Resolution Process: On the first day of the three months prior to the US presidential election (i.e. 1 Sep, 1 Oct, 1 Nov) I will record in a spreadsheet the probabilities (rounded to nearest integer) each forecasting product has most recently assigned to either a Democrat or Republican winning in each Electoral College region. When the actual results are finalized post-election, I will take a Brier score based on the forecasts made for the candidate that ultimately won, and add up the total for each forecasting product.

The forecasting product with the lowest Brier score resolves YES, all other forecasting products resolve NO.

Criteria for Inclusion: For an election forecasting product to be eligible to resolve YES, the forecasting product must:

1. make forecasts for all or nearly all Electoral College regions (e.g. if a forecasting product doesn't track the special districts in Maine and Nebraska, but covers all 50 state-level races, that's fine; so this criterion excludes Metaculus, which only covers 19 battleground states)

2. use numeric probabilities (can’t just label races as “toss-up” or “likely”, needs to be like a percentage chance out of 100)

3. be public with its numbers (so Nate Silver's election model, which will be paywalled, won't qualify)

4. be a cohesive product (so PredictIt, which has some election markets, won’t qualify unless they put together something systematic and organized in the fashion of Polymarket or Manifold)

5. not be too obscure or small; so a lone non-famous analyst making a forecasting product would not merit inclusion

An election forecasting product that someone adds to this question that fails any of these criteria for inclusion will resolve NO and I won’t track its probabilities.

Below are links to the forecasting products/models that meet the criteria for inclusion so far:

• FiveThirtyEight

• The Economist

• The Hill / Decision Desk HQ

• Polymarket

• Manifold