Matchup Prediction
USC
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
USC entering this game.
Momentum Control
71.6%
USC wins
Solid
Game Control
76%
USC wins
Strong
Vegas Spread
USC -21
O/U 69.5
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → Arizona
· 73.9% ATS historically
↓ See full breakdown
Arizona 2023 Schedule
Arizona's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Arizona vs Northern Arizona | -28.5W38–3 | 61.0 | W38–3 | U | Y |
| Sat 9/9 | Arizona at Mississippi State | +9.0L24–31 | 60.0 | L24–31 | U | Y |
| Sat 9/16 | Arizona vs UTEP | -18.0W31–10 | 57.0 | W31–10 | U | Y |
| Sat 9/23 | Arizona at Stanford | -13.0W21–20 | 60.0 | W21–20 | U | N |
| Sat 9/30 | Arizona vs Washington | +20.0L24–31 | 66.0 | L24–31 | U | Y |
| Sat 10/7 | Arizona at USC | +21.0L41–43 | 69.5 | L41–43 | O | Y |
| Sat 10/14 | Arizona at Washington State | +7.5W44–6 | 57.5 | W44–6 | U | Y |
| — Bye Week — | ||||||
| Sat 10/28 | Arizona vs Oregon State | +3.0W27–24 | 57.5 | W27–24 | U | Y |
| Sat 11/4 | Arizona vs UCLA | +2.5W27–10 | 50.0 | W27–10 | U | Y |
| Sat 11/11 | Arizona at Colorado | -6.0W34–31 | 55.5 | W34–31 | O | N |
| Sat 11/18 | Arizona vs Utah | -2.5W42–18 | 45.5 | W42–18 | O | Y |
| Sat 11/25 | Arizona at Arizona State | -12.5W59–23 | 48.5 | W59–23 | O | Y |
| Thu 12/28 | Arizona vs Oklahoma | -2.5W38–24 | 59.5 | W38–24 | O | Y |
USC 2023 Schedule
USC's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/26 | USC vs San José State | -31.5W56–28 | 66.0 | W56–28 | O | N |
| Sat 9/2 | USC vs Nevada | -37.5W66–14 | 63.5 | W66–14 | O | Y |
| Sat 9/9 | USC vs Stanford | -28.5W56–10 | 70.5 | W56–10 | U | Y |
| — Bye Week — | ||||||
| Sat 9/23 | USC at Arizona State | -34.5W42–28 | 62.0 | W42–28 | O | N |
| Sat 9/30 | USC at Colorado | -22.0W48–41 | 74.5 | W48–41 | O | N |
| Sat 10/7 | USC vs Arizona | -21.0W43–41 | 69.5 | W43–41 | O | N |
| Sat 10/14 | USC at Notre Dame | +3.0L20–48 | 61.0 | L20–48 | O | N |
| Sat 10/21 | USC vs Utah | -7.5L32–34 | 51.5 | L32–34 | O | N |
| Sat 10/28 | USC at California | -10.5W50–49 | 67.5 | W50–49 | O | N |
| Sat 11/4 | USC vs Washington | +3.0L42–52 | 76.0 | L42–52 | O | N |
| Sat 11/11 | USC at Oregon | +12.5L27–36 | 78.5 | L27–36 | U | Y |
| Sat 11/18 | USC vs UCLA | -6.0L20–38 | 65.5 | L20–38 | U | N |
| Wed 12/27 | USC vs Louisville | +4.5W42–28 | 58.0 | W42–28 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2023 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
→ Arizona
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 · 2023 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?
USC Edge
USC +1.55
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 5 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
USC Edge
USC +46.5
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 5 games this season
Actual Result
CSS Battle
Arizona
1 — 2 sequences
✗ Predicted incorrectly
GC Battle
Arizona
22.6 — 51.9 GC score
✗ Predicted incorrectly
Game Result
USC won by 2
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on USC 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
Arizona
Jedd Fisch #1
8–19 (30%)
· Yr 3 at school
OC
Brennan Carroll
Yr 3
#1
DC
Johnny Nansen
Yr 2
#1
USC
Lincoln Riley #1
14–3 (82%)
· Yr 2 at school
OC
Josh Henson
Yr 2
#1
DC
Alex Grinch
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 ✓