The four months following the 2020 Elections have been a whirlwind, to say the least. The fervor, meticulosity, and ubiquity that for months accompanied any and all mention of November 3rd seems, on the surface, to have died down. However, there is still much to glean from the less visible (but far from inconsequential) aspects of the election. Professional analysts and dilettantes alike have spent hours upon hours dissecting these aspects in order to gain a better understanding of what exactly contributed to the phenomena that we observed leading up to and following Election Day. There are those who have delved deeper than merely the state level, or even county level results; analyzing voting precincts as well as congressional and legislative districts to get a better grasp of what exactly happened last November. The results of these in-depth analyses have been crucial to our understanding of voting trends. For example, precinct analysis of Orange County, CA revealed a Democratic collapse among Vietnamese voters that was overshadowed by a county wide pro-Democratic swing. The nebulous, notorious cabal of amateur analysts, journalists, and psephologists known as “Election Twitter” has dedicated an impressive amount of time to researching the allocation of split precincts in the hopes of calculating the presidential margins of all 435 U.S. congressional seats. The conclusions have been stunning. Because of increasing interest in state and local elections, the detail with which voters, observers, and candidates can identify shifting trends and pinpoint what circumstances yielded which results has increased astronomically. Much has been learned on a micro level about nearly every state. One notable exception to this is the Commonwealth of Virginia.
What’s up with Virginia? Virginia was one of the many states that experienced a surge in absentee voting last year. The problem with this uptick was not how fast Virginia could count these ballots (it counted well over 95% of them within 24 hours of poll closing), but rather how these ballots were allocated.
In most states, absentees are allocated to precincts. If a voter lives in precinct A, and votes with an absentee ballot, their vote appears in the precinct A tallies. Ostensibly, this makes a fair amount of sense. It’s an efficient way to account for votes that are not of the typical format (in-person) and therefore do not work well with the established infrastructure. However, there is a caveat– Virginia has Central Absentee Precincts (CAP).
In Virginia, a voter who lives in precinct A, but votes by absentee, has their vote tallied in their county’s CAP. To a casual observer who is only concerned with county results, this makes no difference. Decision Desk or the New York Time’s 2020 election results page will display Virginia’s results by county with perfect accuracy. The problem arises when looking deeper than the county level; How did my neighborhood vote? That’s a question that becomes much more complicated with CAPs. It’s easy to figure out how the non-Absentee voters in your precinct voted, but it’s much more difficult to know how many people in your precinct voted Absentee, and how they voted. Sure, you could look at the non-Absentee vote, but that is an incredibly flawed metric. Republicans overwhelmingly voted non-absentee, so those numbers are far from a fair representation of one’s precinct. There is a clear issue here, and the consequence is a lack of meaningful analysis of the 2020 Presidential election in Virginia.
To make the situation even more dire, the CAP/absentee incompatibility issue is time-sensitive. The 2021 Virginia elections are on the horizon and the entire lower chamber is up for grabs. The Virginia House of Delegates consists of 100 seats, and there are dozens of opportunities for county splits, i.e. seats that exist in only certain parts of counties. Republicans and Democrats alike are trying to figure out which seats could be competitive this fall, and the lack of specialized results from the most recent elections could be a major issue for some campaigns. A common district metric is the previous statewide performance within the district. These answer questions like “How did Trump do in this seat in 2016?”, or “How did Tim Kaine manage to win this district in 2018”, or “Did Biden flip this seat in 2020?”. The first two questions can be answered with relative ease. You can find breakdowns of the 2016 presidential and 2018 U.S. Senate elections by Virginia House of Delegate seat on vpap.org – the Virginia Public Access Project. However, there have been no estimates for how Joe Biden did in every single House of Delegate seat. These are serious questions that merit serious answers, and in recognizing the necessity of meaningful analysis, I took the time to go review results from the 2020 elections to provide estimates for each Virginia HoD seat.
How was I able to do this? Well, providing exact figures was impossible for the aforementioned reasons, but I was able to leverage existing information to provide accurate estimates. This information included the complete countywide breakdowns in order to calculate the swings from the 2016 to 2020 presidential election on the county level. I have attached said map below:

We also know how the seats voted in the 2016 presidential election due to the stellar work done by those at the Virginia Public Access Project. I was able to use the known county swings to estimate the swings in House of Delegates seats from the 2016 presidential election. Of course, this presents an obvious problem; this assumes that the swings within counties are uniform, which is obviously false. This is where the estimating comes into play. We know the demographic profile of Virginia precincts, the building blocks of legislative seats. A useful tool in this instance was Dave’s Redistricting App, and I was able to leverage these known demographic quantities to refine my estimates (displayed in the table at the conclusion of this piece). Precinct analysis from other states (where available) has suggested that Joe Biden made great gains among college educated Whites, more or less held steady among Whites without a college degree, slightly fell with African Americans, moderately declined with Asian Americans, and had a steep decline with Hispanic voters compared to Clinton in 2016. In his 2020 election autopsy, former Obama campaign alumnus David Shor provides detailed estimates for these groups– I cannot recommend it highly enough.
Ultimately, I found that Joe Biden won 61 out of the 100 House of Delegates seats, which is actually 6 more seats the Democrats currently possess. It’s unlikely that Democrats will be able to match Biden everywhere, especially in certain suburban seats around Richmond and Virginia Beach, but this is an optimistic result for Democrats. The median seats (two, as there are an even number of seats) tracked closely with the statewide results. Given that Virginia is now a bona fide blue state, I can confidently say that this is good news for Democrats this November. Additionally, Mark Warner, who was also on the 2020 ballot running for U.S. Senate, won 63/100 seats, winning all of the House of Delegates seats Biden won in addition to HoD-14 (Danville), and HoD-54 (Spotsylvania).
2020 Presidential Election Margins by HoD Seat
(Positive Values Indicate Biden Win)
District | 2020 Estimate | District | 2020 Estimate | District | 2020 Estimate | District | 2020 Estimate |
1 | -0.64 | 26 | -0.03 | 51 | 0.13 | 76 | 0.19 |
2 | 0.28 | 27 | 0.06 | 52 | 0.53 | 77 | 0.29 |
3 | -0.67 | 28 | 0.08 | 53 | 0.51 | 78 | -0.16 |
4 | -0.58 | 29 | -0.23 | 54 | -0.02 | 79 | 0.2 |
5 | -0.58 | 30 | -0.24 | 55 | -0.16 | 80 | 0.4 |
6 | -0.59 | 31 | 0.14 | 56 | -0.13 | 81 | 0.02 |
7 | -0.29 | 32 | 0.27 | 57 | 0.61 | 82 | -0.04 |
8 | -0.25 | 33 | -0.07 | 58 | -0.1 | 83 | 0.13 |
9 | -0.46 | 34 | 0.26 | 59 | -0.26 | 84 | 0.05 |
10 | 0.13 | 35 | 0.44 | 60 | -0.14 | 85 | 0.08 |
11 | 0.3 | 36 | 0.5 | 61 | -0.21 | 86 | 0.39 |
12 | 0.06 | 37 | 0.4 | 62 | 0.01 | 87 | 0.31 |
13 | 0.19 | 38 | 0.48 | 63 | 0.09 | 88 | -0.06 |
14 | -0.08 | 39 | 0.42 | 64 | -0.21 | 89 | 0.66 |
15 | -0.48 | 40 | 0.14 | 65 | -0.21 | 90 | 0.35 |
16 | -0.25 | 41 | 0.35 | 66 | 0.12 | 91 | 0.09 |
17 | -0.2 | 42 | 0.25 | 67 | 0.29 | 92 | 0.48 |
18 | -0.23 | 43 | 0.45 | 68 | 0.17 | 93 | 0.16 |
19 | -0.46 | 44 | 0.46 | 69 | 0.74 | 94 | 0.21 |
20 | -0.18 | 45 | 0.6 | 70 | 0.41 | 95 | 0.4 |
21 | 0.11 | 46 | 0.62 | 71 | 0.75 | 96 | -0.04 |
22 | -0.33 | 47 | 0.59 | 72 | 0.15 | 97 | -0.37 |
23 | -0.24 | 48 | 0.5 | 73 | 0.15 | 98 | -0.3 |
24 | -0.36 | 49 | 0.64 | 74 | 0.49 | 99 | -0.18 |
25 | -0.19 | 50 | 0.2 | 75 | 0.07 | 100 | 0.04 |