Tulsa vs. Oklahoma State: Final Score & Recap
Final score, recap & advanced stats
TLSATeam statsOKST
- Q4 5:49OKSTLogan Ward 49 Yd Field Goal 19–12
- Q4 14:14OKSTZane Flores 5 Yd Run (Two-Point Pass Conversion Failed)19–9
- Q3 11:14TLSASeth Morgan 47 Yd Field Goal 19–3
- Q2 2:32TLSASeth Morgan 47 Yd Field Goal 16–3
- Q2 7:49TLSASeth Morgan 38 Yd Field Goal 13–3
- Q1 2:41TLSASeth Morgan 27 Yd Field Goal 10–3
- Q1 9:36TLSABraylin Presley 19 Yd pass from Baylor Hayes (Seth Morgan Kick)7–3
- Q1 11:45OKSTLogan Ward 35 Yd Field Goal 0–3
How the model called it
What the numbers say
- OKST played behind the sticks — third downs that long convert rarely, and TLSA did not face the same ones. 3rd & 9.8 vs 3rd & 5.5
- TLSA lived on explosives rather than sustaining drives — a profile that vanished once those chunk plays were tackled. 14% explosive on a 39% success rate
- PassBaylor Hayes 23/36, 219 YDS, 1 TD
- RushDominic Richardson 31 CAR, 146 YDS
- RecBrody Foley 5 REC, 66 YDS
- PassZane Flores 25/40, 214 YDS
- RushRodney Fields Jr. 17 CAR, 113 YDS
- RecChristian Fitzpatrick 4 REC, 49 YDS
This exact spot, historically
empirical, no ratingsTLSA up 16 entering the 4th quarter. Across 1,243 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q4 0:31TLSA +25%
Seth Morgan 50 yd FG MISSED
- Q1 9:36TLSA +16%
Braylin Presley 19 Yd pass from Baylor Hayes (Seth Morgan Kick)
- Q4 2:23OKST +16%
Zane Flores pass incomplete to Josh Ford
- Q4 3:19TLSA +16%
Angus Davies punt for 36 yds
- Q4 5:37OKST +16%
Dominic Richardson run for 11 yds to the TLSA 28 for a 1ST down
- Q2 7:49TLSA +15%
Seth Morgan 38 Yd Field Goal
FAQ
What was the final score of Tulsa vs. Oklahoma State?
Tulsa 19, Oklahoma State 12.
Did Gridpex's model pick hit?
No — the model picked OKST, which didn't hit. We report the misses too.
| TLSA | OKST | |
|---|---|---|
| 424 | Total yards | 403 |
| 219 | Passing yards | 218 |
| 205 | Rushing yards | 185 |
| 21 | First downs | 24 |
| 7-19 | 3rd down | 4-15 |
| 3-3 | 4th down | 1-4 |
| 23/36 | Comp/Att | 26/42 |
| 6.1 | Yards per pass | 5.2 |
| 4.8 | Yards per rush | 5.6 |
| 1 | Turnovers | 0 |
| 4-34 | Penalties | 3-30 |
| 34:45 | Possession | 25:15 |
Costliest call
Q3 2:26 TLSA punt on 4th & 1 at TLSA 15. The model preferred go for it, a gap of 0.90 points.
Drive chart
every possession, start to finish- Q4 5:49OKSTLogan Ward 49 Yd Field Goal 19–12
- Q4 14:14OKSTZane Flores 5 Yd Run (Two-Point Pass Conversion Failed)19–9
- Q3 11:14TLSASeth Morgan 47 Yd Field Goal 19–3
- Q2 2:32TLSASeth Morgan 47 Yd Field Goal 16–3
- Q2 7:49TLSASeth Morgan 38 Yd Field Goal 13–3
- Q1 2:41TLSASeth Morgan 27 Yd Field Goal 10–3
- Q1 9:36TLSABraylin Presley 19 Yd pass from Baylor Hayes (Seth Morgan Kick)7–3
- Q1 11:45OKSTLogan Ward 35 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 (OKST Elo 1202, TLSA Elo 1046 for reference), with home-field advantage. That projects OKST -8.6 (73% 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#63 of 112 in 2025 by biggest miss · #39 of 129 in 2025 by longest odds.
The 2025 upset archive →Oklahoma State leads 44–28–5 · 38% have been one-possession games
| TLSA | OKST | |
|---|---|---|
| -8.2 (#90) | CORE overall | -22.9 (#130) |
| -8 / +0 | offense / defense | -12 / +11 |
| 1.91 | points / drive | 1.02 |
| 2.62 | allowed / drive | 2.92 |
| 27% | three-and-outs | 38% |
| -4 | 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 →