Michigan vs. Northwestern: Final Score & Recap
Final score, recap & advanced stats
MICHTeam statsNU
- Q4 0:00MICHDominic Zvada 31 Yd Field Goal 24–22
- Q4 12:05NUCaleb Komolafe 6 Yd Run (Two-Point Pass Conversion Failed)21–22
- Q4 13:00NUPreston Stone 1 Yd Run (Jack Olsen Kick)21–16
- Q3 0:41MICHJordan Marshall 1 Yd Run (Dominic Zvada Kick)21–9
- Q3 6:09NUJack Olsen 35 Yd Field Goal 14–9
- Q3 10:29MICHBryce Underwood 9 Yd Run (Dominic Zvada Kick)14–6
- Q2 1:00NUJack Olsen 26 Yd Field Goal 7–6
- Q2 5:22NUJack Olsen 34 Yd Field Goal 7–3
- Q2 13:11MICHJordan Marshall 1 Yd Run (Dominic Zvada Kick)7–0
How the model called it
What the numbers say
- NU lived on explosives rather than sustaining drives — a profile that vanished once those chunk plays were tackled. 14% explosive on a 30% success rate
- PassBryce Underwood 21/32, 280 YDS, 2 INT
- RushJordan Marshall 19 CAR, 142 YDS, 2 TD
- RecAndrew Marsh 12 REC, 189 YDS
- PassPreston Stone 13/27, 184 YDS
- RushCaleb Komolafe 12 CAR, 31 YDS, 1 TD
- RecHunter Welcing 4 REC, 81 YDS
This exact spot, historically
empirical, no ratingsMICH up 12 entering the 4th quarter. Across 1,519 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q4 0:00MICH +71%
Dominic Zvada 31 Yd Field Goal
- Q4 12:05NU +38%
Shotgun #5 C.Komolafe rush right for 6 yards gain to the U-M00 TOUCHDOWN #8 P.Stone pass attempt failed
- Q4 2:10NU +38%
#11 L.Akers punt 45 yards to the U-M37 fair catch by #4 A.Marsh at U-M37
- Q2 12:08NU +22%
#11 L.Akers punt 50 yards to the U-M23 fair catch by #0 S.Morgan at U-M23
- Q4 7:28NU +20%
#11 L.Akers punt 44 yards to the U-M29 #4 A.Marsh return 12 yards to the U-M41 (#49 L.Reardon; #33 B.Brus)
- Q4 7:18MICH +19%
No Huddle-Shotgun #24 B.Kuzdzal rush left for 6 yards gain to the U-M47 (#6 R.Fitzgerald)
FAQ
What was the final score of Michigan vs. Northwestern?
Michigan 24, Northwestern 22.
Did Gridpex's model pick hit?
Yes — the model's pick (MICH) was correct.
| MICH | NU | |
|---|---|---|
| 496 | Total yards | 245 |
| 280 | Passing yards | 184 |
| 216 | Rushing yards | 61 |
| 25 | First downs | 11 |
| 9-14 | 3rd down | 2-12 |
| 0-1 | 4th down | 1-1 |
| 21/32 | Comp/Att | 13/27 |
| 8.8 | Yards per pass | 6.8 |
| 4.8 | Yards per rush | 2.3 |
| 5 | Turnovers | 0 |
| 4-24 | Penalties | 7-55 |
| 33:06 | Possession | 26:54 |
Costliest call
Q2 0:02 MICH field goal on 4th & 5 at NU 42. The model preferred go for it, a gap of 0.57 points.
Drive chart
every possession, start to finish- Q4 0:00MICHDominic Zvada 31 Yd Field Goal 24–22
- Q4 12:05NUCaleb Komolafe 6 Yd Run (Two-Point Pass Conversion Failed)21–22
- Q4 13:00NUPreston Stone 1 Yd Run (Jack Olsen Kick)21–16
- Q3 0:41MICHJordan Marshall 1 Yd Run (Dominic Zvada Kick)21–9
- Q3 6:09NUJack Olsen 35 Yd Field Goal 14–9
- Q3 10:29MICHBryce Underwood 9 Yd Run (Dominic Zvada Kick)14–6
- Q2 1:00NUJack Olsen 26 Yd Field Goal 7–6
- Q2 5:22NUJack Olsen 34 Yd Field Goal 7–3
- Q2 13:11MICHJordan Marshall 1 Yd Run (Dominic Zvada Kick)7–0
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (NU Elo 1516, MICH Elo 1809 for reference), on a neutral field. That projects NU +11.7 (23% 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 profilesMichigan leads 61–15–2 · Michigan has won 9 straight · 37% have been one-possession games
| MICH | NU | |
|---|---|---|
| +17.4 (#22) | CORE overall | -1.8 (#67) |
| +11 / -6 | offense / defense | -0 / +1 |
| 2.70 | points / drive | 2.35 |
| 1.97 | allowed / drive | 2.19 |
| 25% | three-and-outs | 22% |
| -2 | pass over expected | -1 |
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 →