UCLA vs. Northwestern: Final Score & Recap
Final score, recap & advanced stats
UCLATeam statsNU
- Q4 6:19UCLAKwazi Gilmer 29 Yd pass from Nico Iamaleava (Nico Iamaleava Pass to Anthony Woods for Two-Point Conversion)14–17
- Q3 2:48UCLAMateen Bhaghani 25 Yd Field Goal 6–17
- Q2 0:00UCLAMateen Bhaghani 28 Yd Field Goal3–17
- Q2 3:33NUGriffin Wilde 10 Yd pass from Preston Stone (Jack Olsen Kick)0–17
- Q2 13:29NUCaleb Komolafe 9 Yd Run (Jack Olsen Kick)0–10
- Q1 2:24NUJack Olsen 33 Yd Field Goal 0–3
How the model called it
- PassNico Iamaleava 19/27, 180 YDS, 1 TD
- RushNico Iamaleava 14 CAR, 65 YDS
- RecKwazi Gilmer 3 REC, 51 YDS, 1 TD
- PassPreston Stone 12/18, 115 YDS, 1 TD
- RushCaleb Komolafe 27 CAR, 119 YDS, 1 TD
- RecGriffin Wilde 7 REC, 98 YDS, 1 TD
This exact spot, historically
empirical, no ratingsNU up 8 entering the 4th quarter. Across 1,588 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q4 6:22UCLA +52%
Nico Iamaleava pass complete to Anthony Woods for no gain to the UCLA 35
- Q4 1:29UCLA +45%
Nico Iamaleava run for 4 yds to the UCLA 24
- Q4 1:29NU +37%
Luke Akers punt for 50 yds
- Q4 1:55UCLA +37%
Will Karoll punt for 45 yds, Drew Wagner returns for 1 yd to the NU 47
- Q4 3:23NU +25%
Luke Akers punt for 44 yds
- Q2 13:29NU +15%
Caleb Komolafe 9 Yd Run (Jack Olsen Kick)
FAQ
What was the final score of UCLA vs. Northwestern?
UCLA 14, Northwestern 17.
Did Gridpex's model pick hit?
Yes — the model's pick (NU) was correct.
| UCLA | NU | |
|---|---|---|
| 311 | Total yards | 314 |
| 180 | Passing yards | 115 |
| 131 | Rushing yards | 199 |
| 18 | First downs | 21 |
| 7-14 | 3rd down | 6-13 |
| 1-2 | 4th down | 2-2 |
| 19/28 | Comp/Att | 12/18 |
| 6.4 | Yards per pass | 6.4 |
| 4.5 | Yards per rush | 4.7 |
| 0 | Turnovers | 0 |
| 6-60 | Penalties | 2-20 |
| 25:39 | Possession | 34:21 |
Costliest call
Q4 7:50 NU field goal on 4th & 2 at UCLA 2. The model preferred go for it, a gap of 1.39 points.
Drive chart
every possession, start to finish- Q4 6:19UCLAKwazi Gilmer 29 Yd pass from Nico Iamaleava (Nico Iamaleava Pass to Anthony Woods for Two-Point Conversion)14–17
- Q3 2:48UCLAMateen Bhaghani 25 Yd Field Goal 6–17
- Q2 0:00UCLAMateen Bhaghani 28 Yd Field Goal3–17
- Q2 3:33NUGriffin Wilde 10 Yd pass from Preston Stone (Jack Olsen Kick)0–17
- Q2 13:29NUCaleb Komolafe 9 Yd Run (Jack Olsen Kick)0–10
- Q1 2:24NUJack Olsen 33 Yd Field Goal 0–3
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (NU Elo 1411, UCLA Elo 1331 for reference), with home-field advantage. That projects NU -5.6 (66% 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 15 · through week 2 · drive simulation
Season form — 2025
nationally rankedThe matchup, in context
series history + adjusted profiles| UCLA | NU | |
|---|---|---|
| -6.4 (#84) | CORE overall | -1.8 (#67) |
| -2 / +4 | offense / defense | -0 / +1 |
| 1.90 | points / drive | 2.35 |
| 3.43 | allowed / drive | 2.19 |
| 21% | three-and-outs | 22% |
| +1 | 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 →