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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 15, 2026

Accuracy calculated Oct 16, 2026 8:00 AM EDT

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Performance summary

2,842 games evaluated with ospr-2026.1

Games evaluated

2,842

Winner accuracy

68.5%

1,947 correct

Average margin error

22.5

Lower is better

Average score error

13.3

Per-team points

Brier score

0.203

Probability accuracy

Close projection rate

14.1%

Correct and within 7

Regular season vs. playoffs

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

Regular season

Games
2,842
Winner accuracy
68.5%
Margin error
22.5

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 4 25.0% 26.2

Probability calibration

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

Probability Games Predicted Observed Gap Brier
0–9% 13 8.5% 7.7% -0.8 0.069
10–19% 178 15.9% 9.6% -6.4 0.091
20–29% 302 25.5% 23.2% -2.3 0.178
30–39% 445 35.1% 35.1% 0.0 0.227
40–49% 562 45.1% 43.6% -1.5 0.245
50–59% 478 54.9% 57.7% +2.9 0.247
60–69% 404 64.8% 71.0% +6.2 0.205
70–79% 325 74.8% 79.7% +4.9 0.162
80–89% 128 84.0% 86.7% +2.7 0.113
90–99% 7 91.9% 85.7% -6.1 0.127

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 2,368 69.6% 22.4 points
Medium 31 80.6% 23.7 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 1,515 62.4% 22.9 points
Close Game 2,021 62.8% 22.3 points
Upset Possible 1,886 61.9% 22.1 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
Sep 18, 2026 Trotwood-Madison vs. Taft 23–17 72–0 65.6 points
Sep 26, 2026 Bedford vs. Cleveland JFK 18–17 66–0 64.8 points
Sep 18, 2026 John Adams vs. Cleveland JFK 16–18 68–6 64.4 points

Evaluated games

The game-level record behind the summary above.

Sep 25, 2026

Linden McKinley vs. Grandview Heights

Correct
Projected
23–20
Final
46–7
Projected winner
Linden McKinley
Margin error
36.0

Sep 25, 2026

Hebron Lakewood vs. Johnstown Northridge

Correct
Projected
16–21
Final
7–28
Projected winner
Johnstown Northridge
Margin error
17.0

Sep 25, 2026

John Glenn vs. West Muskingum

Correct
Projected
21–26
Final
27–28
Projected winner
West Muskingum
Margin error
3.7

Sep 25, 2026

Indian Valley vs. WL Ridgewood

Correct
Projected
27–21
Final
21–7
Projected winner
Indian Valley
Margin error
7.8

Sep 25, 2026

Indian Creek vs. Bellaire

Correct
Projected
20–21
Final
28–37
Projected winner
Bellaire
Margin error
7.9

Sep 25, 2026

Heath vs. Utica

Correct
Projected
21–20
Final
34–3
Projected winner
Heath
Margin error
29.2

Sep 25, 2026

Gallia Academy vs. Coal Grove

Missed
Projected
15–21
Final
33–13
Projected winner
Coal Grove
Margin error
26.1

Sep 25, 2026

Fairfield Union vs. Liberty Union

Correct
Projected
22–17
Final
44–0
Projected winner
Fairfield Union
Margin error
39.7

Sep 25, 2026

Claymont vs. Sandy Valley

Correct
Projected
28–17
Final
48–0
Projected winner
Claymont
Margin error
36.4

Sep 25, 2026

Bloom-Carroll vs. Logan Elm

Correct
Projected
21–19
Final
34–20
Projected winner
Bloom-Carroll
Margin error
12.0

Sep 25, 2026

Bexley vs. Columbus Academy

Correct
Projected
19–25
Final
0–20
Projected winner
Columbus Academy
Margin error
13.2

Sep 25, 2026

Wauseon vs. Delta

Correct
Projected
19–26
Final
6–48
Projected winner
Delta
Margin error
35.3

Sep 25, 2026

Upper Sandusky vs. Hopewell-Loudon

Correct
Projected
20–26
Final
10–32
Projected winner
Hopewell-Loudon
Margin error
15.1

Sep 25, 2026

Ontario vs. Marion Pleasant

Correct
Projected
25–20
Final
42–28
Projected winner
Ontario
Margin error
8.9

Sep 25, 2026

Keystone vs. Black River

Correct
Projected
25–18
Final
48–7
Projected winner
Keystone
Margin error
33.4

Sep 25, 2026

Huron vs. Port Clinton

Correct
Projected
13–29
Final
21–35
Projected winner
Port Clinton
Margin error
2.9

Sep 25, 2026

Galion vs. Highland

Missed
Projected
23–19
Final
21–24
Projected winner
Galion
Margin error
6.7

Sep 25, 2026

Clyde vs. Perkins

Correct
Projected
17–27
Final
22–62
Projected winner
Perkins
Margin error
29.9

Sep 25, 2026

Clearview vs. Firelands

Correct
Projected
17–21
Final
16–48
Projected winner
Firelands
Margin error
28.3

Sep 25, 2026

Bryan vs. Evergreen

Correct
Projected
18–17
Final
27–5
Projected winner
Bryan
Margin error
21.2

Sep 25, 2026

Brookside vs. Columbia

Correct
Projected
20–26
Final
20–55
Projected winner
Columbia
Margin error
28.6

Sep 25, 2026

Bellevue vs. Milan Edison

Correct
Projected
24–22
Final
42–10
Projected winner
Bellevue
Margin error
30.5

Sep 25, 2026

Poland Seminary vs. South Range

Correct
Projected
19–28
Final
7–47
Projected winner
South Range
Margin error
30.8

Sep 25, 2026

Minerva vs. Salem

Correct
Projected
17–25
Final
14–38
Projected winner
Salem
Margin error
15.5

Sep 25, 2026

Hawken vs. Pepper Pike Orange

Missed
Projected
20–21
Final
53–21
Projected winner
Pepper Pike Orange
Margin error
32.5

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.