App State vs. James Madison: Final Score & Recap
Final score, recap & advanced stats
APPTeam statsJMU
- Q4 1:54APPDavion Dozier 19 Yd pass from JJ Kohl (Dominic De Freitas Kick)10–58
- Q4 4:45JMUMatthew Sluka 35 Yd Run (Morgan Suarez Kick)3–58
- Q4 7:53JMUJobi Malary 9 Yd Run (Morgan Suarez Kick)3–51
- Q4 10:48APPDominic De Freitas 48 Yd Field Goal 3–44
- Q4 13:20JMUJobi Malary 1 Yd Run (Morgan Suarez Kick)0–44
- Q3 4:06JMUMorgan Suarez 26 Yd Field Goal 0–37
- Q3 12:50JMUAlonza Barnett III 7 Yd Run (Morgan Suarez Kick)0–34
- Q2 0:00JMUMorgan Suarez 38 Yd Field Goal 0–27
- Q2 1:26JMUAlonza Barnett III 1 Yd Run (Morgan Suarez Kick)0–24
- Q2 7:39JMUJobi Malary 1 Yd Run (Morgan Suarez Kick)0–17
- Q2 10:25JMUMorgan Suarez 42 Yd Field Goal 0–10
- Q1 6:54JMUWayne Knight 1 Yd Run (Morgan Suarez Kick)0–7
How the model called it
- PassJJ Kohl 6/8, 81 YDS, 1 TD
- RushRashod Dubinion 10 CAR, 25 YDS
- RecDalton Stroman 3 REC, 74 YDS
- PassAlonza Barnett III 22/35, 303 YDS, 1 INT
- RushJobi Malary 8 CAR, 105 YDS, 3 TD
- RecJaylan Sanchez 2 REC, 69 YDS
This exact spot, historically
empirical, no ratingsJMU up 37 entering the 4th quarter. Across 313 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
FAQ
What was the final score of App State vs. James Madison?
App State 10, James Madison 58.
Did Gridpex's model pick hit?
Yes — the model's pick (JMU) was correct.
| APP | JMU | |
|---|---|---|
| 146 | Total yards | 627 |
| 145 | Passing yards | 303 |
| 1 | Rushing yards | 324 |
| 10 | First downs | 32 |
| 1-12 | 3rd down | 8-14 |
| 1-2 | 4th down | 1-1 |
| 14/37 | Comp/Att | 22/35 |
| 3.9 | Yards per pass | 8.7 |
| 0.1 | Yards per rush | 6.0 |
| 1 | Turnovers | 1 |
| 6-57 | Penalties | 7-74 |
| 17:42 | Possession | 42:18 |
Costliest call
Q3 14:26 APP go for it on 4th & 11 at APP 24. The model preferred punt, a gap of 0.98 points.
Drive chart
every possession, start to finish- Q4 1:54APPDavion Dozier 19 Yd pass from JJ Kohl (Dominic De Freitas Kick)10–58
- Q4 4:45JMUMatthew Sluka 35 Yd Run (Morgan Suarez Kick)3–58
- Q4 7:53JMUJobi Malary 9 Yd Run (Morgan Suarez Kick)3–51
- Q4 10:48APPDominic De Freitas 48 Yd Field Goal 3–44
- Q4 13:20JMUJobi Malary 1 Yd Run (Morgan Suarez Kick)0–44
- Q3 4:06JMUMorgan Suarez 26 Yd Field Goal 0–37
- Q3 12:50JMUAlonza Barnett III 7 Yd Run (Morgan Suarez Kick)0–34
- Q2 0:00JMUMorgan Suarez 38 Yd Field Goal 0–27
- Q2 1:26JMUAlonza Barnett III 1 Yd Run (Morgan Suarez Kick)0–24
- Q2 7:39JMUJobi Malary 1 Yd Run (Morgan Suarez Kick)0–17
- Q2 10:25JMUMorgan Suarez 42 Yd Field Goal 0–10
- Q1 6:54JMUWayne Knight 1 Yd Run (Morgan Suarez Kick)0–7
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (JMU Elo 1802, APP Elo 1328 for reference), with home-field advantage. That projects JMU -21.4 (91% to win), essentially in line with the market.
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 — 2025
nationally rankedThe matchup, in context
series history + adjusted profilesApp State leads 6–3 · 44% have been one-possession games
| APP | JMU | |
|---|---|---|
| -18.4 (#121) | CORE overall | +20.6 (#13) |
| -10 / +9 | offense / defense | +5 / -16 |
| 1.87 | points / drive | 3.06 |
| 2.68 | allowed / drive | 1.42 |
| 32% | three-and-outs | 22% |
| +6 | pass over expected | -3 |
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.
Create a free account →You get Pro free for 6 months. No card required.
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 →