Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors UAB,
while Game Control favors Navy.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
61.3%
UAB wins
Lean
Game Control
50.6%
Navy wins
Toss-up
Vegas Spread
UAB -3.5
O/U 52.5
ESPN Bet
Advanced Stats
PPA + Success Rate agree → UAB
· 73.9% ATS historically
↓ See full breakdown
UAB 2023 Schedule
UAB's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/31 | UAB vs North Carolina A&T | -24.5W35–6 | 46.5 | W35–6 | U | Y |
| Sat 9/9 | UAB at Georgia Southern | +7.0L35–49 | 63.0 | L35–49 | O | N |
| Sat 9/16 | UAB vs Louisiana | -2.0L21–41 | 60.0 | L21–41 | O | N |
| Sat 9/23 | UAB at Georgia | +40.0L21–49 | 56.0 | L21–49 | O | Y |
| Sat 9/30 | UAB at Tulane | +22.5L23–35 | 59.5 | L23–35 | U | Y |
| Sat 10/7 | UAB vs South Florida | +3.5W56–35 | 68.5 | W56–35 | O | Y |
| Sat 10/14 | UAB at UTSA | +9.0L20–41 | 67.0 | L20–41 | U | N |
| Sat 10/21 | UAB vs Memphis | +7.5L21–45 | 61.5 | L21–45 | O | N |
| — Bye Week — | ||||||
| Sat 11/4 | UAB vs Florida Atlantic | -1.0W45–42 | 59.5 | W45–42 | O | Y |
| Sat 11/11 | UAB at Navy | -3.5L6–31 | 52.5 | L6–31 | U | N |
| Sat 11/18 | UAB vs Temple | -8.0W34–24 | 61.5 | W34–24 | U | Y |
| Sat 11/25 | UAB at North Texas | +3.0L42–45 | 72.5 | L42–45 | O | Y |
Navy 2023 Schedule
Navy's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/26 | Navy vs Notre Dame | +20.5L3–42 | 49.0 | L3–42 | U | N |
| Sat 9/9 | Navy vs Wagner | -43.5W24–0 | 49.0 | W24–0 | U | N |
| Thu 9/14 | Navy at Memphis | +12.5L24–28 | 47.0 | L24–28 | O | Y |
| — Bye Week — | ||||||
| Sat 9/30 | Navy vs South Florida | -4.0L30–44 | 54.0 | L30–44 | O | N |
| Sat 10/7 | Navy vs North Texas | -6.5W27–24 | 60.5 | W27–24 | U | N |
| Sat 10/14 | Navy at Charlotte | -3.5W14–0 | 44.0 | W14–0 | U | Y |
| Sat 10/21 | Navy vs Air Force | +11.0L6–17 | 34.0 | L6–17 | U | Y |
| — Bye Week — | ||||||
| Sat 11/4 | Navy at Temple | -7.0L18–32 | 46.0 | L18–32 | O | N |
| Sat 11/11 | Navy vs UAB | +3.5W31–6 | 52.5 | W31–6 | U | Y |
| Sat 11/18 | Navy vs East Carolina | -2.5W10–0 | 30.5 | W10–0 | U | Y |
| Sat 11/25 | Navy at SMU | +20.0L14–59 | 46.0 | L14–59 | O | N |
| — Bye Week — | ||||||
| Sat 12/9 | Navy vs Army | +2.0L11–17 | 28.0 | L11–17 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2023 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
→ UAB
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 · 2023 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?
UAB Edge
UAB +0.82
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 7 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Navy Edge
Navy +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 8 games this season
Actual Result
CSS Battle
Navy
2 — 1 sequences
✗ Predicted incorrectly
GC Battle
Navy
64.9 — 12.8 GC score
✓ Predicted correctly
Game Result
Navy won by 25
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
UAB
Trent Dilfer #1
1–2 (33%)
· Yr 1 at school
OC
Alex Mortensen
Yr 1
#1
DC
Sione Ta'ufo'ou
Yr 1
#1
Navy
Brian Newberry #1
1–2 (33%)
· Yr 1 at school
OC
Grant Chesnut
Yr 1
#1
DC
P.J. Volker
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 ✓