Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Navy,
while Game Control favors Houston.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Navy wins
Lean
Game Control
58.3%
Houston wins
Lean
Vegas Spread
Houston -3
O/U 51.0
teamrankings
Advanced Stats
PPA + Success Rate agree → Houston
· 73.9% ATS historically
↓ See full breakdown
Houston 2022 Schedule
Houston's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Houston at UTSA | -3.5W37–35 | 61.5 | W37–35 | O | N |
| Sat 9/10 | Houston at Texas Tech | +3.5L30–33 | 62.5 | L30–33 | O | Y |
| Sat 9/17 | Houston vs Kansas | -8.5L30–48 | 58.0 | L30–48 | O | N |
| Sat 9/24 | Houston vs Rice | -17.5W34–27 | 52.5 | W34–27 | O | N |
| Fri 9/30 | Houston vs Tulane | -5.0L24–27 | 52.0 | L24–27 | U | N |
| Fri 10/7 | Houston at Memphis | +1.5W33–32 | 57.5 | W33–32 | O | Y |
| — Bye Week — | ||||||
| Sat 10/22 | Houston at Navy | -3.0W38–20 | 51.0 | W38–20 | O | Y |
| Sat 10/29 | Houston vs South Florida | -17.0W42–27 | 59.0 | W42–27 | O | N |
| Sat 11/5 | Houston at SMU | +3.5L63–77 | 66.0 | L63–77 | O | N |
| Sat 11/12 | Houston vs Temple | -20.0W43–36 | 56.0 | W43–36 | O | N |
| Sat 11/19 | Houston at East Carolina | +6.0W42–3 | 66.5 | W42–3 | U | Y |
| Sat 11/26 | Houston vs Tulsa | -13.0L30–37 | 66.5 | L30–37 | O | N |
| Fri 12/23 | Houston vs Louisiana | -5.5W23–16 | 56.5 | W23–16 | U | 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
Both Agree
→ Houston
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 +0.57
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 5 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Houston Edge
Houston +6.9
GC Edge (season-to-date)
Teams with this edge win 58.3% of games historically
Based on 6 games this season
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
Houston
Dana Holgorsen #1
19–15 (56%)
· Yr 4 at school
OC
Shannon Dawson
Yr 2
#1
DC
Doug Belk
Yr 2
#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: 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 ✓