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
Auburn -2
O/U 43.0
DraftKings
Advanced Stats
PPA + Success Rate agree → Auburn
· 73.9% ATS historically
↓ See full breakdown
Oklahoma 2024 Schedule
Oklahoma's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/30 | Oklahoma vs Temple | -42.5W51–3 | 59.5 | W51–3 | U | Y |
| Sat 9/7 | Oklahoma vs Houston | -27.5W16–12 | 48.5 | W16–12 | U | N |
| Sat 9/14 | Oklahoma vs Tulane | -13.5W34–19 | 48.5 | W34–19 | O | Y |
| Sat 9/21 | Oklahoma vs Tennessee | +6.0L15–25 | 57.0 | L15–25 | U | N |
| Sat 9/28 | Oklahoma at Auburn | +2.0W27–21 | 43.0 | W27–21 | O | Y |
| — Bye Week — | ||||||
| Sat 10/12 | Oklahoma vs Texas | +16.5L3–34 | 48.5 | L3–34 | U | N |
| Sat 10/19 | Oklahoma vs South Carolina | +1.0L9–35 | 40.5 | L9–35 | O | N |
| Sat 10/26 | Oklahoma at Ole Miss | +19.0L14–26 | 50.0 | L14–26 | U | Y |
| Sat 11/2 | Oklahoma vs Maine | -37.5W59–14 | 48.5 | W59–14 | O | Y |
| Sat 11/9 | Oklahoma at Missouri | -3.5L23–30 | 41.5 | L23–30 | O | N |
| — Bye Week — | ||||||
| Sat 11/23 | Oklahoma vs Alabama | +14.0W24–3 | 47.0 | W24–3 | U | Y |
| Sat 11/30 | Oklahoma at LSU | +4.5L17–37 | 47.5 | L17–37 | O | N |
| Fri 12/27 | Oklahoma vs Navy | +1.0L20–21 | 44.0 | L20–21 | U | Y |
Auburn 2024 Schedule
Auburn's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Auburn vs Alabama A&M | -48.5W73–3 | 58.5 | W73–3 | O | Y |
| Sat 9/7 | Auburn vs California | -11.5L14–21 | 52.5 | L14–21 | U | N |
| Sat 9/14 | Auburn vs New Mexico | -25.5W45–19 | 58.5 | W45–19 | O | Y |
| Sat 9/21 | Auburn vs Arkansas | -2.5L14–24 | 53.5 | L14–24 | U | N |
| Sat 9/28 | Auburn vs Oklahoma | -2.0L21–27 | 43.0 | L21–27 | O | N |
| Sat 10/5 | Auburn at Georgia | +21.0L13–31 | 50.0 | L13–31 | U | Y |
| — Bye Week — | ||||||
| Sat 10/19 | Auburn at Missouri | +3.5L17–21 | 49.5 | L17–21 | U | N |
| Sat 10/26 | Auburn at Kentucky | +2.0W24–10 | 43.5 | W24–10 | U | Y |
| Sat 11/2 | Auburn vs Vanderbilt | -7.5L7–17 | 48.0 | L7–17 | U | N |
| — Bye Week — | ||||||
| Sat 11/16 | Auburn vs UL Monroe | -24.5W48–14 | 46.0 | W48–14 | O | Y |
| Sat 11/23 | Auburn vs Texas A&M | +2.5W43–41 | 47.0 | W43–41 | O | Y |
| Sat 11/30 | Auburn at Alabama | +10.5L14–28 | 50.5 | L14–28 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 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
→ Auburn
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 · 2024 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 +0.83
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Oklahoma Edge
Oklahoma +15.0
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 4 games this season
Actual Result
CSS Battle
Auburn
1 — 0 sequences
✗ Predicted incorrectly
GC Battle
Auburn
50.0 — 33.7 GC score
✗ Predicted incorrectly
Game Result
Oklahoma won by 6
✓ 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 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
16–10 (62%)
· Yr 3 at school
OC
Seth Littrell
Yr 1
#1
DC
Zac Alley
Yr 1
#1
Auburn
Hugh Freeze #1
6–7 (46%)
· Yr 2 at school
OC
Derrick Nix
Yr 1
#1
DC
D. J. Durkin
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: CSS is not a predictive 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: GS is not a predictive 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: CSS is not a predictive 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: GS is not a predictive 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 ✓