Matchup Prediction
Oklahoma
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Oklahoma entering this game.
Momentum Control
71.6%
Oklahoma wins
Solid
Game Control
67.1%
Oklahoma wins
Solid
Vegas Spread
Oklahoma -12.5
O/U 66.5
DraftKings
Advanced Stats
All 4 factors agree → Oklahoma
· 83.1% ATS historically when all four align
↓ See full breakdown
TCU 2023 Schedule
TCU's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | TCU vs Colorado | -20.5L42–45 | 59.5 | L42–45 | O | N |
| Sat 9/9 | TCU vs Nicholls | -41.5W41–6 | 59.5 | W41–6 | U | N |
| Sat 9/16 | TCU at Houston | -7.5W36–13 | 64.0 | W36–13 | U | Y |
| Sat 9/23 | TCU vs SMU | -7.0W34–17 | 63.5 | W34–17 | U | Y |
| Sat 9/30 | TCU vs West Virginia | -14.0L21–24 | 52.0 | L21–24 | U | N |
| Sat 10/7 | TCU at Iowa State | -6.5L14–27 | 52.5 | L14–27 | U | N |
| Sat 10/14 | TCU vs BYU | -5.0W44–11 | 52.5 | W44–11 | O | Y |
| Sat 10/21 | TCU at Kansas State | +5.5L3–41 | 60.0 | L3–41 | U | N |
| — Bye Week — | ||||||
| Thu 11/2 | TCU at Texas Tech | +2.5L28–35 | 59.5 | L28–35 | O | N |
| Sat 11/11 | TCU vs Texas | +13.0L26–29 | 56.0 | L26–29 | U | Y |
| Sat 11/18 | TCU vs Baylor | -13.0W42–17 | 62.0 | W42–17 | U | Y |
| Fri 11/24 | TCU at Oklahoma | +12.5L45–69 | 66.5 | L45–69 | O | N |
Oklahoma 2023 Schedule
Oklahoma's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Oklahoma vs Arkansas State | -36.0W73–0 | 57.5 | W73–0 | O | Y |
| Sat 9/9 | Oklahoma vs SMU | -16.5W28–11 | 68.5 | W28–11 | U | Y |
| Sat 9/16 | Oklahoma at Tulsa | -28.0W66–17 | 58.5 | W66–17 | O | Y |
| Sat 9/23 | Oklahoma at Cincinnati | -13.0W20–6 | 58.0 | W20–6 | U | Y |
| Sat 9/30 | Oklahoma vs Iowa State | -19.5W50–20 | 48.5 | W50–20 | O | Y |
| Sat 10/7 | Oklahoma vs Texas | +4.0W34–30 | 62.0 | W34–30 | O | Y |
| — Bye Week — | ||||||
| Sat 10/21 | Oklahoma vs UCF | -17.0W31–29 | 67.5 | W31–29 | U | N |
| Sat 10/28 | Oklahoma at Kansas | -7.0L33–38 | 66.5 | L33–38 | O | N |
| Sat 11/4 | Oklahoma at Oklahoma State | -6.0L24–27 | 61.5 | L24–27 | U | N |
| Sat 11/11 | Oklahoma vs West Virginia | -13.5W59–20 | 59.5 | W59–20 | O | Y |
| Sat 11/18 | Oklahoma at BYU | -24.5W31–24 | 58.5 | W31–24 | U | N |
| Fri 11/24 | Oklahoma vs TCU | -12.5W69–45 | 66.5 | W69–45 | O | Y |
| Thu 12/28 | Oklahoma vs Arizona | +2.5L24–38 | 59.5 | L24–38 | O | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2023 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Oklahoma
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Oklahoma
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Oklahoma
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 · 2023 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?
Oklahoma Edge
Oklahoma +1.19
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 11 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Oklahoma Edge
Oklahoma +14.4
GC Edge (season-to-date)
Teams with this edge win 67.1% of games historically
Based on 11 games this season
Actual Result
CSS Battle
Oklahoma
4 — 0 sequences
✓ Predicted correctly
GC Battle
Oklahoma
83.5 — 7.2 GC score
✓ Predicted correctly
Game Result
Oklahoma won by 24
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Oklahoma with a moderate edge in both. This is the strongest ATS signal in our backtest: teams in this situation have covered 55.8% of the time (n=113).
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
TCU
Sonny Dykes #1
15–3 (83%)
· Yr 2 at school
OC
Kendal Briles
Yr 1
#1
DC
Joe Gillespie
Yr 1
#1
Oklahoma
Brent Venables #1
9–7 (56%)
· Yr 2 at school
OC
Jeff Lebby
Yr 2
#1
DC
Todd Bates
Yr 2
#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 ✓