Middle Tennessee vs. Wisconsin: Final Score & Recap
Final score, recap & advanced stats
MTSUTeam statsWIS
- Q4 5:48WISLance Mason 17 Yd pass from Danny O'Neil (Nathanial Vakos Kick)10–42
- Q4 10:24WISJayden Ballard 58 Yd pass from Danny O'Neil (Nathanial Vakos Kick)10–35
- Q3 2:44WISVinny Anthony II 14 Yd Run (Nathanial Vakos Kick)10–28
- Q3 7:26WISTrech Kekahuna 61 Yd Run (Nathanial Vakos Kick)10–21
- Q2 1:05MTSUHunter Tipton 4 Yd pass from Nicholas Vattiato (Jacob Hathaway Kick)10–14
- Q2 2:07WISDilin Jones 1 Yd Run (Nathanial Vakos Kick)3–14
- Q2 8:16WISTyrell Henry 3 Yd pass from Danny O'Neil (Nathanial Vakos Kick)3–7
- Q1 4:13MTSUJacob Hathaway 27 Yd Field Goal 3–0
How the model called it
- PassNicholas Vattiato 20/31, 197 YDS, 1 TD, 1 INT
- RushJekail Middlebrook 12 CAR, 27 YDS
- RecNahzae Cox 3 REC, 75 YDS
- PassDanny O'Neil 23/27, 283 YDS, 3 TD, 1 INT
- RushTrech Kekahuna 1 CAR, 61 YDS, 1 TD
- RecLance Mason 7 REC, 102 YDS, 1 TD
This exact spot, historically
empirical, no ratingsWIS up 18 entering the 4th quarter. Across 838 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q2 8:16WIS +15%
Danny O'Neil pass complete to Tyrell Henry for 3 yds for a TD (Nathanial Vakos KICK)
- Q3 14:19MTSU +11%
Rickey Hunt Jr. run for 6 yds to the WIS 48
- Q3 7:26WIS +10%
Trech Kekahuna run for 61 yds for a TD (Nathanial Vakos KICK)
- Q2 1:24WIS +9%
Ashton Logan punt for 37 yds to the MTSU
- Q1 4:13MTSU +6%
Jacob Hathaway 27 yd FG GOOD
FAQ
What was the final score of Middle Tennessee vs. Wisconsin?
Middle Tennessee 10, Wisconsin 42.
Did Gridpex's model pick hit?
Yes — the model's pick (WIS) was correct.
| MTSU | WIS | |
|---|---|---|
| 241 | Total yards | 436 |
| 208 | Passing yards | 283 |
| 33 | Rushing yards | 153 |
| 14 | First downs | 21 |
| 5-14 | 3rd down | 4-9 |
| 1-2 | 4th down | 2-2 |
| 21/32 | Comp/Att | 23/27 |
| 6.5 | Yards per pass | 10.5 |
| 1.2 | Yards per rush | 4.9 |
| 1 | Turnovers | 2 |
| 4-25 | Penalties | 0-0 |
| 29:17 | Possession | 30:43 |
Costliest call
Q2 1:24 MTSU punt on 4th & 3 at MTSU 43. The model preferred go for it, a gap of 0.35 points.
Drive chart
every possession, start to finish- Q4 5:48WISLance Mason 17 Yd pass from Danny O'Neil (Nathanial Vakos Kick)10–42
- Q4 10:24WISJayden Ballard 58 Yd pass from Danny O'Neil (Nathanial Vakos Kick)10–35
- Q3 2:44WISVinny Anthony II 14 Yd Run (Nathanial Vakos Kick)10–28
- Q3 7:26WISTrech Kekahuna 61 Yd Run (Nathanial Vakos Kick)10–21
- Q2 1:05MTSUHunter Tipton 4 Yd pass from Nicholas Vattiato (Jacob Hathaway Kick)10–14
- Q2 2:07WISDilin Jones 1 Yd Run (Nathanial Vakos Kick)3–14
- Q2 8:16WISTyrell Henry 3 Yd pass from Danny O'Neil (Nathanial Vakos Kick)3–7
- Q1 4:13MTSUJacob Hathaway 27 Yd Field Goal 3–0
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (WIS Elo 1573, MTSU Elo 1228 for reference), with home-field advantage. That projects WIS -16.2 (86% to win) — 12.3 points clear of MTSU's market line of -28.5. 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 15 · through week 2 · drive simulation
Season form — 2025
nationally rankedThe matchup, in context
series history + adjusted profiles| MTSU | WIS | |
|---|---|---|
| -15.9 (#113) | CORE overall | -3.3 (#72) |
| -5 / +11 | offense / defense | -11 / -8 |
| 1.93 | points / drive | 1.23 |
| 2.66 | allowed / drive | 2.09 |
| 27% | three-and-outs | 35% |
| +10 | pass over expected | -8 |
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 →