Data Orbital
Graded against the actual result across 10 races (from 24 polls, through 2024).
Head-to-head vs VotePredictor Elections
The fair, apples-to-apples test: on the 10 races Data Orbital actually polled, how its final poll's margin compared to what VotePredictor Elections predicted for those same races.
| Model | Avg miss (pts) | Called right |
|---|---|---|
| Data Orbital | 2.27 | 80% |
| VotePredictor Elections | 1.74 | 90% |
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 (10)
Each race Data Orbital 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.
| Race | Their call | Result | Miss | Call |
|---|---|---|---|---|
| 2024 AZ President | R+7.8 | R+5.5 | 2.3 | ✓ |
| 2024 AZ Senate | R+0.7 | D+2.4 | 3.1 | ✗ |
| 2022 AZ Governor | R+3.1 | D+0.7 | 3.8 | ✗ |
| 2022 AZ Senate | D+1.7 | D+4.9 | 3.2 | ✓ |
| 2020 AZ President | D+0.6 | D+0.3 | 0.3 | ✓ |
| 2020 AZ Senate | D+1.1 | D+2.3 | 1.2 | ✓ |
| 2018 AZ Governor | R+15.6 | R+14.2 | 1.5 | ✓ |
| 2018 AZ Senate | D+8.2 | D+2.3 | 5.8 | ✓ |
| 2016 AZ President | R+3.0 | R+3.5 | 0.5 | ✓ |
| 2016 AZ Senate | R+12.0 | R+13.0 | 1.0 | ✓ |
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 | 6 | 1.67 | -2.61 | 83% |
| 1–3 wk | 9 | 2.84 | -2.23 | 89% |
| 3–6 wk | 7 | 3.70 | -2.04 | 57% |
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 | 10 | 2.3 | D+1.3 |
| 2020 | 7 | 2.9 | D+2.5 |
| 2022 | 3 | 3.4 | R+3.4 |
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.