Trafalgar Group
Graded against the actual result across 88 races (from 163 polls, through 2025).
Head-to-head vs VotePredictor Elections
The fair, apples-to-apples test: on the 87 races Trafalgar Group actually polled, how its final poll's margin compared to what VotePredictor Elections predicted for those same races.
| Model | Avg miss (pts) | Called right |
|---|---|---|
| Trafalgar Group | 4.15 | 66% |
| VotePredictor Elections | 3.53 | 81% |
VotePredictor Elections aggregates all the pollsters, so it's expected to beat any single one on margin — that's the value of averaging. The honest comparison among forecasters is on the combined board.
Every race (87)
Each race Trafalgar Group polled, scored on its final poll — the call right before the vote — against the actual Dem−Rep result. Click a race for its full detail.
Accuracy by time to election
Lower is better. Time to election runs right (election week) to left (~2 months out).
By the numbers
| Time to election | Polls | Avg miss | vs field | Called right |
|---|---|---|---|---|
| ≤1 wk | 60 | 3.79 | -0.45 | 63% |
| 1–3 wk | 49 | 3.83 | -1.23 | 65% |
| 3–6 wk | 37 | 3.56 | -2.14 | 81% |
| 6–9 wk | 17 | 4.77 | -1.37 | 77% |
vs field is this pollster's average miss minus all pollsters' at the same lead time — green beats the field, redtrails it. Our historical polls reach ~2 months out; earlier polling isn't in the record.
Track record by cycle — getting better?
| Year | Polls | Avg miss | Lean (house effect) |
|---|---|---|---|
| 2016 | 15 | 3.5 | R+0.2 |
| 2017 | 4 | 5.5 | R+1.5 |
| 2018 | 19 | 5.0 | R+2.7 |
| 2020 | 39 | 2.1 | R+0.9 |
| 2021 | 3 | 0.8 | D+0.6 |
| 2022 | 56 | 5.6 | R+5.1 |
| 2024 | 24 | 1.7 | D+1.0 |
Do we credit a pollster for fixing its bias? Each cycle, the model re-estimates every pollster's lean from all its earlier polls (walk-forward) and subtracts it before using the poll. We tested weighting recent cycles more — it doesn't help: a pollster's lean in one cycle barely predicts the next (correlation 0.28), so the swings above are mostly noise, and averaging over more history beats chasing the latest cycle. The all-time estimate we use came out within ~0.5% of the best option.