Matchup Prediction
Army
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Army entering this game.
Momentum Control
61.3%
Army wins
Lean
Game Control
49.4%
Army wins
Toss-up
Vegas Spread
Army -1.5
O/U 48.5
DraftKings
Advanced Stats
PPA + Success Rate agree → Army
· 73.9% ATS historically
↓ See full breakdown
Army 2025 Schedule
Army's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/29 | Army vs Tarleton State | -14.5L27–30 | 47.5 | L27–30 | O | N |
| Sat 9/6 | Army at Kansas State | +17.0W24–21 | 48.5 | W24–21 | U | Y |
| — Bye Week — | ||||||
| Sat 9/20 | Army vs North Texas | +2.5L38–45 | 50.5 | L38–45 | O | N |
| Thu 9/25 | Army at East Carolina | +3.5L6–28 | 52.5 | L6–28 | U | N |
| Sat 10/4 | Army at UAB | -6.5W31–13 | 55.5 | W31–13 | U | Y |
| Sat 10/11 | Army vs Charlotte | -17.5W24–7 | 45.5 | W24–7 | U | N |
| Sat 10/18 | Army at Tulane | +10.0L17–24 | 44.5 | L17–24 | U | Y |
| — Bye Week — | ||||||
| Sat 11/1 | Army at Air Force | -1.5W20–17 | 48.5 | W20–17 | U | Y |
| Sat 11/8 | Army vs Temple | -7.5W14–13 | 45.5 | W14–13 | U | N |
| — Bye Week — | ||||||
| Sat 11/22 | Army vs Tulsa | -10.0L25–26 | 43.5 | L25–26 | O | N |
| Sat 11/29 | Army at UTSA | +8.5W27–24 | 50.5 | W27–24 | O | Y |
| — Bye Week — | ||||||
| Sat 12/13 | Army vs Navy | +6.0L16–17 | 38.0 | L16–17 | U | Y |
| Sat 12/27 | Army vs UConn | -5.5W41–16 | 41.5 | W41–16 | O | Y |
Air Force 2025 Schedule
Air Force's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Air Force vs Bucknell | -31.0W49–13 | 54.5 | W49–13 | O | Y |
| — Bye Week — | ||||||
| Sat 9/13 | Air Force at Utah State | -4.0L30–49 | 51.5 | L30–49 | O | N |
| Sat 9/20 | Air Force vs Boise State | +10.5L37–49 | 51.5 | L37–49 | O | N |
| Sat 9/27 | Air Force vs Hawai'i | -7.0L35–44 | 52.5 | L35–44 | O | N |
| Sat 10/4 | Air Force at Navy | +13.5L31–34 | 50.5 | L31–34 | O | Y |
| Sat 10/11 | Air Force at UNLV | +7.0L48–51 | 65.5 | L48–51 | O | Y |
| Sat 10/18 | Air Force vs Wyoming | -4.0W24–21 | 56.5 | W24–21 | U | N |
| — Bye Week — | ||||||
| Sat 11/1 | Air Force vs Army | +1.5L17–20 | 48.5 | L17–20 | U | N |
| Sat 11/8 | Air Force at San José State | +6.0W26–16 | 67.5 | W26–16 | U | Y |
| Sat 11/15 | Air Force at UConn | +7.5L16–26 | 64.5 | L16–26 | U | N |
| Sat 11/22 | Air Force vs New Mexico | +3.5L3–20 | 53.5 | L3–20 | U | N |
| Fri 11/28 | Air Force at Colorado State | -2.5W42–21 | 47.5 | W42–21 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 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
→ Army
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 · 2025 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?
Army Edge
Army +0.17
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?
Army Edge
Army +3.2
GC Edge (season-to-date)
Teams with this edge win 49.4% of games historically
Based on 7 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Army, 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
Army
Jeff Monken #1
81–57 (59%)
· Yr 12 at school
OC
Cody Worley
Yr 2
#1
DC
Nate Woody
Yr 3
#1
Air Force
Troy Calhoun #1
135–89 (60%)
· Yr 19 at school
OC
Mike Thiessen
Yr 3
#1
DC
Brian Knorr
Yr 3
#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 ✓