Matchup Prediction
Tulsa
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Tulsa entering this game.
Momentum Control
73.7%
Tulsa wins
Solid
Game Control
75.9%
Tulsa wins
Solid
Vegas Spread
Tulsa -4.5
O/U 45.5
teamrankings
Advanced Stats
PPA + Success Rate agree → Tulsa
· 73.9% ATS historically
↓ See full breakdown
Tulsa 2022 Schedule
Tulsa's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Tulsa at Wyoming | -6.5L37–40 | 47.0 | L37–40 | O | N |
| Sat 9/10 | Tulsa vs Northern Illinois | -6.5W38–35 | 63.0 | W38–35 | O | N |
| Sat 9/17 | Tulsa vs Jacksonville State | -12.0W54–17 | 64.0 | W54–17 | O | Y |
| Sat 9/24 | Tulsa at Ole Miss | +21.0L27–35 | 66.5 | L27–35 | U | Y |
| Sat 10/1 | Tulsa vs Cincinnati | +10.0L21–31 | 59.0 | L21–31 | U | Y |
| Sat 10/8 | Tulsa at Navy | -4.5L21–53 | 45.5 | L21–53 | O | N |
| — Bye Week — | ||||||
| Fri 10/21 | Tulsa at Temple | -13.5W27–16 | 53.5 | W27–16 | U | N |
| Sat 10/29 | Tulsa vs SMU | +1.0L34–45 | 63.5 | L34–45 | O | N |
| Sat 11/5 | Tulsa vs Tulane | +6.5L13–27 | 56.0 | L13–27 | U | N |
| Thu 11/10 | Tulsa at Memphis | +7.0L10–26 | 62.0 | L10–26 | U | N |
| Fri 11/18 | Tulsa vs South Florida | -14.0W48–42 | 57.5 | W48–42 | O | N |
| Sat 11/26 | Tulsa at Houston | +13.0W37–30 | 66.5 | W37–30 | O | Y |
Navy 2022 Schedule
Navy's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Navy vs Delaware | -13.0L7–14 | 48.5 | L7–14 | U | N |
| Sat 9/10 | Navy vs Memphis | +4.5L13–37 | 47.5 | L13–37 | O | N |
| — Bye Week — | ||||||
| Sat 9/24 | Navy at East Carolina | +16.5W23–20 | 48.5 | W23–20 | U | Y |
| Sat 10/1 | Navy at Air Force | +14.0L10–13 | 38.0 | L10–13 | U | Y |
| Sat 10/8 | Navy vs Tulsa | +4.5W53–21 | 45.5 | W53–21 | O | Y |
| Fri 10/14 | Navy at SMU | +12.5L34–40 | 59.0 | L34–40 | O | Y |
| Sat 10/22 | Navy vs Houston | +3.0L20–38 | 51.0 | L20–38 | O | N |
| Sat 10/29 | Navy vs Temple | -14.5W27–20 | 41.5 | W27–20 | O | N |
| Sat 11/5 | Navy at Cincinnati | +18.5L10–20 | 43.5 | L10–20 | U | Y |
| Sat 11/12 | Navy vs Notre Dame | +17.0L32–35 | 40.5 | L32–35 | O | Y |
| Sat 11/19 | Navy at UCF | +14.5W17–14 | 53.0 | W17–14 | U | Y |
| — Bye Week — | ||||||
| Sat 12/10 | Navy vs Army | -2.5L17–20 | 32.0 | L17–20 | O | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2022 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 · 2022 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?
Tulsa Edge
Tulsa +1.07
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Tulsa Edge
Tulsa +31.2
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 4 games this season
Actual Result
CSS Battle
Navy
4 — 0 sequences
✗ Predicted incorrectly
GC Battle
Navy
78.7 — 7.9 GC score
✗ Predicted incorrectly
Game Result
Navy won by 32
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Tulsa with a large edge. Historically, dominant teams like this are fully priced into the spread — the agreed-upon team covers just 50.2% of the time. The metrics predict game control better than they beat the number.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Tulsa
Philip Montgomery #1
38–46 (45%)
· Yr 8 at school
OC
Philip Montgomery
Yr 2
#1
DC
Luke Olson
Yr 1
#1
Navy
Ken Niumatalolo #1
104–74 (58%)
· Yr 16 at school
OC
Vacant
Yr 2
#1
DC
Brian Newberry
Yr 2
#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 ✓