Rutgers vs. USC: Final Score & Recap
Final score, recap & advanced stats


RUTGTeam statsUSC
- Q3 0:22USCMakai Lemon 40 Yd pass from Miller Moss (Michael Lantz Kick)20–42
- Q3 6:32USCMiller Moss 7 Yd Run (Michael Lantz Kick)20–35
- Q3 8:11RUTGChristian Dremel 25 Yd pass from Athan Kaliakmanis (Chris Long Pass to Athan Kaliakmanis for Two-Point Conversion)20–28
- Q2 0:00RUTGJai Patel 20 Yd Field Goal 12–28
- Q2 1:53USCWoody Marks 22 Yd Run (Michael Lantz Kick)9–28
- Q2 4:37RUTGAntwan Raymond 3 Yd Run (Jai Patel PAT failed)9–21
- Q2 10:26USCKyle Ford 11 Yd pass from Miller Moss (Michael Lantz Kick)3–21
- Q1 2:19USCWoody Marks 1 Yd Run (Michael Lantz Kick)3–14
- Q1 4:10RUTGJai Patel 26 Yd Field Goal 3–7
- Q1 9:58USCWoody Marks 1 Yd Run (Michael Lantz Kick)0–7
How the model called it
- PassAthan Kaliakmanis 27/47, 313 YDS, 1 TD
- RushKyle Monangai 18 CAR, 86 YDS
- RecDymere Miller 11 REC, 131 YDS
- PassMiller Moss 20/28, 308 YDS, 2 TD
- RushWoody Marks 15 CAR, 94 YDS, 3 TD
- RecMakai Lemon 4 REC, 134 YDS, 1 TD
This exact spot, historically
empirical, no ratingsUSC up 22 entering the 4th quarter. Across 822 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q1 9:58USC +9%
Woody Marks run for 1 yd for a TD (Michael Lantz KICK)
- Q1 2:19USC +8%
Woody Marks run for 1 yd for a TD (Michael Lantz KICK)
- Q3 8:11RUTG +8%
Athan Kaliakmanis pass complete to Christian Dremel for 25 yds for a TD (Chris Long pass to Athan Kaliakmanis for Two-Point Conversion)
- Q3 6:32USC +5%
Miller Moss run for 7 yds for a TD (Michael Lantz KICK)
FAQ
What was the final score of Rutgers vs. USC?
Rutgers 20, USC 42.
Did Gridpex's model pick hit?
Yes — the model's pick (USC) was correct.
| RUTG | USC | |
|---|---|---|
| 434 | Total yards | 443 |
| 313 | Passing yards | 308 |
| 121 | Rushing yards | 135 |
| 27 | First downs | 23 |
| 11-22 | 3rd down | 3-6 |
| 3-6 | 4th down | 0-0 |
| 27/47 | Comp/Att | 20/28 |
| 6.7 | Yards per pass | 11.0 |
| 2.9 | Yards per rush | 5.9 |
| 0 | Turnovers | 0 |
| 4-9 | Penalties | 5-43 |
| 36:28 | Possession | 23:32 |
Costliest call
Q2 0:00 RUTG field goal on 4th & 2 at USC 2. The model preferred go for it, a gap of 1.39 points.
Drive chart
every possession, start to finish- Q3 0:22USCMakai Lemon 40 Yd pass from Miller Moss (Michael Lantz Kick)20–42
- Q3 6:32USCMiller Moss 7 Yd Run (Michael Lantz Kick)20–35
- Q3 8:11RUTGChristian Dremel 25 Yd pass from Athan Kaliakmanis (Chris Long Pass to Athan Kaliakmanis for Two-Point Conversion)20–28
- Q2 0:00RUTGJai Patel 20 Yd Field Goal 12–28
- Q2 1:53USCWoody Marks 22 Yd Run (Michael Lantz Kick)9–28
- Q2 4:37RUTGAntwan Raymond 3 Yd Run (Jai Patel PAT failed)9–21
- Q2 10:26USCKyle Ford 11 Yd pass from Miller Moss (Michael Lantz Kick)3–21
- Q1 2:19USCWoody Marks 1 Yd Run (Michael Lantz Kick)3–14
- Q1 4:10RUTGJai Patel 26 Yd Field Goal 3–7
- Q1 9:58USCWoody Marks 1 Yd Run (Michael Lantz Kick)0–7
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (USC Elo 1756, RUTG Elo 1432 for reference), with home-field advantage. That projects USC -15.4 (85% 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 — 2024
nationally rankedThe matchup, in context
series history + adjusted profiles| RUTG | USC | |
|---|---|---|
| -4.8 (#85) | CORE overall | +16.0 (#21) |
| +0 / +5 | offense / defense | +12 / -4 |
| 2.58 | points / drive | 2.61 |
| 2.63 | allowed / drive | 2.05 |
| 24% | three-and-outs | 22% |
| -2 | pass over expected | +12 |
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 →
