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Public validation record

2026 Football Model Performance

These results use official OSPR projections locked before kickoff and evaluated against final scores. Mirrored schedule records and live forecasts are excluded.

Evaluated through Oct 16, 2026

Accuracy calculated Oct 17, 2026 8:01 AM EDT

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Performance summary

3,178 games evaluated with ospr-2026.1

Games evaluated

3,178

Winner accuracy

69.8%

2,217 correct

Average margin error

22.3

Lower is better

Average score error

13.1

Per-team points

Brier score

0.197

Probability accuracy

Close projection rate

14.5%

Correct and within 7

Regular season vs. playoffs

A direct comparison using the selected season, week, team, and OSPR model version.

Regular season

Games
3,178
Winner accuracy
69.8%
Margin error
22.3

Playoffs

Games
0
Winner accuracy
—
Margin error
—

Performance by week

Results for the selected model version and season phase.

Week Games Winner accuracy Margin error
Week 1 355 58.3% 22.0
Week 2 351 61.0% 23.3
Week 3 358 62.3% 21.9
Week 4 354 65.3% 23.5
Week 5 356 74.4% 22.6
Week 6 357 80.4% 22.7
Week 7 358 75.4% 22.0
Week 8 348 71.3% 21.8
Week 9 340 79.7% 20.5

Probability calibration

Observed win rate should approach the average predicted probability as sample sizes grow.

Probability Games Predicted Observed Gap Brier
0–9% 21 8.4% 4.8% -3.7 0.045
10–19% 209 15.8% 8.6% -7.2 0.084
20–29% 351 25.4% 21.1% -4.3 0.168
30–39% 487 35.1% 33.5% -1.6 0.222
40–49% 608 45.1% 43.1% -2.0 0.244
50–59% 533 54.9% 57.4% +2.6 0.246
60–69% 439 64.8% 71.5% +6.7 0.204
70–79% 356 74.8% 80.6% +5.9 0.158
80–89% 157 84.1% 88.5% +4.4 0.101
90–99% 17 91.6% 94.1% +2.5 0.057

Performance by prediction confidence

Newer snapshots use historical calibration and comparable sample size. Legacy snapshots fall back to rating-evidence confidence.

Confidence Games Winner accuracy Average margin error
High 2,686 70.7% 22.2 points
Medium 49 87.8% 23.3 points
Low 443 61.9% 22.6 points

Performance by risk indicator

A game may appear in more than one group because indicators describe different kinds of uncertainty.

Indicator Games Winner accuracy Average margin error
Limited Data 1,516 62.3% 22.9 points
Close Game 2,217 63.5% 22.1 points
Upset Possible 2,064 62.4% 21.9 points
Blowout Range 1 100.0% 23.8 points

Largest misses

The largest margin errors in this selection. A miss is a model result to learn from, not automatically a data error.

Date Matchup Projected Final Margin error
Sep 11, 2026 Farrell vs. Reynolds 25–24 84–0 82.5 points
Sep 25, 2026 Normandy vs. Rocky River 14–28 0–83 68.7 points
Oct 16, 2026 Springfield Northwestern vs. Benjamin Logan 15–25 0–78 68.5 points
Oct 16, 2026 Trimble vs. Waterford 21–24 0–69 65.9 points
Sep 18, 2026 Trotwood-Madison vs. Taft 23–17 72–0 65.6 points

Evaluated games

The game-level record behind the summary above.

Aug 20, 2026

St. Ignatius vs. Avon

Correct
Projected
18–29
Final
21–22
Projected winner
Avon
Margin error
9.8

Aug 20, 2026

Massillon Jackson vs. Chardon

Missed
Projected
22–23
Final
34–13
Projected winner
Chardon
Margin error
21.3

Aug 15, 2026

West Union (club) vs. Foxfire

Correct
Projected
21–22
Final
6–12
Projected winner
Foxfire
Margin error
5.2

How to interpret these numbers

Winner accuracy shows whether OSPR favored the team that won. Average margin error shows how far the projected point margin was from the final margin.

Brier score measures probability quality from 0 to 1; lower is better. Calibration compares predicted win probabilities with observed outcomes.

Small groups can swing sharply, so every percentage is shown with its evaluated game count.

Injuries, roster changes, weather, and information not reflected in recorded results may affect individual games.