We see a larger drop in support for McAuliffe (compared to Biden) in the suburbs and a larger drop among young people, both of which are due to a combination of turnout changes (Democrats staying home) and vote switching (Biden-Youngkin voters). These are groups and areas that have not shown evidence of being particularly partisan in the past. Middle scores tend to include more independents, swing voters and voters for whom models do not have robust projections. A score of 100 is a high likelihood of voting Democratic while a score of 0 is a high likelihood of voting Republican. Our estimates show a fairly even decline in support across Virginia voters, with some exceptions.Īs is often the case, we see the largest drop among “middle scorers” in our Vote Choice Index model and “swing neighborhoods.” 2 Our Vote Choice Index model projects the likelihood that a voter will cast a ballot for a Democratic candidate in a typical two-party race. None of the major or minor conclusions from the original memo have changed. Now that we have received individual-level vote history data from the Virginia Secretary of State, we are updating the graphs and numbers in the memo to reflect the actual vote history. We’d also like to thank Scott Anderson and Carly Hawkins with the Strategic Victory Fund and Brian Stryker and Megan Crowe from Impact Research for their contributions to this analysis.Ī preliminary version of this memo was originally written and circulated immediately after the 2021 election in Virginia at that time, we used turnout projections based on a pre-election turnout model, early voting data, and precinct-level election results.

1 We would like to particularly thank Justine D'Elia-Kueper, Maggie Dart-Padover, Sarah Grant, Alan Julson, Jesse Zlotoff, Matt Zetkulic, Anna Baringer, Russ Rampersad, Dan Buttrey, Jordan Tessler, Mary Toole, and John Kim in particular for their many important contributions to this project. This report would not have been possible without the dedication of many on the Catalist team, whose hard work maintaining this national database is paramount to our ability to produce this report. The authors would also like to thank Meg Schwenzfeier, Hillary Anderson, and Molly Chapman Norton for their feedback and assistance in putting together this memo and the Catalist Data and Analytics departments for the foundational work they do supporting this effort. Edited by Aaron Huertas, Site design by Melissa Amarawardana

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