Sat, Nov 5 2022
·
Week 10
·
🏟 Stanford Stadium
Stanford, CA
·
Turf
·
50,424 cap
Washington State✈ 691 miSame TZ
Matchup Prediction
Washington State
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Washington State entering this game.
Momentum Control
61.3%
Washington State wins
Lean
Game Control
64.9%
Washington State wins
Lean
Vegas Spread
Washington State -3
O/U 48.5
teamrankings
Advanced Stats
All 4 factors agree → Washington State
· 83.1% ATS historically when all four align
↓ See full breakdown
Washington State 2022 Schedule
Washington State's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Washington State vs Idaho | -28.5W24–17 | 63.5 | W24–17 | U | N |
| Sat 9/10 | Washington State at Wisconsin | +17.5W17–14 | 48.5 | W17–14 | U | Y |
| Sat 9/17 | Washington State vs Colorado State | -17.0W38–7 | 51.5 | W38–7 | U | Y |
| Sat 9/24 | Washington State vs Oregon | +6.0L41–44 | 57.0 | L41–44 | O | Y |
| Sat 10/1 | Washington State vs California | -4.0W28–9 | 52.5 | W28–9 | U | Y |
| Sat 10/8 | Washington State at USC | +12.5L14–30 | 64.5 | L14–30 | U | N |
| Sat 10/15 | Washington State at Oregon State | +3.0L10–24 | 51.5 | L10–24 | U | N |
| — Bye Week — | ||||||
| Thu 10/27 | Washington State vs Utah | +7.5L17–21 | 56.5 | L17–21 | U | Y |
| Sat 11/5 | Washington State at Stanford | -3.0W52–14 | 48.5 | W52–14 | O | Y |
| Sat 11/12 | Washington State vs Arizona State | -9.5W28–18 | 59.5 | W28–18 | U | Y |
| Sat 11/19 | Washington State at Arizona | -4.0W31–20 | 63.0 | W31–20 | U | Y |
| Sat 11/26 | Washington State vs Washington | +2.0L33–51 | 60.0 | L33–51 | O | N |
| Sat 12/17 | Washington State vs Fresno State | +5.5L6–29 | 54.0 | L6–29 | U | N |
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 |
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
→ Washington State
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Washington State
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Washington State
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?
Washington State Edge
Washington State +0.29
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 7 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Washington State Edge
Washington State +14.7
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 8 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Washington State with a solid GC edge. Teams with this profile have covered 53.0% of the time historically (n=330) — a mild lean.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Washington State
Jake Dickert #1
3–3 (50%)
· Yr 2 at school
OC
Eric Morris
Yr 1
#1
DC
Brian Ward
Yr 1
#1
Stanford
David Shaw #1
93–45 (67%)
· Yr 12 at school
OC
Tavita Pritchard
Yr 2
#1
DC
Lance Anderson
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 ✓