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University of Cincinnati (Ohio Poll)

Graded against the actual result across 14 races (from 52 polls, through 2012).

Races polled
14
Polls
52
Avg miss
4.92 pts
Most recent
2012

Every race (14)

Each race University of Cincinnati (Ohio Poll) 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
2012 OH PresidentD+1.5D+3.01.5
2012 OH SenateD+3.8D+6.02.2
2010 OH GovernorR+4.0R+2.02.0
2010 OH SenateR+21.0R+17.43.6
2008 OH PresidentD+6.0D+4.61.4
2006 OH GovernorD+22.0D+23.91.9
2006 OH SenateD+12.0D+12.30.3
2004 OH PresidentR+1.0R+2.11.1
2004 OH SenateR+30.0R+27.72.3
2002 OH GovernorR+18.7R+19.50.8
2000 OH PresidentR+10.0R+3.56.5
2000 OH SenateR+28.9R+24.14.8
1998 OH GovernorR+11.0R+5.45.6
1998 OH SenateR+24.0R+12.911.1

Accuracy by time to election

24686–9 wk3–6 wk1–3 wk≤1 wkavg miss (pts)
University of Cincinnati (Ohio Poll)All 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 wk122.36-1.92100%
1–3 wk154.18-0.8987%
3–6 wk107.43+1.6990%
6–9 wk156.04-0.1187%

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)
19981010.4R+10.4
200064.2R+4.2
200231.9D+1.9
200463.2R+1.3
200666.3R+6.3
200855.8R+5.2
201082.8R+2.1
201281.7R+0.9

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.