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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.

Aug 28, 2026

Goshen vs. Hillsboro

Correct
Projected
25–18
Final
49–7
Projected winner
Goshen
Margin error
35.3

Aug 28, 2026

Franklin vs. Valley View

Correct
Projected
18–21
Final
0–37
Projected winner
Valley View
Margin error
33.7

Aug 28, 2026

Elida vs. Van Wert

Missed
Projected
24–23
Final
21–31
Projected winner
Elida
Margin error
10.0

Aug 28, 2026

Celina vs. Wapakoneta

Correct
Projected
25–17
Final
7–6
Projected winner
Celina
Margin error
7.8

Aug 28, 2026

Bishop Fenwick vs. Monroe

Missed
Projected
19–25
Final
41–20
Projected winner
Monroe
Margin error
27.2

Aug 28, 2026

Hamilton Badin vs. Dixie Heights

Correct
Projected
22–21
Final
42–13
Projected winner
Hamilton Badin
Margin error
29.0

Aug 28, 2026

Zanesville vs. Clear Fork

Missed
Projected
22–21
Final
12–38
Projected winner
Zanesville
Margin error
27.2

Aug 28, 2026

Western Brown vs. Simon Kenton

Missed
Projected
23–20
Final
27–34
Projected winner
Western Brown
Margin error
9.8

Aug 28, 2026

Miami Trace vs. Wilmington

Missed
Projected
25–19
Final
7–35
Projected winner
Miami Trace
Margin error
34.1

Aug 28, 2026

Marietta vs. John Marshall

Correct
Projected
18–22
Final
28–37
Projected winner
John Marshall
Margin error
5.5

Aug 28, 2026

Jonathan Alder vs. Columbus Academy

Missed
Projected
22–23
Final
36–12
Projected winner
Columbus Academy
Margin error
24.5

Aug 28, 2026

Jackson vs. Gallia Academy

Correct
Projected
20–19
Final
55–0
Projected winner
Jackson
Margin error
55.0

Aug 28, 2026

Chillicothe vs. Wheelersburg

Missed
Projected
23–24
Final
26–18
Projected winner
Wheelersburg
Margin error
9.1

Aug 28, 2026

Granville vs. Tri-Valley

Missed
Projected
15–28
Final
24–21
Projected winner
Tri-Valley
Margin error
15.9

Aug 28, 2026

Centennial vs. Columbus South

Correct
Projected
19–25
Final
0–29
Projected winner
Columbus South
Margin error
23.4

Aug 28, 2026

Buckeye Valley vs. Africentric

Missed
Projected
20–21
Final
26–0
Projected winner
Africentric
Margin error
27.1

Aug 28, 2026

Bishop Hartley vs. Marion Franklin

Correct
Projected
22–17
Final
28–27
Projected winner
Bishop Hartley
Margin error
3.7

Aug 28, 2026

Bellefontaine vs. Bellbrook

Missed
Projected
24–21
Final
17–49
Projected winner
Bellefontaine
Margin error
35.3

Aug 28, 2026

Athens vs. Unioto

Missed
Projected
23–22
Final
14–33
Projected winner
Athens
Margin error
20.3

Aug 28, 2026

Toledo Woodward vs. Oak Harbor

Correct
Projected
21–24
Final
16–49
Projected winner
Oak Harbor
Margin error
30.9

Aug 28, 2026

Rogers vs. Gibsonburg

Correct
Projected
19–20
Final
27–39
Projected winner
Gibsonburg
Margin error
11.1

Aug 28, 2026

Norwalk vs. Ontario

Correct
Projected
17–25
Final
0–58
Projected winner
Ontario
Margin error
50.7

Aug 28, 2026

Norton vs. Sandy Valley

Correct
Projected
26–16
Final
41–7
Projected winner
Norton
Margin error
24.3

Aug 28, 2026

Maumee vs. Napoleon

Correct
Projected
22–20
Final
24–21
Projected winner
Maumee
Margin error
1.1

Aug 28, 2026

Lexington vs. Shelby

Correct
Projected
18–25
Final
6–48
Projected winner
Shelby
Margin error
34.6

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.