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Baldwin Wallace University Community Research Institute

Graded against the actual result across 11 races (from 22 polls, through 2022).

Races polled
11
Polls
22
Avg miss
6.84 pts
Most recent
2022

Head-to-head vs VotePredictor Elections

The fair, apples-to-apples test: on the 11 races Baldwin Wallace University Community Research Institute actually polled, how its final poll's margin compared to what VotePredictor Elections predicted for those same races.

ModelAvg miss (pts)Called right
Baldwin Wallace University Community Research Institute7.7282%
VotePredictor Elections3.9391%

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 (11)

Each race Baldwin Wallace University Community Research Institute 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.

RaceTheir callResultMissCall
2022 OH GovernorR+16.6R+25.08.4
2022 OH SenateD+4.2R+6.110.3
2020 MI PresidentD+7.0D+2.84.2
2020 OH PresidentR+1.6R+8.06.4
2020 PA PresidentD+5.1D+1.23.9
2020 WI PresidentD+6.7D+0.66.1
2020 MI SenateD+5.9D+1.74.2
2018 OH GovernorR+0.6R+3.73.1
2018 OH SenateD+19.5D+6.812.7
2016 OH PresidentD+8.8R+8.116.9
2016 OH SenateR+12.3R+20.98.6

Accuracy by time to election

24686–9 wk3–6 wk1–3 wk≤1 wkavg miss (pts)
Baldwin Wallace University Community Research InstituteAll pollsters (field average)

Lower is better. Time to election runs right (election week) to left (~2 months out).

By the numbers

Time to electionPollsAvg missvs fieldCalled right
1–3 wk48.62+3.5575%
3–6 wk96.79+1.0589%
6–9 wk96.10-0.0578%

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?

YearPollsAvg missLean (house effect)
201866.4D+6.0
2020105.1D+5.1
202248.8D+8.8

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.