Air Force vs. San José State: Final Score & Recap
Final score, recap & advanced stats
AFTeam statsSJSU
- Q4 5:18SJSUMatt Mercurio 30 Yd Field Goal 6–17
- Q4 13:16AFKyle Patterson 34 Yd pass from Haaziq Daniels (Two-Point Run Conversion Failed)6–14
- Q3 0:43SJSUDerrick Deese Jr. 11 Yd pass from Nick Starkel (Matt Mercurio Kick)0–14
- Q3 6:48SJSUDerrick Deese Jr. 7 Yd pass from Nick Starkel (Matt Mercurio Kick)0–7
How the model called it
- PassHaaziq Daniels 9/17, 92 YDS, 1 TD
- RushBrandon Lewis 9 CAR, 60 YDS
- RecKyle Patterson 3 REC, 56 YDS, 1 TD
- PassNick Starkel 22/29, 226 YDS, 2 TD, 1 INT
- RushKairee Robinson 12 CAR, 31 YDS
- RecBailey Gaither 8 REC, 110 YDS
This exact spot, historically
empirical, no ratingsSJSU up 14 entering the 4th quarter. Across 1,012 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q3 6:48SJSU +30%
Nick Starkel pass complete to Derrick Deese Jr. for 7 yds for a TD, (Matt Mercurio KICK)
- Q4 13:16AF +22%
Haaziq Daniels pass complete to Kyle Patterson for 34 yds for a TD SCHUETTPELZ-ROH kick attempt good, PENALTY SJSU offside (WEBB, Tre) 2 yards to the SJSU1, NO PLAY. (…
- Q3 0:43SJSU +21%
Nick Starkel pass complete to Derrick Deese Jr. for 11 yds for a TD, (Matt Mercurio KICK)
- Q4 9:30SJSU +20%
Nick Starkel pass incomplete to Bailey Gaither
- Q4 13:08AF +12%
Kairee Robinson run for a loss of 2 yards to the SJSt 8
- Q3 2:07SJSU +10%
Nick Starkel pass complete to Tre Walker for a loss of 3 yards to the AFA 17
FAQ
What was the final score of Air Force vs. San José State?
Air Force 6, San José State 17.
Did Gridpex's model pick hit?
No — the model picked AF, which didn't hit. We report the misses too.
| AF | SJSU | |
|---|---|---|
| 298 | Total yards | 294 |
| 92 | Passing yards | 226 |
| 206 | Rushing yards | 68 |
| 17 | First downs | 19 |
| 9-16 | 3rd down | 5-12 |
| 1-2 | 4th down | 0-1 |
| 9/17 | Comp/Att | 22/29 |
| 5.4 | Yards per pass | 7.8 |
| 4.2 | Yards per rush | 2.3 |
| 2 | Turnovers | 1 |
| 4-55 | Penalties | 6-45 |
| 29:24 | Possession | 30:36 |
Costliest call
Q3 12:00 AF punt on 4th & 4 at SJSU 49. The model preferred go for it, a gap of 0.51 points.
Drive chart
every possession, start to finish- Q4 5:18SJSUMatt Mercurio 30 Yd Field Goal 6–17
- Q4 13:16AFKyle Patterson 34 Yd pass from Haaziq Daniels (Two-Point Run Conversion Failed)6–14
- Q3 0:43SJSUDerrick Deese Jr. 11 Yd pass from Nick Starkel (Matt Mercurio Kick)0–14
- Q3 6:48SJSUDerrick Deese Jr. 7 Yd pass from Nick Starkel (Matt Mercurio Kick)0–7
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (SJSU Elo 1352, AF Elo 1711 for reference), with home-field advantage. That projects SJSU +12 (22% to win) — 4.5 points clear of AF's market line of +7.5. That is a disagreement, not a betting edge — sides we favour have not covered at better than breakeven.
Why that percentage is worth reading: across 604 graded in-season games, the calls this model put near 58% came in at 58.2%. The full calibration table is published, bin by bin. Early in the season the cold-start path runs instead and calibrates less well (Brier 0.2028 against 0.1889).
Model as of Sep 1 · through week 1 · drive simulation
Season form — 2020
nationally rankedThe matchup, in context
series history + adjusted profiles#59 of 97 in 2020 by biggest miss · #50 of 107 in 2020 by longest odds.
The 2020 upset archive →Air Force leads 6–3 · 22% have been one-possession games
| AF | SJSU | |
|---|---|---|
| +13.6 (#20) | CORE overall | +8.0 (#36) |
| +12 / -2 | offense / defense | +3 / -5 |
| -28 | pass over expected | +10 |
Bold is the side ahead. CORE strips the situation from every play and solves the schedule out across the league, so these compare two teams that never met.
Key matchups
The analyst read: each team's offense splits crossed against the opponent's defense, with the edges called out.
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Where this number comes from. Every projection on this page is produced by the same model, run before kickoff on opponent-adjusted efficiency, power ratings and situational data — walk-forward validated on eleven seasons and never adjusted after the fact. How the model works →