Matchup Prediction
Air Force
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Air Force entering this game.
Momentum Control
80.6%
Air Force wins
Strong
Game Control
75.9%
Air Force wins
Solid
Vegas Spread
Air Force -11
O/U 34.0
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → Air Force
· 73.9% ATS historically
↓ See full breakdown
Air Force 2023 Schedule
Air Force's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Air Force vs Robert Morris | -47.0W42–7 | 51.0 | W42–7 | U | N |
| Sat 9/9 | Air Force vs Sam Houston | -13.5W13–3 | 36.5 | W13–3 | U | N |
| Fri 9/15 | Air Force vs Utah State | -9.0W39–21 | 45.5 | W39–21 | O | Y |
| Fri 9/22 | Air Force at San José State | -6.0W45–20 | 45.5 | W45–20 | O | Y |
| Sat 9/30 | Air Force vs San Diego State | -10.5W49–10 | 43.5 | W49–10 | O | Y |
| — Bye Week — | ||||||
| Sat 10/14 | Air Force vs Wyoming | -12.5W34–27 | 42.0 | W34–27 | O | N |
| Sat 10/21 | Air Force at Navy | -11.0W17–6 | 34.0 | W17–6 | U | N |
| Sat 10/28 | Air Force at Colorado State | -14.5W30–13 | 47.0 | W30–13 | U | Y |
| Sat 11/4 | Air Force vs Army | -18.5L3–23 | 32.0 | L3–23 | U | N |
| Sat 11/11 | Air Force at Hawai'i | -22.5L13–27 | 47.5 | L13–27 | U | N |
| Sat 11/18 | Air Force vs UNLV | -2.5L27–31 | 46.5 | L27–31 | O | N |
| Fri 11/24 | Air Force at Boise State | +6.5L19–27 | 44.5 | L19–27 | O | N |
| Sat 12/23 | Air Force vs James Madison | -2.5W31–21 | 44.5 | W31–21 | 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
→ Air Force
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?
Air Force Edge
Air Force +2.40
CSS Edge (season-to-date)
Teams with this edge win 80.6% of games historically
Based on 5 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Air Force Edge
Air Force +21.1
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 6 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Air Force 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
Air Force
Troy Calhoun #1
124–78 (61%)
· Yr 17 at school
OC
Mike Thiessen
Yr 3
#1
DC
Brian Knorr
Yr 2
#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: 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 ✓