Tulsa at Sam Houston Week 2 College Football Matchup Tulsa at Sam Houston Matchup - Week 2
Sat, Sep 12 2026 · Week 2 · 🏟 Bowers Stadium Huntsville, TX · Turf · 14,000 cap
Tulsa✈ 376 miSame TZ
Away
VS
Preseason projection — This game has not yet been played and 2026 in-season data is not yet available. Edges are based on 2025 full-season performance. Confidence will increase once in-season games are logged.
📊 Punt & Rally Projection
Tulsa
36
Sam Houston
19
P&R Line Tulsa -17
P&R Total O/U 54
Confidence 63 Moderate
Matchup Prediction
Tulsa has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor Tulsa entering this game.
Momentum Control
61.3%
Tulsa wins
Lean
Game Control
75.9%
Tulsa wins
Solid
Advanced Stats
PPA + Success Rate agree → Tulsa · 73.9% ATS historically
↓ See full breakdown
Tulsa 2026 Schedule
Tulsa's 2026 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/5Tulsa vs Oklahoma State+7
Sat 9/12Tulsa at Sam Houston-17
Sat 9/19Tulsa vs East Texas A&M-20
Sat 9/26Tulsa at Arkansas+8
Thu 10/1Tulsa vs North Texas-6.5
Sat 10/10Tulsa at Navy+5.5
Sat 10/17Tulsa at Rice-10
Fri 10/23Tulsa vs Army-1
— Bye Week —
Sat 11/7Tulsa at Tulane+3
Sat 11/14Tulsa vs Florida Atlantic-6
Sat 11/21Tulsa vs Charlotte-24.5
Sat 11/28Tulsa at UTSA+5
Sam Houston 2026 Schedule
Sam Houston's 2026 Schedule
DateMatchupSpreadTotalResultO/UCover
— Bye Week —
Sat 9/12Sam Houston vs Tulsa+17
— Bye Week —
Sat 9/26Sam Houston at Texas Tech+37
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2025 season (prior year)
Tulsa PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Tulsa
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Tulsa #105
+0.329
Sam Houston #131
+0.161
Tulsa Edge
PPA Passing
Pass efficiency edge · Strong predictor
Tulsa #114
+0.510
Sam Houston #133
+0.288
Tulsa Edge
Havoc Total
Def. disruption rate · Strong predictor
Tulsa #121
0.127
Sam Houston #100
0.144
TFLs, sacks, PBUs, forced fumbles — higher is better
Sam Houston Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Tulsa #106
+7.195
Sam Houston #129
+6.568
Tulsa Edge
Success Rate
Play consistency edge · Solid predictor
Tulsa #97
+0.883
Sam Houston #120
+0.794
Tulsa Edge
Field Position
Avg start (lower=better) · Solid predictor
Tulsa #115
72.6
Sam Houston #124
73.2
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Tulsa Edge
Advanced stats sourced from CFBD · 2025 season (prior year — 2026 data not yet available) · Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
Tulsa Rated Higher
Overall Power Rating
Tulsa #63
0.8
Sam Houston #134
-19.3
Offense Rating
Tulsa #53
16.9
Sam Houston #135
4.6
Defense Rating (lower = better defense)
Tulsa #75
16.1
Sam Houston #127
23.9
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? Tulsa Edge
Avg sequences created per game
Tulsa #57
0.91
Sam Houston #104
0.42
Avg sequences allowed per game (lower is better)
Tulsa #42
0.82
Sam Houston #131
2.08
Tulsa +0.49
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 2025 full season · preseason estimate
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Tulsa Edge
Avg GC score per game (offense)
Tulsa #79
35.0
Sam Houston #126
15.6
Avg GC score allowed per game (lower is better)
Tulsa #103
49.9
Sam Houston #135
69.8
Tulsa +19.4
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 2025 full season · preseason estimate
Coaching Matchup
Tulsa
Tre Lamb #113
4–8 (33%) · Yr 2 at school
OC Ty Darlington Yr 2 #127
DC Mike Gray Yr 2 #97
Staff Rating
2.10 #120
Sam Houston
Phil Longo #124
2–10 (17%) · Yr 2 at school
OC Zack Patterson Yr 2 #130
DC Freddie Aughtry-Lindsay Yr 2 #123
Staff Rating
1.76 #132
About these metrics
Advanced Stats shows matchup-adjusted factor edges (offense vs opponent defense). Combination signals — when PPA, PPO, Success Rate, and Havoc all point the same direction — have historically predicted the SU winner in 95–97% of games and the ATS winner in 82–83% of games (2021–2025, FBS vs FBS, regular season).
Impact: Advanced Stats are the best performance based metric used to predict the outcome of games.

Momentum Control (CSS) measures consecutive scoring sequences — when a team scores, holds the opponent scoreless, then scores again. Teams entering a game with a CSS edge of +1.0 or more have won 71–78% of games historically (2021–2025, FBS vs FBS).
Impact: Momentum Control is a great measure for predicting game outcome but NOT an ATS advantage, data shows this is already considered when lines are set.

Game Control (GC) measures win probability dominance — how thoroughly a team controlled the game from start to finish. Teams with a GC edge of +12 or more have won 67–76% of games historically. When both metrics agree, combined confidence is higher. When they split, treat as a lean at best.
Impact: Game Control is another great measure for predicting game outcome but NOT an ATS advantage, data shows this is already considered when lines are set.

Power Ratings are a custom-built composite of a Teams Talent, Experience & Production, Coaching & Performance Metrics. These are updated constantly with roster changes, performance once the games start for the 2026 season, injuries the team is dealing with and scheduling situations.
Impact: There are a wide range of power ratings available, we think ours is the best, you can decide for yourself