Tulsa vs. Rice Prediction, Odds & Pick
Prediction, odds and the model's read
Our model's read
Scouting report
2026 projection · last season, roster and staff
Where Tulsa gets at Rice: 50th at hitting chunk plays, against a unit 138th at keeping everything in front of them. Rice projects no clear way in against Tulsa.
How
TLSAattacks
RICE
- 1
Take shots
hitting chunk plays · projected
TLSA#50 of 138RICE#138 of 138
The two teams
Tulsa
Tulsa is in year 2 under Tre Lamb. The way in is 126th at staying out of the backfield, and they are 109th at throwing it.
Tulsa has played 1 game against a genuinely tough slate, adjusted for here. That football carries about 0% of what is below; the rest is still the preseason projection.
Projected soft spots
- Offensegetting stopped at the line#126projected
- Offensethrowing it#109projected
- Offensesurviving second and twelve#106projected
Rice
Rice is in year 2 under Scott Abell. The way in is 138th at keeping everything in front of them, and they are 133rd at staying on schedule through the air.
Rice has not played an FBS opponent yet, so this is the projection: last season regressed toward the mean, plus returning production, recruiting, talent and whether the staff is the same one.
Projected soft spots
- Defensehitting chunk plays#138projected
- Offensestaying on schedule through the air#133projected
- Offensesurviving second and twelve#133projected
Ranks are national. Nothing here is last season's number — carrying one forward is measurably worse than saying nothing — and in-season figures are adjusted for who was actually played. This describes the matchup; it is not a prediction and not a pick.
Head coaches only — there is no free feed for coordinators, so on a program where the head coach does not call the offense this describes the staff he hired. Play-calling identity is a style, not a grade: throwing more than the situations warrant is not better than throwing less than they warrant.
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (RICE Elo 1107, TLSA Elo 1268 for reference), with home-field advantage. That projects RICE +3.4 (42% 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
Where the game is won
2026 national rank · right is better
offensethe defense it faces
Moving the ball
TLSA59th105thRICERICE114th44thTLSAThrough the air
TLSA69th96thRICERICE135th104thTLSAOn the ground
TLSA90th86thRICERICE20th82ndTLSAStaying on the field
TLSA135th102ndRICERICE60th54thTLSATaking care of it
TLSA31st88thRICERICE118th14thTLSA
Each bar runs from last in the country on the left to 1st on the right. The filled span is the gap between the offense and the defense it faces.
Season form — 2026
nationally rankedThe matchup, in context
series history + adjusted profilesTulsa leads 10–9–1 · Rice has won 2 straight · 40% have been one-possession games
| TLSA | RICE | |
|---|---|---|
| +0.1 (#69) | CORE overall | -12.6 (#120) |
| -4 / -4 | offense / defense | -10 / +3 |
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.
Create a free account →You get Pro free for 6 months. No card required.
FAQ
Who will win Tulsa vs. Rice?
Gridpex's model favors Tulsa with a 58% win probability.
What's the predicted spread for Tulsa vs. Rice?
The model projects Tulsa by 3.4.
What time is Tulsa vs. Rice and what channel is it on?
Time TBD, at Rice Stadium.
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 →