Matchup Prediction
Oklahoma
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Oklahoma entering this game.
Momentum Control
61.3%
Oklahoma wins
Lean
Game Control
64.9%
Oklahoma wins
Lean
Vegas Spread
Oklahoma -4
O/U 63.0
teamrankings
Advanced Stats
PPA + Success Rate agree → Baylor
· 73.9% ATS historically
↓ See full breakdown
Oklahoma 2021 Schedule
Oklahoma's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Oklahoma vs Tulane | -31.0W40–35 | 66.5 | W40–35 | O | N |
| Sat 9/11 | Oklahoma vs Western Carolina | -52.5W76–0 | 66.0 | W76–0 | O | Y |
| Sat 9/18 | Oklahoma vs Nebraska | -22.5W23–16 | 62.5 | W23–16 | U | N |
| Sat 9/25 | Oklahoma vs West Virginia | -17.5W16–13 | 56.5 | W16–13 | U | N |
| Sat 10/2 | Oklahoma at Kansas State | -12.0W37–31 | 53.0 | W37–31 | O | N |
| Sat 10/9 | Oklahoma vs Texas | -4.0W55–48 | 65.5 | W55–48 | O | Y |
| Sat 10/16 | Oklahoma vs TCU | -12.5W52–31 | 64.5 | W52–31 | O | Y |
| Sat 10/23 | Oklahoma at Kansas | -38.0W35–23 | 66.5 | W35–23 | U | N |
| Sat 10/30 | Oklahoma vs Texas Tech | -18.5W52–21 | 67.0 | W52–21 | O | Y |
| — Bye Week — | ||||||
| Sat 11/13 | Oklahoma at Baylor | -4.0L14–27 | 63.0 | L14–27 | U | N |
| Sat 11/20 | Oklahoma vs Iowa State | -3.0W28–21 | 59.0 | W28–21 | U | Y |
| Sat 11/27 | Oklahoma at Oklahoma State | +4.0L33–37 | 50.0 | L33–37 | O | Y |
| Wed 12/29 | Oklahoma vs Oregon | -7.0W47–32 | 64.0 | W47–32 | O | Y |
Baylor 2021 Schedule
Baylor's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Baylor at Texas State | -13.5W29–20 | 52.5 | W29–20 | U | N |
| Sat 9/11 | Baylor vs Texas Southern | -44.5W66–7 | 53.0 | W66–7 | O | Y |
| Sat 9/18 | Baylor at Kansas | -17.0W45–7 | 48.5 | W45–7 | O | Y |
| Sat 9/25 | Baylor vs Iowa State | +7.0W31–29 | 46.0 | W31–29 | O | Y |
| Sat 10/2 | Baylor at Oklahoma State | +3.5L14–24 | 47.0 | L14–24 | U | N |
| Sat 10/9 | Baylor vs West Virginia | -1.0W45–20 | 45.0 | W45–20 | O | Y |
| Sat 10/16 | Baylor vs BYU | -5.5W38–24 | 52.5 | W38–24 | O | Y |
| — Bye Week — | ||||||
| Sat 10/30 | Baylor vs Texas | -2.0W31–24 | 61.5 | W31–24 | U | Y |
| Sat 11/6 | Baylor at TCU | -7.5L28–30 | 57.0 | L28–30 | O | N |
| Sat 11/13 | Baylor vs Oklahoma | +4.0W27–14 | 63.0 | W27–14 | U | Y |
| Sat 11/20 | Baylor at Kansas State | +2.5W20–10 | 49.5 | W20–10 | U | Y |
| Sat 11/27 | Baylor vs Texas Tech | -14.0W27–24 | 51.5 | W27–24 | U | N |
| Sat 12/4 | Baylor vs Oklahoma State | +7.0W21–16 | 45.0 | W21–16 | U | Y |
| Sat 1/1 | Baylor vs Ole Miss | +1.0W21–7 | 60.5 | W21–7 | U | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2021 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
→ Baylor
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 · 2021 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 +0.88
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 8 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Oklahoma Edge
Oklahoma +13.1
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 9 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Oklahoma 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
Oklahoma
Lincoln Riley #1
48–8 (86%)
· Yr 5 at school
OC
Bill Bedenbaugh
Yr 1
#1
DC
Alex Grinch
Yr 1
#1
Baylor
Dave Aranda #1
5–7 (42%)
· Yr 2 at school
OC
Jeff Grimes
Yr 1
#1
DC
Ron Roberts
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 ✓