Matchup Prediction
Toss-up — no clear edge
Neither metric shows a meaningful pre-game edge in this matchup.
Momentum Control
58.4%
—
Lean
Game Control
75.9%
Air Force wins
Solid
Vegas Spread
Air Force -10
O/U 50.0
teamrankings
Advanced Stats
All 4 factors agree → Air Force
· 83.1% ATS historically when all four align
↓ See full breakdown
Air Force 2022 Schedule
Air Force's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Air Force vs Northern Iowa | -14.5W48–17 | 46.5 | W48–17 | O | Y |
| Sat 9/10 | Air Force vs Colorado | -17.5W41–10 | 50.0 | W41–10 | O | Y |
| Fri 9/16 | Air Force at Wyoming | -16.5L14–17 | 47.0 | L14–17 | U | N |
| Fri 9/23 | Air Force vs Nevada | -24.0W48–20 | 47.0 | W48–20 | O | Y |
| Sat 10/1 | Air Force vs Navy | -14.0W13–10 | 38.0 | W13–10 | U | N |
| Sat 10/8 | Air Force at Utah State | -11.5L27–34 | 54.0 | L27–34 | O | N |
| Sat 10/15 | Air Force at UNLV | -10.0W42–7 | 50.0 | W42–7 | U | Y |
| Sat 10/22 | Air Force vs Boise State | -2.5L14–19 | 46.5 | L14–19 | U | N |
| — Bye Week — | ||||||
| Sat 11/5 | Air Force vs Army | -7.0W13–7 | 40.5 | W13–7 | U | N |
| Sat 11/12 | Air Force vs New Mexico | -21.0W35–3 | 37.5 | W35–3 | O | Y |
| Sat 11/19 | Air Force vs Colorado State | -22.0W24–12 | 43.0 | W24–12 | U | N |
| Sat 11/26 | Air Force at San Diego State | -2.0W13–3 | 43.5 | W13–3 | U | Y |
| Thu 12/22 | Air Force vs Baylor | +3.5W30–15 | 42.0 | W30–15 | O | Y |
UNLV 2022 Schedule
UNLV's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/27 | UNLV vs Idaho State | -23.0W52–21 | 50.0 | W52–21 | O | Y |
| Sat 9/10 | UNLV at California | +12.0L14–20 | 49.5 | L14–20 | U | Y |
| Sat 9/17 | UNLV vs North Texas | -2.5W58–27 | 62.5 | W58–27 | O | Y |
| Sat 9/24 | UNLV at Utah State | -3.0W34–24 | 61.5 | W34–24 | U | Y |
| Fri 9/30 | UNLV vs New Mexico | -14.0W31–20 | 44.0 | W31–20 | O | N |
| Fri 10/7 | UNLV at San José State | +6.5L7–40 | 51.5 | L7–40 | U | N |
| Sat 10/15 | UNLV vs Air Force | +10.0L7–42 | 50.0 | L7–42 | U | N |
| Sat 10/22 | UNLV at Notre Dame | +26.0L21–44 | 46.5 | L21–44 | O | Y |
| — Bye Week — | ||||||
| Sat 11/5 | UNLV at San Diego State | +5.0L10–14 | 47.0 | L10–14 | U | Y |
| Fri 11/11 | UNLV vs Fresno State | +9.0L30–37 | 61.5 | L30–37 | O | Y |
| Sat 11/19 | UNLV at Hawai'i | -11.0L25–31 | 56.5 | L25–31 | U | N |
| Sat 11/26 | UNLV vs Nevada | -12.5W27–22 | 49.0 | W27–22 | U | 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
All 4 Agree
→ Air Force
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Air Force
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 · 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?
Air Force +0.00
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?
Air Force Edge
Air Force +30.2
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
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
Air Force
Troy Calhoun #1
111–75 (60%)
· Yr 16 at school
OC
Mike Thiessen
Yr 2
#1
DC
Brian Knorr
Yr 1
#1
UNLV
Marcus Arroyo #1
2–16 (11%)
· Yr 3 at school
OC
Nick Holz
Yr 1
#1
DC
Keith Heyward
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 ✓