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 -31
O/U 66.5
teamrankings
Advanced Stats
All 4 factors agree → Oklahoma
· 83.1% ATS historically when all four align
↓ See full breakdown
Tulane 2021 Schedule
Tulane's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Tulane at Oklahoma | +31.0L35–40 | 66.5 | L35–40 | O | Y |
| Sat 9/11 | Tulane vs Morgan State | -47.5W69–20 | 58.0 | W69–20 | O | Y |
| Sat 9/18 | Tulane at Ole Miss | +14.0L21–61 | 77.0 | L21–61 | O | N |
| Sat 9/25 | Tulane vs UAB | -2.5L21–28 | 55.0 | L21–28 | U | N |
| Sat 10/2 | Tulane at East Carolina | -3.0L29–52 | 65.0 | L29–52 | O | N |
| Thu 10/7 | Tulane vs Houston | +6.5L22–40 | 60.0 | L22–40 | O | N |
| — Bye Week — | ||||||
| Thu 10/21 | Tulane at SMU | +14.0L26–55 | 70.5 | L26–55 | O | N |
| Sat 10/30 | Tulane vs Cincinnati | +27.5L12–31 | 61.5 | L12–31 | U | Y |
| Sat 11/6 | Tulane at UCF | +13.5L10–14 | 57.0 | L10–14 | U | Y |
| Sat 11/13 | Tulane vs Tulsa | +3.0L13–20 | 55.5 | L13–20 | U | N |
| Sat 11/20 | Tulane vs South Florida | -5.5W45–14 | 59.5 | W45–14 | U | Y |
| Sat 11/27 | Tulane at Memphis | +5.5L28–33 | 58.0 | L28–33 | O | Y |
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 |
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
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 · 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?
Tulane Edge
Tulane +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?
Tulane Edge
Tulane +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
5 — 1 sequences
✗ Predicted incorrectly
GC Battle
Oklahoma
87.9 — 3.7 GC score
✗ Predicted incorrectly
Game Result
Oklahoma won by 5
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
Tulane
Willie Fritz #1
30–35 (46%)
· Yr 6 at school
OC
Chip Long
Yr 1
#1
DC
Chris Hampton
Yr 1
#1
Oklahoma
Lincoln Riley #1
48–8 (86%)
· Yr 5 at school
OC
Bill Bedenbaugh
Yr 1
#1
DC
Alex Grinch
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 ✓