Sat, Nov 19 2022
·
Week 12
·
🏟 California Memorial Stadium
Berkeley, CA
·
Turf
·
62,717 cap
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Stanford,
while Game Control favors California.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
61.3%
Stanford wins
Lean
Game Control
58.6%
California wins
Lean
Vegas Spread
California -5
O/U 46.0
teamrankings
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
Stanford 2022 Schedule
Stanford's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Stanford vs Colgate | -40.0W41–10 | 51.5 | W41–10 | U | N |
| Sat 9/10 | Stanford vs USC | +9.5L28–41 | 66.5 | L28–41 | O | N |
| — Bye Week — | ||||||
| Sat 9/24 | Stanford at Washington | +14.0L22–40 | 62.5 | L22–40 | U | N |
| Sat 10/1 | Stanford at Oregon | +17.0L27–45 | 63.0 | L27–45 | O | N |
| Sat 10/8 | Stanford vs Oregon State | +4.5L27–28 | 53.0 | L27–28 | O | Y |
| Sat 10/15 | Stanford at Notre Dame | +16.5W16–14 | 53.5 | W16–14 | U | Y |
| Sat 10/22 | Stanford vs Arizona State | -3.0W15–14 | 52.0 | W15–14 | U | N |
| Sat 10/29 | Stanford at UCLA | +16.5L13–38 | 64.5 | L13–38 | U | N |
| Sat 11/5 | Stanford vs Washington State | +3.0L14–52 | 48.5 | L14–52 | O | N |
| Sat 11/12 | Stanford at Utah | +23.5L7–42 | 54.0 | L7–42 | U | N |
| Sat 11/19 | Stanford at California | +5.0L20–27 | 46.0 | L20–27 | O | N |
| Sat 11/26 | Stanford vs BYU | +6.0L26–35 | 57.5 | L26–35 | O | N |
California 2022 Schedule
California's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | California vs UC Davis | -14.0W34–13 | 44.0 | W34–13 | O | Y |
| Sat 9/10 | California vs UNLV | -12.0W20–14 | 49.5 | W20–14 | U | N |
| Sat 9/17 | California at Notre Dame | +13.5L17–24 | 41.5 | L17–24 | U | Y |
| Sat 9/24 | California vs Arizona | -3.5W49–31 | 50.0 | W49–31 | O | Y |
| Sat 10/1 | California at Washington State | +4.0L9–28 | 52.5 | L9–28 | U | N |
| — Bye Week — | ||||||
| Sat 10/15 | California at Colorado | -15.0L13–20 | 49.0 | L13–20 | U | N |
| Sat 10/22 | California vs Washington | +7.5L21–28 | 54.5 | L21–28 | U | Y |
| Sat 10/29 | California vs Oregon | +16.5L24–42 | 56.5 | L24–42 | O | N |
| Sat 11/5 | California at USC | +21.5L35–41 | 60.5 | L35–41 | O | Y |
| Sat 11/12 | California at Oregon State | +11.5L10–38 | 47.0 | L10–38 | O | N |
| Sat 11/19 | California vs Stanford | -5.0W27–20 | 46.0 | W27–20 | O | Y |
| Fri 11/25 | California vs UCLA | +11.5L28–35 | 62.5 | L28–35 | O | Y |
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?
Stanford Edge
Stanford +0.11
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 9 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
California Edge
California +7.5
GC Edge (season-to-date)
Teams with this edge win 58.6% of games historically
Based on 10 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
Stanford
David Shaw #1
93–45 (67%)
· Yr 12 at school
OC
Tavita Pritchard
Yr 2
#1
DC
Lance Anderson
Yr 2
#1
California
Justin Wilcox #1
26–28 (48%)
· Yr 6 at school
OC
Bill Musgrave
Yr 2
#1
DC
Peter Sirmon
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 ✓