Matchup Prediction
Army
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Army entering this game.
Momentum Control
73.7%
Army wins
Solid
Game Control
75.9%
Army wins
Solid
Vegas Spread
Army -13.5
O/U 50.5
DraftKings
Advanced Stats
PPA + Success Rate agree → Army
· 73.9% ATS historically
↓ See full breakdown
Army 2024 Schedule
Army's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/30 | Army vs Lehigh | -28 | — | — | — | — |
| Sat 9/7 | Army at Florida Atlantic | +1.5W24–7 | 42.5 | W24–7 | U | Y |
| — Bye Week — | ||||||
| Sat 9/21 | Army vs Rice | -7.0W37–14 | 44.0 | W37–14 | O | Y |
| Thu 9/26 | Army at Temple | -11.0W42–14 | 46.5 | W42–14 | O | Y |
| Sat 10/5 | Army at Tulsa | -13.5W49–7 | 50.5 | W49–7 | O | Y |
| Sat 10/12 | Army vs UAB | -27.0W44–10 | 55.5 | W44–10 | U | Y |
| Sat 10/19 | Army vs East Carolina | -17.5W45–28 | 54.0 | W45–28 | O | N |
| — Bye Week — | ||||||
| Sat 11/2 | Army vs Air Force | -18.0W20–3 | 38.5 | W20–3 | U | N |
| Sat 11/9 | Army at North Texas | -6.5W14–3 | 68.0 | W14–3 | U | Y |
| — Bye Week — | ||||||
| Sat 11/23 | Army vs Notre Dame | +14.5L14–49 | 44.5 | L14–49 | O | N |
| Sat 11/30 | Army vs UTSA | -6.5W29–24 | 53.5 | W29–24 | U | N |
| Fri 12/6 | Army vs Tulane | +4.5W35–14 | 46.5 | W35–14 | O | Y |
| Sat 12/14 | Army vs Navy | -6.0 | 39.5 | — | — | — |
| Sat 12/28 | Army vs Louisiana Tech | -15.0W27–6 | 44.5 | W27–6 | U | Y |
Tulsa 2024 Schedule
Tulsa's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/29 | Tulsa vs Northwestern State | -37.5W62–28 | 55.5 | W62–28 | O | N |
| Sat 9/7 | Tulsa at Arkansas State | +9.5L24–28 | 65.5 | L24–28 | U | Y |
| Sat 9/14 | Tulsa vs Oklahoma State | +17.5L10–45 | 62.5 | L10–45 | U | N |
| Sat 9/21 | Tulsa at Louisiana Tech | +3.0W23–20 | 56.5 | W23–20 | U | Y |
| Sat 9/28 | Tulsa at North Texas | +7.0L20–52 | 65.5 | L20–52 | O | N |
| Sat 10/5 | Tulsa vs Army | +13.5L7–49 | 50.5 | L7–49 | O | N |
| — Bye Week — | ||||||
| Sat 10/19 | Tulsa at Temple | +3.5L10–20 | 51.5 | L10–20 | U | N |
| Sat 10/26 | Tulsa vs UTSA | +9.5W46–45 | 52.5 | W46–45 | O | Y |
| Sat 11/2 | Tulsa at UAB | +2.5L21–59 | 57.5 | L21–59 | O | N |
| — Bye Week — | ||||||
| Thu 11/14 | Tulsa vs East Carolina | +16.0L31–38 | 63.5 | L31–38 | O | Y |
| Sat 11/23 | Tulsa at South Florida | +17.5L30–63 | 60.0 | L30–63 | O | N |
| Sat 11/30 | Tulsa vs Florida Atlantic | +2.5L16–63 | 57.5 | L16–63 | O | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 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 · 2024 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 +1.17
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Army Edge
Army +48.9
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 5 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Army 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
Army
Jeff Monken #1
70–55 (56%)
· Yr 11 at school
OC
Cody Worley
Yr 1
#1
DC
Nate Woody
Yr 3
#1
Tulsa
Kevin Wilson #1
4–8 (33%)
· Yr 2 at school
OC
Steve Spurrier Jr.
Yr 2
#1
DC
Chris Polizzi
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: 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 ✓