Matchup Prediction
Texas
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Texas entering this game.
Momentum Control
61.3%
Texas wins
Lean
Game Control
64.9%
Texas wins
Lean
Vegas Spread
Texas -7.5
O/U 65.0
teamrankings
Advanced Stats
PPA + Success Rate agree → Texas
· 73.9% ATS historically
↓ See full breakdown
Texas 2022 Schedule
Texas's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Texas vs UL Monroe | -37.0W52–10 | 64.5 | W52–10 | U | Y |
| Sat 9/10 | Texas vs Alabama | +21.0L19–20 | 64.0 | L19–20 | U | Y |
| Sat 9/17 | Texas vs UTSA | -13.0W41–20 | 57.5 | W41–20 | O | Y |
| Sat 9/24 | Texas at Texas Tech | -7.0L34–37 | 60.0 | L34–37 | O | N |
| Sat 10/1 | Texas vs West Virginia | -7.5W38–20 | 61.0 | W38–20 | U | Y |
| Sat 10/8 | Texas vs Oklahoma | -7.5W49–0 | 65.0 | W49–0 | U | Y |
| Sat 10/15 | Texas vs Iowa State | -15.5W24–21 | 48.5 | W24–21 | U | N |
| Sat 10/22 | Texas at Oklahoma State | -6.5L34–41 | 58.5 | L34–41 | O | N |
| — Bye Week — | ||||||
| Sat 11/5 | Texas at Kansas State | -3.0W34–27 | 54.5 | W34–27 | O | Y |
| Sat 11/12 | Texas vs TCU | -7.5L10–17 | 65.0 | L10–17 | U | N |
| Sat 11/19 | Texas at Kansas | -9.0W55–14 | 63.5 | W55–14 | O | Y |
| Fri 11/25 | Texas vs Baylor | -10.0W38–27 | 55.0 | W38–27 | O | Y |
| Thu 12/29 | Texas vs Washington | -3.0L20–27 | 67.0 | L20–27 | U | N |
Oklahoma 2022 Schedule
Oklahoma's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Oklahoma vs UTEP | -31.0W45–13 | 58.0 | W45–13 | U | Y |
| Sat 9/10 | Oklahoma vs Kent State | -33.5W33–3 | 73.0 | W33–3 | U | N |
| Sat 9/17 | Oklahoma at Nebraska | -10.5W49–14 | 65.5 | W49–14 | U | Y |
| Sat 9/24 | Oklahoma vs Kansas State | -13.5L34–41 | 53.0 | L34–41 | O | N |
| Sat 10/1 | Oklahoma at TCU | -5.0L24–55 | 69.5 | L24–55 | O | N |
| Sat 10/8 | Oklahoma vs Texas | +7.5L0–49 | 65.0 | L0–49 | U | N |
| Sat 10/15 | Oklahoma vs Kansas | -10.5W52–42 | 66.0 | W52–42 | O | N |
| — Bye Week — | ||||||
| Sat 10/29 | Oklahoma at Iowa State | -1.5W27–13 | 58.0 | W27–13 | U | Y |
| Sat 11/5 | Oklahoma vs Baylor | -3.0L35–38 | 61.5 | L35–38 | O | N |
| Sat 11/12 | Oklahoma at West Virginia | -8.5L20–23 | 68.5 | L20–23 | U | N |
| Sat 11/19 | Oklahoma vs Oklahoma State | -7.0W28–13 | 67.5 | W28–13 | U | Y |
| Sat 11/26 | Oklahoma at Texas Tech | -2.0L48–51 | 65.5 | L48–51 | O | N |
| Thu 12/29 | Oklahoma vs Florida State | +10.5L32–35 | 67.0 | L32–35 | U | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2022 season
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
→ Texas
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
PPA Passing
Pass efficiency edge · Strong predictor
Havoc Total
Def. disruption rate · Strong predictor
TFLs, sacks, PBUs, forced fumbles — higher is better
Points Per Opp
Drive-finishing edge · Strong predictor
Success Rate
Play consistency edge · Solid predictor
Field Position
Avg start (lower=better) · Solid predictor
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Advanced stats sourced from CFBD · 2022 season ·
Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences
Who builds scoring momentum?
Texas Edge
Texas +0.60
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 5 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Texas Edge
Texas +17.9
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 5 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Texas with a solid GC edge. Teams with this profile have covered 53.0% of the time historically (n=330) — a mild lean.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Texas
Steve Sarkisian #1
5–7 (42%)
· Yr 2 at school
OC
Kyle Flood
Yr 2
#1
DC
Pete Kwiatkowski
Yr 1
#1
Oklahoma
Brent Venables #1
0–0 (0%)
· Yr 1 at school
OC
Jeff Lebby
Yr 1
#1
DC
Todd Bates
Yr 1
#1
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 ✓
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 ✓