Matchup Prediction
Toss-up — no clear edge
Neither metric shows a meaningful pre-game edge in this matchup.
Momentum Control
58.4%
—
Lean
Game Control
50.6%
—
Toss-up
Vegas Spread
Oklahoma -42.5
O/U 59.5
DraftKings
Advanced Stats
All 4 factors agree → Oklahoma
· 83.1% ATS historically when all four align
↓ See full breakdown
Temple 2024 Schedule
Temple's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/30 | Temple at Oklahoma | +42.5L3–51 | 59.5 | L3–51 | U | N |
| Sat 9/7 | Temple at Navy | +11.5L11–38 | 43.5 | L11–38 | O | N |
| Sat 9/14 | Temple vs Coastal Carolina | +17.5L20–28 | 51.5 | L20–28 | U | Y |
| Sat 9/21 | Temple vs Utah State | +6.5W45–29 | 53.5 | W45–29 | O | Y |
| Thu 9/26 | Temple vs Army | +11.0L14–42 | 46.5 | L14–42 | O | N |
| Sat 10/5 | Temple at UConn | +17.5L20–29 | 49.0 | L20–29 | U | Y |
| — Bye Week — | ||||||
| Sat 10/19 | Temple vs Tulsa | -3.5W20–10 | 51.5 | W20–10 | U | Y |
| Sat 10/26 | Temple at East Carolina | +8.5L34–56 | 48.5 | L34–56 | O | N |
| — Bye Week — | ||||||
| Sat 11/9 | Temple at Tulane | +25.5L6–52 | 50.5 | L6–52 | O | N |
| Sat 11/16 | Temple vs Florida Atlantic | -2.0W18–15 | 50.0 | W18–15 | U | Y |
| Fri 11/22 | Temple at UTSA | +16.5L27–51 | 56.0 | L27–51 | O | N |
| Sat 11/30 | Temple vs North Texas | +10.5L17–24 | 63.5 | L17–24 | U | Y |
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 |
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
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 · 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?
Temple Edge
Temple +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 0 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Temple Edge
Temple +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 0 games this season
Actual Result
CSS Battle
Oklahoma
4 — 0 sequences
✗ Predicted incorrectly
GC Battle
Oklahoma
91.9 — 3.7 GC score
✗ Predicted incorrectly
Game Result
Oklahoma won by 48
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Oklahoma, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Temple
Stan Drayton #1
6–18 (25%)
· Yr 3 at school
OC
Danny Langsdorf
Yr 3
#1
DC
Everett Withers
Yr 2
#1
Oklahoma
Brent Venables #1
16–10 (62%)
· Yr 3 at school
OC
Seth Littrell
Yr 1
#1
DC
Zac Alley
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 ✓