Sat, Sep 23 2023
·
Week 4
·
🏟 Nippert Stadium
Cincinnati, OH
·
Turf
·
40,000 cap
Oklahoma✈ 760 mi+1 hr TZ
Matchup Prediction
Oklahoma
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Oklahoma entering this game.
Momentum Control
80.6%
Oklahoma wins
Strong
Game Control
75.9%
Oklahoma wins
Solid
Vegas Spread
Oklahoma -13
O/U 58.0
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → Oklahoma
· 73.9% ATS historically
↓ See full breakdown
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 |
Cincinnati 2023 Schedule
Cincinnati's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Cincinnati vs Eastern Kentucky | -21.5W66–13 | 57.5 | W66–13 | O | Y |
| Sat 9/9 | Cincinnati at Pittsburgh | +6.5W27–21 | 44.5 | W27–21 | O | Y |
| Sat 9/16 | Cincinnati vs Miami (OH) | -14.5L24–31 | 44.5 | L24–31 | O | N |
| Sat 9/23 | Cincinnati vs Oklahoma | +13.0L6–20 | 58.0 | L6–20 | U | N |
| Fri 9/29 | Cincinnati at BYU | +1.0L27–35 | 47.5 | L27–35 | O | N |
| — Bye Week — | ||||||
| Sat 10/14 | Cincinnati vs Iowa State | -4.0L10–30 | 42.5 | L10–30 | U | N |
| Sat 10/21 | Cincinnati vs Baylor | -2.5L29–32 | 51.5 | L29–32 | O | N |
| Sat 10/28 | Cincinnati at Oklahoma State | +7.0L13–45 | 53.0 | L13–45 | O | N |
| Sat 11/4 | Cincinnati vs UCF | +3.5L26–28 | 59.5 | L26–28 | U | Y |
| Sat 11/11 | Cincinnati at Houston | +3.5W24–14 | 53.5 | W24–14 | U | Y |
| Sat 11/18 | Cincinnati at West Virginia | +4.5L21–42 | 52.5 | L21–42 | O | N |
| Sat 11/25 | Cincinnati vs Kansas | +7.5L16–49 | 59.5 | L16–49 | 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
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
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 +3.00
CSS Edge (season-to-date)
Teams with this edge win 80.6% of games historically
Based on 2 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Oklahoma Edge
Oklahoma +19.3
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 3 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
Brent Venables #1
9–7 (56%)
· Yr 2 at school
OC
Jeff Lebby
Yr 2
#1
DC
Todd Bates
Yr 2
#1
Cincinnati
Scott Satterfield #1
2–1 (67%)
· Yr 1 at school
OC
Brad Glenn
Yr 1
#1
DC
Bryan Brown
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 ✓