44.2%    53.4%
054    34,462   36,551    47.1%    49.9%
064    39,350   47,395    43.8%    52.8%
092    36,564   40,601    46.0%    51.1%
093    37,934   44,925    44.4%    52.6%
094    34,826   39,970    45.3%    52.0%
097    42,210   44,471    47.4%    50.0%
122    51,835   72,452    40.9%    57.1%
126    33,618   39,298    44.9%    52.5%
133    38,149   51,111    41.9%    56.2%

032    29,613   38,322    43.5%    53.4%
070    48,246   77,306    37.5%    60.1%
084    22,626   35,019    37.8%    58.5%
085    32,212   43,653    41.5%    56.3%
089    40,761   57,531    40.5%    57.1%
106    53,674   73,313    41.2%    56.3%
129    35,924   48,318    41.5%    55.8%
150    39,872   56,019    40.5%    56.9%

Dist    Casta   Wright   Casta%  Wright%
========================================
014    25,863   34,522    40.7%    54.3%
028    53,363   64,123    44.3%    53.2%
029    42,256   51,097    43.7%    52.9%
054    33,036   36,749    45.4%    50.5%
064    37,396   46,264    42.5%    52.6%
092    35,180   40,269    44.8%    51.3%
093    36,501   44,700    43.2%    52.9%
094    33,630   39,603    44.3%    52.1%
097    35,954   44,647    43.0%    53.4%
122    51,488   69,624    41.2%    55.7%
126    32,979   38,409    44.6%    52.0%
133    36,456   50,069    40.9%    56.2%

032    28,939   36,856    42.2%    53.7%
070    46,349   75,914    36.6%    60.0%
084    21,625   34,530    36.8%    58.8%
085    31,967   42,990    41.6%    55.9%
089    39,378   56,345    39.8%    56.9%
106    50,925   71,782    39.9%    56.3%
129    35,326   46,707    41.5%    54.8%
150    38,995   55,111    40.0%    56.6%

Not a whole lot to say here. The near-misses look farther away, and the reaches look out of reach. It’s important to remember that a lot of these districts weren’t on anyone’s radar going into 2016, and that the trend has been heavily favorable to the Democrats. We certainly hope those trends continue, but even if they do that doesn’t mean the district in question is on the verge of being competitive.

Here are the districts that Trump won or came close it. For this, I’m going to reprint the Biden/Trump numbers, to make it easier to illustrate the point I want to make.


Dist    Hegar   Cornyn   Hegar%  Cornyn%
========================================
031    23,609   28,980    43.5%    53.4%
074    22,397   25,232    45.5%    51.2%

034    27,567   26,236    49.8%    47.4%
035    22,735   18,926    52.7%    43.8%
080    25,339   19,960    54.1%    42.6%

038    28,050   20,464    56.2%    41.0%
041    29,594   24,797    52.8%    44.3%
117    49,759   40,386    53.6%    43.5%
118    31,726   25,841    53.5%    43.6%
144    16,246   14,108    51.8%    45.0%

Dist    Casta   Wright   Casta%  Wright%
========================================
031    24,700   26,837    46.5%    50.5%
074    22,942   23,836    47.4%    49.2%

034    27,816   24,985    51.0%    45.8%
035    23,684   17,094    56.2%    40.5%
080    25,945   18,750    56.2%    40.6%

038    29,097   18,502    59.2%    37.7%
041    30,611   22,881    55.5%    41.5%
117    49,871   38,567    54.2%    41.9%
118    32,568   24,454    55.2%    41.5%
144    16,851   13,251    54.1%    42.6%

Dist    Biden    Trump   Biden%   Trump%
========================================
031    25,315   33,101    42.9%    56.1%
074    23,478   27,319    45.6%    53.1%

034    29,226   26,606    51.7%    47.0%
035    24,991   21,049    53.8%    45.3%
080    26,251   22,543    53.3%    45.8%

038    29,116   21,573    56.8%    42.1%
041    31,956   25,187    55.5%    43.7%
117    53,983   39,495    56.8%    41.6%
118    34,228   25,848    56.2%    42.4%
144    17,365   14,599    53.6%    45.0%

We don’t see the same pattern here that we did before. In these districts, Trump is outrunning Cornyn and Wright. Biden is still outperforming Hegar and Castaneda, but not by as much. That makes HDs 31 and 74 closer, especially for Castaneda. This suggests two things to me. One is that as was claimed in that Texas Signal story, there really was more of a Trump effect than a Republican shift. It also appears that Castaneda benefitted from her Latina surname; one could also argue that Cornyn got some incumbent benefit as well. The main point is that the story of these districts is a little more nuanced than some of the discourse would have you believe. Doesn’t mean there aren’t issues for Dems to confront, just that it’s not a one-dimensional situation.

Finally, here are the districts that the Dems picked up in the 2016 and 2018 cycles.


Dist    Hegar   Cornyn   Hegar%  Cornyn%
========================================
045    57,413   54,996    49.5%    47.4%
047    69,906   66,452    50.2%    47.7%
052    51,448   45,369    51.6%    45.5%
065    40,789   38,039    50.3%    46.7%
102    37,879   29,970    54.5%    43.1%
105    31,769   24,477    54.8%    42.2%
107    34,360   26,248    55.1%    42.1%
113    36,185   31,239    52.2%    45.0%
114    42,291   36,918    52.3%    45.6%
115    39,307   31,859    53.8%    43.6%
135    37,050   36,728    48.9%    48.4%
136    55,420   44,710    53.8%    43.4%

Dist    Casta   Wright   Casta%  Wright%
========================================
045    54,943   53,725    48.2%    47.1%
047    66,419   64,426    48.7%    47.3%
052    48,688   44,402    49.7%    45.3%
065    39,040   36,949    49.2%    46.6%
102    37,549   28,844    54.5%    41.9%
105    31,723   23,639    55.2%    41.1%
107    34,364   25,234    55.5%    40.8%
113    36,116   30,540    52.4%    44.3%
114    42,043   35,411    52.6%    44.3%
115    38,704   30,803    53.5%    42.6%
135    36,487   35,845    48.6%    47.8%
136    52,576   43,535    52.0%    43.0%

Even with the erosion of support from the top of the ticket, Dems still held these districts at the Senate and RRC level. The gain were maintained. I know what the narrative for 2020 was, but it’s hard for me to see that as anything but a rousing success.

Precinct analysis: State House districts 2020, part 1

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020
State Senate district comparisons

Joe Biden carried 74 State House districts in 2020. That’s seven more than were won by Democratic candidates, but two fewer than Beto in 2018. Eight districts won by Biden were held by Republican incumbents, and there were two that were flipped one way or the other:


Dist    Biden    Trump   Biden%   Trump%
========================================
026    45,192   42,349    50.9%    47.7%
066    47,844   39,729    53.7%    44.6%
067    52,872   43,876    53.6%    44.5%
096    44,828   43,538    50.0%    48.6%
108    57,513   43,250    56.2%    42.3%
112    37,369   31,167    53.6%    44.7%
121    49,034   46,430    50.6%    47.9%
132    51,737   50,223    50.0%    48.5%
134    67,814   42,523    60.6%    38.0%
138    34,079   31,171    51.5%    47.1%

For comparison, here’s the analysis from 2018. The one Republican-held district that Beto won but Biden didn’t is HD64, which I’ll get to next. Biden won HD96, which Beto did not win. I have no idea how Morgan Meyer held on in HD108 with that strong a wind blowing against him, but you have to tip your cap. You also have to wonder how much longer he can do this – yes, I know, redistricting is coming, but Dallas is getting close to being Travis County at this point, and you just have to wonder how many seats winnable by Republicans there are if current trends continue. Note that Sarah Davis faced nearly the same conditions in 2020 as she had in 2018, except for having a stronger opponent. Meyer had the same opponent (Joanna Cattanach) as in 2018, and she raised good money, but he managed to win anyway.

I still don’t feel like we have a good understanding of why there were so many Biden/Republican voters. There’s been a lot done to try to explain why Republicans did better with Latino voters in 2020, while everyone is more or less taking it for granted that the stampede of former Republicans who are now voting Democratic is just part of the landscape. I look at these numbers and I am reminded of the same kind of splits we saw in 2016, when there were tons of people who voted for Hillary Clinton but then mostly voted Republican otherwise. I was skeptical of the optimism we had (at least initially) for CDs 07 and 32 and other districts because of those gaps, and then 2018 came along and erased those concerns. So what do we make of this? A last gasp of anti-Trump energy from people who still think of themselves (and vote like) Republicans, or a leading indicator of more to come in 2022? I wish I knew, and I wish there were people actively trying to find out. Note that doesn’t necessarily bring us closer to winning statewide, as Beto had a smaller margin than Biden did, but it does meant that the battle for the Legislature and Congress will continue to be heated, even with new maps.

Next up are the near misses, and the farther-out-but-still-within-sight districts that I had been keeping an eye on following 2018. Most of these are familiar:


Dist    Biden    Trump   Biden%   Trump%
========================================
014    30,188   33,690    45.9%    51.3%
028    60,101   63,906    47.8%    50.8%
029    45,951   51,494    46.5%    52.1%
054    35,995   36,093    48.9%    49.0%
064    42,908   46,093    47.2%    50.7%
092    39,262   39,386    49.0%    49.2%
093    40,679   43,897    47.3%    51.0%
094    37,375   38,724    48.3%    50.1%
097    41,007   42,494    48.2%    50.0%
122    57,972   68,621    45.2%    53.5%
126    36,031   38,651    47.6%    51.1%
133    43,263   47,038    47.3%    51.4%

032    31,699   38,011    44.7%    53.6%
070    53,870   75,198    40.9%    57.1%
084    24,928   34,575    41.1%    57.1%
085    34,743   43,818    43.6%    55.0%
089    45,410   55,914    44.0%    54.1%
106    59,024   70,752    44.8%    53.7%
129    38,941   47,389    44.4%    54.0%
150    42,933   55,261    43.1%    55.5%

Generally speaking, Beto did better in these districts than Biden did, which is consistent with Beto scoring higher overall, but not everywhere. Biden outpaced him in some more urban areas, like HDs 133, 122, and the aforementioned HD96. Usually where Beto did better it wasn’t by much, less than a point or so, but with bigger differences in less urban areas like HDs 14, 32, and 84. It may be that there was less-than-expected Republican turnout in 2018, so it’s hard to extrapolate to 2022, but it’s important to remember that the trend from 2016 is strongly Democratic in all of these places. And it’s happening in places you haven’t been paying attention to as well. HD70 may not look competitive, and I didn’t include it in the 2018 analysis (Beto got 40.4% there compared to 58.8% for Cruz), but in 2016 it was carried by Trump by a 61.6 to 32.2 margin. This district in northern Collin County used to be a landslide for Republicans, and now it’s on the long-range sensors for Democrats, in the same way that HDs 126 and 133 and 150 are.

Not everything is rainbows and puppies. There were two districts that Beto won and Biden lost. You can probably guess what kind of districts they were. Here they are, along with the other close and longer-term-something-to-think-about districts.


Dist    Biden    Trump   Biden%   Trump%
========================================
031    25,315   33,101    42.9%    56.1%
074    23,478   27,319    45.6%    53.1%

034    29,226   26,606    51.7%    47.0%
035    24,991   21,049    53.8%    45.3%
080    26,251   22,543    53.3%    45.8%

038    29,116   21,573    56.8%    42.1%
041    31,956   25,187    55.5%    43.7%
117    53,983   39,495    56.8%    41.6%
118    34,228   25,848    56.2%    42.4%
144    17,365   14,599    53.6%    45.0%

If you’ve been wondering why Reps like Ryan Guillen and Eddie Morales were voting for permitless carry and the bills to restrict cities’ ability to reduce police funding, that right there is the likely answer. Guillen has been around forever and likely was pretty safe even with that Trump surge, but Morales was defending an open seat. I don’t want to think about how much more obnoxious the media narrative of the 2020 election in Texas would have been had the Republicans flipped this one.

The three “near miss” districts, HDs 34, 35, and 80, look worrisome and will no doubt give the Republicans some ideas about what the 2022 map should look like, but keep two things in mind: One, as you will see in the next post, this was more of a Trump thing than anything else. Republicans did not do nearly as well farther down on the ballot. And two, nine of the Democratic “near miss” districts were closer than the 4.7 point margin in HD34. If the current map were to stay in place, we’d have more targets than they would.

The five longer-range districts don’t concern me much, especially the two Bexar County districts, where Biden had a higher percentage than Clinton in each and a bigger margin in HD117 (Clinton carried HD118 by a 55.1-40.0 margin). They were both closer than they were in 2018, but the overall trend in Bexar County is bluer.

Finally, here are the seats that the Democrats picked up in either 2016 (HD107) or 1028:


Dist    Biden    Trump   Biden%   Trump%
========================================
045    61,435   53,123    52.6%    45.5%
047    76,336   61,983    54.1%    43.9%
052    55,056   44,664    53.9%    43.7%
065    44,884   36,126    54.5%    43.9%
102    41,123   27,279    59.1%    39.2%
105    33,634   23,879    57.6%    40.9%
107    36,691   24,880    58.6%    39.8%
113    38,175   30,600    54.8%    43.9%
114    47,215   32,340    58.5%    40.1%
115    42,618   29,510    58.1%    40.3%
135    39,657   36,114    51.6%    47.0%
136    59,654   43,190    56.6%    40.9%

As we know, the narrative from the 2020 election is that Democrats went big trying to take over the State House and win a bunch of Congressional seats, but failed to do any of that and so the year was a big success for the Republicans. I don’t dispute the basic premise, but I feel like it’s only part of the story. Democrats did regain that State Senate seat they lost in the 2019 special election debacle, they won a State Board of Education seat for the first time in my memory, they won more appellate court benches, and they completed the flip of Fort Bend County. None of that gained much notice. More to the point, the Republicans had big plans to win back what they had lost in 2018, the year that they claimed was a huge fluke driven by Betomania and anti-Trump fervor. Yet they failed to retake CDs 07 and 32, and they only took back one of the 12 State House seats they had lost, which was balanced out by their loss of HD134, but somehow that’s never mentioned. They spent a ton of money on these races, Dave Carney was predicting they would gains seats overall, and they had expressed confidence in their ability to hold SD19. They not only failed broadly on all this, but Biden did better overall in the seats Beto carried in 2018, as the new Dem incumbents mostly cruised. Sometimes I wonder what the story would have been if Dems had won only six or seven seats in 2018, then picked up the others last year. Would we still think of 2020 as a failure that way? I have no idea.

So this is how things looked from a Presidential perspective. As we know, Biden ran ahead of the other Democrats on the statewide ballot, so you may be wondering how this looked from that viewpoint. The next entry in this series will be the State House districts for the Senate and Railroad Commissioner races. Tune in next time for the exciting followup to this very special episode.

Precinct analysis: State Senate district comparisons

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons
State Senate districts 2020

Let me start with some Twitter:

There’s more to the thread, but those are the bits I wanted to highlight. It’s true, as noted in the previous post, that Dems lost some ground in the Latino districts in 2020. You’ll see that here in a minute. But it’s also very much true that they gained a lot of votes elsewhere, in the more white districts. Some of those are the ones that flipped in 2018 or might have flipped in 2020 had they been on the ballot. Some were in places where Dems were already strong. Some were in districts that actually look to be competitive now, having not been so even four years ago. Why don’t I just show you the data?


Dist   1216R   1216D    1620R   1620D   1220R     1220D	Dem net
===============================================================
14    -9,951  56,887   26,677  97,954   16,726  154,841  138,115
08    -7,593  38,270   32,030  82,158   24,437  120,428   95,991
16   -22,137  35,202   21,611  58,302     -526   93,504   94,030
17   -19,619  38,114   34,892  56,566   15,273   94,680   79,407
25     3,422  37,037   65,613  95,402   69,035  132,439   63,404
07    -6,676  33,604   42,494  60,489   35,818   94,093   58,275
15    -6,708  27,545   28,163  48,882   21,455   76,427   54,972
10    -8,347  13,076   23,099  54,113   14,752   67,189   52,437
26    -2,174  20,179   20,009  44,154   17,835   64,333   46,498
09       -60  17,910   24,193  48,973   24,133   66,883   42,750
12    13,859  30,860   59,095  84,527   72,954  115,387   42,433
23    -3,003   3,751   13,010  43,679   10,007   47,430   37,423
29    -1,674  34,889   29,559  30,398   27,885   65,287   37,402
05    14,069  25,990   54,548  74,087   68,617  100,077   31,460
11     1,957  20,541   46,098  46,384   48,055   66,925   18,870
06    -4,554  20,223   21,712  13,637   17,158   33,860   16,702
13    -2,928      72   16,907  30,419   13,979   30,491   16,512
19    10,638  16,958   45,127  42,821   55,765   59,779    4,014
02    11,532  10,026   35,894  38,391   47,426   48,417      991

As discussed before, the columns represent the difference in vote total for the given period and party, so “1216” means 2012 to 2016, “1620” means 2016 to 2020, and “1220” means 2012 to 2020. Each column has a D or an R in it, so “1216R” means the difference between 2016 Donald Trump and 2012 Mitt Romney for the Presidential table, and so forth. In each case, I subtract the earlier year’s total from the later year’s total, so the “-9,951” for SD114 in the “1216R” column means that Donald Trump got 9,951 fewer votes in 2016 in SD14 than Mitt Romney got, and the “56,887” for SD14 in the “1216D” column means that Hillary Clinton got 56,887 more votes than Barack Obama got. “Dem net” at the end just subtracts the “1220R” total from the “1220D” total, which is the total number of votes that Biden netted over Obama. Clear? I hope so.

These are the districts where Dems gained over the course of these three elections. Lots of Republican turf in there, including the two D flips from 2018 and the two districts that both Biden and Beto carried but didn’t flip in 2018 (SDs 08 and 17), but the big gainer is that Democratic stronghold of SD14, where demography plus population growth plus a heavy duty turnout game led to a vast gain. Really, we Dems don’t appreciate Travis County enough. SD15, my district, has a nice showing as well, while SD26 is there to remind us that not all Latino districts went the way of the Valley.

We have the two 2018 flip districts, SDs 16, now practically a D powerhouse, and 10, which didn’t shift quite as much but was the most Dem-leaning Romney district from 2012 – you may recall, Wendy Davis won re-election there despite it going only 45% for Obama – and we have the two Biden-won Republican in 08 – who knew this one would shift so radically left – and 17. We’ve discussed SD07 before, and how it’s now teetering on swing status and won’t be of much use to the Republicans when they try to shore themselves up, but look at SD25, a district that has moved strongly left despite encompassing Comal County, the I-35 version of Montgomery. Look at the shifts in SD12, which is still not competitive but also not as big a GOP stronghold, and SD05, which has moved along with Williamson County. The key takeaway here is that more of the Senate is going to have to be centered on the Houston-San Antonio-D/FW triangle, and that part of the state is much more Democratic than it was a decade ago. This is the big problem Republicans have to solve.

Dems have some room to improve as well. I discussed SD13 in the Harris County reviews, and I believe there’s untapped potential in this district. It’s 80% Democratic to begin with, so improvements in turnout and voter registration are going to pay off in a big way. SD23 was more like 13 in 2016, but acquitted itself nicely in 2020. I suspect there are a lot of voters here who will need more contact and engagement in 2022. I know there were votes left on the table in 2018, and we need to be conscious of that.

Finally, there are three other Latino districts besides SD26 in this list. We’ve discussed SD06 before, which had a big uptick in Democrats while seeing fewer Republicans in 2016, then saw more Republicans turn out in 2020. In the end, the Dem percentage was basically the same in 2020 as in 2012, with a larger net margin, but the trend needs watching. SD19, which Dems took back in 2020 after that embarrassing special election loss, had a similar pattern as with SD06 except with a smaller net Republican gain in 2020. This district has a lot of border turf, which trended red in 2020, but it also has a good chunk of Bexar County, which got bluer and likely mitigated the overall shift. I feel like this district is more likely to drift in a Republican direction than SD06 is, but that will depend to some extent on how it’s redrawn. SD29, anchored in El Paso, had the same big Dem shift in 2016, then saw roughly equivalent gains by both parties in 2020. I think it’s more likely to get bluer over time, and there’s always room for Dem growth in El Paso, though as with SDs 13 and 23, it will require engagement.

Overall, these 19 districts represent a net gain of over 900K votes for Dems. Joe Biden collected about 600K more votes than 2012 Obama did, so there’s votes going the other way as well. Here are those districts:


Dist   1216R   1216D    1620R   1620D   1220R     1220D	Dem net
===============================================================
18    15,109  19,337   58,614  49,787   73,723   69,124  -4,599
04    10,564  14,667   54,680  39,023   65,244   53,690 -11,554
24    11,125   7,102   51,143  42,472   62,268   49,574 -12,694
21     9,828  13,573   43,738  26,297   53,566   39,870 -13,696
20     7,675  17,839   42,214  18,130   49,889   35,969 -13,920
22    17,969   6,092   48,183  37,910   66,152   44,002 -22,150
27     7,486  15,779   37,504   6,942   44,990   22,721 -22,269
28     6,727  -2,691   33,163  17,453   39,890   14,762 -25,128
31     6,956   3,954   36,050  10,696   43,006   14,650 -28,356
01    11,123  -6,966   34,452  17,623   45,575   10,657 -34,918
30    30,275   7,133   75,839  47,839  106,114   54,972 -51,142
03    20,610  -6,936   48,423  14,385   69,033    7,449 -61,584

Here’s the current Senate map, to remind you of where these districts are. SDs 22 and 24 have the most turf inside the big population triangle, while SD04 has most of its people there. SD22 currently includes Johnson and Ellis Counties, and it’s not too hard to imagine them beginning to trend blue over the next decade, while SD24 includes Bell and Coryell, which also have that potential.

I’m actually a little surprised to see that SDs 04 and 18 got a little bluer in 2016, before snapping back in 2020. I’ll have to take a closer look at them, on a county by county basis, to see what the big factors were. Fort Bend is going our way, and I have hope that we can make progress in Montgomery, and that’s going to be a big key to this decade.

The big Republican gainers, as noted in the last post, are mostly in East Texas and West Texas/the Panhandle, with SD03 including the north part of Montgomery. The main question will be how much of these districts will have to include the faster-growing parts of the state. That’s a calculation that won’t be very friendly to the incumbents, one way or another.

Finally, there are the three Latino districts, SDs 20, 21, and 27. All three followed the same pattern of a Dem gain in 2016 followed by a bigger Republican gain in 2020. SD27 remained solidly Democratic, while 20 and 21 are much closer to swing status though as noted in the previous post the incumbents all ran comfortably ahead of the pack. Republicans could certainly try to make a district more amenable to them out of this part of the state. How that would affect their other priorities, and how much of what we saw in 2020 continues past that year are the big questions. All other Dems carried these three districts as well, more or less at the same level as Biden. The good news for the Republicans then is that the new voters that Trump brought in were there for more than just him.

As you can see, there are fewer districts in which Dems lost ground, and the total number of votes they ceded is about a third of what they picked up elsewhere. You can see how G. Elliott Morris’ tweet thread applies here. As was the case with the State House and Congress, the Republican gerrymander of the State Senate in 2011 was very effective, until it wasn’t. It’s the same story here as it is for the other chambers, which is how do they assess the risk of a strategy that aims to gain them seats versus one that just aims to hold on to what they’ve got.

Next up will be a look at the State House district results from 2020. When the 2020 data for Congress and the SBOE finally show up, I’ll do the same for them as well. Let me know what you think.

Precinct analysis: State Senate districts 2020

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County
Harris County State Senate comparisons

Hey, look, we now have some 2020 district data. I found it all on the new Texas Legislative Council redistricting landing page. As of last week, when I went digging, only the State Senate and State House have 2020 data, so I’m going to spend a little time with them.

The 2020 State Senate election results by district are here. The first thing you need to know is that Joe Biden carried 15 of the 31 Senate districts. Here they are, in descending order of Biden’s percentage:


Dist    Biden    Trump   Biden%   Trump%
========================================
23    237,533   52,415    80.9%    17.8%
13    208,895   46,896    80.8%    18.1%
14    347,953  132,727    70.8%    27.0%
29    180,899   87,022    66.5%    32.0%
26    191,570   92,307    66.4%    32.0%
06    123,709   61,089    66.1%    32.6%
15    208,552  110,485    64.5%    34.1%
27    125,040   90,758    57.3%    41.6%
16    210,107  159,233    56.0%    42.5%
19    176,256  149,924    53.3%    45.3%
21    155,987  132,733    53.2%    45.3%
10    199,896  170,688    53.1%    45.4%
20    143,598  128,363    52.2%    46.6%
17    212,242  193,514    51.6%    47.0%
08    231,252  211,190    51.3%    46.9%

For the record, Beto carried the same fifteen districts in 2018. I’ll do a separate post on comparisons with other years, but I figured that was a thought many of you might have, so let’s address it here.

Only Biden carried the two Republican districts, SD08 and SD17. The range for other Democrats in SD08 was 46.4% (Chrysta Castaneda) to 48.1% (Elizabeth Frizell), and in SD17 from 46.5% (Gisela Triana) to 49.0% (Tina Clinton). Every Democrat got over 50% in each of the 13 Dem-held districts. This is consistent with what we’ve seen in Harris and Fort Bend Counties, where Biden outperformed the rest of the ticket by three or four points. For what it’s worth, we saw a very similar pattern in 2016, when Hillary Clinton ran ahead of other Dems, in some cases by quite a bit more. I’m thinking specifically of CDs 07 and 32, but there are other examples. My big question all throughout the 2018 cycle was whether those voters who voted for Clinton but otherwise generally voted Republican downballot would be inclined to vote for more Democrats that year, and judging by the results I’d say the answer was mostly Yes. We’ll have to see what happens this time around.

I’m sure you’ve noticed the lower-than-expected percentages in the Latino districts. SD20 is Chuy Hinojosa, and he won re-election by a 58.5% to 48.5% margin. SD21 is Judith Zaffirini, and she cruised 60.1% to 39.9%, while our old friend Eddie Lucio took SD27 64.8% to 35.2%. You may recall that in an earlier post on the Latino vote in 2020, one factor put forward for Trump’s better-than-expected performance was incumbency. As you can see, these incumbent Dems all ran comfortably ahead of Joe Biden. Now take a look at SD19, where Roland Gutierrez knocked out incumbent Pete Flores with a seemingly unimpressive 49.9% to 46.7% score. However much stock you put in the overall hypothesis, I’d say Flores’ incumbency helped him here. Not enough, thankfully. As for the two urban districts, SDs 06, 26, and 29, I’ve discussed SD06 before, so I’ll skip it. SD26 is basically on par with 2016, while SD29 slipped a bit from then but improved by a little bit over 2012. Again, I’ll get into more detail in a subsequent post.

Where Democrats really improved is in the whiter urban and suburban districts. SD14 was always a Democratic stronghold, but it really punched above its weight in 2020. No Republican district generated as many votes for Trump as SD14 did for Biden, and only one Republican district had a wider margin for Trump. We Dems maybe don’t appreciate Travis County as much as we should. I’ve discussed SD15 and how it went from a solid Dem district to a powerhouse in 2020. Look at SD16, which was a Dem takeover in 2018, and marvel at how Mitt Romney won it in 2012 with 57% of the vote. This is the kind of voting behavior shift that should have Republicans worried, and as you’ll see there’s more where that came from. Similar story at a lesser scale in SD10, which Trump carried in 2016 by a fraction of a point.

And then we have the two Republican districts that Biden carried. Both were battlegrounds in 2018, and I think the closeness of the race in SD08 was a genuine surprise to a lot of people, myself included. That’s a district that has shifted enormously, but it’s got more company than you might think. To understand that better, let’s look at the districts that Trump won, as above sorted by the percentage that Biden got.


Dist    Biden    Trump   Biden%   Trump%
========================================
09    161,000  166,632    48.3%    50.0%
25    256,178  302,919    45.1%    53.3%
07    188,150  232,201    44.1%    54.5%
05    199,253  250,002    43.4%    54.5%
12    211,292  270,287    43.2%    55.2%
11    161,818  232,156    40.4%    58.0%
02    138,917  208,774    39.4%    59.2%
18    161,933  271,898    36.8%    61.9%
22    128,415  253,102    33.2%    65.4%
04    142,522  281,331    33.2%    65.5%
24    126,340  257,861    32.3%    65.9%
30    121,646  329,601    26.5%    71.9%
01     92,593  265,715    25.5%    73.3%
28     76,925  222,872    25.3%    73.3%
03     77,364  294,559    20.6%    78.4%
31     59,684  229,768    20.3%    78.2%

Biden came within less than six thousand votes of taking a 16th Senate district, which would have been a majority. SD09 was Beto’s nearest miss for a sixteenth as well, though he came a little closer. The top five here for Biden are the same for Beto, with SDs 05 and 07 flipped; indeed, all of these districts are more or less sorted in the same way for both years.

I will have more numbers in the next post to show just how much movement there’s been, but in the meantime feel free to look at the 2012 district results and see for yourself just how uncompetitive these district used to be. The 2011 Senate map gerrymander was extremely effective, until all of a sudden it wasn’t. The Republicans will have some challenges ahead of them this fall.

There is of course some spare capacity for the Republicans to use, but it’s not as simple as it looks. Here’s the current map, to illustrate. None of SDs 01, 28, or 31 is anywhere near a Democratic stronghold. SDs 03 and 30 do border on Dem areas, and of course those other three districts can be sliced and diced to siphon off some Dem support, but it’s not quite that simple. For one thing, shifting the center of gravity in these districts from their rural centers towards the urban and suburban parts of the state means that their rural constituents – the Republican base – get less attention and power. They also increase the risk of a primary challenge from an opponent in a higher population area. I think playing defense will be a more urgent priority for the Republicans – they may try to carve out a more amenable South Texas district to capitalize on the Latino shift, but it’s not clear how persistent that will be, and there are still Voting Rights Act protections in place to guard against that, however tenuously – but maybe they could take a shot at Sen. Powell in SD10. As with the Congressional map, it’s a question of their risk tolerance as well as their appetite for gain. We’ll know in a few months.

Precinct analysis: State Senate comparisons

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3
Brazoria County

No, I had not planned to do any more of these, at least not until we got the statewide numbers. But then I got an email from Marc Campos on behalf of Sen. Carol Alvarado, who had seen the earlier comparison posts and wanted to know if I had those numbers for SD06. I didn’t at the time, but I do now thanks to getting the full jurisdiction data, so I went back and filled in the blanks. And so here we are.


Dist   Romney    Obama Johnson  Stein
=====================================
SD04   44,973   12,531     502    165
SD06   43,852   89,584   1,004    537
SD07  196,017   93,774   2,844    816
SD11   67,586   29,561   1,106    366
SD13   26,894  144,882   1,041    524
SD15   88,851  131,838   2,198    933
SD17  109,529   79,412   2,265    737
SD18    7,161    3,804      97     25

Dist    Trump  Clinton Johnson  Stein
=====================================
SD04   45,530   17,091   2,123    376
SD06   39,310  109,820   3,666  1,770
SD07  189,451  127,414  10,887  2,632
SD11   63,827   37,409   3,537    918
SD13   24,061  143,864   3,046  1,787
SD15   82,163  159,360   8,511  2,389
SD17   91,838  105,496   7,455  1,764
SD18    8,780    6,017     476    119

Dist    Trump    Biden     Lib    Grn
=====================================
SD04   55,426   25,561     936    145
SD06   61,089  123,708   1,577    770
SD07  232,201  188,150   4,746  1,216
SD11   77,325   51,561   1,605    389
SD13   38,198  166,939   1,474    753
SD15  110,485  208,552   3,444  1,045
SD17  110,788  140,986   2,706    720
SD18   15,118   12,735     331     91

Dist   Romney    Obama Johnson  Stein
=====================================
SD04   77.31%   21.54%   0.86%  0.28%
SD06   32.49%   66.37%   0.74%  0.40%
SD07   66.80%   31.96%   0.97%  0.28%
SD11   68.53%   29.97%   1.12%  0.37%
SD13   15.52%   83.58%   0.60%  0.30%
SD15   39.70%   58.90%   0.98%  0.42%
SD17   57.06%   41.37%   1.18%  0.38%
SD18   64.59%   34.31%   0.87%  0.23%

Dist    Trump  Clinton Johnson  Stein
=====================================
SD04   69.92%   26.25%   3.26%  0.58%
SD06   25.43%   71.05%   2.37%  1.15%
SD07   57.34%   38.57%   3.30%  0.80%
SD11   60.39%   35.39%   3.35%  0.87%
SD13   13.93%   83.27%   1.76%  1.03%
SD15   32.55%   63.13%   3.37%  0.95%
SD17   44.46%   51.07%   3.61%  0.85%
SD18   57.04%   39.09%   3.09%  0.77%

Dist    Trump    Biden     Lib    Grn
=====================================
SD04   67.54%   31.15%   1.14%  0.18%
SD06   32.64%   66.10%   0.84%  0.41%
SD07   54.47%   44.13%   1.11%  0.29%
SD11   59.08%   39.40%   1.23%  0.30%
SD13   18.42%   80.51%   0.71%  0.36%
SD15   34.15%   64.46%   1.06%  0.32%
SD17   43.41%   55.25%   1.06%  0.28%
SD18   53.47%   45.04%   1.17%  0.32%

I’ve limited the comparisons to the Presidential numbers from 2012 through 2020, which you see above, and the Senate numbers for 2012 and 2020, which I’ll present next. There wasn’t much difference between the Senate numbers and the RRC numbers, so I made this a little easier on myself. There’s nothing in this data that we haven’t seen and talked about before, but it’s worth taking a minute and reviewing it all again.

If we look at SD06, which is a heavily Latino district, you can see the increase in support for Trump from 2016 to 2020, which has been the story everyone has been talking about. I think it’s instructive to include the 2012 numbers, because the net change over the eight year period is basically zero from a percentage perspective – Obama carried SD06 by a 66-32 margin, while Biden carried it 66-33 – the vote gap increased by over 16K in the Dems’ favor. It’s true that Biden won SD06 by fewer votes than Hillary Clinton did, and that Trump closed the gap from 2016 by eight thousand votes, but the overall trend for this period is one that I find as a Democrat to be satisfactory. The overall direction is what I want, even if it’s not as fast as I’d like it to be. What happens next is the argument we’re all having, and there’s data to support either position. We’ll just have to see how it goes.

The flip side of that is what happened in SD07, Dan Patrick’s former district and one of the redder places in the state in 2012. Here, the trend is unmistakably in one direction. Mitt Romney’s SD07 was as Republican as SD06 was Democratic. Hillary Clinton shaved 41K off of the Dem deficit in 2016, and Joe Biden shrunk it by another 18K. In 2020, SD07 was only a ten-point GOP district. It would not be crazy to view it as a swing district, at least at the Presidential level, in 2024. I don’t know what the Republican redistricting plan is, but they’re not going to have a lot of spare capacity to borrow from in SD07. Just take a look at SD17 – which includes a lot of turf outside Harris County – to see why this make them a little nervous.

Finally, a few words about a couple of districts I don’t usually think about in these analyses, SD13 and SD15. The total number of votes in SD13 didn’t increase very much from 2012 to 2020 – indeed, it’s the one place I see where both Trump and Clinton got fewer votes than their counterparts in 2012 – and that is something I’d like to understand better. (For what it’s worth, Borris Miles got about 40K votes in Fort Bend in 2020, while Rodney Ellis got 32K in 2012. That’s a slightly higher growth rate than in Harris, but still kind of slow compared to other districts.) Trump 2020 snipped a couple of percentage points off Romney’s deficit, from down 68 to down 62, but that’s still a net 10K votes for Dems. As for SD15, it’s an example of a strong Democratic district that really stepped it up over the past eight years, performing in that way much like a lot of formerly dark red areas. Biden gained 55K net votes over Obama, as SD15 went from a 19 point Dem district to a 30 point Dem district. We’re going to need more like this around the state as we go forward.


Dist     Cruz   Sadler   MyersCollins
=====================================
SD04   44,387   12,129     849    408
SD06   45,066   84,671   1,701  1,364
SD07  194,269   90,258   4,579  2,116
SD11   66,327   28,875   1,736    779
SD13   27,839  139,516   1,866  1,357
SD15   88,594  127,006   3,709  2,178
SD17  107,576   76,803   3,396  1,801
SD18    7,135    3,637     175     78

Dist   Cornyn    Hegar     Lib    Grn
=====================================
SD04   56,085   23,380   1,405    393
SD06   59,310  115,620   3,609  2,257
SD07  237,216  173,948   7,682  2,796
SD11   77,887   47,787   2,508    854
SD13   39,386  157,671   3,502  2,149
SD15  114,616  195,264   6,065  2,657
SD17  118,460  128,628   3,892  1,603
SD18   15,268   11,859     554    180

Dist     Cruz   Sadler   MyersCollins
=====================================
SD04   76.30%   20.85%   1.46%  0.70%
SD06   33.39%   62.73%   1.26%  1.01%
SD07   66.20%   30.76%   1.56%  0.72%
SD11   67.26%   29.28%   1.76%  0.79%
SD13   16.06%   80.49%   1.08%  0.78%
SD15   39.58%   56.74%   1.66%  0.97%
SD17   56.05%   40.01%   1.77%  0.94%
SD18   64.35%   32.80%   1.58%  0.70%

Dist	Cornyn   Hegar     Lib    Grn
=====================================
SD04   69.02%   28.77%   1.73%  0.48%
SD06   32.80%   63.95%   2.00%  1.25%
SD07   55.64%   40.80%   1.80%  0.66%
SD11   60.36%   37.03%   1.94%  0.66%
SD13   19.43%   77.78%   1.73%  1.06%
SD15   35.43%   60.35%   1.87%  0.82%
SD17   46.42%   50.40%   1.53%  0.63%
SD18   54.80%   42.56%   1.99%  0.65%

The Senate numbers don’t tell us a whole lot that we didn’t already know, but do note that MJ Hegar slightly increased the percentage point gap in SD06, where it had shrunk by a point for Biden. That may be more a reflection of Paul Sadler’s candidacy than anything else, but I wanted to point it out. Hegar’s overall numbers are lesser than Biden’s, as we knew, but the same trends exist in the districts. If you never had the 2016 data for the Presidential race and only knew how things changed from 2012 to 2020 as you do with the Senate races, I wonder how people’s perceptions would differ.

This time I really mean it when I say that’s all she wrote. When we have the full numbers from the Texas Legislative Council I’ll have more to say, and then the real fun will begin when redistricting gets underway. (And by “fun” I mean “existential horror”, but you get the idea.) Let me know what you think.

Precinct analysis: Brazoria County

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2
Fort Bend, part 3

Once more around the block, this time in Brazoria County. Let’s just dive in:


Dist    Trump    Biden     Lib     Grn
======================================
CD14   44,480   19,715     823     160
CD22   45,953   42,513   1,037     257
				
HD25   38,939   16,277     727     132
HD29   51,494   45,951   1,133     285
				
CC1    19,383    8,439     407      72
CC2    22,456   17,024     494     106
CC3    24,355   12,614     496     102
CC4    24,239   24,151     463     137

Dist   Cornyn    Hegar     Lib     Grn
======================================
CD14   43,874   18,748   1,440     357
CD22   46,831   40,011   1,579     522
				
HD25   38,413   15,432   1,251     314
HD29   52,292   43,327   1,768     565
				
CC1    19,080    7,985     687     182
CC2    22,849   15,885     742     209
CC3    24,398   11,802     736     228
CC4    24,378   23,087     854     260

Dist   Wright    Casta     Lib     Grn
======================================
CD14   43,325   18,349   1,620     508
CD22   45,672   39,005   1,980     989
				
HD25   37,900   15,098   1,435     434
HD29   51,097   42,256   2,165   1,063
				
CC1    18,727    7,834     791     253
CC2    22,351   15,535     885     399
CC3    23,844   11,430     927     394
CC4    24,075   22,555     997     451

Dist    Trump    Biden     Lib     Grn
======================================
CD14   68.24%   30.25%   1.26%   0.25%
CD22   51.20%   47.36%   1.16%   0.29%
				
HD25   69.44%   29.03%   1.30%   0.24%
HD29   52.09%   46.48%   1.15%   0.29%
				
CC1    68.49%   29.82%   1.44%   0.25%
CC2    56.03%   42.48%   1.23%   0.26%
CC3    64.83%   33.58%   1.32%   0.27%
CC4    49.48%   49.30%   0.95%   0.28%

Dist   Cornyn    Hegar     Lib     Grn
======================================
CD14   68.11%   29.10%   2.24%   0.55%
CD22   52.65%   44.98%   1.78%   0.59%
				
HD25   69.33%   27.85%   2.26%   0.57%
HD29   53.39%   44.23%   1.80%   0.58%
				
CC1    68.30%   28.59%   2.46%   0.65%
CC2    57.58%   40.03%   1.87%   0.53%
CC3    65.65%   31.76%   1.98%   0.61%
CC4    50.18%   47.52%   1.76%   0.54%

Dist   Wright    Casta     Lib     Grn
======================================
CD14   67.91%   28.76%   2.54%   0.80%
CD22   52.11%   44.50%   2.26%   1.13%
				
HD25   69.08%   27.52%   2.62%   0.79%
HD29   52.91%   43.75%   2.24%   1.10%
				
CC1    67.84%   28.38%   2.87%   0.92%
CC2    57.06%   39.66%   2.26%   1.02%
CC3    65.16%   31.23%   2.53%   1.08%
CC4    50.07%   46.91%   2.07%   0.94%

As an extra point of comparison, here are the numbers from the four district races:


Weber     45,245  70.76%
Bell      18,700  29.24%

Nehls     44,332  50.51%
Kulkarni  38,962  44.39%
LeBlanc    4,477   5.10%

Vasut     38,936  71.38%
Henry     15,613  28.62%

Thompson  54,594  56.69%
Boldt     41,712  43.31%

Not really a whole lot to remark upon. Brazoria County has slowly shifted blue since 2012, but not by that much. There’s still a lot of work to be done there, and in the short term the most likely place where any effect would be felt is in the appellate courts. HD29 was a dark horse swing district following the 2018 election, but as you can see Rep. Ed Thompson punches above his weight, so it’s going to take more than some demography to seriously challenge him, and that’s assuming the Republicans don’t touch up his district a bit later on this year. I have no idea what Congressional districts will have a piece of Brazoria County going forward, but I’d bet that at least at the beginning they’re all some shade of red.

The main opportunity for Dems here is at the local level, where Commissioners Court Precinct 4 is pretty close to even. None of the county offices – Commissioners Court, Constable, Justice of the Peace – were challenged in 2020, so there’s the starting point to improve things on the ground and begin construction on a bench. That may change with redistricting as well, of course, but county elections can see change happen quickly under the right circumstances. My wish for Brazoria County is for there to be more activity at this level, starting next year.

Precinct analysis: Fort Bend County, part 3

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1
Fort Bend, part 2

We wrap up our look at Fort Bend County with a look at the three executive offices that were on the ballot – County Attorney, Sheriff, and Tax Assessor.


Dist   Rogers   Lawson Rogers% Lawson%
======================================
CD09   15,023   50,782  22.83%  77.17%
CD22  145,087  127,054  53.31%  46.69%
				
HD26   43,626   39,504  52.48%  47.52%
HD27   24,389   56,616  30.11%  69.89%
HD28   66,099   54,828  54.66%  45.34%
HD85   26,625   26,552  50.07%  49.93%
				
CC1    37,971   37,058  50.61%  49.39%
CC2    17,680   50,002  26.12%  73.88%
CC3    62,634   44,214  58.62%  41.38%
CC4    41,822   46,562  47.32%  52.68%


Dist    Nehls    Fagan  Nehls%  Fagan%
======================================
CD09   14,833   51,165  22.47%  77.53%
CD22  146,932  128,505  53.35%  46.65%
				
HD26   44,560   39,723  52.87%  47.13%
HD27   24,035   57,421  29.51%  70.49%
HD28   66,891   55,267  54.76%  45.24%
HD85   26,899   26,911  49.99%  50.01%
				
CC1    38,247   37,720  50.35%  49.65%
CC2    17,442   50,439  25.69%  74.31%
CC3    63,111   44,910  58.42%  41.58%
CC4    42,964   46,599  47.97%  52.03%


Dist Pressler   Turner  Press% Turner%
======================================
CD09   15,165   50,611  23.06%  76.94%
CD22  147,338  124,999  54.10%  45.90%
				
HD26   44,460   38,767  53.42%  46.58%
HD27   24,799   56,167  30.63%  69.37%
HD28   66,903   54,081  55.30%  44.70%
HD85   26,904   26,301  50.57%  49.43%
				
CC1    38,516   36,606  51.27%  48.73%
CC2    17,829   49,779  26.37%  73.63%
CC3    63,433   43,533  59.30%  40.70%
CC4    42,722   45,692  48.32%  51.68%

The most remarkable thing about these three races is the consistency. There’s less than a point of variance in the three races, in whichever district you look. That was not the case in Harris County, where Sheriff Ed Gonzalez ran well ahead of the pack, and where we often see a fairly wide range of results at the countywide level. Bridgette Smith-Lawson and Eric Fagan had identical percentages overall – there were about 3500 more votes cast in the Sheriff’s race, but the marginal voters broke for each candidate exactly as the overlapping voters had – and they both finished about 0.7 points ahead of Carmen Turner. I’ve often said that blowout races are boring to analyze because they don’t offer much insight into anything, but sometimes the same is true for close races. A few more people voted for James Pressler than for Steve Rogers, but not in a way that demonstrated any strengths or weaknesses on the part of anyone involved. Just one of those things, and it ultimately meant nothing as far as the outcome was concerned.

I’ve mentioned Commissioners Court Precinct 1 a few times, and here I should note that incumbent Commissioner Vincent Morales won with 52.30% of the vote, ahead of the other Republicans here indeed every other Republican in Fort Bend. Judicial candidate Maggie Jaramillo was next best in that district, with 52.17% of the vote. Another piece of evidence for the relative advantage that Latino Republicans had, in this election at least, and perhaps a cautionary tale for the 2024 campaign by Democrats to unseat Morales and cement a 4-1 membership on the Court. Morales’ incumbency and his appeal to independent/soft Dem Latino voters will make it that much harder to oust him. If the plan is to endanger him via the redistricting process, my advice is to add in a bit of buffer, because he will likely overperform the baseline.

That’s it for Fort Bend. I’ll try to work on Brazoria County next. Let me know what you think.

Precinct analysis: Fort Bend County, part 2

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE
Fort Bend, part 1

This post is going to focus on the judicial races in Fort Bend County. There are a lot of them – seven statewide, four appellate, five district and county – and I don’t want to split them into multiple posts because there’s not enough to say about them, nor do I want to present you with a wall of numbers that will make your eyes glaze over. So, I’m going to do a bit of analysis up top, then put all the number beneath the fold for those who want a closer look or to fact-check me. I’ll have one more post about the Fort Bend county races, and then maybe I’ll take a crack at Brazoria County, which will be even more manual labor than these posts were.

The point of interest at the statewide level is in the vote differentials between the three races that included a Libertarian candidate and the four races that did not. Just eyeballing the totals and bearing in mind that there’s some variance in each group, the Republican candidate got an increase of a bit more than half of the Libertarian vote total in each district, while the Democrats were more or less around the same level. That comports with the general thesis that Libertarians tend to take votes away from Republicans more than Democrats, though the effect here was pretty small. It’s also a small sample, and every county has its own characteristics, so don’t go drawing broad conclusions. For what it’s worth, there wasn’t anything here to contradict that piece of conventional wisdom.

For the appellate court races, the thing I have obsessed over is the incredibly small margin in the election for Chief Justice of the 14th Court of Appeals, which Jane Robinson lost by 1500 votes, or 0.06 percentage points. We saw in Harris County that she trailed the two victorious Democrats, Veronica Rivas-Molloy and Amparo Guerra, who were part of a trend in Harris County where Latino candidates generally out-performed the rest of the ticket. That wasn’t quite the case in Fort Bend. Robinson again trailed Rivas-Molloy by a little – in overall vote total, Robinson trailed Rivas-Molloy by about two thousand votes, while Republican Tracy Christopher did an equivalent amount better than Russell Lloyd. But unlike in Harris, Robinson outperformed Guerra, by about a thousand votes, and Guerra barely beat out Tamika Craft, who was farther behind the pack in Harris County. I don’t have a good explanation for that, it looks to me just like a weird result that has no obvious cause or correlation to what we saw elsewhere. It’s also the case, as we discussed in part one of the Fort Bend results, that if Dems had done a better job retaining voters downballot, none of this would matter all that much.

Finally, in the district court races (there were four of them, plus one county court), the results that grabbed my attention were in a couple of contests that appeared one after the other. Republican Maggie Jaramillo, running for the 400th District Court, was the closest member of Team GOP to win, as she lost to Tameika Carter by ten thousand votes. In the next race, for the 434th District Court, Republican Jim Shoemake lost to Christian Becerra by twenty-two thousand votes. This was the difference between a three-point loss for Jaramillo, and a six-and-a-half point loss for Shoemake. Jaramillo was the top performing Republican candidate in any race in Fort Bend, while Becerra was sixth best among Dems, trailing Joe Biden, three statewide judicial candidates, and Sheriff Eric Fagan. You may have noticed that they’re both Latinos, though the effect appears to have been a bit greater for the Republican Jaramillo. Becerra was the only Dem besides Biden to carry Commissioners Court Precinct 1, though that may not have been strictly a Latino candidate phenomenon – Elizabeth Frizell had the next highest percentage, with Veronica Rivas-Molloy and Tina Clinton close behind. (Amy Clark Meachum and Staci Williams, both in three-candidate races, came closer to carrying CC1 than any other candidates, but their percentage of the vote was lower.) Again, no broad conclusions here, just an observation.

Click on for the race data, and remember I had to piece this together by hand, so my numbers may be a little off from the official state totals when those come out. County races are next. Let me know what you think.

(more…)

RIP, Rep. Ron Wright

Condolences to his friends and family.

Rep. Ron Wright

U.S. Rep. Ron Wright, an Arlington Republican, has died.

His campaign staff announced the news Monday. Wright had lived for years with cancer and was diagnosed with COVID-19 in January. He was 67.

“His wife Susan was by his side and he is now in the presence of their Lord and Savior,” the statement said. “Over the past few years, Congressman Wright had kept a rigorous work schedule on the floor of the U.S. House of Representatives and at home in Texas’ Congressional District 6 while being treated for cancer. For the previous two weeks, Ron and Susan had been admitted to Baylor Hospital in Dallas after contracting COVID-19.”

Wright was diagnosed with lung cancer in late 2018, per the Fort Worth Star-Telegram. He was previously hospitalized in mid-September.

Wright was in his second term in the U.S. House, but he was no stranger to Congress or local politics. A fan of bow ties, Wright was a fixture in the Tarrant County political scene. In the late 1990s, Wright was a columnist for the Star-Telegram. In 2000, he shifted to the political arena to serve as former U.S. Rep. Joe Barton’s district director and as an at-large member of the Arlington City Council through 2008. From 2004-08, Wright held the post of mayor pro tempore.

[…]

The district is historically Republican, but Democrats made some effort to challenge the district in the last two cycles. Even so, Wright won reelection by a 9-percentage-point margin in 2020.

There will be a special election at some point for this seat, and it should be pretty competitive. CD06 was carried by Trump by a 51-48 margin in 2020; Joe Biden’s performance there closely matches Beto’s 48% in 2018. Trump had won CD06 by a 54-42 margin in 2016, so this was a big shift in the Dem direction, with Tarrant County leading the way. CD06 was low on the Dem target list in 2020, but I expect it to get a lot more attention in 2021. If this develops as a D versus R runoff, look for a lot of money to be spent on it.

That’s for another day. Today we mourn the passing of Rep. Ron Wright. May he rest in peace.

Precinct analysis: Fort Bend County, part 1

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk
HCDE

I’ve finally run out of Harris County races from 2020 to analyze, so let’s move over to Fort Bend County. I’ve said before that while Fort Bend provides downloadable Excel files on their county elections page, they format these results in a way that makes it harder for me to do the same analysis I do with Harris County. Basically, Harris County puts all the results on one worksheet, with the totals for every candidate given in each precinct. For district races, that means a blank in the results when the precinct in question is not in that district, but the cell for that district is there. That makes it super easy for me to use Excel functions to add up the vote totals for, say, the Presidential candidates in the precincts where, say, the HD134 voters are. I can do practically every race in a matter of an hour or two, and indeed I spend more time formatting the blog posts than I do the calculations.

Fort Bend, on the other hand, separates each race into its own worksheet, which is fine in and of itself, except that for district races they only include the precincts for that race on the worksheet in question. That completely nullifies the formulas I use for Harris County, and when I went and looked to see how I did it in 2016, I saw that I manually added the relevant cells for each of the countywide races, an approach that is inelegant, labor intensive, and prone to error. But it was the best I could do, so I did it again that way here. I can tell you that my results are not fully accurate, and I know this because the subtotals don’t add up correctly, but they’re close enough to suffice. The one exception is for the County Commissioner precincts, which are fully grouped together in Fort Bend – each precinct number is four digits, with the first digit being a one, two, three, or four, and that first digit is the Commissioner precinct. So those at least are easy to add up correctly. The rest is messy, but I did the best I could. When the official state reports come out in March and they’re off from mine, you’ll know why.

Anyway. That’s a lot of minutia, so let’s get to the numbers.


Dist    Trump    Biden    Lib    Grn
====================================
CD09   15,527   52,998    414    292
CD22  142,191  142,554  2,614    799
				
HD26   42,389   45,097    743    283
HD27   24,191   59,921    576    296
HD28   65,043   61,103  1,212    313
HD85   26,661   29,016    503    197
				
CC1    37,765   40,253    699    261
CC2    18,054   52,525    441    307
CC3    61,437   49,976  1,120    247
CC4    40,460   52,798    768    276

Dist   Trump%   Biden%   Lib%   Grn%
====================================
CD09   22.43%   76.55%  0.60%  0.42%
CD22   49.34%   49.47%  0.91%  0.28%
				
HD26   47.89%   50.95%  0.84%  0.32%
HD27   28.47%   70.51%  0.68%  0.35%
HD28   50.95%   47.86%  0.95%  0.25%
HD85   47.29%   51.47%  0.89%  0.35%
				
CC1    47.82%   50.97%  0.89%  0.33%
CC2    25.31%   73.64%  0.62%  0.43%
CC3    54.48%   44.31%  0.99%  0.22%
CC4    42.90%   55.99%  0.81%  0.29%


Dist   Cornyn    Hegar    Lib    Grn
====================================
CD09   15,345   49,730  1,082    639
CD22  145,632  129,254  4,277  1,473
				
HD26   43,650   40,478  1,264    506
HD27   24,695   55,984  1,308    672
HD28   66,532   55,483  1,859    580
HD85   26,653   26,678    949    355
				
CC1    38,088   37,124  1,318    447
CC2    17,948   49,130  1,123    626
CC3    63,061   45,045  1,614    489
CC4    41,877   47,685  1,304    550

Dist  Cornyn%   Hegar%   Lib%   Grn%
====================================
CD09   22.97%   74.45%  1.62%  0.96%
CD22   51.89%   46.06%  1.52%  0.52%
				
HD26   50.82%   47.12%  1.47%  0.59%
HD27   29.88%   67.73%  1.58%  0.81%
HD28   53.46%   44.58%  1.49%  0.47%
HD85   48.78%   48.83%  1.74%  0.65%
				
CC1    49.48%   48.23%  1.71%  0.58%
CC2    26.08%   71.38%  1.63%  0.91%
CC3    57.22%   40.87%  1.46%  0.44%
CC4    45.81%   52.16%  1.43%  0.60%

Dist   Wright    Casta    Lib    Grn
====================================
CD09   14,727   50,118    923    769
CD22  142,842  125,932  4,794  2,479
				
HD26   42,848   39,268  1,367    860
HD27   23,874   55,827  1,267    850
HD28   65,253   54,232  2,115  1,011
HD85   26,165   26,418    968    521
				
CC1    37,302   36,877  1,341    640
CC2    17,328   49,299    984    776
CC3    61,909   43,760  1,924    863
CC4    41,027   46,114  1,468    969

Dist  Wright%   Casta%   Lib%	Grn%
====================================
CD09   22.13%   75.32%  1.39%  1.16%
CD22   51.75%   45.62%  1.74%  0.90%
				
HD26   50.80%   46.56%  1.62%  1.02%
HD27   29.18%   68.23%  1.55%  1.04%
HD28   53.22%   44.23%  1.72%  0.82%
HD85   48.39%   48.86%  1.79%  0.96%
				
CC1    48.98%   48.42%  1.76%  0.84%
CC2    25.34%   72.09%  1.44%  1.13%
CC3    57.08%   40.35%  1.77%  0.80%
CC4    45.80%   51.48%  1.64%  1.08%

The first number to consider is not about any of the districts. It’s simply this: John Cornyn received 3K more votes in Fort Bend County than Donald Trump did, but MJ Hegar got over 16K fewer votes than Joe Biden. Jim Wright got about as many votes as Trump did, but Chrysta Castaneda got 19K fewer votes than Biden. That trend continued in the district races as well. Troy Nehls got 2K more votes than Trump did in CD22, while Sri Kulkarni got 19K fewer votes. Jacey Jetton got a thousand more votes than Trump did in HD26, while Sarah DeMerchant got 4,500 fewer votes than Biden did. Biden clearly got a few Republican crossover votes, but by far the difference between his performance and everyone else’s on the ballot was that there was a significant number of people who voted for Joe Biden and then didn’t vote in other races. That was just not so on the Republican side.

I don’t have a single explanation for this. It’s a near reverse of what happened in Harris County in 2004, when George Bush clearly got some Democratic crossovers, but by and large there were a lot of Bush-only voters, while the folks who showed up for John Kerry generally stuck around and voted for the other Dems. I don’t think what happened here in Fort Bend is a function of straight ticket voting, or its removal in this case, because there’s a world of difference between someone who picks and chooses what races to vote in and someone who votes for President and then goes home – I just don’t believe that latter person would have selected the “straight Democratic” choice if it had been there. In 2004, my theory was that Bush was a brand name candidate who drew out more casual voters who didn’t really care about the other races, while Kerry voters were more hardcore. I don’t buy that here because if anything I would have expected the Trump voters to be more likely to be one and done. It’s a mystery to me, but it’s one that state and Fort Bend Democrats need to try to figure out. At the very least, we could have won HD26, and we could have elected Jane Robinson to the 14th Court of Appeals if we’d done a better job downballot here.

One other possibility I will mention: Sri Kulkarni wrote an article in the Texas Signal that analyzed his loss and cited a large disinformation campaign against him that contributed to his defeat. That may be a reason why the Libertarian candidate did as well as he did in that race. I don’t doubt Kulkarni’s account of his own race, but I hesitate to fully accept this explanation. Dems had a larger dropoff of the vote in CD09 as well – about 3K fewer votes for Hegar and Castaneda, less than 1K fewer for Cornyn and Wright – and the dropoff in CD22 was pretty consistent for other Dems as well, though Kulkarni did generally worse. It may have moved the needle somewhat against him, but it doesn’t explain what happened with other Dems. Again, someone with more time and resources available to them – the TDP, in particular – should do a deeper dive on this. I do believe that disinformation was an issue for Dems last year, and will be an increasing problem going forward, and we need to get our arms around that. I just believe there were other causes as well, and we need to understand those, too.

One more thing: Kulkarni ran a lot closer to the Biden standard in Harris County than he did in Fort Bend. Biden and Trump were virtually tied in CD22 in Harris County, with the vote going 21,912 for Trump to 21,720 for Biden; Nehls defeated Kulkarni 20,953 to 19,743 in Harris. That’s the kind of result that one can easily attribute to Biden crossovers, and doesn’t raise any flags about the level of undervoting. I haven’t looked at Brazoria County yet, but my point here is just that Fort Bend County was very different in its behavior than Harris County was. And again, for the Nth time, we need to understand why. That is the point I’m trying to sledgehammer home.

Moving on, HD28 was a steeper hill to climb than perhaps we thought it would be. Eliz Markowitz got about 1,500 fewer votes than MJ Hegar did, and about 300 fewer than Castanada, while Gary Gates outperformed both Jim Wright and John Cornyn. It should be noted that while Dems in general lost HD28 by 20 points or so in 2016, Markowitz and other Dems were losing it by ten or eleven points in 2020. In total vote terms, a gap of 16-18K votes in 2016 was reduced to 12-13K votes in 2020. The shift is real, and even if it didn’t net us any extra seats, it’s still there.

The other way that shift manifested was in the County Commissioner precincts. In 2016, Republicans won three of the four precincts, with two-term Democrat Richard Morrison in Precinct 1 finally getting unseated after he had won against badly tainted opponents in previous years. There was a lot of movement in the Dem direction in Precinct 4, however, and that came to fruition in 2018 when Ken DeMerchant (yes, Sarah’s husband) flipped that seat. As you can see, there was no retreat in CC4 in 2020, and it probably wouldn’t take too much tinkering to make Precinct 1 a fifty-fifty or better proposition for Dems. It didn’t happen in either county this year, but in 2024, aided by demography and maybe a bit of gerrymandering, both Harris and Fort Bend counties can have 4-1 Democratic majorities on their Commissioners Courts.

I do have totals for the other Fort Bend races, though they’re not dramatically different from what you see here. I will put them together in a future post just to have it on the record. As always, let me know what you think.

Precinct analysis: HCDE

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor
County Clerk

There are three HCDE At Large positions, which are elected countywide. Two were on the ballot this year, to run against Republicans who had won those seats in 2014. (The other At Large position was elected in 2018.) These are the last countywide elections on the ballot, so they’re way at the bottom – other county positions, like Commissioner and JP and Constable come next, then municipal/school board/MUD, if any. There are no money in these races. People don’t know much about them, and tend to vote on party lines. I say all this to say that there ought not to be that much variance in these races. And yet, as you will see from the two HCDE At Large races we had, there was some.


Dist	Wolfe	Davis   Wolfe%  Davis%
======================================
CD02  175,106  157,537  52.64%  47.36%
CD07  146,573  152,854  48.95%  51.05%
CD08   25,370   15,298  62.38%  37.62%
CD09   36,041  121,236  22.92%  77.08%
CD10  100,960   60,861  62.39%  37.61%
CD18   56,070  182,708  23.48%  76.52%
CD22   21,105   20,600  50.61%  49.39%
CD29   46,743  104,044  31.00%  69.00%
CD36   81,230   49,211  62.27%  37.73%
				
SBOE4 100,609  341,191  22.77%  77.23%
SBOE6 374,142  356,723  51.19%  48.81%
SBOE8 214,447  166,436  56.30%  43.70%
				
SD04   54,897   23,241  70.26%  29.74%
SD06   54,521  120,734  31.11%  68.89%
SD07  231,012  175,107  56.88%  43.12%
SD11   75,587   47,839  61.24%  38.76%
SD13   35,736  161,092  18.16%  81.84%
SD15  109,068  197,941  35.53%  64.47%
SD17  113,430  126,454  47.29%  52.71%
SD18   14,947   11,944  55.58%  44.42%
				
HD126  38,074   34,059  52.78%  47.22%
HD127  53,126   35,952  59.64%  40.36%
HD128  47,466   22,448  67.89%  32.11%
HD129  46,738   35,812  56.62%  43.38%
HD130  69,090   32,953  67.71%  32.29%
HD131   9,532   45,049  17.46%  82.54%
HD132  49,533   49,013  50.26%  49.74%
HD133  48,999   36,952  57.01%  42.99%
HD134  46,177   58,556  44.09%  55.91%
HD135  35,508   37,663  48.53%  51.47%
HD137   9,978   21,062  32.15%  67.85%
HD138  30,859   31,585  49.42%  50.58%
HD139  14,830   45,543  24.56%  75.44%
HD140   8,732   22,411  28.04%  71.96%
HD141   6,588   36,582  15.26%  84.74%
HD142  13,241   42,323  23.83%  76.17%
HD143  11,319   24,910  31.24%  68.76%
HD144  13,293   17,049  43.81%  56.19%
HD145  14,250   27,573  34.07%  65.93%
HD146  10,685   43,855  19.59%  80.41%
HD147  14,345   53,881  21.03%  78.97%
HD148  21,042   37,730  35.80%  64.20%
HD149  20,950   31,202  40.17%  59.83%
HD150  54,842   40,186  57.71%  42.29%
				
CC1    87,740  284,053  23.60%  76.40%
CC2   146,425  148,116  49.71%  50.29%
CC3   220,829  213,731  50.82%  49.18%
CC4   234,204  218,452  51.74%  48.26%
				
JP1    87,700  167,753  34.33%  65.67%
JP2    32,838   50,056  39.61%  60.39%
JP3    50,303   69,274  42.07%  57.93%
JP4   229,535  188,368  54.93%  45.07%
JP5   197,764  218,253  47.54%  52.46%
JP6     7,567   27,643  21.49%  78.51%
JP7    17,310  101,368  14.59%  85.41%
JP8    66,181   41,637  61.38%  38.62%

Dist  Sumners    BrownSumners%  Brown%
======================================
CD02  178,239  153,781  53.68%  46.32%
CD07  149,276  149,677  49.93%  50.07%
CD08   25,684   14,930  63.24%  36.76%
CD09   37,140  119,868  23.65%  76.35%
CD10  102,002   59,509  63.15%  36.85%
CD18   58,363  179,885  24.50%  75.50%
CD22   21,470   20,157  51.58%  48.42%
CD29   48,719  101,542  32.42%  67.58%
CD36   82,330   47,970  63.18%  36.82%
				
SBOE4 104,920  335,772  23.81%  76.19%
SBOE6 380,664  348,912  52.18%  47.82%
SBOE8 217,639  162,636  57.23%  42.77%
				
SD04   55,470   22,553  71.09%  28.91%
SD06   56,723  117,949  32.47%  67.53%
SD07  234,209  171,238  57.77%  42.23%
SD11   76,651   46,635  62.17%  37.83%
SD13   36,983  159,472  18.83%  81.17%
SD15  112,316  193,986  36.67%  63.33%
SD17  115,691  123,829  48.30%  51.70%
SD18   15,180   11,660  56.56%  43.44%
				
HD126  38,802   33,248  53.85%  46.15%
HD127  53,889   35,026  60.61%  39.39%
HD128  47,977   21,854  68.70%  31.30%
HD129  47,448   34,995  57.55%  42.45%
HD130  69,768   32,168  68.44%  31.56%
HD131   9,953   44,558  18.26%  81.74%
HD132  50,241   48,064  51.11%  48.89%
HD133  49,739   36,091  57.95%  42.05%
HD134  47,419   57,143  45.35%  54.65%
HD135  36,083   36,890  49.45%  50.55%
HD137  10,151   20,831  32.76%  67.24%
HD138  31,484   30,891  50.48%  49.52%
HD139  15,396   44,842  25.56%  74.44%
HD140   9,181   21,845  29.59%  70.41%
HD141   7,029   36,060  16.31%  83.69%
HD142  13,760   41,694  24.81%  75.19%
HD143  11,837   24,277  32.78%  67.22%
HD144  13,736   16,529  45.39%  54.61%
HD145  14,723   26,947  35.33%  64.67%
HD146  11,056   43,390  20.31%  79.69%
HD147  14,922   53,129  21.93%  78.07%
HD148  21,679   36,894  37.01%  62.99%
HD149  21,361   30,695  41.03%  58.97%
HD150  55,588   39,258  58.61%  41.39%
				
CC1    91,042  279,998  24.54%  75.46%
CC2   149,445  144,410  50.86%  49.14%
CC3   224,188  209,572  51.68%  48.32%
CC4   238,548  213,342  52.79%  47.21%
				
JP1    90,547  164,215  35.54%  64.46%
JP2    33,772   48,840  40.88%  59.12%
JP3    51,467   67,910  43.11%  56.89%
JP4   233,006  184,205  55.85%  44.15%
JP5   201,206  214,079  48.45%  51.55%
JP6     7,975   27,140  22.71%  77.29%
JP7    18,116  100,374  15.29%  84.71%
JP8    67,134   40,559  62.34%  37.66%

As noted above, there are no 2016 races to compare to, so this is what we have. And what we have is Erica Davis doing a bit better against Bob Wolfe (no, not Michael Wolfe, he ran for a JP slot and lost in the primary) than David Brown did against Don Sumners. Davis got 864K votes, putting her in the upper echelon of Dems, while Brown got 847K, more in the middle. (Sumners got 14K more votes than Wolfe; there were 3K more undervotes in that race.) That translated to two points in the percentages – Davis won 55.6 to 44.4, while Brown won 54.6 to 45.4. Davis’ performance is reflected in the districts – she carried HD138 and CC2, and came close in HD132. Brown was fine, it’s just that Davis did better.

So the question is why? There are two obvious possibilities. One is that Sumners was a more familiar name – he had won the seat in 2014, and was elected Tax Assessor in 2010, so this was the third time in recent years he had been on a countywide ballot. (Sumners had also been Treasurer in the 90s, but no one is going to remember that.) Maybe that familiarity got him a few votes. The other possibility is that Davis was the only female candidate among the four, and she drew some extra votes because of that. There’s no way to know, and a sample size of one is far too small to draw any conclusions scientifically. The point here is just what I said up front – even in these similar races, there can be and will be some variance in the voting. Stuff like this is why I find these trips through the numbers so fascinating. You just never know what you’ll find.

That’s it for my tour of Harris County in the 2020 elections. I have the Fort Bend County data from their election results page, and while they are kind enough to provide a full Excel canvass, they do it in a weird way that forces me to do these calculations all over again. I’m working on it and will have a report or two from Fort Bend shortly. I hope you enjoyed this series.

Precinct analysis: County Clerk 2020 and 2018

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff
Tax Assessor

We weren’t supposed to have a County Clerk race on the ballot in 2020, but we did following the health-related resignation of Diane Trautman in May. That gave us a battle of Stan Stanart, former County Clerk whom Trautman had deposed in 2018, and Teneshia Hudspeth, former chief elections person under Stanart. Hudspeth won easily, and though her 835K total votes were on the lower end for Democratic countywide candidates, her 53.76% of the vote was pretty close to Trautman’s 54.60% from two years before. The 2018 election was a non-Presidential year, with record turnout for such a contest, and the 2018 Clerk race also featured a Libertarian candidate, so comparisons are a bit tricky. My advice is to look at Hudspeth’s percentages compared to Trautman’s. Here’s the 2020 race:


Dist  Stanart Hudspeth Stanart% Hudspeth%
=========================================
CD02  181,707  151,509   54.53%    45.47%
CD07  153,335  147,437   50.98%    49.02%
CD08   26,037   14,710   63.90%    36.10%
CD09   37,941  119,087   24.16%    75.84%
CD10  103,442   58,506   63.87%    36.13%
CD18   60,497  178,172   25.35%    74.65%
CD22   22,018   19,747   52.72%    47.28%
CD29   50,483   99,634   33.63%    66.37%
CD36   83,484   47,160   63.90%    36.10%
				
SBOE4 108,536  332,265   24.62%    75.38%
SBOE6 389,609  343,285   53.16%    46.84%
SBOE8 220,799  160,413   57.92%    42.08%
				
SD04   56,013   22,252   71.57%    28.43%
SD06   58,816  115,690   33.70%    66.30%
SD07  237,989  168,687   58.52%    41.48%
SD11   77,992   45,722   63.04%    36.96%
SD13   38,148  158,482   19.40%    80.60%
SD15  115,748  191,422   37.68%    62.32%
SD17  118,870  122,163   49.32%    50.68%
SD18   15,368   11,547   57.10%    42.90%
				
HD126  39,346   32,856   54.49%    45.51%
HD127  54,464   34,684   61.09%    38.91%
HD128  48,497   21,457   69.33%    30.67%
HD129  48,407   34,399   58.46%    41.54%
HD130  70,686   31,495   69.18%    30.82%
HD131  10,184   44,299   18.69%    81.31%
HD132  51,079   47,460   51.84%    48.16%
HD133  51,079   35,518   58.98%    41.02%
HD134  49,424   56,156   46.81%    53.19%
HD135  36,914   36,293   50.42%    49.58%
HD137  10,430   20,635   33.57%    66.43%
HD138  32,119   30,383   51.39%    48.61%
HD139  15,914   44,364   26.40%    73.60%
HD140   9,567   21,385   30.91%    69.09%
HD141   7,122   35,961   16.53%    83.47%
HD142  14,114   41,357   25.44%    74.56%
HD143  12,295   23,775   34.09%    65.91%
HD144  13,990   16,257   46.25%    53.75%
HD145  15,404   26,341   36.90%    63.10%
HD146  11,411   43,173   20.91%    79.09%
HD147  15,494   52,686   22.73%    77.27%
HD148  22,919   35,897   38.97%    61.03%
HD149  21,718   30,328   41.73%    58.27%
HD150  56,366   38,803   59.23%    40.77%
				
CC1    94,155  277,561   25.33%    74.67%
CC2   152,576  141,645   51.86%    48.14%
CC3   229,070  206,538   52.59%    47.41%
CC4   243,143  210,221   53.63%    46.37%
				
JP1    94,708  161,313   36.99%    63.01%
JP2    34,728   47,948   42.00%    58.00%
JP3    52,202   67,235   43.71%    56.29%
JP4   236,302  181,977   56.49%    43.51%
JP5   205,591  211,174   49.33%    50.67%
JP6     8,522   26,546   24.30%    75.70%
JP7    18,695   99,939   15.76%    84.24%
JP8    68,196   39,833   63.13%    36.87%

Nothing we haven’t seen before by this point. It’s possible Stanart did a little better than expected because of name recognition, but who can tell. The 2018 analysis was part of a package deal. Here’s the County Clerk’s race on its own:


Dist  Stanart Trautman  Gomez  Under Stanart%   Traut%  Gomez%
==============================================================
CD02  135,427  116,744  6,717  6,221   52.31%   45.09%   2.59%
CD07  116,383  116,488  5,648  6,706   48.79%   48.84%   2.37%
CD08   17,784   10,221    679    520   62.00%   35.63%   2.37%
CD09   23,329   93,625  2,504  2,376   19.53%   78.37%   2.10%
CD10   71,172   39,707  2,623  1,970   62.71%   34.98%   2.31%
CD18   39,159  138,311  4,892  4,087   21.47%   75.84%   2.68%
CD22   15,265   15,184    857    711   48.76%   48.50%   2.74%
CD29   30,313   82,449  3,916  2,627   25.98%   70.66%   3.36%
CD36   60,467   35,918  2,452  2,036   61.18%   36.34%   2.48%

SBOE6 287,300  269,837 14,477 15,045   50.26%   47.21%   2.53%

HD126  29,277   24,586  1,293  1,074   53.08%   44.58%   2.34%
HD127  41,017   25,198  1,634  1,260   60.45%   37.14%   2.41%
HD128  34,735   15,876  1,142    915   67.12%   30.68%   2.21%
HD129  35,567   26,799  1,739  1,582   55.48%   41.80%   2.71%
HD130  51,064   22,942  1,722  1,365   67.43%   30.30%   2.27%
HD131   6,110   34,855    864    717   14.61%   83.33%   2.07%
HD132  32,579   32,090  1,680  1,023   49.10%   48.37%   2.53%
HD133  40,721   28,089  1,552  2,192   57.87%   39.92%   2.21%
HD134  37,977   47,211  2,090  3,692   43.51%   54.09%   2.39%
HD135  26,584   27,712  1,379  1,033   47.75%   49.77%   2.48%
HD137   7,257   16,167    678    552   30.11%   67.08%   2.81%
HD138  23,336   23,515  1,257  1,100   48.51%   48.88%   2.61%
HD139  10,545   35,238  1,128    961   22.48%   75.12%   2.40%
HD140   5,269   17,569    722    490   22.36%   74.57%   3.06%
HD141   3,921   26,852    622    438   12.49%   85.53%   1.98%
HD142   8,579   30,125    850    662   21.69%   76.16%   2.15%
HD143   7,405   20,178    952    699   25.95%   70.71%   3.34%
HD144   8,949   13,629    786    450   38.30%   58.33%   3.36%
HD145   9,596   21,809  1,226    834   29.41%   66.84%   3.76%
HD146   8,082   34,044    931  1,065   18.77%   79.07%   2.16%
HD147  10,013   42,972  1,576  1,316   18.35%   78.76%   2.89%
HD148  15,587   29,671  1,907  1,695   33.05%   62.91%   4.04%
HD149  14,042   23,985    859    785   36.11%   61.68%   2.21%
HD150  41,087   27,535  1,699  1,354   58.43%   39.16%   2.42%

CC1    61,603  218,965  6,875  6,563   21.43%   76.18%   2.39%
CC2   105,901  114,124  6,772  5,028   46.69%   50.32%   2.99%
CC3   164,601  157,515  7,843  8,035   49.89%   47.74%   2.38%
CC4   177,194  158,043  8,798  7,628   51.50%   45.94%   2.56%

I included undervotes in the county candidates’ analyses in 2018 because I was trying to analyze the effects of straight ticket voting as well. As I said, if you compare just the Democratic candidates’ percentages, you see that Hudspeth and Trautman had fairly similar performances, with the drops we have noted before in some of the Latino districts. Trautman knocked it out of the park in HD134, which was more Republican in 2018. Hudspeth had among the higher scores this year in HDs 131 and 141. I fully expect she’ll build on her performance in 2022, when she will be the incumbent running for re-election, though as always the first question is what will the national atmosphere look like.

Precinct analysis: Presidential results by Congressional district

From Daily Kos Elections, the breakdown of how Presidential voting went in each of Texas’ 36 Congressional districts:

Two districts did in fact flip on the presidential level: Trump lost the 24th District in the Dallas-Fort Worth suburbs while recapturing the 23rd District along the border with Mexico. Biden, however, made major gains in a number of other suburban districts and nearly won no fewer than seven of them. Trump, meanwhile, surged in many heavily Latino areas and likewise came close to capturing three, but except for the 24th, every Trump seat is in GOP hands and every Biden seat is represented by Democrats. The 24th, which includes the suburbs north of Dallas and Fort Worth, is a good place to start because it saw one of the largest shifts between 2016 and 2020. The district began the decade as heavily Republican turf—it backed Mitt Romney 60-38—but Trump carried it by a substantially smaller 51-44 margin four years later.

Biden continued the trend and racked up a 52-46 win this time, but the area remained just red enough downballot to allow Republican Beth Van Duyne to manage a 49-47 victory in an expensive open-seat race against Democrat Candace Valenzuela.

Biden fell just short of winning seven other historically red suburban seats: the 2nd, 3rd, 6th, 10th, 21st, 22nd, and 31st, where Trump’s margins ranged from just one to three points and where the swings from 2016 ranged from seven points in the 22nd all the way to 13 points in the 3rd, the biggest shift in the state. However, as in the 24th, Biden’s surge did not come with sufficient coattails, as Republicans ran well ahead of Trump in all of these seats. (You can check out our guide for more information about each district.)

Two seats that Democrats flipped in 2018 and stayed blue last year also saw large improvements for Biden. The 7th District in west Houston, parts of which were once represented by none other than George H.W. Bush from 1967 to 1971, had swung from 60-39 Romney to 48-47 Clinton, and Biden carried it 54-45 in 2020. Democratic Rep. Lizzie Fletcher won by a smaller 51-47 spread against Wesley Hunt, who was one of the House GOP’s best fundraisers. The 32nd District in the Dallas area, likewise, had gone from 57-41 Romney to 49-47 Clinton. This time, Biden took it 54-44 as Democratic Rep. Colin Allred prevailed 52-46.

Biden’s major gains in the suburbs, though, came at the same time that Trump made serious inroads in predominantly Latino areas on or near the southern border with Mexico. That rightward shift may have cost Team Blue the chance to flip the open 23rd District, which stretches from San Antonio west to the outskirts of the El Paso area.

A full breakdown by county and district is here, and a comparison of percentages from 2016 and 2020 is here. CD23 went from being a Romney district to a Clinton district to a Trump district, though in all cases it was close. The red flags are in CDs 15, 28, and 34. In CD15, incumbent Vicente Gonzalez won by only three points, in a district Biden carried by one point, a huge drop from Clinton’s 57-40 win in 2016. Everyone’s least favorite Democrat Henry Cuellar had an easy 19-point win, but Biden only carried CD28 by four points, down from Clinton’s 20-point margin. It’s not crazy to think that Jessica Cisneros could have lost that race, though of course we’ll never know. This wasn’t the scenario I had in mind when I griped that CD28 was not a “safe” district, but it does clearly illustrate what I meant. And Filemon Vela, now a DNC Vice Chair, also had a relatively easy 55-42 win, but in a district Biden carried 52-48 after Clinton had carried it 59-38. Not great, Bob.

We don’t have the full downballot results – we’ll probably get them in March from the Texas Legislative Council – but the Harris County experience suggests there will be some variance, and that other Dems may do a little better in those districts. How much of this was Trump-specific and how much is long-term is of course the big question. The Georgia Senate runoffs, coupled with the 2018 results, suggest that having Trump on the ballot was better for Republicans than not having him on the ballot. On the other hand, 2022 will be a Democratic midterm year, and the last couple of them did not go well. On the other other hand, Trump is leaving office in complete disgrace and with approval levels now in the low 30s thanks to the armed insurrection at the Capitol, and for all the damage he did to the economy and the COVID mitigation effort, Biden is in a position to make big progress in short order. It’s just too early to say what any of this means, but suffice it to say that both Ds and Rs have challenges and opportunities ahead of them.

There are some very early third-party efforts at drawing new Congressional districts – see here and here for a couple I’ve come across. We still need the actual Census numbers, and as I’ve said before, the Republicans will have to make decisions about how much risk they want to expose themselves to. The way these maps are drawn suggests to me that “pack” rather than “crack” could be the strategy, but again this is all very early. There is also the possibility that the Democratic Congress can push through voting rights reform that includes how redistricting can be done, though the clock and potentially the Supreme Court will be factors. And if there’s one thing we should have learned over the last 20 years, it’s that due to Texas’ rapid growth, the districts you draw at the beginning of the decade may look quite a bit different by the end of the decade. We’re at the very start of a ten-year journey. A lot is going to happen, and the farther out we get the harder it is to see the possibilities.

Precinct analysis: Tax Assessor 2020 and 2016

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney
Sheriff

Tax Assessor Ann Harris Bennett is the third incumbent from 2016 running for re-election. Like Sheriff Ed Gonzalez, she improved her performance pretty significantly from four years ago. Unlike either Gonzalez or DA Kim Ogg, she came off a close race – she was actually trailing after early voting, and did just well enough on Election Day to pull out a eight thousand vote victory. In 2020, she won by ten points, with a Libertarian candidate also in the mix. Here’s how 2020 looked for Bennett:


Dist    Daniel  Bennett     Lib Daniel%Bennett%   Lib%
======================================================
CD02   174,454  151,148  11,516  51.15%  44.32%  3.38%
CD07   148,007  146,906   9,535  47.97%  47.62%  3.09%
CD08    24,960   14,786   1,419  59.88%  35.47%  3.40%
CD09    35,972  117,815   4,676  22.43%  73.47%  2.92%
CD10    98,983   58,837   5,631  59.77%  35.53%  3.40%
CD18    57,057  175,920   8,077  23.44%  72.28%  3.32%
CD22    20,650   19,913   1,660  48.18%  46.46%  3.87%
CD29    46,205  101,024   4,961  30.09%  65.80%  3.23%
CD36    79,503   48,053   4,570  59.41%  35.91%  3.42%
						
SBOE4  100,919  330,636  13,852  22.66%  74.23%  3.11%
SBOE6  374,836  342,677  24,239  50.53%  46.20%  3.27%
SBOE8  210,036  161,090  13,954  54.54%  41.83%  3.62%
						
SD04    53,982   22,540   2,570  68.25%  28.50%  3.25%
SD06    53,863  117,046   5,997  30.45%  66.16%  3.39%
SD07   227,833  169,249  13,705  55.46%  41.20%  3.34%
SD11    74,156   46,328   4,608  59.28%  37.04%  3.68%
SD13    36,043  156,250   5,976  18.18%  78.81%  3.01%
SD15   110,239  189,765  10,747  35.48%  61.07%  3.46%
SD17   115,088  121,733   7,376  47.13%  49.85%  3.02%
SD18    14,587   11,494   1,066  53.73%  42.34%  3.93%
						
HD126   37,713   32,939   2,327  51.68%  45.13%  3.19%
HD127   52,360   34,525   3,193  58.13%  38.33%  3.54%
HD128   46,291   22,223   2,192  65.47%  31.43%  3.10%
HD129   46,005   34,465   3,291  54.92%  41.15%  3.93%
HD130   67,940   31,860   3,420  65.82%  30.87%  3.31%
HD131    9,557   43,780   1,586  17.40%  79.71%  2.89%
HD132   48,284   47,303   3,782  48.59%  47.60%  3.81%
HD133   49,924   35,385   2,408  56.91%  40.34%  2.75%
HD134   48,604   55,747   2,949  45.30%  51.95%  2.75%
HD135   34,905   36,408   2,567  47.25%  49.28%  3.47%
HD137    9,845   20,352   1,178  31.38%  64.87%  3.75%
HD138   30,750   30,377   2,169  48.58%  47.99%  3.43%
HD139   14,994   44,096   1,832  24.61%  72.38%  3.01%
HD140    8,661   21,724   1,000  27.60%  69.22%  3.19%
HD141    6,617   35,561   1,217  15.25%  81.95%  2.80%
HD142   13,268   41,110   1,631  23.69%  73.40%  2.91%
HD143   11,211   24,369   1,121  30.55%  66.40%  3.05%
HD144   12,895   16,646   1,072  42.12%  54.38%  3.50%
HD145   14,110   26,467   1,630  33.43%  62.71%  3.86%
HD146   10,878   42,506   1,661  19.76%  77.22%  3.02%
HD147   14,762   51,621   2,518  21.42%  74.92%  3.65%
HD148   21,733   35,555   2,479  36.36%  59.49%  4.15%
HD149   20,767   30,361   1,522  39.44%  57.67%  2.89%
HD150   53,716   39,022   3,300  55.93%  40.63%  3.44%
						
CC1     89,315  274,496  11,676  23.79%  73.10%  3.11%
CC2    143,799  143,691  10,434  48.27%  48.23%  3.50%
CC3    220,064  206,206  14,217  49.96%  46.81%  3.23%
CC4    232,613  210,012  15,718  50.75%  45.82%  3.43%
						
JP1     90,963  160,043   8,734  35.02%  61.62%  3.36%
JP2     32,249   48,712   2,804  38.50%  58.15%  3.35%
JP3     49,382   67,843   3,512  40.90%  56.19%  2.91%
JP4    226,115  182,066  14,185  53.54%  43.11%  3.36%
JP5    196,782  210,577  13,981  46.70%  49.98%  3.32%
JP6      7,542   26,611   1,383  21.22%  74.88%  3.89%
JP7     17,840   98,244   3,456  14.92%  82.19%  2.89%
JP8     64,918   40,309   3,990  59.44%  36.91%  3.65%

Bennett’s 834K vote total was the lowest among the non-judicial countywide candidates, and only ahead of five judicial candidates. Thanks in part to the 52K votes that the Libertarian candidate received, however, she led challenger and former District Clerk Chris Daniel by over 148K votes, which is one of the bigger margins. If you want to examine the belief that Libertarian candidates mostly take votes away from Republicans, look at some of the district totals, especially HDs like 132, 135, and 138. We can’t know for sure how Daniel might have done in a two-person race, but it seems reasonable to me to say he’d have improved at least somewhat. Bennett did about as well as you’d expect someone who got 53% of the vote would do. If the final score would have been closer in a two-person race, it’s not because she’d have received fewer votes or gotten a lower percentage.

Here’s the 2016 comparison, in which Bennett knocked off incumbent Mike Sullivan. She trailed by about five thousand votes when the totals were first displayed on Election Night, with Sullivan having slight leads in both mail ballots and in person early votes – yes, that’s right, Republicans used to try to compete on mail ballots – but got nearly 52% of the Election Day vote, which was a big enough part of the vote to push her over the top.


Dist  Sullivan  Bennett  Sullivan%  Bennett%
============================================
CD02   168,936  105,778     61.50%    38.50%
CD07   147,165  106,727     57.96%    42.04%
CD09    29,855  103,511     22.39%    77.61%
CD10    83,213   34,795     70.51%    29.49%
CD18    53,558  148,586     26.49%    73.51%
CD29    41,555   88,942     31.84%    68.16%
				
SBOE6  357,083  249,953     58.82%    41.18%
				
HD126   37,003   24,186     60.47%    39.53%
HD127   50,028   23,460     68.08%    31.92%
HD128   42,659   16,238     72.43%    27.57%
HD129   44,072   24,777     64.01%    35.99%
HD130   60,429   20,277     74.88%    25.12%
HD131    8,121   37,906     17.64%    82.36%
HD132   39,094   29,321     57.14%    42.86%
HD133   50,116   25,241     66.50%    33.50%
HD134   49,352   39,410     55.60%    44.40%
HD135   33,528   26,112     56.22%    43.78%
HD137    9,664   17,099     36.11%    63.89%
HD138   28,827   22,096     56.61%    43.39%
HD139   13,707   38,266     26.37%    73.63%
HD140    7,556   19,790     27.63%    72.37%
HD141    5,934   32,109     15.60%    84.40%
HD142   11,599   33,182     25.90%    74.10%
HD143   10,372   22,294     31.75%    68.25%
HD144   11,810   15,188     43.74%    56.26%
HD145   12,669   21,519     37.06%    62.94%
HD146   11,323   36,903     23.48%    76.52%
HD147   14,119   43,254     24.61%    75.39%
HD148   20,434   26,999     43.08%    56.92%
HD149   16,639   26,389     38.67%    61.33%
HD150   50,472   25,358     66.56%    33.44%
				
CC1     82,916  231,040     26.41%    73.59%
CC2    134,067  117,084     53.38%    46.62%
CC3    202,128  149,943     57.41%    42.59%
CC4    220,415  149,294     59.62%    40.38%

Again, there’s nothing here we haven’t seen before, but as Mike Sullivan nearly hung on, you can see what an almost-successful Republican looked like in 2016. Note the margins he had in CDs 02 and 07, and the various now-competitive State Rep districts. I mean, Sullivan won HD134 by eleven points. He won CC4 by almost 20 points, and CC3 by fifteen. We don’t live in that world now.

Precinct analysis: Sheriff 2020 and 2016

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney
County Attorney

Behold your 2020 vote champion in Harris County: Sheriff Ed Gonzalez, running for his second term in office. I’ll get into the details of Gonzalez’s domination in a minute. Here are the numbers for 2020:


Dist     Danna  Gonzalez    Danna%  Gonzalez%
=============================================
CD02   170,422   166,902    50.52%     49.48%
CD07   141,856   162,417    46.62%     53.38%
CD08    24,788    16,406    60.17%     39.83%
CD09    35,308   122,871    22.32%     77.68%
CD10    98,458    65,239    60.15%     39.85%
CD18    54,869   186,236    22.76%     77.24%
CD22    20,466    21,710    48.53%     51.47%
CD29    43,503   109,304    28.47%     71.53%
CD36    79,327    52,648    60.11%     39.89%
				
SBOE4   96,435   349,282    21.64%     78.36%
SBOE6  363,916   378,161    49.04%     50.96%
SBOE8  208,646   176,291    54.20%     45.80%
				
SD04    53,758    25,277    68.02%     31.98%
SD06    50,944   126,617    28.69%     71.31%
SD07   224,433   186,884    54.56%     45.44%
SD11    74,078    50,852    59.30%     40.70%
SD13    35,054   162,823    17.72%     82.28%
SD15   106,009   204,899    34.10%     65.90%
SD17   110,189   133,749    45.17%     54.83%
SD18    14,532    12,635    53.49%     46.51%
				
HD126   36,979    36,165    50.56%     49.44%
HD127   51,960    38,105    57.69%     42.31%
HD128   46,345    24,235    65.66%     34.34%
HD129   45,743    37,938    54.66%     45.34%
HD130   67,658    35,780    65.41%     34.59%
HD131    9,271    45,531    16.92%     83.08%
HD132   47,705    51,772    47.96%     52.04%
HD133   47,629    39,951    54.38%     45.62%
HD134   44,590    62,513    41.63%     58.37%
HD135   34,389    39,591    46.48%     53.52%
HD137    9,680    21,648    30.90%     69.10%
HD138   30,004    33,385    47.33%     52.67%
HD139   14,623    46,351    23.98%     76.02%
HD140    8,109    23,412    25.73%     74.27%
HD141    6,449    36,900    14.88%     85.12%
HD142   12,684    43,278    22.67%     77.33%
HD143   10,463    26,455    28.34%     71.66%
HD144   12,685    17,965    41.39%     58.61%
HD145   13,322    29,035    31.45%     68.55%
HD146   10,562    44,351    19.23%     80.77%
HD147   13,955    54,824    20.29%     79.71%
HD148   20,375    39,637    33.95%     66.05%
HD149   20,574    32,068    39.08%     60.92%
HD150   53,242    42,844    55.41%     44.59%
				
CC1     85,139   289,925    22.70%     77.30%
CC2    141,416   156,934    47.40%     52.60%
CC3    214,450   226,063    48.68%     51.32%
CC4    227,992   230,814    49.69%     50.31%
				
JP1     84,929   174,954    32.68%     67.32%
JP2     31,274    52,644    37.27%     62.73%
JP3     48,485    72,207    40.17%     59.83%
JP4    223,758   199,021    52.93%     47.07%
JP5    191,671   229,696    45.49%     54.51%
JP6      6,846    28,930    19.14%     80.86%
JP7     17,135   102,122    14.37%     85.63%
JP8     64,899    44,162    59.51%     40.49%

Only Joe Biden (918,193) got more votes than Sheriff Ed (903,736) among Dems that had a Republican opponent; District Court Judge Michael Gomez (868,327) was next in line. Gonzalez’s 235K margin of victory, and his 57.46% of the vote were easily the highest. He carried SBOE6, HD132, HD138, and all four Commissioners Court precincts, while coming close in CD02 and HD126. He even made SD07, HD133, and JP4 look competitive.

How dominant was Ed Gonzalez in 2020? He got more votes in their district than the following Democratic incumbents:

CD07: Gonzalez 162,417, Lizzie Fletcher 159,529
CD18: Gonzalez 186,236, Sheila Jackson Lee 180,952
SD13: Gonzalez 162,823, Borris Miles 159,936
HD135: Gonzalez 39,591, Jon Rosenthal 36,760
HD142: Gonzalez 43,278, Harold Dutton 42,127
HD144: Gonzalez 17,965, Mary Ann Perez 17,516
HD145: Gonzalez 29,035, Christina Morales 27,415
HD149: Gonzalez 32,068, Hubert Vo 31,919
JP1: Gonzalez 174,954, Eric Carter 166,759

That’s pretty damn impressive. Gonzalez is the incumbent, he’s in law enforcement and may be the most visible county official after Judge Hidalgo, he had a solid term with basically no major screwups, he’s well liked by the Democratic base, and he ran against a frequent flyer who had no apparent base of support. At least in 2020, this is as good as it gets.

Obviously, Gonzalez did better than he did in 2016, but let’s have a quick look at the numbers anyway.


Dist   Hickman  Gonzalez  Hickman%  Gonzalez%
=============================================
CD02   162,915   111,689    59.33%     40.67%
CD07   139,292   113,853    55.02%     44.98%
CD09    26,869   106,301    20.18%     79.82%
CD10    81,824    36,293    69.27%     30.73%
CD18    48,766   153,342    24.13%     75.87%
CD29    35,526    95,138    27.19%     72.81%
				
SBOE6  341,003   265,358    56.24%     43.76%
				
HD126   36,539    24,813    59.56%     40.44%
HD127   48,891    24,516    66.60%     33.40%
HD128   41,694    17,117    70.89%     29.11%
HD129   41,899    26,686    61.09%     38.91%
HD130   59,556    21,256    73.70%     26.30%
HD131    7,054    38,887    15.35%     84.65%
HD132   38,026    30,397    55.57%     44.43%
HD133   47,648    27,378    63.51%     36.49%
HD134   44,717    43,480    50.70%     49.30%
HD135   32,586    27,180    54.52%     45.48%
HD137    8,893    17,800    33.32%     66.68%
HD138   27,480    23,366    54.05%     45.95%
HD139   12,746    39,223    24.53%     75.47%
HD140    6,376    20,972    23.31%     76.69%
HD141    5,485    32,573    14.41%     85.59%
HD142   10,801    33,924    24.15%     75.85%
HD143    9,078    23,689    27.70%     72.30%
HD144   10,765    16,194    39.93%     60.07%
HD145   10,785    23,462    31.49%     68.51%
HD146   10,144    37,991    21.07%     78.93%
HD147   12,100    45,136    21.14%     78.86%
HD148   17,701    29,776    37.28%     62.72%
HD149   15,702    27,266    36.54%     63.46%
HD150   49,904    26,142    65.62%     34.38%
				
CC1     74,178   239,211    23.67%     76.33%
CC2    125,659   125,416    50.05%     49.95%
CC3    193,214   158,164    54.99%     45.01%
CC4    213,519   156,417    57.72%     42.28%

Gonzalez ran against Ron Hickman, former Constable in Precinct 4, who was appointed following Adrian Garcia’s resignation to run for Mayor of Houston in 2015. Hickman had been well respected as Constable and wasn’t a controversial selection, but he was quickly dogged with a scandal involving lost and destroyed evidence from his Constable days, as well as the usual bugaboo of jail overcrowding; his opposition to misdemeanor bail reform did not help with that. With all that, Gonzalez got “only” 52.84% of the vote in 2016, which was ahead of most judicial candidates but behind both Kim Ogg and Vince Ryan. My thought at the time was that Gonzalez maxed out the Democratic vote, but didn’t get many crossovers. Clearly, he knocked that second item out of the park this year. I’m not going to go into a more detailed comparison – I’ll leave that to you this time – but it should be obvious that Gonzalez built on his performance from 2016. We’ll see what he can do with the next four years.

Precinct analysis: County Attorney 2020 and 2016

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities
District Attorney

The office of County Attorney gets less attention than District Attorney, but as we have seen it’s vitally important. Vince Ryan held the office for three terms before being ousted in the primary by Christian Menefee. Menefee’s overall performance was similar to Ryan’s in 2016 – I’ll get to that in a minute – but as we saw in the previous post that doesn’t mean there can’t be a fair bit of variance. Let’s see where that takes us. Here’s the 2020 breakdown:


Dist     Nation  Menefee  Nation% Menefee%
==========================================
CD02    178,265  154,520   53.57%   46.43%
CD07    149,139  151,213   49.65%   50.35%
CD08     25,809   14,986   63.27%   36.73%
CD09     37,016  119,594   23.64%   76.36%
CD10    102,438   59,410   63.29%   36.71%
CD18     58,121  179,867   24.42%   75.58%
CD22     21,591   20,074   51.82%   48.18%
CD29     48,935  100,744   32.69%   67.31%
CD36     82,457   48,040   63.19%   36.81%
				
SBOE4   104,688  334,552   23.83%   76.17%
SBOE6   380,793  351,322   52.01%   47.99%
SBOE8   218,290  162,575   57.31%   42.69%
				
SD04     55,522   22,733   70.95%   29.05%
SD06     56,939  117,097   32.72%   67.28%
SD07    235,108  171,376   57.84%   42.16%
SD11     76,866   46,710   62.20%   37.80%
SD13     36,807  159,259   18.77%   81.23%
SD15    112,115  194,216   36.60%   63.40%
SD17    115,210  125,384   47.89%   52.11%
SD18     15,204   11,676   56.56%   43.44%
				
HD126    38,751   33,320   53.77%   46.23%
HD127    53,950   35,101   60.58%   39.42%
HD128    48,046   21,796   68.79%   31.21%
HD129    47,571   35,152   57.51%   42.49%
HD130    69,976   32,109   68.55%   31.45%
HD131     9,822   44,446   18.10%   81.90%
HD132    50,540   47,980   51.30%   48.70%
HD133    49,624   36,901   57.35%   42.65%
HD134    46,775   58,410   44.47%   55.53%
HD135    36,489   36,696   49.86%   50.14%
HD137    10,191   20,871   32.81%   67.19%
HD138    31,535   30,924   50.49%   49.51%
HD139    15,325   44,753   25.51%   74.49%
HD140     9,241   21,586   29.98%   70.02%
HD141     6,943	  35,992   16.17%   83.83%
HD142    13,733   41,540   24.85%   75.15%
HD143    11,934   24,039   33.17%   66.83%
HD144    13,762   16,387   45.65%   54.35%
HD145    14,777   26,896   35.46%   64.54%
HD146    11,016   43,379   20.25%   79.75%
HD147    14,738   53,266   21.67%   78.33%
HD148    21,758   36,937   37.07%   62.93%
HD149    21,400   30,636   41.13%   58.87%
HD150    55,873   39,332   58.69%   41.31%
				
CC1      90,530  280,069   24.43%   75.57%
CC2     149,810  143,859   51.01%   48.99%
CC3     224,601  210,646   51.60%   48.40%
CC4     238,830  213,877   52.76%   47.24%
				
JP1      90,035  165,193   35.28%   64.72%
JP2      33,965   48,473   41.20%   58.80%
JP3      51,412   67,741   43.15%   56.85%
JP4     233,642  184,203   55.92%   44.08%
JP5     201,673  214,852   48.42%   51.58%
JP6       7,971   26,993   22.80%   77.20%
JP7      17,824  100,329   15.09%   84.91%
JP8      67,249   40,667   62.32%   37.68%

Menefee scored 54.66% of the vote, better than Ogg by almost a point, and better than Ryan’s 53.72% in 2016 by slightly more. Ryan was consistently an upper echelon performer in his three elections, and that was true in 2016 as well, as only Ogg, Hillary Clinton, and judicial candidate Kelly Johnson had more votes than his 685,075, with those three and Mike Engelhart being the only ones with a larger margin of victory than Ryan’s 95K. Menefee, who collected 848,451 total votes and won by a margin of 145K, was also top tier. His vote total trailed all of the statewide candidates except Chrysta Castaneda and Gisela Triana (one better than Kim Ogg), though his percentage was better than everyone except Joe Biden and Tina Clinton. He outpaced three of the four appellate court candidates (he trailed Veronica Rivas-Molloy) and all but four of the local judicial candidates. His margin of victory was eighth best, behind Biden, Castaneda, two statewide judicials, and three local judicials. (And Ed Gonzalez, but we’ll get to him next.)

Here’s my 2016 precinct analysis post for the County Attorney race, and here’s the relevant data from that year:


Dist    Leitner     Ryan  Leitner%   Ryan%
==========================================
CD02    158,149  113,363    58.25%  41.75%
CD07    135,129  116,091    53.79%  46.21%
CD09     25,714  106,728    19.42%  80.58%
CD10     80,244   36,703    68.62%  31.38%
CD18     46,062  154,354    22.98%  77.02%
CD29     35,312   93,732    27.36%  72.64%
				
SBOE6   331,484  269,022    55.20%  44.80%
				
HD126    34,999   25,571    57.78%  42.22%
HD127    47,719   24,876    65.73%  34.27%
HD128    40,809   17,464    70.03%  29.97%
HD129    41,206   26,677    60.70%  39.30%
HD130    58,268   21,630    72.93%  27.07%
HD131     6,719   39,011    14.69%  85.31%
HD132    37,294   30,571    54.95%  45.05%
HD133    46,509   28,002    62.42%  37.58%
HD134    42,937   44,634    49.03%  50.97%
HD135    31,651   27,468    53.54%  46.46%
HD137     8,661   17,869    32.65%  67.35%
HD138    26,893   23,486    53.38%  46.62%
HD139    11,874   39,721    23.01%  76.99%
HD140     6,316   20,762    23.33%  76.67%
HD141     4,969   32,887    13.13%  86.87%
HD142    10,179   34,249    22.91%  77.09%
HD143     8,745   23,486    27.13%  72.87%
HD144    10,725   16,024    40.09%  59.91%
HD145    10,858   22,921    32.14%  67.86%
HD146     9,532   38,323    19.92%  80.08%
HD147    11,719   45,087    20.63%  79.37%
HD148    17,529   29,206    37.51%  62.49%
HD149    15,405   27,290    36.08%  63.92%
HD150    48,085   26,950    64.08%  35.92%
				
CC1      70,740  240,579    22.72%  77.28%
CC2     123,739  124,368    49.87%  50.13%
CC3     188,415  160,213    54.04%  45.96%
CC4     206,707  158,990    56.52%  43.48%

Kim Ogg did slightly better in the districts in 2016 than Vince Ryan did (most notably in CD02, though Ryan outdid her in HD134), which is what you’d expect given her overall better performance. In a similar fashion, Menefee did slightly better in the districts than Ogg did, as expected given his superior totals. He won CD07 by a thousand more votes than Ogg did, and carried HD135 where Ogg did not. He lost CC2 by two points and 6K votes, while Ogg lost it by four points and 12K votes. His lead in CD29 was 6K smaller than Ryan’s was, while Ogg lost 10K off of her lead in CD29 from 2016.

Overall, Menefee improved on Ryan’s 2016 totals, and made larger gains than Ogg did over her 2016 numbers. Like Ogg, he lost ground in the Latino districts – CD29, HD140, HD143, HD144, CC2 – but not by as much. He had higher vote totals in the Latino State Rep districts, though by small amounts in HDs 140, 143, and 144, and increased the lead over what Ryan had achieved in HDs 145 and 148. Like Ogg, he also lost ground in HD149, going from a 12K lead to a 9K lead, and in HD128, going from a 23K deficit to a 27K deficit (Ogg went from down 21K to down 27K). He gained ground in HD127 (from down 23K to down 19K; Ogg stayed roughly the same) and lost only about a thousand net votes in HD130 as Ogg went from down 34K to down 39K. He posted strong gains in HD126 (down 9K to down 5K), HD133 (down 18K to down 13K), and HD150 (down 21K to down 16K).

On the whole, a very strong initial performance by Menefee. As I said, County Attorney is generally a lower-profile job than District Attorney and Sheriff, but between bail reform, the multiple election lawsuits, and the forthcoming Republican legislative assault on local control, there should be many chances for Menefee to make statements about what he does and can do. He’ll have a solid chance to build on what he did this year when he’s next up for election.

Precinct analysis: District Attorney 2020 and 2016

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages
Other cities

We move on now to the county executive office races for Harris County in 2020, which will be the end of the line for Harris County precinct analyses. I do have a copy of the Fort Bend canvass, though they do theirs in an annoyingly weird way, and will try to put something together for them after I’m done with this batch. With the four executive offices that were on the ballot for their regular election in 2020 – District Attorney, County Attorney, Sheriff, and Tax Assessor – we can not only view the data for this year, but do a nice comparison to 2016, since three of the four Democrats were running for re-election. We begin with the office of District Attorney:


Dist   Huffman      Ogg   Huffman%    Ogg%
==========================================
CD02   181,395  153,831     54.11%  45.89%
CD07   151,171  152,168     49.84%  50.16%
CD08    26,099   14,788     63.83%  36.17%
CD09    38,774  118,363     24.68%  75.32%
CD10   104,070   58,639     63.96%  36.04%
CD18    61,750  177,517     25.81%  74.19%
CD22    21,915   20,050     52.22%  47.78%
CD29    51,805   98,693     34.42%  65.58%
CD36    83,428   47,862     63.54%  36.46%
				
SBOE4  112,135  329,155     25.41%  74.59%
SBOE6  386,230  351,903     52.33%  47.67%
SBOE8  222,042  160,854     57.99%  42.01%
				
SD04    56,181   22,546     71.36%  28.64%
SD06    60,192  114,828     34.39%  65.61%
SD07   238,787  169,996     58.41%  41.59%
SD11    77,642   46,770     62.41%  37.59%
SD13    39,376  157,461     20.00%  80.00%
SD15   116,146  192,255     37.66%  62.34%
SD17   116,482  126,617     47.92%  52.08%
SD18    15,601   11,441     57.69%  42.31%
				
HD126   39,478   33,020     54.45%  45.55%
HD127   55,071   34,468     61.51%  38.49%
HD128   48,573   21,680     69.14%  30.86%
HD129   48,042   35,285     57.65%  42.35%
HD130   70,936   31,731     69.09%  30.91%
HD131   10,680   43,720     19.63%  80.37%
HD132   51,619   47,325     52.17%  47.83%
HD133   50,014   37,668     57.04%  42.96%
HD134   47,324   59,450     44.32%  55.68%
HD135   37,256   36,324     50.63%  49.37%
HD137   10,453   20,788     33.46%  66.54%
HD138   31,908   30,922     50.78%  49.22%
HD139   16,318   44,125     27.00%  73.00%
HD140    9,831   21,145     31.74%  68.26%
HD141    7,624   35,399     17.72%  82.28%
HD142   14,736   40,758     26.55%  73.45%
HD143   12,636   23,549     34.92%  65.08%
HD144   14,258   16,030     47.07%  52.93%
HD145   15,480   26,476     36.90%  63.10%
HD146   11,608   43,070     21.23%  78.77%
HD147   15,669   52,711     22.91%  77.09%
HD148   22,652   36,721     38.15%  61.85%
HD149   21,576   30,596     41.36%  58.64%
HD150   56,664   38,952     59.26%  40.74%
				
CC1     95,557  277,035     25.65%  74.35%
CC2    153,715  141,830     52.01%  47.99%
CC3    227,974  210,631     51.98%  48.02%
CC4    243,161  212,418     53.37%  46.63%
				
JP1     93,091  164,781     36.10%  63.90%
JP2     35,099   47,838     42.32%  57.68%
JP3     53,148   66,595     44.39%  55.61%
JP4    238,031  181,915     56.68%  43.32%
JP5    204,724  214,657     48.82%  51.18%
JP6      8,739   26,466     24.82%  75.18%
JP7     19,549   99,068     16.48%  83.52%
JP8     68,026   40,594     62.63%  37.37%

Here’s the same data from 2016. I’m going to reprint the table below and then do some comparisons, but at a macro level, Kim Ogg was the second-most successful candidate in Harris County in 2016. Her 696,955 votes and her 108,491-vote margin of victory were second only to Hillary Clinton. Ogg received 54.22% of the vote in 2016. She fell a little short of that percentage in 2020, garnering 53.89% of the vote this year, while increasing her margin to 121,507 votes. She was more middle of the pack this year, as the overall Democratic performance was up from 2016. She trailed all of the statewide candidates in total votes except for Gisela Triana, who was less than 300 votes behind her, though her percentage was higher than all of them except Joe Biden and the three Court of Criminal Appeals candidates. She had fewer votes than three of the four appellate court candidates (she was exactly nine votes behind Jane Robinson), but had a higher percentage than three of the four. Among the district and county court candidates, Ogg had more votes and a higher percentage than seven, more votes but a lower percentage than two, and fewer votes and a lower percentage than six.

(Writing all that out makes me think it was Republicans who were skipping judicial races more than Democrats. In the race immediately above DA, Democrat Julia Maldonado got 3,354 more votes than Ogg, but Republican Alyssa Lemkuil got 17,325 fewer votes than Mary Nan Huffman. In the race immediately after DA, Democrat Lesley Briones got 14,940 more votes than Ogg, but Republican Clyde Leuchtag got 30,357 fewer votes than Huffman. That sure looks like less Republican participation to me.)

Here’s the district breakdown for the DA race from 2016. It’s not as comprehensive as this year’s, but it’s good enough for these purposes.


Dist  Anderson      Ogg  Anderson%    Ogg%
==========================================
CD02   156,027  117,810     56.98%  43.02%
CD07   135,065  118,837     53.20%  46.80%
CD09    26,881  106,334     20.18%  79.82%
CD10    78,602   38,896     66.90%  33.10%
CD18    47,408  154,503     23.48%  76.52%
CD29    36,581   93,437     28.14%  71.86%
				
SBOE6  328,802  277,271     54.25%  45.75%
				
HD126   34,499   26,495     56.56%  43.44%
HD127   46,819   26,260     64.07%  35.93%
HD128   39,995   18,730     68.11%  31.89%
HD129   40,707   27,844     59.38%  40.62%
HD130   57,073   23,239     71.06%  28.94%
HD131    7,301   38,651     15.89%  84.11%
HD132   36,674   31,478     53.81%  46.19%
HD133   46,242   29,195     61.30%  38.70%
HD134   43,962   45,142     49.34%  50.66%
HD135   31,190   28,312     52.42%  47.58%
HD137    8,728   18,040     32.61%  67.39%
HD138   26,576   24,189     52.35%  47.65%
HD139   12,379   39,537     23.84%  76.16%
HD140    6,613   20,621     24.28%  75.72%
HD141    5,305   32,677     13.97%  86.03%
HD142   10,428   34,242     23.34%  76.66%
HD143    9,100   23,434     27.97%  72.03%
HD144   10,758   16,100     40.06%  59.94%
HD145   11,145   22,949     32.69%  67.31%
HD146   10,090   38,147     20.92%  79.08%
HD147   12,156   45,221     21.19%  78.81%
HD148   17,538   29,848     37.01%  62.99%
HD149   15,352   27,535     35.80%  64.20%
HD150   47,268   28,160     62.67%  37.33%
				
CC1     73,521  240,194     23.44%  76.56%
CC2    123,178  126,996     49.24%  50.76%
CC3    187,095  164,487     53.22%  46.78%
CC4    204,103  164,355     55.39%  44.61%

The shifts within districts are perhaps more subtle than you might think. A few stand out – CD07 goes from a 6.4 point win for Devon Anderson in 2016 to a narrow Ogg win in 2020, powered in large part by a ten-point shift in Ogg’s favor in HD134. On the flip side, Ogg carried CC2 by a point and a half in 2016 but lost it by four points in 2020, as her lead in CD29 went from 43 points to 31 points. Overall, Ogg saw modest gains in Republican turf – CD02, HD126, HD133, HD150, CC3, CC4 – and some Democratic turf – CD18, HD146, HD147, HD148, CC1 – and some modest losses in each – CD10, CD29, HD128, HD140, HD143, HD144, HD145, CC2.

In a lot of places, the percentages went one way or the other, but the gap in total votes didn’t change. CD09 is a good example of this – Ogg won it by 80K votes in each year, but with about 24K more votes cast in 2020, split evenly between her and Huffman, that lowered her percentage by four points. Same thing in HD127, which Ogg lost by 20,559 in 2016 and 20,603 in 2020, but added three percentage points because 16K more votes were cast. In the three Latino State Rep districts cited above, Ogg had more votes in 2020 in HD140, HD143, and HD145 than she did in 2016 – she had 70 fewer votes in HD144 – but her improvements in the first two districts were in the hundreds, while Huffman outperformed Anderson by 2,300 in HD140, by 3,500 in HD143, and by 3,500 in HD144; Huffman improved by 4,300 in HD145 while Ogg added 3,500 votes. As we’ve discussed before, it will be interesting to see how these districts perform going forward, and in lower-turnout scenarios.

So we see some changes in where the vote was, with Ogg building a bit on 2016, in the same way that Joe Biden built a bit on what Hillary Clinton did in 2016. As I write this, I haven’t actually taken this close a look at the district changes in the other county races, so we’ll learn and discover together. I think we can expect that some of this behavior is mirrored elsewhere, but this is the only race with an incumbent running for re-election who did basically as well as they had done before, so the patterns may be a little harder to discern. But that’s what makes this exercise so interesting each cycle. Let me know what you think.

Precinct analysis: Other cities

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2
Judicial averages

I mentioned in an earlier post that I might look at election results from other cities that had their own races in November. Turns out there were quite a few of them that had their elections conducted by Harris County, and thus had their results in the spreadsheet I got. Let’s have a look.


City            Trump  Biden  Lib  Grn  Trump%  Biden%   Lib%   Grn%
====================================================================
Baytown         3,879  2,394   55   21  61.10%  37.71%  0.87%  0.33%
Bellaire        4,553  6,565  115   29  40.43%  58.29%  1.02%  0.26%
Deer Park      11,192  3,622  167   39  74.51%  24.11%  1.11%  0.26%
Friendswood     5,312  4,357  144   24  54.00%  44.29%  1.46%  0.24%
Galena Park     1,026  1,614   18    9  38.47%  60.52%  0.67%  0.34%
Humble          5,084  6,274  107   53  44.14%  54.47%  0.93%  0.46%
Katy            4,373  1,918   82   17  68.44%  30.02%  1.28%  0.27%
La Porte       11,561  5,036  201   69  68.54%  29.86%  1.19%  0.41%
League City     1,605  1,196   38    4  56.45%  42.07%  1.34%  0.14%
Missouri City     457  2,025    8    8  18.29%  81.06%  0.32%  0.32%
Nassau Bay      1,433  1,003   32    4  57.97%  40.57%  1.29%  0.16%
Pearland        5,397  7,943   84   32  40.11%  59.03%  0.62%  0.24%
Seabrook        5,532  2,768  104   21  65.66%  32.85%  1.23%  0.25%
Webster         4,594  4,850  159   33  47.68%  50.33%  1.65%  0.34%

City           Cornyn  Hegar  Lib  Grn Cornyn%  Hegar%   Lib%   Grn%
====================================================================
Baytown         3,814  2,255  119   49  61.15%  36.16%  1.91%  0.79%
Bellaire        5,312  5,762   93   48  47.37%  51.38%  0.83%  0.43%
Deer Park      11,098  3,355  269   90  74.93%  22.65%  1.82%  0.61%
Friendswood     5,380  4,009  221   74  55.56%  41.40%  2.28%  0.76%
Galena Park       892  1,408   40   42  37.45%  59.11%  1.68%  1.76%
Humble          5,098  5,927  233   98  44.89%  52.19%  2.05%  0.86%
Katy            4,401  1,749  129   40  69.65%  27.68%  2.04%  0.63%
La Porte       11,361  4,743  365  108  68.53%  28.61%  2.20%  0.65%
League City     1,654  1,099   39   18  58.86%  39.11%  1.39%  0.64%
Missouri City     458  1,934   38   25  18.66%  78.78%  1.55%  1.02%
Nassau Bay      1,471    928   43   12  59.94%  37.82%  1.75%  0.49%
Pearland        5,432  7,551  190  113  40.89%  56.83%  1.43%  0.85%
Seabrook        5,561  2,545  190   43  66.69%  30.52%  2.28%  0.52%
Webster         4,625  4,541  230   82  48.80%  47.91%  2.43%  0.87%

City           Wright  Casta  Lib  Grn Wright%  Casta%   Lib%   Grn%
====================================================================
Baytown         3,681  2,306  129   51  59.02%  36.97%  2.07%  0.82%
Bellaire        5,227  5,444  142  115  46.61%  48.54%  1.27%  1.03%
Deer Park      10,894  3,355  294  109  73.55%  22.65%  1.98%  0.74%
Friendswood     5,216  3,901  253  155  53.86%  40.28%  2.61%  1.60%
Galena Park       801  1,478   45   42  33.63%  62.05%  1.89%  1.76%
Humble          4,872  5,962  247  156  42.90%  52.50%  2.18%  1.37%
Katy            4,365  1,677  141   74  69.08%  26.54%  2.23%  1.17%
La Porte       11,057  4,773  393  175  66.70%  28.79%  2.37%  1.06%
League City     1,616  1,069   49   38  57.51%  38.04%  1.74%  1.35%
Missouri City     421  1,944   38   34  17.15%  79.19%  1.55%  1.38%
Nassau Bay      1,417    898   60   28  57.74%  36.59%  2.44%  1.14%
Pearland        5,205  7,571  189  172  39.18%  56.98%  1.42%  1.29%
Seabrook        5,477  2,439  232   83  65.68%  29.25%  2.78%  1.00%
Webster         4,488  4,416  283  165  47.35%  46.59%  2.99%  1.74%

A few words of caution before we begin. Most of these city races were at large – they were for Mayor or were citywide propositions (some of these towns had literally an entire alphabet’s worth of props for the voters), a few were At Large City Council races. Baytown, Katy, and Webster were City Council races that did not appear to be at large; League City had a Council race that didn’t give any indication one way or the other. Some of these cities – Friendswood, Katy, League City, Missouri City, and Pearland – are not fully contained within Harris County, so these are just partial results. As with the city of Houston, there’s no guarantee that Harris County precinct boundaries match city boundaries, or that precincts are contained entirely within that city, so the results from the other races may contain voters who aren’t in the city specified. Basically, consider these all to be approximations, and we’ll be fine.

I had no idea what to expect from these numbers. With the exception of Bellaire and Galena Park, all of these place are on the outer edges of Harris County, so generally in the red zone, but not exclusively. I expected Galena Park and Missouri City to be blue, I expected Baytown and Deer Park and Friendswood to be red, and the rest I either didn’t have any preconceived notions or was a little surprised. I wouldn’t have expected Bellaire or Humble to be blue – Bellaire is squarely in the CD07/HD134 part of town, so while it’s not all that shocking, I feel quite confident saying that if I did this same exercise in 2012, I’d have gotten a different result. The Katy area is getting bluer, which is how Dems won HD132 in 2018, but apparently that is not the case for the city of Katy proper, or at least the Harris County part of it. I’d guess the Brazoria County part of Pearland is redder than the Harris County part. As for La Porte, it’s not that I’m surprised that it’s red, it’s more that I’d never thought much about it.

I don’t have a whole lot more to say here – I don’t have past data handy, so I can’t make any comparisons, but even if I did we already mostly have the picture from earlier posts. It’s the same geography, just different pieces of it. There’s been a push by the TDP lately to get more local officials elected in towns like these, which is often a challenge in low-turnout May elections. There clearly some opportunities, though, and we should look to support candidates who put themselves out there in places where they’re not the norm. I have a friend who ran for Humble ISD in 2017, and while she didn’t win, that’s the sort of effort we need to get behind. Keep an eye out for what you can do this May, and find some good people to work with.

Precinct analysis: The judicial averages

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1
Appellate courts, Part 2

As you know, I use the average totals and percentages from local judicial races as my go-to metric for determining partisan indexes for each district. That’s because these are two-candidate races, and generally speaking people vote in them on the party label and not on detailed knowledge of the individual candidates. I’ve looked at this data in various ways over the years – in 2018, it was all about undervoting, as my contribution to the deeply annoying great straight-ticket voting debate. This year, I just want to provide as comprehensive a look as I can at what the partisan index of each district is, so without further ado here are the averages and minimum/maximum values for each district:


Dist    Avg R    Avg D  Avg R%  Avg D%
======================================
CD02  180,657  152,260  54.26%  45.74%
CD07  152,705  147,943  50.79%  49.21%
CD08   25,930   14,830  63.62%  36.38%
CD09   37,855  119,136  24.11%  75.89%
CD10  103,043   58,975  63.60%  36.40%
CD18   59,751  178,574  25.07%  74.93%
CD22   21,796   19,965  52.19%  47.81%
CD29   49,285  100,975  32.80%  67.20%
CD36   82,990   47,534  63.58%  36.42%
				
SBOE4 106,801  333,572  24.25%  75.75%
SBOE6 387,513  345,132  52.89%  47.11%
SBOE8 219,698  161,490  57.64%  42.36%
				
SD04   55,837   22,370  71.40%  28.60%
SD06   57,502  117,156  32.92%  67.08%
SD07  236,992  169,822  58.26%  41.74%
SD11   77,482   46,126  62.68%  37.32%
SD13   38,020  158,384  19.36%  80.64%
SD15  114,322  192,386  37.27%  62.73%
SD17  118,535  122,335  49.21%  50.79%
SD18   15,323   11,618  56.88%  43.12%
				
HD126  39,112   33,088  54.17%  45.83%
HD127  54,309   34,783  60.96%  39.04%
HD128  48,197   21,688  68.97%  31.03%
HD129  48,127   34,606  58.17%  41.83%
HD130  70,364   31,748  68.91%  31.09%
HD131  10,092   44,290  18.56%  81.44%
HD132  50,934   47,797  51.59%  48.41%
HD133  50,892   35,660  58.80%  41.20%
HD134  49,172   56,015  46.75%  53.25%
HD135  36,694   36,599  50.07%  49.93%
HD137  10,422   20,732  33.45%  66.55%
HD138  31,922   30,597  51.06%  48.94%
HD139  15,711   44,501  26.09%  73.91%
HD140   9,326   21,677  30.08%  69.92%
HD141   7,106   35,937  16.51%  83.49%
HD142  13,933   41,496  25.14%  74.86%
HD143  11,999   24,126  33.21%  66.79%
HD144  13,786   16,469  45.57%  54.43%
HD145  14,992   26,765  35.90%  64.10%
HD146  11,408   43,008  20.96%  79.04%
HD147  15,323   52,737  22.51%  77.49%
HD148  22,392   36,300  38.15%  61.85%
HD149  21,640   30,536  41.47%  58.53%
HD150  56,160   39,038  58.99%  41.01%
				
CC1    93,365  277,707  25.16%  74.84%
CC2   150,891  143,324  51.29%  48.71%
CC3   228,295  207,558  52.38%  47.62%
CC4   241,461  211,606  53.29%  46.71%
				
JP1    93,441  162,045  36.57%  63.43%
JP2    34,172   48,572  41.30%  58.70%
JP3    51,782   67,626  43.37%  56.63%
JP4   235,236  182,956  56.25%  43.75%
JP5   204,805  212,367  49.09%  50.91%
JP6     8,152   26,921  23.24%  76.76%
JP7    18,654   99,583  15.78%  84.22%
JP8    67,769   40,125  62.81%  37.19%


Dist    Max R    Min D  Max R%  Min D%
======================================
CD02  185,931  148,006  55.68%  44.32%
CD07  159,695  144,247  52.54%  47.46%
CD08   26,439   14,393  64.75%  35.25%
CD09   40,013  116,625  25.54%  74.46%
CD10  105,177   57,133  64.80%  35.20%
CD18   63,096  174,763  26.53%  73.47%
CD22   22,436   19,262  53.81%  46.19%
CD29   55,680   94,745  37.02%  62.98%
CD36   84,840   45,634  65.02%  34.98%
				
SBOE4 117,378  322,667  26.67%  73.33%
SBOE6 401,507  336,009  54.44%  45.56%
SBOE8 224,690  156,133  59.00%  41.00%
				
SD04   56,905   21,704  72.39%  27.61%
SD06   64,474  110,326  36.88%  63.12%
SD07  242,602  164,480  59.60%  40.40%
SD11   79,333   44,482  64.07%  35.93%
SD13   40,293  155,638  20.56%  79.44%
SD15  118,813  187,188  38.83%  61.17%
SD17  124,541  119,169  51.10%  48.90%
SD18   15,619   11,279  58.07%  41.93%
				
HD126  40,053   31,945  55.63%  44.37%
HD127  55,452   33,703  62.20%  37.80%
HD128  49,089   20,798  70.24%  29.76%
HD129  49,387   33,547  59.55%  40.45%
HD130  71,729   30,669  70.05%  29.95%
HD131  11,027   43,306  20.30%  79.70%
HD132  52,228   46,423  52.94%  47.06%
HD133  53,008   34,318  60.70%  39.30%
HD134  53,200   53,340  49.93%  50.07%
HD135  37,600   35,481  51.45%  48.55%
HD137  10,831   20,255  34.84%  65.16%
HD138  32,956   29,493  52.77%  47.23%
HD139  16,700   43,426  27.78%  72.22%
HD140  10,796   20,276  34.75%  65.25%
HD141   7,844   35,148  18.25%  81.75%
HD142  15,015   40,325  27.13%  72.87%
HD143  13,599   22,554  37.62%  62.38%
HD144  14,965   15,326  49.40%  50.60%
HD145  16,455   25,318  39.39%  60.61%
HD146  11,924   42,368  21.96%  78.04%
HD147  16,147   51,800  23.76%  76.24%
HD148  23,754   35,054  40.39%  59.61%
HD149  22,315   29,713  42.89%  57.11%
HD150  57,274   37,933  60.16%  39.84%
				
CC1    98,310  271,971  26.55%  73.45%
CC2   158,199  135,874  53.80%  46.20%
CC3   236,301  201,920  53.92%  46.08%
CC4   248,120  205,046  54.75%  45.25%
				
JP1    99,574  157,709  38.70%  61.30%
JP2    36,841   45,917  44.52%  55.48%
JP3    54,016   65,253  45.29%  54.71%
JP4   240,145  177,376  57.52%  42.48%
JP5   211,698  206,389  50.63%  49.37%
JP6     9,694   25,425  27.60%  72.40%
JP7    19,825   98,162  16.80%  83.20%
JP8    69,422   38,580  64.28%  35.72%


Dist    Min R    Max D  Min R%  Max D%
======================================
CD02  175,786  157,942  52.67%  47.33%
CD07  145,575  154,644  48.49%  51.51%
CD08   25,520   15,264  62.57%  37.43%
CD09   36,275  121,193  23.04%  76.96%
CD10  101,112   61,042  62.36%  37.64%
CD18   56,673  182,314  23.71%  76.29%
CD22   21,218   20,673  50.65%  49.35%
CD29   45,744  105,745  30.20%  69.80%
CD36   81,336   49,507  62.16%  37.84%
				
SBOE4 100,933  342,178  22.78%  77.22%
SBOE6 373,961  359,113  51.01%  48.99%
SBOE8 215,025  167,034  56.28%  43.72%
				
SD04   55,047   23,216  70.34%  29.66%
SD06   53,562  122,474  30.43%  69.57%
SD07  231,452  175,578  56.86%  43.14%
SD11   75,844   48,065  61.21%  38.79%
SD13   36,086  160,806  18.33%  81.67%
SD15  109,597  198,247  35.60%  64.40%
SD17  112,679  127,956  46.83%  53.17%
SD18   15,000   11,985  55.59%  44.41%
				
HD126  38,215   34,107  52.84%  47.16%
HD127  53,344   35,933  59.75%  40.25%
HD128  47,390   22,477  67.83%  32.17%
HD129  46,964   36,012  56.60%  43.40%
HD130  69,298   32,900  67.81%  32.19%
HD131   9,584   44,980  17.56%  82.44%
HD132  49,625   49,260  50.18%  49.82%
HD133  48,359   37,729  56.17%  43.83%
HD134  45,698   59,519  43.43%  56.57%
HD135  35,662   37,653  48.64%  51.36%
HD137   9,997   21,240  32.00%  68.00%
HD138  30,912   31,792  49.30%  50.70%
HD139  14,891   45,442  24.68%  75.32%
HD140   8,496   22,687  27.25%  72.75%
HD141   6,751   36,444  15.63%  84.37%
HD142  13,366   42,296  24.01%  75.99%
HD143  11,100   25,218  30.56%  69.44%
HD144  13,029   17,345  42.90%  57.10%
HD145  14,011   28,167  33.22%  66.78%
HD146  10,824   43,630  19.88%  80.12%
HD147  14,469   53,867  21.17%  78.83%
HD148  21,053   38,031  35.63%  64.37%
HD149  20,955   31,398  40.03%  59.97%
HD150  55,070   40,198  57.81%  42.19%
				
CC1    88,636  283,723  23.80%  76.20%
CC2   146,468  149,847  49.43%  50.57%
CC3   220,181  215,729  50.51%  49.49%
CC4   234,765  219,028  51.73%  48.27%
				
JP1    87,533  168,977  34.12%  65.88%
JP2    32,564   50,632  39.14%  60.86%
JP3    50,336   69,338  42.06%  57.94%
JP4   230,567  188,394  55.03%  44.97%
JP5   197,305  219,993  47.28%  52.72%
JP6     7,269   28,198  20.50%  79.50%
JP7    17,578  100,870  14.84%  85.16%
JP8    66,324   41,925  61.27%  38.73%

There were 15 contested District or County court races, with another 12 that had only a Democrat running. All of the numbers are from the contested races. The first table is just the average vote total for each candidate in that district; I then computed the percentage from those average values. For the second and third tables, I used the Excel MAX and MIN functions to get the highest and lowest vote totals for each party in each district. It should be noted that the max Republican and min Democratic totals in a given district (and vice versa) may not belong to the candidates from the same race, as the total number of votes in each race varies. Consider these to be a bit more of a theoretical construct, to see what the absolute best and worst case scenario for each party was this year.

One could argue that Democrats did better than expected this year, given the partisan levels they faced. Both Lizzie Fletcher and Jon Rosenthal won re-election, in CD07 and HD135, despite running in districts that were tilted slightly against them. The one Republican that won in a district that tilted Democratic was Precinct 5 Constable Ted Heap, who won as his JP colleague Russ Ridgway fell; as previously noted, Dan Crenshaw clearly outperformed the baseline in CD02. The tilt in Commissioners Court Precinct 3 was too much for Michael Moore to overcome, though perhaps redistricting and four more years of demographic change will move things in the Democratic direction for 2024. As for Precinct 2, I believe Adrian Garcia would have been re-elected if he had been on the ballot despite the Republican tilt in that precinct, mostly because the Latino Democratic candidates generally carried the precinct. He will also get a hand from redistricting when that happens. I believe being the incumbent would have helped him regardless, as Jack Morman ran ahead of the pack in 2018, just not by enough to hang on.

The “Republican max” (table 2) and “Democratic max” (table 3) values give you a picture of the range of possibility in each district. At their high end for Republicans, CD02 and SBOE6 don’t look particularly competitive, while CD07 and HD135 look like they really got away, while HD144 looks like a missed opportunity, and JP5 could have maybe been held in both races. HD134 remained stubbornly Democratic, however. On the flip side, you can see that at least one Democratic judicial candidate took a majority in CD07, HD135, HD138, and CC2, while CC3 and CC4 both look enticingly close, and neither HDs 134 nor 144 look competitive at all. If nothing else, this is a reminder that even in these judicial races, there can be a lot of variance.

On the subject of undervoting, as noted in the Appellate Court posts, the dropoff rate in those races was about 4.7% – there wasn’t much change from the first race to the fourth. For the contested local judicial races, the undervote rate ranged from 5.06% in the first race to 6.54%, in the seventh (contested) race from the end. There was a downward trend as you got farther down the ballot, but it wasn’t absolute – as noted, there were six races after the most-undervoted race, all with higher vote totals. The difference between the highest turnout race to the lowest was about 24K votes, from 1.568 million to 1.544 million. It’s not nothing, but in the grand scheme of things it’s pretty minimal.

The twelve unopposed Democrats in judicial races clearly show how unopposed candidates always do better than candidates that have opponents. Every unopposed judicial candidate collected over one million votes. Kristen Hawkins, the first unopposed judicial candidate, and thus most likely the first unopposed candidate on everyone’s ballot, led the way with 1.068 million votes, about 200K more votes than Michael Gomez, who was the leading votegetter in a contested race. Every unopposed Democratic candidate got a vote from at least 61.25% of all voters, with Hawkins getting a vote from 64.44% of all. I have always assumed that some number of people feel like they need to vote in each race, even the ones with only one candidate.

I’m going to analyze the vote in the non-Houston cities next. As always, please let me know what you think.

Precinct analysis: Appellate courts, part 2

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions
Appellate courts, Part 1

Here’s the more traditional look at the Court of Appeals races. Unlike the Supreme Court and CCA, all of these races just have two candidates, so we get a purer view of each district’s partisan measure.


Dist    Chris    Robsn  Chris%  Robsn%
======================================
CD02  184,964  152,768  54.77%  45.23%
CD07  157,736  147,670  51.65%  48.35%
CD08   26,431   14,916  63.92%  36.08%
CD09   39,195  119,621  24.68%  75.32%
CD10  104,717   59,540  63.75%  36.25%
CD18   62,244  178,810  25.82%  74.18%
CD22   22,412   20,080  52.74%  47.26%
CD29   51,407  100,718  33.79%  66.21%
CD36   84,772   47,797  63.95%  36.05%
				
SBOE4 111,462  333,791  25.03%  74.97%
SBOE6 398,123  345,585  53.53%  46.47%
SBOE8 224,293  162,545  57.98%  42.02%
				
SD04   56,898   22,562  71.61%  28.39%
SD06   59,896  116,837  33.89%  66.11%
SD07  241,721  170,662  58.62%  41.38%
SD11   79,273   46,425  63.07%  36.93%
SD13   39,578  158,975  19.93%  80.07%
SD15  118,283  192,558  38.05%  61.95%
SD17  122,640  122,169  50.10%  49.90%
SD18   15,589   11,734  57.05%  42.95%
				
HD126  39,903   33,263  54.54%  45.46%
HD127  55,384   34,979  61.29%  38.71%
HD128  49,071   21,878  69.16%  30.84%
HD129  49,357   34,835  58.62%  41.38%
HD130  71,485   31,992  69.08%  30.92%
HD131  10,547   44,331  19.22%  80.78%
HD132  51,970   48,189  51.89%  48.11%
HD133  52,531   35,414  59.73%  40.27%
HD134  51,636   55,503  48.20%  51.80%
HD135  37,498   36,828  50.45%  49.55%
HD137  10,775   20,855  34.07%  65.93%
HD138  32,788   30,669  51.67%  48.33%
HD139  16,375   44,551  26.88%  73.12%
HD140   9,795   21,511  31.29%  68.71%
HD141   7,493   35,952  17.25%  82.75%
HD142  14,378   41,649  25.66%  74.34%
HD143  12,559   24,038  34.32%  65.68%
HD144  14,250   16,410  46.48%  53.52%
HD145  15,600   26,725  36.86%  63.14%
HD146  11,819   43,211  21.48%  78.52%
HD147  16,024   52,771  23.29%  76.71%
HD148  23,255   36,320  39.03%  60.97%
HD149  22,187   30,741  41.92%  58.08%
HD150  57,197   39,304  59.27%  40.73%
				
CC1    97,397  278,086  25.94%  74.06%
CC2   154,992  143,474  51.93%  48.07%
CC3   234,325  208,116  52.96%  47.04%
CC4   247,164  212,247  53.80%  46.20%
				
JP1    97,730  161,507  37.70%  62.30%
JP2    35,419   48,550  42.18%  57.82%
JP3    53,112   67,814  43.92%  56.08%
JP4   239,927  183,854  56.62%  43.38%
JP5   210,230  213,175  49.65%  50.35%
JP6     8,570   26,891  24.17%  75.83%
JP7    19,569   99,806  16.39%  83.61%
JP8    69,321   40,326  63.22%  36.78%


Dist    Lloyd   Molloy  Lloyd% Molloy%
======================================
CD02  182,465  155,019  54.07%  45.93%
CD07  155,392  149,641  50.94%  49.06%
CD08   26,105   15,215  63.18%  36.82%
CD09   38,009  120,873  23.92%  76.08%
CD10  103,826   60,311  63.26%  36.74%
CD18   59,729  181,164  24.79%  75.21%
CD22   22,012   20,440  51.85%  48.15%
CD29   47,790  104,691  31.34%  68.66%
CD36   83,738   48,699  63.23%  36.77%
			
SBOE4 105,088  340,408  23.59%  76.41%
SBOE6 392,723  350,361  52.85%  47.15%
SBOE8 221,255  165,285  57.24%  42.76%
				
SD04   56,516   22,841  71.22%  28.78%
SD06   55,876  121,303  31.54%  68.46%
SD07  238,891  173,275  57.96%  42.04%
SD11   78,393   47,111  62.46%  37.54%
SD13   38,185  160,335  19.23%  80.77%
SD15  114,913  195,701  37.00%  63.00%
SD17  120,892  123,589  49.45%  50.55%
SD18   15,400   11,900  56.41%  43.59%
				
HD126  39,359   33,787  53.81%  46.19%
HD127  54,725   35,562  60.61%  39.39%
HD128  48,591   22,310  68.53%  31.47%
HD129  48,813   35,233  58.08%  41.92%
HD130  71,017   32,409  68.66%  31.34%
HD131   9,999   44,913  18.21%  81.79%
HD132  51,123   48,982  51.07%  48.93%
HD133  52,075   35,754  59.29%  40.71%
HD134  50,815   56,050  47.55%  52.45%
HD135  36,859   37,440  49.61%  50.39%
HD137  10,494   21,131  33.18%  66.82%
HD138  32,143   31,246  50.71%  49.29%
HD139  15,702   45,174  25.79%  74.21%
HD140   8,932   22,448  28.46%  71.54%
HD141   6,966   36,461  16.04%  83.96%
HD142  13,717   42,333  24.47%  75.53%
HD143  11,615   25,061  31.67%  68.33%
HD144  13,600   17,131  44.25%  55.75%
HD145  14,768   27,651  34.81%  65.19%
HD146  11,569   43,424  21.04%  78.96%
HD147  15,344   53,409  22.32%  77.68%
HD148  22,543   37,048  37.83%  62.17%
HD149  21,838   31,134  41.23%  58.77%
HD150  56,458   39,961  58.55%  41.45%
				
CC1    93,785  281,473  24.99%  75.01%
CC2   150,775  147,845  50.49%  49.51%
CC3   231,120  210,968  52.28%  47.72%
CC4   243,386  215,770  53.01%  46.99%
				
JP1    94,795  164,261  36.59%  63.41%
JP2    33,861   50,188  40.29%  59.71%
JP3    51,723   69,237  42.76%  57.24%
JP4   236,701  186,804  55.89%  44.11%
JP5   206,960  216,197  48.91%  51.09%
JP6     7,778   27,817  21.85%  78.15%
JP7    18,795  100,517  15.75%  84.25%
JP8    68,453   41,035  62.52%  37.48%


Dist    Adams   Guerra  Adams% Guerra%
======================================
CD02  184,405  152,836  54.68%  45.32%
CD07  157,212  147,381  51.61%  48.39%
CD08   26,351   14,919  63.85%  36.15%
CD09   38,998  119,778  24.56%  75.44%
CD10  104,820   59,234  63.89%  36.11%
CD18   61,326  179,332  25.48%  74.52%
CD22   22,218   20,211  52.37%  47.63%
CD29   48,121  104,386  31.55%  68.45%
CD36   84,501   47,871  63.84%  36.16%
			
SBOE4 107,293  337,920  24.10%  75.90%
SBOE6 397,124  345,286  53.49%  46.51%
SBOE8 223,535  162,743  57.87%  42.13%
				
SD04   56,904   22,386  71.77%  28.23%
SD06   56,357  120,880  31.80%  68.20%
SD07  241,466  170,348  58.63%  41.37%
SD11   79,098   46,319  63.07%  36.93%
SD13   39,476  158,887  19.90%  80.10%
SD15  116,690  193,656  37.60%  62.40%
SD17  122,412  121,729  50.14%  49.86%
SD18   15,549   11,745  56.97%  43.03%
				
HD126  39,813   33,289  54.46%  45.54%
HD127  55,237   34,999  61.21%  38.79%
HD128  48,957   21,899  69.09%  30.91%
HD129  49,340   34,653  58.74%  41.26%
HD130  71,559   31,806  69.23%  30.77%
HD131  10,266   44,574  18.72%  81.28%
HD132  51,808   48,208  51.80%  48.20%
HD133  52,597   35,086  59.99%  40.01%
HD134  51,370   55,317  48.15%  51.85%
HD135  37,274   36,945  50.22%  49.78%
HD137  10,724   20,876  33.94%  66.06%
HD138  32,559   30,808  51.38%  48.62%
HD139  16,147   44,644  26.56%  73.44%
HD140   8,966   22,430  28.56%  71.44%
HD141   7,254   36,084  16.74%  83.26%
HD142  14,142   41,863  25.25%  74.75%
HD143  11,744   24,953  32.00%  68.00%
HD144  13,658   17,072  44.45%  55.55%
HD145  14,824   27,584  34.96%  65.04%
HD146  11,928   43,032  21.70%  78.30%
HD147  15,656   53,073  22.78%  77.22%
HD148  22,757   36,812  38.20%  61.80%
HD149  22,195   30,784  41.89%  58.11%
HD150  57,176   39,156  59.35%  40.65%
				
CC1    95,892  278,971  25.58%  74.42%
CC2   152,017  146,563  50.91%  49.09%
CC3   233,933  207,769  52.96%  47.04%
CC4   246,110  212,648  53.65%  46.35%
				
JP1    95,938  162,864  37.07%  62.93%
JP2    34,099   49,931  40.58%  59.42%
JP3    52,405   68,430  43.37%  56.63%
JP4   239,343  183,827  56.56%  43.44%
JP5   209,649  213,147  49.59%  50.41%
JP6     7,852   27,792  22.03%  77.97%
JP7    19,566   99,631  16.41%  83.59%
JP8    69,100   40,329  63.15%  36.85%


Dist     Wise    Craft   Wise%  Craft%
======================================
CD02  187,076  150,161  55.47%  44.53%
CD07  160,323  144,461  52.60%  47.40%
CD08   26,468   14,814  64.12%  35.88%
CD09   39,255  119,480  24.73%  75.27%
CD10  105,224   58,786  64.16%  35.84%
CD18   62,464  178,398  25.93%  74.07%
CD22   22,479   19,942  52.99%  47.01%
CD29   51,350  100,685  33.78%  66.22%
CD36   85,152   47,195  64.34%  35.66%
				
SBOE4 111,160  333,956  24.97%  75.03%
SBOE6 403,452  338,891  54.35%  45.65%
SBOE8 225,179  161,076  58.30%  41.70%
				
SD04   57,202   22,111  72.12%  27.88%
SD06   59,943  116,758  33.92%  66.08%
SD07  242,902  168,936  58.98%  41.02%
SD11   79,698   45,696  63.56%  36.44%
SD13   39,579  158,895  19.94%  80.06%
SD15  119,640  190,784  38.54%  61.46%
SD17  125,186  119,108  51.24%  48.76%
SD18   15,641   11,636  57.34%  42.66%
				
HD126  40,122   32,983  54.88%  45.12%
HD127  55,653   34,618  61.65%  38.35%
HD128  49,175   21,666  69.42%  30.58%
HD129  49,744   34,245  59.23%  40.77%
HD130  71,894   31,468  69.56%  30.44%
HD131  10,420   44,469  18.98%  81.02%
HD132  52,080   47,898  52.09%  47.91%
HD133  53,487   34,292  60.93%  39.07%
HD134  53,678   53,121  50.26%  49.74%
HD135  37,617   36,577  50.70%  49.30%
HD137  10,841   20,738  34.33%  65.67%
HD138  33,111   30,252  52.26%  47.74%
HD139  16,338   44,533  26.84%  73.16%
HD140   9,677   21,649  30.89%  69.11%
HD141   7,162   36,255  16.50%  83.50%
HD142  14,336   41,735  25.57%  74.43%
HD143  12,465   24,123  34.07%  65.93%
HD144  14,238   16,400  46.47%  53.53%
HD145  15,761   26,507  37.29%  62.71%
HD146  12,019   42,980  21.85%  78.15%
HD147  16,327   52,404  23.75%  76.25%
HD148  24,026   35,407  40.43%  59.57%
HD149  22,369   30,513  42.30%  57.70%
HD150  57,250   39,088  59.43%  40.57%
				
CC1    98,291  276,873  26.20%  73.80%
CC2   155,580  142,504  52.19%  47.81%
CC3   236,903  204,782  53.64%  46.36%
CC4   249,017  209,766  54.28%  45.72%
				
JP1   100,430  158,362  38.81%  61.19%
JP2    35,440   48,448  42.25%  57.75%
JP3    52,981   67,919  43.82%  56.18%
JP4   240,598  182,662  56.84%  43.16%
JP5   212,371  210,308  50.24%  49.76%
JP6     8,629   26,793  24.36%  75.64%
JP7    19,649   99,743  16.46%  83.54%
JP8    69,693   39,690  63.71%  36.29%

If you just went by these results, you might think Dems did worse overall in Harris County than they actually did. None of the four candidates carried CD07, and only Veronica Rivas-Molloy carried HD135. They all still carried Harris County, by margins ranging from 6.0 to 8.7 points and 94K to 137K votes, but it’s clear they could have done better, and as we well know, even doing a little better would have carried Jane Robinson and Tamika Craft (who, despite her low score here still lost overall by less than 20K votes out of over 2.3 million ballots cast) to victory.

I don’t have a good explanation for any of this. Maybe the Libertarian candidates that some statewide races had a bigger effect on those races than we think. Maybe the incumbents had an advantage that enabled them to get a better share of the soft partisan vote. Maybe the Chron endorsements helped the incumbents. And maybe the lack of straight ticket voting did matter. The undervote rate in these races was around 4.7%, which is pretty low, but in 2018 it was around 2.7%. Picking on the Robinson race again, had the undervote rate been 2.7% instead of the 4.68% it actually was, there would have been an additional 36,154 votes cast. At the same 53.43% rate for Robinson, she would have received another 19,317 votes, with Tracy Christopher getting 16,837. That’s a 2,480 vote net for Robinson, which would be enough for her to win, by 1,291 votes. Tamika Craft would still fall short, but Dems would have won three out of four races instead of just two.

Of course, we can’t just give straight ticket voting back to Harris County and not the other nine counties. I’m not going to run through the math for each county, but given that Christopher did better in the non-Harris Counties, we can assume she’s net a few votes in them if straight ticket voting were still in effect. Maybe it wouldn’t be enough – remember, there were far more votes in Harris than in the other nine, and the Republican advantage wasn’t that much bigger, so the net would be smaller. It’s speculation built on guesswork, and it’s all in service of making up for the fact that the Democratic candidates could have done better in Harris County with the votes that were cast than they did. Let’s not get too wishful in our thinking here.

So does this affect my advice from the previous post? Not really – we still need to build on what we’re already doing, and figure out how to do better in the places where we need to do better. Maybe a greater focus judicial races is needed, by which I mean more money spent to advertise the Democratic judicial slate. As we’ve observed, these are close races in what is clearly very swingy territory, at least for now. With close races, there’s a broad range of possible factors that could change the outcome. Pick your preference and get to work on it.

Precinct analysis: Appellate courts, part 1

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial
Other jurisdictions

My next two posts in this series will focus on the 1st and 14th Courts of Appeals. These courts are a little strange electorally, as the elections cover ten counties in all, and over the past few elections they have proven to be pretty darned balanced. As we know, turnout in Harris County has gone up a lot in recent years, and the county has gone from evenly split to strongly blue, yet the balance in these ten counties persists. In this post, I’m going to do a bit of a historical review, to look at the trends and see if we can spot the underlying metrics.


2008 - 1st CoA Pl 3 (50.58%)

County   Tot Votes   Share  DemVotes    Dem%
============================================
Harris   1,111,642  70.74%   585,249  52.65%
Others     459,704  29.26%   209,510  45.57%

2012 - 14th CoA Pl 3 (47.74%)

County   Tot Votes   Share  DemVotes    Dem%
============================================
Harris   1,137,580  69.82%   580,356  51.01%
Others     491,673  30.18%   197,511  40.17%

2016 - 1st CoA Pl 4 (48.95%)

County   Tot Votes   Share  DemVotes    Dem%
============================================
Harris   1,273,638  69.00%   671,908  52.76%
Others     572,258  31.00%   231,702  40.49%

2018 - 1st CoA Pl 2 (50.93%)

County   Tot Votes   Share  DemVotes    Dem%
============================================
Harris   1,187,403  68.63%   647,398  54.52%
Others     542,765  31.37%   233,693  43.06%

2020 - 1st CoA Pl 3 (50.76%)

County   Tot Votes   Share  DemVotes    Dem%
============================================
Harris   1,575,122  68.23%   856,056  54.35%
Others     733,364  31.77%   314,644  42.90%

2020 - 1st CoA Pl 5 (50.10%)

County   Tot Votes   Share  DemVotes    Dem%
============================================
Harris   1,573,903  68.24%   845,951  53.75%
Others     732,455  31.76%   309,497  42.25%

2020 - 14th CoA Chief Justice (49.97%)

County   Tot Votes   Share  DemVotes    Dem%
============================================
Harris   1,575,801  68.23%   841,923  53.43%
Others     733,698  31.77%   312,231  42.56%

2020 - 14th CoA Pl 7 (49.57%)

County   Tot Votes   Share  DemVotes    Dem%
============================================
Harris   1,573,716  68.25%   833,925  52.99%
Others     732,057  31.75%   309,115  42.23%

A couple of points of explanation here. For 2008, 2012, 2016, and 2018, I picked the top Democratic performer among the appellate court candidates. For 2008, that meant the one Democratic winner. In 2018, as every Dem won their race, I went with the candidate with the narrowest victory, since what I’m most interested in is the threshold needed to win. For 2020, I included all four candidates.

In each table, I separated out the total votes cast in that race from Harris County, and from all the other counties. “Share” is the share of the vote that came from Harris County, so in the 2008 race 70.74% of the total vote came from Harris County. “DemVotes” is the total number of votes the Democratic candidate got, in Harris and in the other counties, and “Dem%” is the percentage of the vote that Democratic candidate got.

We see that the share of the vote from Harris County has dropped every year, from over 70% in 2008 to a bit more than 68% this year. That doesn’t appear to be predictive of anything, as Dems swept these races in 2018 and won two out of four this year, with the lowest-performing Dem having (by a tiny amount) the largest Harris County vote share. The rise of Fort Bend County as a Democratic bastion has no doubt mitigated the shrinking contribution from Harris, but that points out again the importance of counties around Harris, as the reddening of Galveston and the smaller counties has kept these races competitive. One thing I hadn’t realized till I went through this exercise was that Waller County was quite close to even in 2008, but gave Republicans a 7K vote edge in 2020. Indeed, Dem candidates in Waller in 2020 were getting about the same number of votes as Dem candidates in Waller in 2008, after two cycles of failing to meet the 2008 number, as the Republican vote steadily climbed. As we have discussed before, Jane Robinson lost her race by 0.06 percentage points, or a bit more than a thousand votes out of over 1.5 million votes cast. In a race that close, you can point to many, many ways in which a small difference would have changed the outcome.

That’s one reason why these races interest me so much. For one, the appellate courts were a place where Dems made numerous pickups in 2020, yet still fell a bit short of expectations – I at least thought we’d win all four of these, given how well we’d done in 2018. But as you can see, it wasn’t quite to be. I don’t want to downplay the races we did win – Veronica Rivas Molloy and Amparo Guerra are both terrific candidates, and they are now the only Latinas on that court – I’m just greedy enough to have wanted more.

What’s frustrating to me is that I can’t tell what I think is the magic formula here. The difference between Guerra, who won by four thousand votes and 0.20 percentage points, and Robinson is tiny enough to be rounding error. The main difference is that Guerra won Harris County by ten thousand votes more than Robinson did, while Robinson did five thousand votes better in the other counties than Guerra did (she lost them by 421K while Guerra lost them by 426K). We know that Latinx candidates generally did better in Harris County this year than their peers, but that wasn’t the case outside Harris County. And even if it was, that’s not much of a lesson to learn. It was a game of inches, and we won one and lost one.

Ultimately, I think the path here is the same as the path I’ve described in the various “key counties” posts. We’re starting to move in the right direction in Brazoria County, and if we can keep that going that could be enough to tip the scales to the blue side on a longer-term basis. Basically, if we keep doing what we’re doing we’ll likely be at least competitive in these races, and if we can step it up a bit, especially but not exclusively in Brazoria, we can do better than that. Maybe not the deepest insight you’ll ever read, but it’s what I’ve got.

(Assuming that the judicial districts don’t get redrawn, which I suppose they could. In 2004, the First and Fourteenth districts included Burleson, Trinity, and Walker Counties plus the current ten. We’d have zero chance of winning these races if those three were added back in. I have no idea what the process or criteria for defining the judicial districts is. I’m just saying that if Republicans decided to do something about this, they probably could.)

Next up, I’ll do the district breakdown for these four races in Harris County. After that, more judicial races and then on to the other county races. As always, let me know what you think.

Precinct analysis: Other jurisdictions

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016
Statewide judicial

You may be wondering “Hey, how come you haven’t reported on data from SBOE and State Senate districts?” Well, I’ll tell you, since the SBOE and Senate serve four-year terms with only half of the races up for election outside of redistricting years, the results in the districts that aren’t on the ballot are not discernable to me. But! I was eventually able to get a spreadsheet that defined all of the relevant districts for each individual precinct, and that allowed me to go back and fill in the empty values. And now here I present them to you. Oh, and as a special bonus, I merged the data from the 2012 city of Houston bond elections into this year’s totals and pulled out the numbers for the city of Houston for the top races. So here you have it:


Dist     Trump    Biden    Lib    Grn  Trump%  Biden%   Lib%   Grn%
===================================================================
SBOE4  110,192  350,258  3,530  1,787  23.66%  75.20%  0.76%  0.38%
SBOE6  371,101  391,911  8,796  2,157  47.95%  50.64%  1.14%  0.28%
SBOE8  219,337  176,022  4,493  1,185  54.69%  43.89%  1.12%  0.30%
								
SD04    55,426   25,561    936    145  67.54%  31.15%  1.14%  0.18%
SD06    61,089  123,708  1,577    770  32.64%  66.10%  0.84%  0.41%
SD07   232,201  188,150  4,746  1,216  54.47%  44.13%  1.11%  0.29%
SD11    77,325   51,561  1,605    389  59.08%  39.40%  1.23%  0.30%
SD13    38,198  166,939  1,474    753  18.42%  80.51%  0.71%  0.36%
SD15   110,485  208,552  3,444  1,045  34.15%  64.46%  1.06%  0.32%
SD17   110,788  140,986  2,706    720  43.41%  55.25%  1.06%  0.28%
SD18    15,118   12,735	   331     91  53.47%  45.04%  1.17%  0.32%

Hou    285,379  535,713  8,222  2,704  34.30%  64.39%  0.99%  0.32%
Harris 415,251  382,480  8,597  2,425  51.34%  47.29%  1.06%  0.30%


Dist    Cornyn    Hegar    Lib    Grn Cornyn%  Hegar%   Lib%   Grn%
===================================================================
SBOE4  110,002  330,420  8,479  5,155  23.62%  70.94%  1.82%  1.11%
SBOE6  387,726  359,196 13,130  4,964  50.68%  46.95%  1.72%  0.65%
SBOE8  220,500  164,540  7,608  2,770  55.76%  41.61%  1.92%  0.70%
								
SD04    56,085   23,380  1,405    393  69.02%  28.77%  1.73%  0.48%
SD06    59,310  115,620  3,609  2,257  32.80%  63.95%  2.00%  1.25%
SD07   237,216  173,948  7,682  2,796  55.64%  40.80%  1.80%  0.66%
SD11    77,887   47,787  2,508    854  60.36%  37.03%  1.94%  0.66%
SD13    39,386  157,671  3,502  2,149  19.43%  77.78%  1.73%  1.06%
SD15   114,616  195,264  6,065  2,657  35.43%  60.35%  1.87%  0.82%
SD17   118,460  128,628  3,892  1,603  46.42%  50.40%  1.53%  0.63%
SD18    15,268   11,859    554    180  54.80%  42.56%  1.99%  0.65%

Hou    297,735  498,078 14,537  7,021  36.43%  60.94%  1.78%  0.86%
Harris 420,493  356,080 14,680  5,868  52.75%  44.67%  1.84%  0.74%


Dist    Wright    Casta    Lib    Grn Wright%  Casta%   Lib%   Grn%
===================================================================
SBOE4  102,521  332,324  8,247  7,160  22.01%  71.35%  1.77%  1.54%
SBOE6  379,555  347,938 16,311  9,217  50.40%  46.21%  2.17%  1.22%
SBOE8  214,771  163,095  8,573  4,631  54.92%  41.70%  2.19%  1.18%
								
SD04    54,997   22,915  1,715    685  68.48%  28.53%  2.14%  0.85%
SD06    54,732  118,635  3,389  2,751  30.49%  66.09%  1.89%  1.53%
SD07   232,729  169,832  9,084  4,902  54.59%  39.84%  2.13%  1.15%
SD11    75,580   47,284  2,906  1,454  59.41%  37.17%  2.28%  1.14%
SD13    37,009  156,577  3,653  3,306  18.45%  78.08%  1.82%  1.65%
SD15   111,109  192,351  6,833  4,347  34.34%  59.45%  2.11%  1.34%
SD17   115,654  124,174  4,931  3,219  45.32%  48.66%  1.93%  1.26%
SD18    15,037   11,590    620    344  54.50%  42.01%  2.25%  1.25%

Hou    286,759  491,191 16,625 11,553  34.47%  59.04%  2.00%  1.39%
Harris 410,088  352,168 16,506  9,455  50.71%  43.54%  2.04%  1.17%

Dist     Hecht  Meachum    Lib  Hecht% Meachum%  Lib%
=====================================================
SBOE4  104,675  334,600 10,745  23.26%  74.35%  2.39%
SBOE6  387,841  349,776 17,294  51.38%  46.33%  2.29%
SBOE8  217,760  164,210  9,466  55.63%  41.95%  2.42%
						
SD04    55,773   22,920  1,721  69.36%  28.50%  2.14%
SD06    56,313  117,884  4,832  31.45%  65.85%  2.70%
SD07   235,317  172,232  9,800  56.38%  41.27%  2.35%
SD11    77,081   47,122  3,169  60.52%  37.00%  2.49%
SD13    37,495  158,731  4,500  18.68%  79.08%  2.24%
SD15   113,248  194,232  7,612  35.94%  61.64%  2.42%
SD17   119,941  123,630  5,196  48.21%  49.70%  2.09%
SD18    15,108   11,836    675  54.70%  42.85%  2.44%

Dist      Boyd   Will's    Lib   Boyd% Will's%   Lib%
=====================================================
SBOE4  104,397  336,102  8,832  23.23%  74.80%  1.97%
SBOE6  380,861  354,806 15,618  50.69%  47.23%  2.08%
SBOE8  217,360  164,288  8,525  55.71%  42.11%  2.18%
						
SD04    55,481   22,982  1,621  69.28%  28.70%  2.02%
SD06    56,932  117,444  4,132  31.89%  65.79%  2.31%
SD07   234,080  173,025  8,683  56.30%  41.61%  2.09%
SD11    76,633   47,377  2,834  60.42%  37.35%  2.23%
SD13    36,755  160,184  3,557  18.33%  79.89%  1.77%
SD15   111,564  195,699  6,798  35.52%  62.31%  2.16%
SD17   116,011  126,731  4,723  46.88%  51.21%  1.91%
SD18    15,162   11,755    627  55.05%  42.68%  2.28%


Dist     Busby   Triana    Lib  Busby% Triana%   Lib%
=====================================================
SBOE4  104,071  335,587  9,074  23.19%  74.79%  2.02%
SBOE6  389,317  343,673 17,392  51.88%  45.80%  2.32%
SBOE8  218,278  162,376  9,125  56.00%  41.66%  2.34%
						
SD04    55,864   22,402  1,739  69.83%  28.00%  2.17%
SD06    55,719  118,801  4,006  31.21%  66.55%  2.24%
SD07   235,948  169,843  9,532  56.81%  40.89%  2.30%
SD11    77,324   46,265  3,101  61.03%  36.52%  2.45%
SD13    37,498  158,536  3,962  18.75%  79.27%  1.98%
SD15   113,780  192,651  7,220  36.28%  61.42%  2.30%
SD17   120,435  121,393  5,349  48.72%  49.11%  2.16%
SD18    15,098   11,746    682  54.85%  42.67%  2.48%


Dist    Bland    Cheng  Bland%   Cheng%
=======================================
SBOE4  112,465  336,620  25.04%  74.96%
SBOE6  401,946  350,154  53.44%  46.56%
SBOE8  225,783  164,516  57.85%  42.15%
				
SD04    57,378   22,793  71.57%  28.43%
SD06    60,243  118,418  33.72%  66.28%
SD07   243,089  172,941  58.43%  41.57%
SD11    79,757   47,134  62.85%  37.15%
SD13    40,242  160,069  20.09%  79.91%
SD15   119,474  194,619  38.04%  61.96%
SD17   124,299  123,453  50.17%  49.83%
SD18    15,712   11,864  56.98%  43.02%


Dist     BertR  Frizell  BertR% Frizell%
=======================================
SBOE4  107,445  340,670  23.98%  76.02%
SBOE6  392,514  355,217  52.49%  47.51%
SBOE8  221,860  166,900  57.07%  42.93%
				
SD04    56,609   23,176  70.95%  29.05%
SD06    57,800  120,402  32.44%  67.56%
SD07   239,113  175,071  57.73%  42.27%
SD11    78,483   47,818  62.14%  37.86%
SD13    38,419  161,433  19.22%  80.78%
SD15   115,389  197,276  36.90%  63.10%
SD17   120,576  125,566  48.99%  51.01%
SD18    15,430   12,046  56.16%  43.84%


Dist     Yeary  Clinton  Yeary%Clinton%
=======================================
SBOE4  107,727  339,999  24.06%  75.94%
SBOE6  387,309  359,489  51.86%  48.14%
SBOE8  221,725  166,780  57.07%  42.93%
				
SD04    56,405   23,323  70.75%  29.25%
SD06    58,285  119,666  32.75%  67.25%
SD07   238,608  175,225  57.66%  42.34%
SD11    78,085   48,109  61.88%  38.12%
SD13    38,214  161,577  19.13%  80.87%
SD15   114,407  197,949  36.63%  63.37%
SD17   117,277  128,438  47.73%  52.27%
SD18    15,480   11,982  56.37%  43.63%


Dist    Newell    Birm  Newell%   Birm%
=======================================
SBOE4  110,449  336,329  24.72%  75.28%
SBOE6  392,944  352,514  52.71%  47.29%
SBOE8  223,453  164,440  57.61%  42.39%
				
SD04    56,669   22,936  71.19%  28.81%
SD06    59,575  117,944  33.56%  66.44%
SD07   240,463  172,769  58.19%  41.81%
SD11    78,816   47,161  62.56%  37.44%
SD13    39,166  160,126  19.65%  80.35%
SD15   116,700  195,074  37.43%  62.57%
SD17   119,849  125,464  48.86%  51.14%
SD18    15,608   11,810  56.93%  43.07%

To be clear, “Harris” refers to everything that is not the city of Houston. It includes the other cities, like Pasadena and Deer Park and so forth, as well as unincorporated Harris County. There are some municipal results in the 2020 canvass, and maybe I’ll take a closer look at them later – I generally haven’t done that for non-Houston cities in the past, but this year, we’ll see. Please note also that there are some precincts that include a piece of Houston but are not entirely Houston – the boundaries don’t coincide. Basically, I skipped precincts that had ten or fewer votes in them for the highest-turnout 2012 referendum, and added up the rest. So those values are approximate, but close enough for these purposes. I don’t have city of Houston results for most elections, but I do have them for a few. In 2008, Barack Obama got 61.0% in Houston and 39.5% in non-Houston Harris County. In 20122018, Beto reached a new height with 65.4% in Houston; that calculation was done by a reader, and unfortunately he didn’t do the corresponding total for Harris County. Joe Biden’s 64.39% fits in just ahead of Adrian Garcia in 2012, and about a point behind Beto. Not too bad.

SBOE4 is a mostly Black district primarily in Harris County with a piece in Fort Bend as well; Lawrence Allen, son of State Rep. Alma Allen and an unsuccessful candidate for HD26 in the Dem primary this year, is its incumbent. SBOE8 is a heavily Republican district with about half of its voters in Harris County and about a third in Montgomery County. It was won this year by Audrey Young over a Libertarian opponent, succeeding Barbara Cargill. Cargill was unopposed in 2016 and beat a Dem candidate in 2012 by a 71-29 margin, getting about 66% of the vote in Harris County. Like just about everywhere else, that part of the county is a lot less red than it used to be. SBOE6 was of course the focus of attention after Beto carried it in 2018. Biden fell a tad short of Beto’s mark, though Trump also fell short of Ted Cruz. No other Dem managed to win the vote there, with the range being about four to seven points for the Republicans, which does represent an improvement over 2018. Michelle Palmer lost by two points here, getting 47.38% of the vote (there was a Libertarian candidate as well; the victorious Republican got 49.76%), as the Dems won one of the three targeted, Beto-carried seats, in SBOE5. I presume the Republicans will have a plan to make the SBOE a 10-5 split in their favor again, but for now the one gain Dems made in a districted office was there.

I don’t think I’ve ever done a full accounting of State Senate districts in previous precinct analyses. Only three of the eight districts that include a piece of Harris County are entirely within Harris (SDs 06, 07, and 15; 13 extends into Fort Bend), and only SD17 is competitive. Beto and a couple of others carried SD17 in 2018 – I don’t have the full numbers for it now, but Rita Lucido won the Harris County portion of SD17 by a 49.4-48.8 margin in 2018, and every Dem except Kathy Cheng won SD17 this year, with everyone else except Gisela Triana exceeding Lucido’s total or margin or both. An awful lot of HD134 is in SD17, so this is just another illustration of HD134’s Democratic shift.

The other interesting district here is SD07, which Dan Patrick won by a 68.4-31.6 margin in 2012, and Paul Bettencourt won by a 57.8-40.3 margin in 2018. Every Dem had a smaller gap than that this year, with most of them bettering David Romero’s percentage from 2018, and Biden losing by just over ten points. It would be really interesting to see how this district trended over the next decade if we just kept the same lines as we have now, but we will get new lines, so the question becomes “do the Republicans try to shore up SD07”, and if so how? SD17 is clearly the higher priority, and while you could probably leave SD07 close to what it is now, with just a population adjustment, it doesn’t have much spare capacity. If there’s a lesson for Republicans from the 2011 redistricting experience, it’s that they have to think in ten-year terms, and that’s a very hard thing to do. We’ll see how they approach it.

Precinct analysis: Statewide judicial

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts
Comparing 2012 and 2016

We’re going to take a look at the seven statewide judicial races in this post, with all of the districts considered so far grouped together. You’re about to have a lot of numbers thrown at you, is what I’m saying. I’m ordering these races in a particular way, which is to put the contests that included a Libertarian candidate first (there were no Green candidates for any statewide judicial position, or indeed any judicial position on the Harris County ballot), and then the contests that were straight up D versus R next. There were three of the former and four of the latter, and we’ll see what we can determine about the effect that a Libertarian may have had on these races as we go.


Dist    Hecht  Meachum    Lib  Hecht% Meachum%   Lib%
=====================================================
CD02  179,887  154,785  7,979  52.50%   45.17%  2.33%
CD07  154,058  149,348  6,725  49.68%   48.16%  2.17%
CD08   25,686   15,145  1,014  61.38%   36.19%  2.42%
CD09   37,479  119,471  3,516  23.36%   74.45%  2.19%
CD10  101,965   60,290  3,917  61.36%   36.28%  2.36%
CD18   58,684  179,178  5,906  24.07%   73.50%  2.42%
CD22   21,575   20,271  1,140  50.19%   47.16%  2.65%
CD29   48,349  101,662  4,049  31.38%   65.99%  2.63%
CD36   82,593   48,435  3,259  61.50%   36.07%  2.43%
						
HD126  38,883   33,427  1,726  52.52%   45.15%  2.33%
HD127  53,978   35,464  2,040  59.00%   38.77%  2.23%
HD128  48,000   22,103  1,606  66.94%   30.82%  2.24%
HD129  47,867   35,292  2,208  56.07%   41.34%  2.59%
HD130  69,884   32,443  2,440  66.70%   30.97%  2.33%
HD131   9,887   44,240  1,236  17.86%   79.91%  2.23%
HD132  50,149   48,527  2,544  49.54%   47.94%  2.51%
HD133  51,732   35,958  1,730  57.85%   40.21%  1.93%
HD134  50,646   56,804  2,018  46.27%   51.89%  1.84%
HD135  36,285   36,987  1,891  48.28%   49.21%  2.52%
HD137  10,333   20,930    827  32.20%   65.22%  2.58%
HD138  31,730   30,982  1,548  49.38%   48.21%  2.41%
HD139  15,475   44,630  1,365  25.17%   72.60%  2.22%
HD140   9,151   21,719    840  28.86%   68.49%  2.65%
HD141   6,824   35,967    981  15.59%   82.17%  2.24%
HD142  13,637   41,662  1,238  24.12%   73.69%  2.19%
HD143  11,821   24,338    938  31.87%   65.61%  2.53%
HD144  13,535   16,631    867  43.61%   53.59%  2.79%
HD145  14,758   26,918  1,255  34.38%   62.70%  2.92%
HD146  11,363   43,152  1,235  20.38%   77.40%  2.22%
HD147  14,973   53,050  1,799  21.44%   75.98%  2.58%
HD148  22,163   36,851  1,701  36.50%   60.70%  2.80%
HD149  21,616   30,814  1,133  40.36%   57.53%  2.12%
HD150  55,585   39,695  2,339  56.94%   40.66%  2.40%
					
CC1    92,529  278,828  8,580  24.35%   73.39%  2.26%
CC2   149,483  145,171  7,746  49.43%   48.01%  2.56%
CC3   228,402  210,197 10,006  50.91%   46.86%  2.23%
CC4   239,862  214,392 11,173  51.54%   46.06%  2.40%
						
JP1    93,898  163,620  6,237  35.60%   62.03%  2.36%
JP2    33,762   49,003  2,174  39.75%   57.69%  2.56%
JP3    51,276   68,138  2,733  41.98%   55.78%  2.24%
JP4   233,213  185,525  9,970  54.40%   43.28%  2.33%
JP5   204,389  214,695  9,945  47.64%   50.04%  2.32%
JP6     7,834   27,042  1,074  21.79%   75.22%  2.99%
JP7    18,495   99,632  2,600  15.32%   82.53%  2.15%
JP8    67,409   40,933  2,772  60.67%   36.84%  2.49%

Dist     Boyd Williams    Lib   Boyd%Williams%   Lib%
=====================================================
CD02  177,810  155,876  7,349  52.14%   45.71%  2.15%
CD07  149,700  152,887  5,923  48.52%   49.56%  1.92%
CD08   25,674   15,116    894  61.59%   36.26%  2.14%
CD09   37,235  120,311  2,810  23.22%   75.03%  1.75%
CD10  101,850   60,145  3,613  61.50%   36.32%  2.18%
CD18   57,552  180,778  5,054  23.65%   74.28%  2.08%
CD22   21,529   20,300  1,030  50.23%   47.36%  2.40%
CD29   48,900  101,209  3,423  31.85%   65.92%  2.23%
CD36   82,368   48,573  2,879  61.55%   36.30%  2.15% 

HD126  38,664   33,525  1,557  52.43%   45.46%  2.11%
HD127  53,700   35,556  1,891  58.92%   39.01%  2.07%
HD128  48,078   22,019  1,431  67.22%   30.78%  2.00%
HD129  47,371   35,620  2,000  55.74%   41.91%  2.35%
HD130  69,697   32,424  2,234  66.79%   31.07%  2.14%
HD131   9,814   44,580    937  17.74%   80.57%  1.69%
HD132  50,168   48,466  2,311  49.70%   48.01%  2.29%
HD133  49,946   37,393  1,520  56.21%   42.08%  1.71%
HD134  47,593   59,069  1,938  43.82%   54.39%  1.78%
HD135  36,215   37,075  1,607  48.35%   49.50%  2.15%
HD137  10,226   21,044    708  31.98%   65.81%  2.21%
HD138  31,413   31,231  1,372  49.07%   48.79%  2.14%
HD139  15,293   44,932  1,208  24.89%   73.14%  1.97%
HD140   9,270   21,715    677  29.28%   68.58%  2.14%
HD141   6,943   36,106    738  15.86%   82.46%  1.69%
HD142  13,649   41,816  1,006  24.17%   74.05%  1.78%
HD143  11,953   24,211    783  32.35%   65.53%  2.12%
HD144  13,712   16,444    757  44.36%   53.19%  2.45%
HD145  14,749   26,907  1,082  34.51%   62.96%  2.53%
HD146  10,957   43,683    985  19.70%   78.53%  1.77%
HD147  14,628   53,564  1,547  20.98%   76.81%  2.22%
HD148  21,551   37,172  1,616  35.72%   61.61%  2.68%
HD149  21,554   30,949    980  40.30%   57.87%  1.83%
HD150  55,473   39,693  2,090  57.04%   40.81%  2.15%
						
CC1    90,441  281,651  7,183  23.85%   74.26%  1.89%
CC2   149,519  144,951  6,793  49.63%   48.11%  2.25%
CC3   224,732  213,022  8,935  50.31%   47.69%  2.00%
CC4   237,926  215,574 10,064  51.33%   46.50%  2.17%
						
JP1    90,471  166,282  5,724  34.47%   63.35%  2.18%
JP2    33,968   48,891  1,877  40.09%   57.70%  2.22%
JP3    51,567   68,134  2,269  42.28%   55.86%  1.86%
JP4   232,446  185,828  8,942  54.41%   43.50%  2.09%
JP5   201,507  217,080  8,748  47.15%   50.80%  2.05%
JP6     7,848   26,989    935  21.94%   75.45%  2.61%
JP7    17,772  100,858  2,001  14.73%   83.61%  1.66%
JP8    67,039   41,136  2,479  60.58%   37.18%  2.24%

Dist    Busby   Triana    Lib  Busby%  Triana%   Lib%
=====================================================
CD02  180,619  152,062  8,019  53.01%   44.63%  2.35%
CD07  154,593  146,826  6,759  50.16%   47.64%  2.19%
CD08   25,758   14,928    955  61.86%   35.85%  2.29%
CD09   37,362  119,463  3,094  23.36%   74.70%  1.93%
CD10  102,251   59,298  3,908  61.80%   35.84%  2.36%
CD18   58,913  178,629  5,394  24.25%   73.53%  2.22%
CD22   21,575   20,090  1,118  50.43%   46.96%  2.61%
CD29   47,694  102,644  3,275  31.05%   66.82%  2.13%
CD36   82,901   47,695  3,069  62.02%   35.68%  2.30%

HD126  38,980   33,040  1,658  52.91%   44.84%  2.25%
HD127  54,112   34,934  2,025  59.42%   38.36%  2.22%
HD128  48,180   21,765  1,477  67.46%   30.47%  2.07%
HD129  47,955   34,683  2,230  56.51%   40.87%  2.63%
HD130  70,019   31,790  2,447  67.16%   30.49%  2.35%
HD131   9,827   44,382  1,012  17.80%   80.37%  1.83%
HD132  50,189   48,200  2,493  49.75%   47.78%  2.47%
HD133  51,870   35,055  1,814  58.45%   39.50%  2.04%
HD134  51,239   55,036  2,250  47.21%   50.71%  2.07%
HD135  36,361   36,664  1,790  48.60%   49.01%  2.39%
HD137  10,325   20,780    812  32.35%   65.11%  2.54%
HD138  31,761   30,656  1,497  49.69%   47.96%  2.34%
HD139  15,489   44,606  1,222  25.26%   72.75%  1.99%
HD140   8,987   21,995    659  28.40%   69.51%  2.08%
HD141   6,791   36,116    798  15.54%   82.64%  1.83%
HD142  13,605   41,732  1,042  24.13%   74.02%  1.85%
HD143  11,665   24,588    733  31.54%   66.48%  1.98%
HD144  13,471   16,721    744  43.54%   54.05%  2.40%
HD145  14,593   27,092  1,061  34.14%   63.38%  2.48%
HD146  11,412   42,928  1,129  20.57%   77.39%  2.04%
HD147  15,183   52,758  1,661  21.81%   75.80%  2.39%
HD148  22,402   36,229  1,688  37.14%   60.06%  2.80%
HD149  21,574   30,729  1,065  40.42%   57.58%  2.00%
HD150  55,675   39,155  2,284  57.33%   40.32%  2.35%
						
CC1    92,822  277,923  7,778  24.52%   73.42%  2.05%
CC2   149,446  144,793  6,922  49.62%   48.08%  2.30%
CC3   228,849  207,334  9,987  51.29%   46.47%  2.24%
CC4   240,549  211,588 10,904  51.95%   45.70%  2.35%
						
JP1    94,735  161,383  6,127  36.12%   61.54%  2.34%
JP2    33,518   49,255  1,882  39.59%   58.18%  2.22%
JP3    51,327   68,119  2,341  42.14%   55.93%  1.92%
JP4   233,635  183,442  9,668  54.75%   42.99%  2.27%
JP5   204,626  212,437  9,722  47.95%   49.78%  2.28%
JP6     7,711   27,250    875  21.52%   76.04%  2.44%
JP7    18,508   99,518  2,270  15.39%   82.73%  1.89%
JP8    67,606   40,234  2,706  61.16%   36.40%  2.45%

Dist    Bland    Cheng  Bland%   Cheng%
=======================================
CD02  186,706  154,725  54.68%   45.32%
CD07  159,574  149,326  51.66%   48.34%
CD08   26,540   15,186  63.61%   36.39%
CD09   39,465  120,736  24.63%   75.37%
CD10  105,349   60,323  63.59%   36.41%
CD18   62,985  180,105  25.91%   74.09%
CD22   22,415   20,441  52.30%   47.70%
CD29   51,670  102,080  33.61%   66.39%
CD36   85,490   48,367  63.87%   36.13%

HD126  40,209   33,586  54.49%   45.51%
HD127  55,788   35,414  61.17%   38.83%
HD128  49,423   22,087  69.11%   30.89%
HD129  49,640   35,394  58.38%   41.62%
HD130  71,946   32,493  68.89%   31.11%
HD131  10,622   44,674  19.21%   80.79%
HD132  52,183   48,781  51.68%   48.32%
HD133  53,308   35,720  59.88%   40.12%
HD134  52,985   55,899  48.66%   51.34%
HD135  37,544   37,368  50.12%   49.88%
HD137  10,776   21,212  33.69%   66.31%
HD138  32,815   31,243  51.23%   48.77%
HD139  16,488   44,881  26.87%   73.13%
HD140   9,808   21,860  30.97%   69.03%
HD141   7,537   36,159  17.25%   82.75%
HD142  14,573   41,837  25.83%   74.17%
HD143  12,622   24,375  34.12%   65.88%
HD144  14,320   16,647  46.24%   53.76%
HD145  15,721   27,079  36.73%   63.27%
HD146  12,136   43,482  21.82%   78.18%
HD147  16,299   53,306  23.42%   76.58%
HD148  23,760   36,701  39.30%   60.70%
HD149  22,218   31,229  41.57%   58.43%
HD150  57,472   39,861  59.05%   40.95%
				
CC1    98,928  280,012  26.11%   73.89%
CC2   156,101  145,437  51.77%   48.23%
CC3   236,143  210,982  52.81%   47.19%
CC4   249,022  214,861  53.68%   46.32%
				
JP1    99,802  162,942  37.98%   62.02%
JP2    35,454   49,274  41.84%   58.16%
JP3    53,615   68,275  43.99%   56.01%
JP4   241,226  186,223  56.43%   43.57%
JP5   211,577  216,054  49.48%   50.52%
JP6     8,598   27,274  23.97%   76.03%
JP7    20,093  100,384  16.68%   83.32%
JP8    69,829   40,866  63.08%   36.92%

Dist    BertR  Frizell  BertR% Frizell%
=======================================
CD02  182,683  156,878  53.80%   46.20%
CD07  154,962  152,062  50.47%   49.53%
CD08   26,171   15,356  63.02%   36.98%
CD09   38,285  121,530  23.96%   76.04%
CD10  103,856   61,112  62.96%   37.04%
CD18   60,147  182,281  24.81%   75.19%
CD22   22,094   20,602  51.75%   48.25%
CD29   49,588  103,742  32.34%   67.66%
CD36   84,033   49,223  63.06%   36.94%
				
HD126  39,527   33,961  53.79%   46.21%
HD127  54,907   35,913  60.46%   39.54%
HD128  48,755   22,498  68.43%   31.57%
HD129  48,845   35,746  57.74%   42.26%
HD130  71,099   32,881  68.38%   31.62%
HD131  10,143   45,055  18.38%   81.62%
HD132  51,129   49,476  50.82%   49.18%
HD133  51,832   36,580  58.63%   41.37%
HD134  50,395   57,371  46.76%   53.24%
HD135  36,941   37,669  49.51%   50.49%
HD137  10,540   21,336  33.07%   66.93%
HD138  32,162   31,590  50.45%   49.55%
HD139  15,861   45,360  25.91%   74.09%
HD140   9,330   22,296  29.50%   70.50%
HD141   7,087   36,609  16.22%   83.78%
HD142  14,019   42,335  24.88%   75.12%
HD143  12,089   24,821  32.75%   67.25%
HD144  13,871   17,022  44.90%   55.10%
HD145  15,087   27,539  35.39%   64.61%
HD146  11,553   43,886  20.84%   79.16%
HD147  15,480   53,890  22.32%   77.68%
HD148  22,624   37,382  37.70%   62.30%
HD149  21,970   31,301  41.24%   58.76%
HD150  56,572   40,268  58.42%   41.58%
				
CC1    94,471  283,329  25.01%   74.99%
CC2   152,430  147,946  50.75%   49.25%
CC3   231,007  213,789  51.94%   48.06%
CC4   243,911  217,725  52.84%   47.16%
				
JP1    94,825  166,188  36.33%   63.67%
JP2    34,572   49,950  40.90%   59.10%
JP3    52,322   69,282  43.03%   56.97%
JP4   237,425  188,270  55.77%   44.23%
JP5   207,011  218,653  48.63%   51.37%
JP6     8,115   27,625  22.71%   77.29%
JP7    18,911  101,267  15.74%   84.26%
JP8    68,638   41,554  62.29%   37.71%

Dist    Yeary  Clinton  Yeary% Clinton%
=======================================
CD02  181,198  157,995  53.42%   46.58%
CD07  151,549  154,946  49.45%   50.55%
CD08   26,274   15,252  63.27%   36.73%
CD09   38,213  121,550  23.92%   76.08%
CD10  103,978   60,908  63.06%   36.94%
CD18   59,656  182,560  24.63%   75.37%
CD22   21,975   20,676  51.52%   48.48%
CD29   50,071  103,069  32.70%   67.30%
CD36   83,847   49,311  62.97%   37.03%

HD126  39,406   34,008  53.68%   46.32%
HD127  54,799   35,974  60.37%   39.63%
HD128  48,866   22,330  68.64%   31.36%
HD129  48,336   36,186  57.19%   42.81%
HD130  71,143   32,784  68.45%   31.55%
HD131  10,107   45,059  18.32%   81.68%
HD132  51,349   49,189  51.07%   48.93%
HD133  50,252   37,973  56.96%   43.04%
HD134  47,809   59,740  44.45%   55.55%
HD135  36,998   37,557  49.63%   50.37%
HD137  10,513   21,328  33.02%   66.98%
HD138  31,954   31,731  50.18%   49.82%
HD139  15,775   45,409  25.78%   74.22%
HD140   9,482   22,099  30.02%   69.98%
HD141   7,189   36,455  16.47%   83.53%
HD142  14,134   42,173  25.10%   74.90%
HD143  12,173   24,673  33.04%   66.96%
HD144  13,989   16,866  45.34%   54.66%
HD145  15,119   27,441  35.52%   64.48%
HD146  11,410   43,976  20.60%   79.40%
HD147  15,255   54,067  22.01%   77.99%
HD148  22,154   37,759  36.98%   63.02%
HD149  21,889   31,344  41.12%   58.88%
HD150  56,659   40,145  58.53%   41.47%
				
CC1    93,178  284,268  24.69%   75.31%
CC2   152,526  147,534  50.83%   49.17%
CC3   228,374  215,887  51.41%   48.59%
CC4   242,683  218,581  52.61%   47.39%
				
JP1    92,164  168,445  35.36%   64.64%
JP2    34,638   49,779  41.03%   58.97%
JP3    52,563   68,943  43.26%   56.74%
JP4   237,318  188,099  55.78%   44.22%
JP5   205,042  220,128  48.23%   51.77%
JP6     8,132   27,549  22.79%   77.21%
JP7    18,576  101,549  15.46%   84.54%
JP8    68,328   41,778  62.06%   37.94%

Dist   Newell    Birm  Newell%    Birm%
=======================================
CD02  183,283  155,303  54.13%   45.87%
CD07  154,445  151,554  50.47%   49.53%
CD08   26,375   15,075  63.63%   36.37%
CD09   39,055  120,306  24.51%   75.49%
CD10  104,616   60,043  63.53%   36.47%
CD18   61,174  180,645  25.30%   74.70%
CD22   22,249   20,322  52.26%   47.74%
CD29   51,148  101,583  33.49%   66.51%
CD36   84,501   48,451  63.56%   36.44%

HD126  39,784   33,498  54.29%   45.71%
HD127  55,127   35,497  60.83%   39.17%
HD128  49,062   22,055  68.99%   31.01%
HD129  48,920   35,437  57.99%   42.01%
HD130  71,414   32,353  68.82%   31.18%
HD131  10,424   44,586  18.95%   81.05%
HD132  51,878   48,536  51.66%   48.34%
HD133  51,273   36,800  58.22%   41.78%
HD134  49,412   57,931  46.03%   53.97%
HD135  37,337   37,104  50.16%   49.84%
HD137  10,697   21,067  33.68%   66.32%
HD138  32,371   31,165  50.95%   49.05%
HD139  16,204   44,873  26.53%   73.47%
HD140   9,722   21,767  30.87%   69.13%
HD141   7,342   36,259  16.84%   83.16%
HD142  14,466   41,754  25.73%   74.27%
HD143  12,491   24,246  34.00%   66.00%
HD144  14,227   16,561  46.21%   53.79%
HD145  15,377   27,059  36.24%   63.76%
HD146  11,707   43,563  21.18%   78.82%
HD147  15,713   53,487  22.71%   77.29%
HD148  22,748   37,026  38.06%   61.94%
HD149  22,175   30,953  41.74%   58.26%
HD150  56,974   39,704  58.93%   41.07%
				
CC1    95,668  281,099  25.39%   74.61%
CC2   154,203  145,222  51.50%   48.50%
CC3   231,571  211,887  52.22%   47.78%
CC4   245,404  215,077  53.29%   46.71%
				
JP1    94,960  165,091  36.52%   63.48%
JP2    35,233   48,975  41.84%   58.16%
JP3    53,108   68,215  43.77%   56.23%
JP4   238,952  185,854  56.25%   43.75%
JP5   208,027  216,365  49.02%   50.98%
JP6     8,409   27,151  23.65%   76.35%
JP7    19,213  100,651  16.03%   83.97%
JP8    68,944   40,983  62.72%   37.28%

Another word about the order in which these races appeared. On the Harris County election returns page, they appeared in the order you’d expect: first was the Supreme Court Chief Justice race, then Places 6, 7, and 8, followed by Court of Criminal Appeals Places 3, 4, and 9. In other words, the order a random person off the streets might have put them in if they had been tasked with it. For whatever the reason, on the Secretary of State election returns page, the order is different: Chief Justice, then Supreme Court Places 8, 6, and 7, followed by CCA Places 4, 9, and 3. I have no idea why they did it this way.

What difference does it make? The answer is in the total number of votes cast. The generally accepted wisdom is that the farther down the ballot, the more likely it is that a voter will skip the race, presumably because they thought “well, that’s all the voting I have in me, I’m going to call it quits now”. This was the underpinning of the many breathless articles about the effect of not having straight ticket voting, which came with the implicit assumption that Democratic voters would have less endurance in them, thus giving Republican candidates farther down the ballot an advantage. You know how I felt about that.

That said, the dropoff effect was there, albeit in a small amount. Here are the turnout totals for each race, going by the order on the Harris County ballot, which I’m taking as the proper order for elsewhere in the state. (You can check other county election sites to check this, I’ve already spent too much time on it.)


Position      Statewide     Harris
==================================
President    11,315,056  1,640,818
Senate       11,144,040  1,614,525
RRC          11,000,982  1,594,345
SC Chief     10,997,978  1,596,369
SC Place 6   10,954,061  1,591,486
SC Place 7   10,961,811  1,590,486
SC Place 8   10,948,768  1,588,895
CCA Place 3  10,918,384  1,584,608
CCA Place 4  10,898,223  1,583,031
CCA Place 9  10,879,051  1,580,131

I included the other statewide races here for comparison. There is some dropoff, but it’s pretty small – at both the statewide and Harris County level, the last race still got more than 96% of the vote total of the Presidential race. The dropoff among just the state offices is much more minimal, which I can understand – if all you care about is who’s running the country, you’ll probably stop after President, Senate, and Congress, which will be the third race on your ballot. Note also that with one exception in each column, the totals comport with their order on the ballot. Someday I might like to meet the person who decides to get off the bus after voting in three of the four Supreme Court races, or one of the three CCA races. Today is not that day, however.

The other thing to talk about here is how the candidates in races with a Libertarian candidate did versus the ones in races without a Libertarian. My eyeball sense of it is that the Republican candidates in two-person races picked up more of the erstwhile Libertarian voters in the redder districts, and the effect was more diffuse in the Dem districts, but I can’t say that with any level of rigor. There are too many factors to consider, including the gender and race of the candidates and their campaign finances and tenure in office and who knows what else. Maybe someone with a PhD can create a viable model for this.

Beyond that, what we see in these numbers is what we’ve been seeing all along. CD07 was a slightly tougher environment than it was in 2018, with three of the seven Democratic candidates carrying it. CD02 is basically a seven- or eight-point Republican district. HD135 leaned slightly Democratic, while HDs 132 and 138 leaned slightly more Republican, and HD134 completed its journey to becoming a Democratic district. Commissioner Precincts 2, 3, and 4 were all slightly to slightly-more-than-slightly red, but it won’t take much in redistricting to flip that around, at least for precincts 2 and 3. Everyone carried Constable/JP precinct 5, while precinct 4 remains a bit of a stretch. Lather, rinse, repeat.

If you’re wondering why I haven’t included SBOE and State Senate districts in these reports before now, wonder no more. I’ll be delving into those next. Let me know what you think.

Precinct analysis: Comparing to 2012 and 2016

Introduction
Congressional districts
State Rep districts
Commissioners Court/JP precincts

I had meant to get to this last week, but SeditionPalooza took up too much of my time, so here we are. The intent of this post is to compare vote totals in each of the State Rep districts from 2012 to 2016, from 2016 to 2020, and from 2012 to 2020. The vote totals compared are from the Presidential and Railroad Commissioner races for each of these years, and for the Senate races from 2012 and 2020, as there was no Senate race in 2016.

President

								
Dist   12-16 R   12-16D   16-20R   16-20D   12-20R   12-20D
===========================================================
HD126   -3,207    5,285    6,100    9,611    2,893   14,896
HD127     -931    6,042    8,547   12,707    7,616   18,749
HD128      124    2,272    8,728    6,208    8,852    8,480
HD129   -3,226    5,992    8,844   11,033    5,618   17,025
HD130    2,216    6,749   14,229   13,325   16,445   20,074
HD131     -649    2,707    4,306    6,683    3,657    9,390
HD132    3,065   10,267   15,786   20,304   18,851   30,571
HD133   -7,791    8,688    5,592   12,018   -2,199   20,706
HD134  -10,938   15,346    6,692   17,904   -4,246   33,250
HD135   -2,571    6,505    6,664   11,473    4,093   17,978
HD137     -537    2,443    2,451    4,167    1,914    6,610
HD138   -2,804    6,451    6,537    9,433    3,733   15,884
HD139   -1,294    1,187    4,847    6,854    3,553    8,041
HD140     -733    4,416    4,146    1,855    3,413    6,271
HD141      222     -681    2,604    4,453    2,826    3,772
HD142      290    2,084    4,703    8,880    4,993   10,964
HD143   -1,042    3,226    4,500    1,495    3,458    4,721
HD144   -1,039    3,561    4,057    1,523    3,018    5,084
HD145   -1,291    5,594    5,310    5,088    4,019   10,682
HD146   -1,633     -884    2,459    6,864      826    5,980
HD147   -1,272    3,583    4,602    9,933    3,330   13,516
HD148   -1,489    8,544    5,634   10,180    4,145   18,724
HD149   -3,879    3,420    8,154    4,696    4,275    8,116
HD150      503    8,228   10,180   15,037   10,683   23,265
							
Total  -39,906  121,025  155,672  211,724  115,766  332,749

Senate

	
Dist    12-20R   12-20D
=======================
HD126    3,705   13,479
HD127    8,876   16,687
HD128    8,999    7,330
HD129    7,238   14,684
HD130   18,113   17,564
HD131    3,413    8,389
HD132   19,527   28,278
HD133    2,610   16,268
HD134    3,330   27,237
HD135    4,898   16,279
HD137    2,129    6,023
HD138    4,594   14,227
HD139    3,602    6,608
HD140    2,611    5,499
HD141    2,460    2,779
HD142    4,903    9,702
HD143    2,619    4,082
HD144    2,577    4,485
HD145    3,562   10,103
HD146    1,337    4,811
HD147    4,019   12,164
HD148    5,762   16,497
HD149    4,282    7,157
HD150   11,865   20,878
		
Total  137,031  291,210

RRC

								
Dist   12-16 R   12-16D   16-20R   16-20D   12-20R   12-20D
===========================================================
HD126   -1,676    3,559    4,735   10,131    3,059   13,690
HD127    1,006    4,180    6,933   13,217    7,939   17,397
HD128      989    1,200    7,749    6,681    8,738    7,881
HD129   -1,550    3,595    7,325   12,422    5,775   16,017
HD130    4,403    4,540   13,107   12,954   17,510   17,494
HD131     -465    1,814    3,419    6,824    2,954    8,638
HD132    4,638    8,171   14,267   19,768   18,905   27,939
HD133   -4,382    3,417    5,039   14,285      657   17,702
HD134   -5,177    6,106    5,497   23,976      320   30,082
HD135   -1,163    4,634    5,398   11,950    4,235   16,584
HD137     -132    1,538    1,929    4,571    1,797    6,109
HD138   -1,483    4,248    5,378   10,328    3,895   14,576
HD139     -551      -83    3,837    7,033    3,286    6,950
HD140     -321    2,969    2,874    2,855    2,553    5,824
HD141      181     -896    2,165    3,773    2,346    2,877
HD142      844    1,204    3,814    8,568    4,658    9,772
HD143     -550    1,586    3,148    2,910    2,598    4,496
HD144     -530    2,677    2,993    2,255    2,463    4,932
HD145     -531    3,369    3,983    7,142    3,452   10,511
HD146   -1,047   -2,256    1,853    7,402      806    5,146
HD147      104      536    3,510   11,837    3,614   12,373
HD148      665    4,416    4,945   12,352    5,610   16,768
HD149   -3,089    2,133    6,698    5,331    3,609    7,464
HD150    2,552    6,010    8,826   14,942   11,378   20,952
								
Total   -7,265   68,667  129,422  233,507  122,157  302,174

The columns represent the difference in vote total for the given period and party, so “12-16” means 2012 to 2016, “16-20” means 2016 to 2020, and “12-20” means 2012 to 2020. Each column has a D or an R in it, so “12-16R” means the difference between 2016 Donald Trump and 2012 Mitt Romney for the Presidential table, and so forth. In each case, I subtract the earlier year’s total from the later year’s total, so the “-3,207” for HD126 in the “12-16R” column for President means that Donald Trump got 3,207 fewer votes in HD126 than Mitt Romney got, and the “5,285” for HD126 in the “12-16D” column for President means that Hillary Clinton got 5,285 more votes than Barack Obama got. Clear? I hope so.

Note that there were 130K more votes cast in Harris County as a whole in 2016 than there were in 2012, and 320K more votes cast in the county in 2020 over 2016, which makes a grand total of 450K more votes in 2020 than 2012. Some districts grow faster than others, but as a general rule given the overall totals you should expect increases in each district to some extent.

I have left percentages and third party totals out of this discussion. As I have shown before, tracking changes in vote percentages can give a misleading view of whether the actual gap is growing or narrowing, and by how much. I also want to emphasize that in 2012, Harris County was very much a 50-50 proposition, and now it is very much not. Doing it this way help illustrate how and where that has happened, and by how much.

And yet, with all that said, I’m going to start with an observation about percentages. In 2012, Mitt Romney got 60% or more of the vote in eight State Rep districts – HDs 126, 127, 128, 129, 130, 133, 138, and 150. Ted Cruz, running for Senate against Paul Sadler, got 60% or more of the vote in ten State Rep districts, the same eight as Romney plus HDs 132 and 135 – yes, the same 132 and 135 that Dems won in 2018. I didn’t publish an analysis of the RRC race from that year, but a review of the spreadsheet that I created at the time confirmed that Christi Craddick, running against Dale Henry, got 60% or more of the vote in eleven State Rep districts, the same ten as Cruz plus HD134. In other words, every single Republican-held State Rep district in Harris County in 2012 was at least a 60% Republican district in the Railroad Commissioner race. Mitt Romney, it should be noted, just missed getting to 60% in HDs 132 and 135, and was over 57% in HD134, as was Cruz. (Let’s just say Cruz fell way short of that mark in 2018.)

You can see how much the vote totals shifted at the Presidential level from 2012 to 2016. Trump got nearly 40K fewer votes than Romney, a combination of crossovers, third-party and write-in voting, and just the gentle degradation of the Republican brand, as you can see by Wayne Christian’s reduced vote totals from Christie Craddick. Still, in 2016, Donald Trump scored 60% or more of the vote in three State Rep districts: HDs 127, 128, and 130. In 2016, Wayne Christian, running for RRC against Grady Yarbrough, scored 60% or more of the vote in four State Rep districts: the three that Trump got plus HD150. And finally, in 2016, Eva Guzman, running for State Supreme Court, scored 60% or more of the vote in six State Rep districts: the four Christian got plus HDs 129 and 133. HDs 132 and 135 were clearly competitive at the Presidential level – Trump won 132 by four points and 135 by two points; he also lost HD138 by a hair. He lost votes compared to Romney in 18 of 24 districts.

It is certainly true that Republicans in general and Donald Trump in particular did better in 2020 than most people expected them to do – surely, they did better than I expected them to do. Trump gained 155K votes over his 2016 total, which put 2020 Trump more than 100K votes ahead of Mitt Romney. Even though Joe Biden gained 211K votes over Hillary Clinton, for a net gain of 56K, Trump had net gains on Biden in seven districts – HDs 128, 130, 140, 143, 144, 145, and 149, with the latter five being Democratic districts and four of the five being Latino. Still, Dems had a net gain from 2012 to 2020 in every district except HD128, and some of those gains were truly huge – just look at 133 and 134, for starters. And Trump’s gains in the Dem districts largely melted away by the time you got to the RRC race, with Chrysta Castaneda coming close to matching Jim Wright’s increases in 140, 143, and 144, and far exceeding him in 145. It’s hard to say from this what if any staying power the Trump gains may have, though Dems should be paying close attention to what happened there regardless.

Anyway, back to the percentages: In 2020, Donald Trump, John Cornyn, and Jim Wright scored 60% or more of the vote in two State Rep districts: HDs 128 and 130. The only statewide Republicans to score 60% or more in a third State Rep district were the statewide judicial candidates who did not have a Libertarian opponent – Jane Bland, Bert Richardson, Kevin Patrick, and David Newell – who also reached that level in HD127. I haven’t published the statewide judicial race analysis yet so you’ll have to take my word for it for now, but in any event I trust you see the pattern. This is what I mean when I say that Republicans just don’t have any spare capacity in Harris County, and that will present problems for them in redistricting. Look at the numbers in districts like 126 and 129 and 133 and 150 in 2020, and compare them to the numbers in 132 and 135 and 138 in 2012. Where do you think things are going to be in another couple of cycles?

I’ve thrown a lot of words and numbers at you, so I’ll wrap it up here. I hope this helps illustrate what I’ve been saying, about how Dem gains have largely come from huge steps forward in formerly Republican turf, and how there’s still very much room for Dems to improve in their strongholds. We need to keep building on our gains from this past decade as we proceed into the 20s. I’ll have a look at the statewide judicial races next. Let me know what you think.

Precinct analysis: Commissioners Court and JP/Constable precincts

Introduction
Congressional districts
State Rep districts

We now zoom in for a look at various county districts, which are also called “precincts”. I don’t know why we have County Commissioner precincts and JP/Constable precincts to go along with regular voting precincts – it makes for a certain amount of either monotony or inaccuracy when I have to write about them – but it is what it is. Dems made a priority of County Commissioner Precinct 3 and didn’t get it, but did flip a longstanding Republican Justice of the Peace bench.


Dist    Trump    Biden    Lib    Grn  Trump%  Biden%   Lib%   Grn%
==================================================================
CC1    90,536  295,657  3,355  1,338  23.16%  75.64%  0.86%  0.34%
CC2   154,159  154,516  3,250  1,028  49.26%  49.37%  1.04%  0.33%
CC3   220,205  234,323  4,876  1,328  47.79%  50.86%  1.06%  0.29%
CC4   235,730  233,697  5,338  1,435  49.50%  49.08%  1.12%  0.30%

Dist    Trump    Biden    Lib    Grn  Trump%  Biden%   Lib%   Grn%
==================================================================
JP1    85,426  182,182  3,199    822  31.45%  67.07%  1.18%  0.30%
JP2    35,864   51,624    741    330  40.50%  58.29%  0.84%  0.37%
JP3    53,543   70,746  1,055    375  42.59%  56.27%  0.84%  0.30%
JP4   232,147  199,750  4,698  1,250  53.02%  45.62%  1.07%  0.29%
JP5   199,292  236,253  4,525  1,384  45.14%  53.52%  1.03%  0.31%
JP6     8,554   28,500    357    158  22.77%  75.86%  0.95%  0.42%
JP7    17,977  104,457    835    464  14.53%  84.42%  0.67%  0.38%
JP8    67,827   44,681  1,409    346  59.36%  39.10%  1.23%  0.30%

Dist   Cornyn    Hegar    Lib    Grn Cornyn%  Hegar%   Lib%   Grn%
==================================================================
CC1    94,601  278,805  6,735  3,743  24.20%  71.33%  1.72%  0.96%
CC2   152,772  144,150  6,038  2,703  48.82%  46.06%  1.93%  0.86%
CC3   229,016  214,734  7,608  3,129  49.71%  46.61%  1.65%  0.68%
CC4   241,839  216,469  8,836  3,314  50.79%  45.46%  1.86%  0.70%

Dist   Cornyn    Hegar    Lib    Grn Cornyn%  Hegar%   Lib%   Grn%
==================================================================
JP1    93,109  167,648  4,655  2,101  34.28%  61.72%  1.71%  0.77%
JP2    35,186   48,126  1,638    946  39.73%  54.34%  1.85%  1.07%
JP3    52,663   67,120  2,257  1,121  41.89%  53.39%  1.80%  0.89%
JP4   235,664  186,072  8,077  2,923  53.82%  42.50%  1.84%  0.67%
JP5   205,996  217,791  7,543  3,288  46.66%  49.33%  1.71%  0.74%
JP6     8,342   26,680    795    472  22.20%  71.02%  2.12%  1.26%
JP7    19,157   99,241  2,051  1,291  15.48%  80.21%  1.66%  1.04%
JP8    68,111   41,480  2,201    747  59.61%  36.30%  1.93%  0.65%

Dist   Wright    Casta    Lib    Grn Wright%  Casta%   Lib%   Grn%
==================================================================
CC1    90,035  276,291  7,330  5,863  23.03%  70.68%  1.88%  1.50%
CC2   146,598  145,934  6,329  3,756  46.84%  46.63%  2.02%  1.20%
CC3   223,852  208,983  9,167  5,678  48.59%  45.36%  1.99%  1.23%
CC4   236,362  212,151 10,305  5,711  49.64%  44.55%  2.16%  1.20%

Dist   Wright    Casta    Lib    Grn Wright%  Casta%   Lib%   Grn%
==================================================================
JP1    90,194  163,531  5,804  3,640  33.20%  60.20%  2.14%  1.34%
JP2    32,881   49,373  1,605  1,218  37.13%  55.75%  1.81%  1.38%
JP3    50,924   67,644  2,207  1,398  40.51%  53.81%  1.76%  1.11%
JP4   230,575  183,069  9,233  5,036  52.66%  41.81%  2.11%  1.15%
JP5   200,704  213,004  8,895  5,800  45.46%  48.25%  2.01%  1.31%
JP6     7,490   27,172    730    651  19.94%  72.33%  1.94%  1.73%
JP7    17,970   98,421  2,115  2,039  14.52%  79.54%  1.71%  1.65%
JP8    66,109   41,145  2,542  1,226  57.86%  36.01%  2.22%  1.07%

First things first, the Justice of the Peace and Constable precincts are the same. There are eight of them, and for reasons I have never understood they are different sizes – as you can see, JPs 4 and 5 are roughly the size of Commissioners Court precincts, at least as far as voting turnout goes, JP1 is smaller but still clearly larger than the rest, and JP6 is tiny. When I get to have a conversation with someone at the county about their plans for redistricting, I plan to ask if there’s any consideration for redrawing these precincts. Note that there are two JPs in each precinct – Place 1 was up for election this cycle, with Place 2 on the ballot in 2022. The Constables are on the ballot with the Place 1 JPs. I’ll return to them in a minute.

You may recall from my first pass at Harris County data, Donald Trump had a super slim lead in Commissioners Court Precinct 2, home of Adrian Garcia. That was from before the provisional ballots were cured. There were something like five or six thousand provisional ballots, and overall they were pretty Democratic – I noted before that this almost pushed Jane Robinson over the top in her appellate court race – though they weren’t uniformly pro-Dem; Wesley Hunt in CD07 and Mike Schofield in HD132 netted a few votes from the provisionals, among those that I looked at more closely. In CC2, the provisional ballots put Joe Biden ever so slightly ahead of Trump, by a teensy but incrementally larger lead than Trump had had. MJ Hegar lost CC2 by a noticeable amount, and Chrysta Castaneda missed it by a hair.

Now, in 2018 Beto won CC2 by over six points. Every statewide candidate except for Lupe Valdez carried it, and every countywide candidate except for Lina Hidalgo carried it. Oddly enough, Adrian Garcia himself just squeaked by, taking the lead about as late in the evening as Judge Hidalgo did to claim the majority on the Court for Dems. I’d have thought Garcia would easily run ahead of the rest of the ticket, but it was largely the reverse. The conclusion I drew from this was that being an incumbent Commissioner was an advantage – not quite enough of one in the end for Jack Morman, but almost.

I say that for the obvious reason that you might look at these numbers and be worried about Garcia’s future in 2022. I don’t think we can take anything for granted, but remember two things. One is what I just said, that there’s an incumbent’s advantage here, and I’d expect Garcia to benefit from it in two years’ time. And two, we will have new boundaries for these precincts by then. I fully expect that the Dem majority will make Garcia’s re-election prospects a little better, as the Republican majority had done for Morman in 2011.

The bigger question is what happens with the two Republican-held precincts. I’ve spoken about how there’s no spare capacity on the Republican side to bolster their existing districts while moving in on others. That’s not the case here for Dems with Commissioners Court. Given free rein, you could easily draw four reasonable Dem districts. The main thing that might hold you back is the Voting Rights Act, since you can’t retrogress Precinct 1. The more likely play is to dump some Republican turf from Precincts 2 and 3 into Precinct 4, making it redder while shoring up 2 for the Dems and making 3 more competitive. I wouldn’t sit around in my first term in office if I’m Tom Ramsey, is what I’m saying.

I should note that Beto also won CC3, as did Mike Collier and Justin Nelson and Kim Olson, but that’s largely it; I didn’t go back to check the various judicial races but my recollection is that maybe a couple of the Dem judicials carried it. Overall, CC3 was still mostly red in 2018, with a few blue incursions, and it remained so in 2020. I feel like it would be gettable in 2024 even without a boost from redistricting, but why take the chance? Dems can set themselves up here, and they should.

What about the office Dems flipped? That would be Justice of the Peace, Place 1, where longtime jurist Russ Ridgway finally met his match. You will note that Precinct 5 Constable Ted Heap held on by a 51.5 to 48.5 margin, almost the exact mirror of Israel Garcia’s 51.4 to 48.6 win over Ridgway. What might account for the difference? For one, as we’ve seen, candidates with Latino surnames have generally done a couple of points better than the average. For two, it’s my observation that more people probably know their Constable’s name than either of their JPs’ names. Your neighborhood may participate in a Constable patrol program, and even if you don’t you’ve surely seen road signs saying that the streets are overseen by Constable so-and-so. I think those two factors may have made the difference; I’m told Garcia was a very active campaigner as well, and that could have helped, but I can’t confirm that or compare his activity to Dem Constable candidate Mark Alan Harrison, so I’ll just leave it as a second-hand observation. Dems can certainly aim for the Place 2 JP in Precinct 5, and even though Precinct 4 was in the red I’d really like to see someone run against Laryssa Korduba, who is (as of last report, anyway) the only JP in Harris County who no longer officiates weddings following the Obergefell ruling. She’s consistent about it, and acting legally by not doing any weddings, and that’s fine by me as a personal choice, but that doesn’t mean the people of Precinct 4 couldn’t do better for themselves. I’d like to see them have that choice in 2022.

Next up, some comparisons to 2012 and 2016. Next week, we get into judicial races and county races. Let me know what you think.

Precinct analysis: State Rep districts

Introduction
Congressional districts

We move now to State Rep districts, which is my usual currency since they provide complete coverage of the county with no partial pieces. You can also get a much more nuanced view of how things have shifted over time. There are more numbers here since there are more districts, so buckle up.


Dist    Trump   Biden    Lib    Grn  Trump%  Biden%   Lib%   Grn%
=================================================================
HD126  38,651  36,031    740    264  51.07%  47.61%  0.98%  0.35%
HD127  53,644  38,409  1,024    215  57.50%  41.17%  1.10%  0.23%
HD128  49,349  23,343    742    198  67.02%  31.70%  1.01%  0.27%
HD129  47,389  38,941  1,125    246  54.03%  44.40%  1.28%  0.28%
HD130  69,369  35,958  1,298    220  64.92%  33.65%  1.21%  0.21%
HD131  10,508  45,904    331    192  18.46%  80.63%  0.58%  0.34%
HD132  50,223  51,737  1,190    360  48.52%  49.98%  1.15%  0.35%
HD133  47,038  43,262    965    201  51.43%  47.30%  1.06%  0.22%
HD134  42,523  67,811  1,356    238  37.99%  60.58%  1.21%  0.21%
HD135  36,114  39,657    862    246  46.98%  51.58%  1.12%  0.32%
HD137  10,382  22,509    308    144  31.14%  67.51%  0.92%  0.43%
HD138  31,171  34,079    703    226  47.10%  51.50%  1.06%  0.34%
HD139  15,691  46,918    511    241  24.76%  74.05%  0.81%  0.38%
HD140  10,259  22,819    227    150  30.67%  68.21%  0.68%  0.45%
HD141   7,443  37,222    289    178  16.49%  82.47%  0.64%  0.39%
HD142  14,187  43,334    469    189  24.39%  74.48%  0.81%  0.32%
HD143  13,229  25,318    282    141  33.95%  64.97%  0.72%  0.36%
HD144  14,598  17,365    308    150  45.03%  53.56%  0.95%  0.46%
HD145  15,393  28,572    462    185  34.50%  64.05%  1.04%  0.41%
HD146  10,938  45,784    439    204  19.07%  79.81%  0.77%  0.36%
HD147  14,437  56,279    734    278  20.13%  78.46%  1.02%  0.39%
HD148  20,413  41,117    901    203  32.59%  65.65%  1.44%  0.32%
HD149  22,419  32,886    428    172  40.10%  58.82%  0.77%  0.31%
HD150  55,261  42,933  1,125    287  55.48%  43.10%  1.13%  0.29%

Dist   Cornyn   Hegar    Lib    Grn Cornyn%  Hegar%   Lib%   Grn%
=================================================================
HD126  39,298  33,618  1,343    535  52.54%  44.95%  1.80%  0.72%
HD127  54,433  35,689  1,690    543  58.94%  38.64%  1.83%  0.59%
HD128  48,646  22,029  1,323    447  67.15%  30.41%  1.83%  0.62%
HD129  48,318  35,924  1,715    603  55.82%  41.50%  1.98%  0.70%
HD130  70,329  32,961  1,933    551  66.49%  31.16%  1.83%  0.52%
HD131  10,557  43,670    938    621  18.92%  78.28%  1.68%  1.11%
HD132  50,865  48,460  2,011    774  49.81%  47.46%  1.97%  0.76%
HD133  51,111  38,148  1,232    471  56.19%  41.94%  1.35%  0.52%
HD134  48,629  61,015  1,408    489  43.60%  54.70%  1.26%  0.44%
HD135  36,728  37,050  1,427    628  48.43%  48.86%  1.88%  0.83%
HD137  10,617  20,914    629    343  32.66%  64.34%  1.94%  1.06%
HD138  31,993  31,508  1,183    486  49.09%  48.35%  1.82%  0.75%
HD139  15,984  44,273  1,168    647  25.75%  71.33%  1.88%  1.04%
HD140   9,771  21,167    630    423  30.54%  66.17%  1.97%  1.32%
HD141   7,409  35,278    820    511  16.83%  80.14%  1.86%  1.16%
HD142  14,269  41,061  1,055    562  25.06%  72.10%  1.85%  0.99%
HD143  12,535  23,679    737    511  33.46%  63.21%  1.97%  1.36%
HD144  14,107  16,246    629    374  44.99%  51.81%  2.01%  1.19%
HD145  15,236  26,758    899    490  35.12%  61.68%  2.07%  1.13%
HD146  11,598  43,259    938    563  20.58%  76.76%  1.66%  1.00%
HD147  15,359  53,237  1,359    707  21.74%  75.34%  1.92%  1.00%
HD148  22,087  37,707  1,303    489  35.86%  61.23%  2.12%  0.79%
HD149  22,329  30,630    888    471  41.11%  56.39%  1.63%  0.87%
HD150  56,019  39,872  1,959    650  56.87%  40.48%  1.99%  0.66%

Dist   Wright   Casta    Lib    Grn Wright%  Casta%   Lib%   Grn%
=================================================================
HD126  38,409  32,979  1,562    942  51.98%  44.63%  2.11%  1.27%
HD127  53,034  35,348  1,948  1,026  58.05%  38.69%  2.13%  1.12%
HD128  47,576  22,153  1,382    605  66.34%  30.89%  1.93%  0.84%
HD129  46,707  35,326  2,084  1,095  54.81%  41.46%  2.45%  1.29%
HD130  69,295  31,825  2,387    981  66.32%  30.46%  2.28%  0.94%
HD131   9,786  43,714    930    899  17.69%  79.01%  1.68%  1.62%
HD132  49,947  47,483  2,288  1,389  49.40%  46.96%  2.26%  1.37%
HD133  50,069  36,455  1,636    998  56.16%  40.89%  1.83%  1.12%
HD134  47,504  57,938  2,155  1,239  43.65%  53.23%  1.98%  1.14%
HD135  35,845  36,487  1,706    988  47.78%  48.63%  2.27%  1.32%
HD137  10,168  20,606    695    589  31.72%  64.28%  2.17%  1.84%
HD138  31,201  30,796  1,377    859  48.57%  47.94%  2.14%  1.34%
HD139  15,235  44,188  1,166    895  24.78%  71.87%  1.90%  1.46%
HD140   8,840  21,955    515    509  27.78%  69.00%  1.62%  1.60%
HD141   6,885  35,470    766    654  15.73%  81.03%  1.75%  1.49%
HD142  13,584  41,134  1,041    788  24.02%  72.74%  1.84%  1.39%
HD143  11,494  24,467    657    563  30.91%  65.81%  1.77%  1.51%
HD144  13,250  16,851    603    417  42.58%  54.15%  1.94%  1.34%
HD145  14,246  27,135    903    703  33.14%  63.12%  2.10%  1.64%
HD146  10,964  42,686  1,034    947  19.71%  76.73%  1.86%  1.70%
HD147  14,711  52,289  1,554  1,199  21.09%  74.96%  2.23%  1.72%
HD148  21,527  36,656  1,580    869  35.50%  60.46%  2.61%  1.43%
HD149  21,458  30,419    976    727  40.05%  56.77%  1.82%  1.36%
HD150  55,111  38,995  2,186  1,127  56.57%  40.03%  2.24%  1.16%

There’s a lot here, and I’m going to try to limit the analysis in this post to just what’s here, since I will have a separate post that looks back at previous elections. I’m going to pick a few broad themes here and will continue when I get to that subsequent post.

It’s clear that the big districts for Republicans crossing over to vote for Biden were HDs 133 and 134. Biden basically hit Beto’s number in 134, and he made 133 nearly as competitive as 126. The same effect is visible but smaller in 126, 129, 138, and 150, but it’s more noticeable in the lower downballot Democratic total than the Republican number. Some of those votes migrate to third party candidates, some may be people just voting at the Presidential level – it’s hard to say for sure. In 2016, there were bigger third party totals at the Presidential level, but this year those numbers were more like prior norms.

However you look at this, the fact remains that Republicans don’t have a lot of areas of strength. Only HDs 128 and 130 performed consistently at a 60% level for them; as we will see with the judicial races, some candidates reached that number in HD127 as well. Spoiler alert for my future post: That’s a big change from 2012. We’ll get into that later, but what that means for now is what I was saying in the Congressional post, which is that there’s little spare capacity for Republicans to distribute. There’s some red they can slosh into HDs 132, 135, and 138 if they want, but it’s going to be hard to make more than a few Republican incumbents feel safe.

I’m still not comfortable calling HD134 a Democratic district – which is a bit meaningless anyway as we head into redistricting – but the numbers are what they are. There’s still some volatility, mostly in judicial races as you’ll see, but this district just isn’t what it used to be. After the 2016 election, when Greg Abbott went hard at Sarah Davis and the Trump effect was already obvious, I wondered what Republicans would do with that district, since they didn’t seem to care about Davis. Abbott subsequently rediscovered his pragmatic side, but Davis is now history, and this district is at least as blue as Harris County is overall, so they have a whole different problem to contemplate. If anyone reading this is of a mind to mourn Davis’ demise, I say put 100% of the blame on Donald Trump and the degeneracy he has brought forward in the GOP. Sarah Davis never took my advice to leave the Republican Party, but a lot of her former voters did. The future is always in motion, but at this point I would not expect them to come back.

On the flip side, Trump and the Republicans saw some gains in Democratic areas. The two that stand out to me are HDs 144 and 149 – Dems were well above 60% in the latter in 2016. Note how Chrysta Castaneda was the best performer in this group among Dems – her numbers in HD144 were comparable to Rep. Mary Ann Perez’s totals. As for 149, it was the inverse of HD133, more or less, without anyone making it look competitive. Here, Biden did about as well as Rep. Hubert Vo. I think this is more likely to be a Trump-catalyzed fluke than the start of a trend, but we’ll just have to see what the next elections tell us.

Finally, I should probably do a separate post on third party voting by State Rep district this cycle, but for now let me state the obvious that there was a whole lot less of it than in 2016, for a variety of reasons. I didn’t bother naming the Libertarian and Green candidates in the column headers above because honestly, even with the kerfuffle over both Republicans and Democrats trying to force them off the ballot for filing fee non-payment, there just wasn’t any attention on them this year. HD148 was the high-water mark for the Libertarian candidate in 2016 at the Presidential level, and HD134 topped the chart for Railroad Commissioner levels, with 4.53% in the former and an eye-popping 12.18% in the latter; the Chron endorsement of Mark Miller for RRC in 2016 surely helped him there. HD148 was the “winner” this year for each, though at much tamer 1.44% and 2.68%, respectively. For the Greens in 2016, it was HD137 for President (1.30%) and HD145 for RRC (6.49%), and this year it was HD144 (0.46%) for President and HD137 (1.84%) for RRC. You can say what you want about which third party affects which major party – I will note that Chrysta Castaneda outperformed Grady Yarbrough in HD134 by fifteen points, while Wayne Christian was four points better than Jim Wright in the same district. HD134 shifted strongly Dem in 2020, but the quality of the Dem also mattered.

Next up is a look at County Commissioner and JP/Constable precincts, and after that we’ll get that deeper look at 2020 versus 2016 and 2012. Let me know what you think.

Precinct analysis: Congressional districts

Introduction

All right, let’s get this party started. In the past I’ve generally done the top races by themselves, but any race involving Trump provides challenges, because his level of support just varies in comparison to other Republicans depending on where you look. So this year it felt right to include the other statewide non-judicial results in my Presidential analyses, and the only way to do that without completely overwhelming you with a wall of numbers was to break it out by district types. That seemed to also pair well with a closer look at the competitive districts of interest, of which there were more than usual this year. So let’s begin with a look at the Congressional districts in Harris County. Only CDs 02, 07, 18, and 29 are fully in Harris County – we won’t have the complete data on all Congressional districts until later – so just keep that in mind.


Dist    Trump    Biden    Lib    Grn  Trump%  Biden%   Lib%   Grn%
==================================================================
CD02  174,980  170,428  4,067    969  49.93%  48.63%  1.16%  0.28%
CD07  143,176  170,060  3,416    903  45.09%  53.55%  1.08%  0.28%
CD08   25,484   16,629    520     87  59.65%  38.93%  1.22%  0.20%
CD09   39,372  125,237  1,066    589  23.68%  75.32%  0.64%  0.35%
CD10  101,390   65,714  2,023    431  59.80%  38.76%  1.19%  0.25%
CD18   57,669  189,823  2,382    962  22.99%  75.68%  0.95%  0.38%
CD22   21,912   21,720    522    137  49.47%  49.04%  1.18%  0.31%
CD29   52,937  106,229  1,265    649  32.86%  65.95%  0.79%  0.40%
CD36   83,710   52,350  1,558    402  60.65%  37.93%  1.13%  0.29%

Dist   Cornyn    Hegar    Lib    Grn Cornyn%  Hegar%   Lib%   Grn%
==================================================================
CD02  180,504  157,923  6,215  2,164  52.37%  45.82%  1.80%  0.63%
CD07  152,741  154,670  4,939  2,161  48.90%  49.52%  1.58%  0.69%
CD08   25,916   15,259    846    221  61.67%  36.31%  2.01%  0.53%
CD09   39,404  118,424  2,725  1,677  24.54%  73.76%  1.70%  1.04%
CD10  102,919   60,687  3,168    939  61.71%  36.39%  1.90%  0.56%
CD18   60,111  178,680  4,806  2,468  24.68%  73.35%  1.97%  1.01%
CD22   21,975   20,283    898    377  50.92%  47.00%  2.08%  0.87%
CD29   51,044   99,415  3,022  1,969  33.26%  64.77%  1.97%  1.28%
CD36   83,614   48,814  2,598    913  61.92%  36.15%  1.92%  0.68%

Dist   Wright    Casta    Lib    Grn Wright%  Casta%   Lib%   Grn%
==================================================================
CD02  176,484  153,628  7,631  4,122  51.62%  44.94%  2.23%  1.21%
CD07  149,114  149,853  6,276  3,974  48.22%  48.46%  2.03%  1.29%
CD08   25,558   14,796    992    394  61.23%  35.45%  2.38%  0.94%
CD09   37,090  117,982  2,764  2,570  23.12%  73.55%  1.72%  1.60%
CD10  101,414   58,873  3,758  1,793  61.15%  35.50%  2.27%  1.08%
CD18   57,783  177,020  5,021  3,846  23.71%  72.65%  2.06%  1.58%
CD22   21,026   20,231  1,007    675  48.97%  47.12%  2.35%  1.57%
CD29   46,954  102,354  2,802  2,334  30.40%  66.27%  1.81%  1.51%
CD36   81,424   48,619  2,880  1,300  60.66%  36.22%  2.15%  0.97%

Dist      GOP      Dem    Lib    Grn    GOP%    Dem%   Lib%   Grn%
==================================================================
CD02  192,828  148,374  5,524         55.61%  42.79%  1.59%
CD07  149,054  159,529  5,542         47.75%  50.79%  1.76%
CD08   25,906   15,212    926         61.62%  36.18%  2.20%
CD09   35,634  121,576  4,799         22.00%  75.04%  2.96%
CD10  103,180   60,388  3,496         61.76%  36.15%  2.09%
CD18   58,033  180,952  4,514  3,396  23.51%  73.29%  1.83%  1.38%
CD22   20,953   19,743  2,291         48.74%  45.93%  5.33%
CD29   42,840  111,305  2,328         27.38%  71.13%  1.49%
CD36   84,721   46,545  2,579    985  62.84%  34.52%  1.91%  0.73%

The first three tables are the Presidential, Senate, and Railroad Commissioner results, in that order. Subsequent presentations with State Rep and JP/Constable precincts will be done in the same fashion. For this post, I have also included the actual Congressional results – each Congressional race had both a Dem and a Republican, which doesn’t always happen, so they provide a good point of comparison. The candidate labeled as “Green” in CD18 was actually an independent – only CD36 had an actual Green Party candidate. In the other Congressional races, there were only three candidates.

How competitive CD02 looks depends very much on how you’re looking at it. On the one hand, Joe Biden came within 1.3 points, with Trump failing to reach fifty percent. On the other hand, Dan Crenshaw won by almost thirteen points, easily exceeding his marks from 2018 while clearly getting some crossover support. In between was everything else – MJ Hegar and Chrysta Castaneda trailed by about six and a half points each, with third-party candidates taking an increasing share of the vote. As we’ll see, most of the time the spread was between seven and nine points. That doesn’t tell us too much about what CD02 will look like going forward, but it does tell us that it doesn’t have a large reserve of Republican votes in it that can be used to bolster other Republicans. One possible outcome is that the map-drawers decide that Crenshaw will punch above his weight – he certainly fundraises at a very high level – which will allow them to leave him in a seemingly-narrow district while tending to more urgent matters elsewhere. The downside there is that if and when Crenshaw decides he’s made for bigger things, this district would be that much harder to hold with a different Republican running in it.

Another possibility is that Republicans will decide that they’re better off turning CD07 into a more Dem-friendly district, and using the space Republican capacity from CD07 to bolster CDs 02 and maybe 10. Lizzie Fletcher didn’t win by much, though I will note that Wesley Hunt’s 47.75% is a mere 0.28 points better than John Culberson in 2018. (There was no Libertarian candidate in 2018; do we think that hurt Hunt or Fletcher more in this context?) But other than Biden, no Dem came close to matching Fletcher’s performance – Hegar and Castaneda were among the top finishers in CD07, as we will see going forward. Like Crenshaw, Fletcher got some crossovers as well. It’s a big question how the Republicans will approach CD07 in the redistricting process. In years past, before the big blue shift in the western parts of Harris County, my assumption had been that the weight of CD07 would continue to move west, probably poking into Fort Bend and Waller counties. I’m less sure of that now – hell, I have no idea what they will do. I have suggested that they make CD07 more Democratic, which would enable them to shore up CD02, CD10, maybe CD22. They could try to add enough Republicans to tilt CD07 red, and at least make Fletcher work that much harder if not endanger her. Or who knows, they could throw everything out and do a radical redesign, in which case who knows what happens to CD07. Harris is going to get a certain number of full and partial Congressional districts in it no matter what, and there are Republican incumbents who will want to keep various areas for themselves, and the Voting Rights Act is still in effect, so there are some constraints. But there’s nothing to say that CD07 will exist in some form as we now know it. Expect the unexpected, is what I’m saying.

None of the other districts had as large a variance in the Trump vote. He trailed Cornyn and Wright in total votes in every district except CDs 29 and 36 (he also led Wright in 22). He trailed the Republican Congressional candidate in every district except 09, 18, and 29, the three strong D districts. Conversely, Joe Biden led every Democratic candidate in every district except for Sylvia Garcia in CD29; Garcia likely got about as many crossover votes as Lizzie Fletcher did. I’m amused to see Trump beat the designated sacrificial lamb candidate in CD18, partly because he was one of the co-plaintiffs on the state lawsuit to throw out all of the drive-through votes, and partly because I saw far more yard signs for Wendell Champion in my mostly-white heavily Democratic neighborhood (*) than I did for Trump. Maybe this is what was meant by “shy Trump voters”.

One more point about redistricting. Mike McCaul won the Harris County portion of CD10 by 43K votes; he won it by 46K in 2012 and 47K in 2016. He won overall by 30K, after squeaking through in 2018 by 13K votes. He had won in 2012 by 64K votes, and in 2016 by 59K votes. Now, a big driver of that is the ginormous growth in the Travis County Dem vote – he went from a 14K deficit in Travis in 2012 to a 57K deficit in 2020. The point I’m making is that there’s not a well of spare Republican votes in CD10 that could be used to redden CD07, not without putting CD10 at risk. Again, the Republicans could throw the current map out and start over from scratch – there will be new districts to include, so to some extent that will happen anyway – it’s just that Harris County is going to be of limited, and decreasing, use to them. They have to work around Harris, not with it. It’s going to make for some interesting decisions on their part.

I’ll have a look at the State Rep districts next. Let me know what you think.

(*) The two main precincts for my neighborhood went for Biden over Trump by a combined 68-28.