Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Navy,
while Game Control favors Temple.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
71.6%
Navy wins
Solid
Game Control
58.3%
Temple wins
Lean
Vegas Spread
Navy -14.5
O/U 41.5
teamrankings
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
Temple 2022 Schedule
Temple's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/2 | Temple at Duke | +9.5L0–30 | 51.5 | L0–30 | U | N |
| Sat 9/10 | Temple vs Lafayette | -13.5W30–14 | 39.5 | W30–14 | O | Y |
| Sat 9/17 | Temple vs Rutgers | +18.0L14–16 | 42.5 | L14–16 | U | Y |
| Sat 9/24 | Temple vs Massachusetts | -10.0W28–0 | 44.0 | W28–0 | U | Y |
| Sat 10/1 | Temple at Memphis | +18.5L3–24 | 50.0 | L3–24 | U | N |
| — Bye Week — | ||||||
| Thu 10/13 | Temple at UCF | +23.5L13–70 | 46.5 | L13–70 | O | N |
| Fri 10/21 | Temple vs Tulsa | +13.5L16–27 | 53.5 | L16–27 | U | Y |
| Sat 10/29 | Temple at Navy | +14.5L20–27 | 41.5 | L20–27 | O | Y |
| Sat 11/5 | Temple vs South Florida | +3.5W54–28 | 49.0 | W54–28 | O | Y |
| Sat 11/12 | Temple at Houston | +20.0L36–43 | 56.0 | L36–43 | O | Y |
| Sat 11/19 | Temple vs Cincinnati | +17.0L3–23 | 48.5 | L3–23 | U | N |
| Sat 11/26 | Temple vs East Carolina | +9.5L46–49 | 52.0 | L46–49 | 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
Split
Metrics disagree
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?
Navy Edge
Navy +1.17
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 6 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Temple Edge
Temple +8.5
GC Edge (season-to-date)
Teams with this edge win 58.3% of games historically
Based on 7 games this season
Actual Result
CSS Battle
Navy
1 — 0 sequences
✓ Predicted correctly
GC Battle
Navy
88.0 — 5.8 GC score
✗ Predicted incorrectly
Game Result
Navy won by 7
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
Temple
Stan Drayton #1
0–0 (0%)
· Yr 1 at school
OC
Danny Langsdorf
Yr 1
#1
DC
D. J. Eliot
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 ✓