Civiqs
Graded against the actual result across 53 races (from 72 polls, through 2022).
Head-to-head vs the VotePredictor model
The fair, apples-to-apples test: on the 53 races Civiqs actually polled, how its final poll's margin compared to what the VotePredictor model predicted for those same races.
| Model | Avg miss (pts) | Called right |
|---|---|---|
| Civiqs | 4.29 | 83% |
| VotePredictor | 3.63 | 85% |
VotePredictor 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 (53)
Each race Civiqs 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 | 10 | 5.32 | +1.04 | 80% |
| 1–3 wk | 21 | 4.84 | -0.23 | 76% |
| 3–6 wk | 30 | 4.13 | -1.61 | 80% |
| 6–9 wk | 11 | 7.64 | +1.49 | 91% |
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) |
|---|---|---|---|
| 2020 | 39 | 5.3 | D+5.1 |
| 2022 | 32 | 4.8 | D+3.7 |
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.