Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Arizona,
while Game Control favors Utah.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
61.3%
Arizona wins
Lean
Game Control
76%
Utah wins
Strong
Vegas Spread
Utah -17.5
O/U 67.5
teamrankings
Advanced Stats
All 4 factors agree → Utah
· 83.1% ATS historically when all four align
↓ See full breakdown
Arizona 2022 Schedule
Arizona's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Arizona at San Diego State | +6.0W38–20 | 46.5 | W38–20 | O | Y |
| Sat 9/10 | Arizona vs Mississippi State | +11.5L17–39 | 57.5 | L17–39 | U | N |
| Sat 9/17 | Arizona vs North Dakota State | +3.0W31–28 | 49.0 | W31–28 | O | Y |
| Sat 9/24 | Arizona at California | +3.5L31–49 | 50.0 | L31–49 | O | N |
| Sat 10/1 | Arizona vs Colorado | -17.5W43–20 | 57.5 | W43–20 | O | Y |
| Sat 10/8 | Arizona vs Oregon | +13.5L22–49 | 70.5 | L22–49 | O | N |
| Sat 10/15 | Arizona at Washington | +14.5L39–49 | 71.5 | L39–49 | O | Y |
| — Bye Week — | ||||||
| Sat 10/29 | Arizona vs USC | +14.0L37–45 | 74.0 | L37–45 | O | Y |
| Sat 11/5 | Arizona at Utah | +17.5L20–45 | 67.5 | L20–45 | U | N |
| Sat 11/12 | Arizona at UCLA | +19.5W34–28 | 76.5 | W34–28 | U | Y |
| Sat 11/19 | Arizona vs Washington State | +4.0L20–31 | 63.0 | L20–31 | U | N |
| Fri 11/25 | Arizona vs Arizona State | -4.0W38–35 | 66.5 | W38–35 | O | N |
Utah 2022 Schedule
Utah's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Utah at Florida | -2.5L26–29 | 52.0 | L26–29 | O | N |
| Sat 9/10 | Utah vs Southern Utah | -45.5W73–7 | 58.5 | W73–7 | O | Y |
| Sat 9/17 | Utah vs San Diego State | -21.5W35–7 | 48.0 | W35–7 | U | Y |
| Sat 9/24 | Utah at Arizona State | -16.5W34–13 | 54.0 | W34–13 | U | Y |
| Sat 10/1 | Utah vs Oregon State | -10.5W42–16 | 54.0 | W42–16 | O | Y |
| Sat 10/8 | Utah at UCLA | -3.0L32–42 | 64.5 | L32–42 | O | N |
| Sat 10/15 | Utah vs USC | -3.5W43–42 | 65.0 | W43–42 | O | N |
| — Bye Week — | ||||||
| Thu 10/27 | Utah at Washington State | -7.5W21–17 | 56.5 | W21–17 | U | N |
| Sat 11/5 | Utah vs Arizona | -17.5W45–20 | 67.5 | W45–20 | U | Y |
| Sat 11/12 | Utah vs Stanford | -23.5W42–7 | 54.0 | W42–7 | U | Y |
| Sat 11/19 | Utah at Oregon | -2.5L17–20 | 60.0 | L17–20 | U | N |
| Sat 11/26 | Utah at Colorado | -30.0W63–21 | 52.0 | W63–21 | O | Y |
| Fri 12/2 | Utah vs USC | +3.0W47–24 | 67.5 | W47–24 | O | Y |
| Mon 1/2 | Utah vs Penn State | +1.5L21–35 | 55.5 | L21–35 | 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
All 4 Agree
→ Utah
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Utah
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Utah
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?
Arizona Edge
Arizona +0.41
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 8 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Utah Edge
Utah +33.7
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 8 games this season
Actual Result
CSS Battle
Utah
2 — 0 sequences
✗ Predicted incorrectly
GC Battle
Utah
94.1 — 1.7 GC score
✓ Predicted correctly
Game Result
Utah won by 25
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
Arizona
Jedd Fisch #1
1–11 (8%)
· Yr 2 at school
OC
Brennan Carroll
Yr 2
#1
DC
Johnny Nansen
Yr 1
#1
Utah
Kyle Whittingham #1
144–70 (67%)
· Yr 18 at school
OC
Andy Ludwig
Yr 2
#1
DC
Morgan Scalley
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 ✓