Nevada vs. San Diego State: Final Score & Recap
Final score, recap & advanced stats
NEVTeam statsSDSU
- Q4 3:46SDSUMatt Araiza 44 Yd Field Goal 17–13
- Q4 10:31NEVDevonte Lee 1 Yd Run (Brandon Talton Kick)17–10
- Q3 1:24SDSUChance Bell 3 Yd Run (Matt Araiza Kick)10–10
- Q3 7:12NEVElijah Cooks 13 Yd pass from Carson Strong (Brandon Talton Kick)10–3
- Q2 13:15SDSUMatt Araiza 21 Yd Field Goal 3–3
- Q1 3:22NEVBrandon Talton 34 Yd Field Goal 3–0
How the model called it
What the numbers say
- SDSU played behind the sticks — third downs that long convert rarely, and NEV did not face the same ones. 3rd & 8.1 vs 3rd & 5.3
- PassCarson Strong 19/26, 147 YDS, 1 TD, 1 INT
- RushToa Taua 12 CAR, 19 YDS
- RecBrendan O'Leary-Orange 1 REC, 50 YDS
- PassRyan Agnew 18/35, 196 YDS, 1 INT
- RushChance Bell 11 CAR, 40 YDS, 1 TD
- RecKobe Smith 5 REC, 40 YDS
This exact spot, historically
empirical, no ratingsTied entering the 4th quarter. Across 1,332 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q4 10:31NEV +41%
Devonte Lee run for 1 yd for a TD (Brandon Talton KICK)
- Q4 2:49NEV +40%
Carson Strong sacked by Cameron Thomas for a loss of 7 yards to the Nevad 21
- Q3 7:12NEV +32%
Carson Strong pass complete to Elijah Cooks for 13 yds for a TD (Brandon Talton KICK)
- Q4 1:25NEV +29%
Toa Taua run for a loss of 3 yards to the SDSt 45
- Q3 1:24SDSU +24%
Chance Bell run for 3 yds for a TD (Matt Araiza KICK)
- Q4 2:35SDSU +22%
Ryan Agnew pass complete to Kobe Smith for 4 yds to the SDSt 42
FAQ
What was the final score of Nevada vs. San Diego State?
Nevada 17, San Diego State 13.
Did Gridpex's model pick hit?
No — the model picked SDSU, which didn't hit. We report the misses too.
| NEV | SDSU | |
|---|---|---|
| 226 | Total yards | 309 |
| 197 | Passing yards | 196 |
| 29 | Rushing yards | 113 |
| 12 | First downs | 18 |
| 2-12 | 3rd down | 7-18 |
| 2-2 | 4th down | 2-3 |
| 20/27 | Comp/Att | 18/35 |
| 7.3 | Yards per pass | 5.6 |
| 1.0 | Yards per rush | 2.9 |
| 1 | Turnovers | 1 |
| 4-28 | Penalties | 9-79 |
| 27:41 | Possession | 32:19 |
Costliest call
Q4 15:00 NEV punt on 4th & 1 at NEV 45. The model preferred go for it, a gap of 1.25 points.
Drive chart
every possession, start to finish- Q4 3:46SDSUMatt Araiza 44 Yd Field Goal 17–13
- Q4 10:31NEVDevonte Lee 1 Yd Run (Brandon Talton Kick)17–10
- Q3 1:24SDSUChance Bell 3 Yd Run (Matt Araiza Kick)10–10
- Q3 7:12NEVElijah Cooks 13 Yd pass from Carson Strong (Brandon Talton Kick)10–3
- Q2 13:15SDSUMatt Araiza 21 Yd Field Goal 3–3
- Q1 3:22NEVBrandon Talton 34 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 (SDSU Elo 1502, NEV Elo 1099 for reference), with home-field advantage. That projects SDSU -18.5 (88% 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 — 2019
nationally rankedThe matchup, in context
series history + adjusted profiles#53 of 105 in 2019 by biggest miss · #13 of 124 in 2019 by longest odds · #37 of 51 in 2019 by biggest poll gap.
The 2019 upset archive →San Diego State leads 10–6 · 50% have been one-possession games
| NEV | SDSU | |
|---|---|---|
| -14.4 (#109) | CORE overall | +0.9 (#57) |
| -9 / +6 | offense / defense | -10 / -11 |
| 1.65 | points / drive | 1.85 |
| 2.59 | allowed / drive | 1.22 |
| 37% | three-and-outs | 24% |
| +6 | pass over expected | -2 |
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 →