Tulsa vs. SMU: Final Score & Recap
Final score, recap & advanced stats
TLSATeam statsSMU
- Q4 2:24SMUCollin Rogers 22 Yd Field Goal 10–69
- Q4 9:59TLSAKamdyn Benjamin 5 Yd pass from Cardell Williams (Chase Meyer Kick)10–66
- Q3 3:50SMUCamar Wheaton 48 Yd Run (Collin Rogers Kick)3–66
- Q3 8:21SMUVelton Gardner 1 Yd Run (Collin Rogers Kick)3–59
- Q2 4:37SMUMoochie Dixon 17 Yd pass from Preston Stone (Collin Rogers Kick)3–52
- Q2 7:34SMUCamar Wheaton 4 Yd Run (Collin Rogers Kick)3–45
- Q2 11:35SMURJ Maryland 62 Yd pass from Preston Stone (Collin Rogers Kick)3–38
- Q2 12:07SMUCollin Rogers 42 Yd Field Goal 3–31
- Q1 0:26SMUIsaiah Nwokobia 25 Yd Interception Return (Collin Rogers Kick)3–28
- Q1 1:46SMUJaylan Knighton 11 Yd Run (Collin Rogers Kick)3–21
- Q1 4:44TLSAChase Meyer 35 Yd Field Goal 3–14
- Q1 9:34SMUTyler Lavine 1 Yd Run (Collin Rogers Kick)0–14
- Q1 14:10SMURomello Brinson 74 Yd pass from Preston Stone (Collin Rogers Kick)0–7
How the model called it
- PassBraylon Braxton 10/20, 92 YDS, 2 INT
- RushAnthony Watkins 15 CAR, 50 YDS
- RecDevan Williams 3 REC, 57 YDS
- PassPreston Stone 15/20, 371 YDS, 3 TD
- RushCamar Wheaton 9 CAR, 80 YDS, 2 TD
- RecRJ Maryland 2 REC, 95 YDS, 1 TD
This exact spot, historically
empirical, no ratingsSMU up 63 entering the 4th quarter. Across 96 historically comparable game states (within ±5 pts and ±8 min, from 3,056 games):
- Q1 14:10SMU +6%
Preston Stone pass complete to Romello Brinson for 74 yds for a TD (Collin Rogers KICK)
FAQ
What was the final score of Tulsa vs. SMU?
Tulsa 10, SMU 69.
Did Gridpex's model pick hit?
Yes — the model's pick (SMU) was correct.
| TLSA | SMU | |
|---|---|---|
| 247 | Total yards | 638 |
| 124 | Passing yards | 446 |
| 123 | Rushing yards | 192 |
| 14 | First downs | 26 |
| 5-17 | 3rd down | 4-10 |
| 0-2 | 4th down | 1-1 |
| 14/25 | Comp/Att | 22/29 |
| 5.0 | Yards per pass | 15.4 |
| 2.6 | Yards per rush | 4.9 |
| 2 | Turnovers | 0 |
| 3-35 | Penalties | 3-19 |
| 30:13 | Possession | 29:47 |
Costliest call
Q3 5:53 TLSA go for it on 4th & 10 at SMU 34. The model preferred field goal, a gap of 0.43 points.
Drive chart
every possession, start to finish- Q4 2:24SMUCollin Rogers 22 Yd Field Goal 10–69
- Q4 9:59TLSAKamdyn Benjamin 5 Yd pass from Cardell Williams (Chase Meyer Kick)10–66
- Q3 3:50SMUCamar Wheaton 48 Yd Run (Collin Rogers Kick)3–66
- Q3 8:21SMUVelton Gardner 1 Yd Run (Collin Rogers Kick)3–59
- Q2 4:37SMUMoochie Dixon 17 Yd pass from Preston Stone (Collin Rogers Kick)3–52
- Q2 7:34SMUCamar Wheaton 4 Yd Run (Collin Rogers Kick)3–45
- Q2 11:35SMURJ Maryland 62 Yd pass from Preston Stone (Collin Rogers Kick)3–38
- Q2 12:07SMUCollin Rogers 42 Yd Field Goal 3–31
- Q1 0:26SMUIsaiah Nwokobia 25 Yd Interception Return (Collin Rogers Kick)3–28
- Q1 1:46SMUJaylan Knighton 11 Yd Run (Collin Rogers Kick)3–21
- Q1 4:44TLSAChase Meyer 35 Yd Field Goal 3–14
- Q1 9:34SMUTyler Lavine 1 Yd Run (Collin Rogers Kick)0–14
- Q1 14:10SMURomello Brinson 74 Yd pass from Preston Stone (Collin Rogers Kick)0–7
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (SMU Elo 1653, TLSA Elo 1219 for reference), with home-field advantage. That projects SMU -19.8 (90% 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 — 2023
nationally rankedThe matchup, in context
series history + adjusted profilesSMU leads 17–13 · SMU has won 2 straight · 57% have been one-possession games
| TLSA | SMU | |
|---|---|---|
| -17.5 (#118) | CORE overall | +13.9 (#25) |
| -6 / +12 | offense / defense | +4 / -9 |
| 1.77 | points / drive | 2.76 |
| 3.02 | allowed / drive | 1.37 |
| 34% | three-and-outs | 20% |
| -8 | 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 →