Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Navy,
while Game Control favors Tulsa.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
61.3%
Navy wins
Lean
Game Control
76%
Tulsa wins
Strong
Vegas Spread
Tulsa -11
O/U 46.0
teamrankings
Advanced Stats
PPA + Success Rate agree → Tulsa
· 73.9% ATS historically
↓ See full breakdown
Navy 2021 Schedule
Navy's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Navy vs Marshall | +3.5L7–49 | 46.5 | L7–49 | O | N |
| Sat 9/11 | Navy vs Air Force | +6.0L3–23 | 40.0 | L3–23 | U | N |
| — Bye Week — | ||||||
| Sat 9/25 | Navy at Houston | +20.0L20–28 | 47.0 | L20–28 | O | Y |
| Sat 10/2 | Navy vs UCF | +15.0W34–30 | 52.5 | W34–30 | O | Y |
| Sat 10/9 | Navy vs SMU | +13.5L24–31 | 57.0 | L24–31 | U | Y |
| Thu 10/14 | Navy at Memphis | +11.0L17–35 | 55.5 | L17–35 | U | N |
| Sat 10/23 | Navy vs Cincinnati | +28.5L20–27 | 49.5 | L20–27 | U | Y |
| Fri 10/29 | Navy at Tulsa | +11.0W20–17 | 46.0 | W20–17 | U | Y |
| Sat 11/6 | Navy at Notre Dame | +21.0L6–34 | 47.5 | L6–34 | U | N |
| — Bye Week — | ||||||
| Sat 11/20 | Navy vs East Carolina | +3.5L35–38 | 46.0 | L35–38 | O | Y |
| Sat 11/27 | Navy at Temple | -13.5W38–14 | 42.0 | W38–14 | O | Y |
| — Bye Week — | ||||||
| Sat 12/11 | Navy at Army | -7.0W17–13 | 35.5 | W17–13 | U | N |
Tulsa 2021 Schedule
Tulsa's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 9/2 | Tulsa vs UC Davis | -22.0L17–19 | 54.5 | L17–19 | U | N |
| Sat 9/11 | Tulsa at Oklahoma State | +11.5L23–28 | 51.0 | L23–28 | U | Y |
| Sat 9/18 | Tulsa at Ohio State | +24.5L20–41 | 60.5 | L20–41 | O | Y |
| Sat 9/25 | Tulsa vs Arkansas State | -14.5W41–34 | 65.0 | W41–34 | O | N |
| Fri 10/1 | Tulsa vs Houston | -3.0L10–45 | 54.0 | L10–45 | O | N |
| Sat 10/9 | Tulsa vs Memphis | -3.0W35–29 | 60.5 | W35–29 | O | Y |
| Sat 10/16 | Tulsa at South Florida | -7.5W32–31 | 56.0 | W32–31 | O | N |
| — Bye Week — | ||||||
| Fri 10/29 | Tulsa vs Navy | -11.0L17–20 | 46.0 | L17–20 | U | N |
| Sat 11/6 | Tulsa at Cincinnati | +22.5L20–28 | 56.0 | L20–28 | U | Y |
| Sat 11/13 | Tulsa at Tulane | -3.0W20–13 | 55.5 | W20–13 | U | Y |
| Sat 11/20 | Tulsa vs Temple | -22.0W44–10 | 50.5 | W44–10 | O | Y |
| Sat 11/27 | Tulsa at SMU | +6.0W34–31 | 63.0 | W34–31 | O | Y |
| Mon 12/20 | Tulsa vs Old Dominion | -7.5W30–17 | 55.0 | W30–17 | 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
→ Tulsa
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?
Navy Edge
Navy +0.21
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 6 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Tulsa Edge
Tulsa +26.0
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 7 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
CSS and GC disagree on this matchup. When the metrics split, historical cover rates are essentially random — treat this as a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Navy
Ken Niumatalolo #1
101–69 (59%)
· Yr 15 at school
OC
Vacant
Yr 1
#1
DC
Brian Newberry
Yr 1
#1
Tulsa
Philip Montgomery #1
31–43 (42%)
· Yr 7 at school
OC
Philip Montgomery
Yr 1
#1
DC
Joseph Gillespie
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 ✓