Sun, Oct 17 2021
·
Week 7
·
🏟 Husky Stadium
Seattle, WA
·
Turf
·
70,500 cap
UCLA✈ 956 miSame TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Washington,
while Game Control favors UCLA.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Washington wins
Lean
Game Control
58.3%
UCLA wins
Lean
Vegas Spread
Washington -1.5
O/U 55.5
teamrankings
Advanced Stats
All 4 factors agree → UCLA
· 83.1% ATS historically when all four align
↓ See full breakdown
UCLA 2021 Schedule
UCLA's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/28 | UCLA vs Hawai'i | -17.5W44–10 | 67.0 | W44–10 | U | Y |
| Sat 9/4 | UCLA vs LSU | +2.0W38–27 | 64.0 | W38–27 | O | Y |
| — Bye Week — | ||||||
| Sat 9/18 | UCLA vs Fresno State | -11.0L37–40 | 64.0 | L37–40 | O | N |
| Sat 9/25 | UCLA at Stanford | -4.0W35–24 | 60.5 | W35–24 | U | Y |
| Sat 10/2 | UCLA vs Arizona State | -3.0L23–42 | 56.5 | L23–42 | O | N |
| Sat 10/9 | UCLA at Arizona | -16.0W34–16 | 60.0 | W34–16 | U | Y |
| Sat 10/16 | UCLA at Washington | +1.5W24–17 | 55.5 | W24–17 | U | Y |
| Sat 10/23 | UCLA vs Oregon | -1.0L31–34 | 62.5 | L31–34 | O | N |
| Sat 10/30 | UCLA at Utah | +6.0L24–44 | 60.5 | L24–44 | O | N |
| — Bye Week — | ||||||
| Sat 11/13 | UCLA vs Colorado | -18.0W44–20 | 57.5 | W44–20 | O | Y |
| Sat 11/20 | UCLA at USC | -4.5W62–33 | 66.5 | W62–33 | O | Y |
| Sat 11/27 | UCLA vs California | -6.5W42–14 | 58.5 | W42–14 | U | Y |
| Tue 12/28 | UCLA vs NC State | +2.0 | 60.0 | — | — | — |
Washington 2021 Schedule
Washington's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Washington vs Montana | -22.5L7–13 | 54.0 | L7–13 | U | N |
| Sat 9/11 | Washington at Michigan | +6.5L10–31 | 47.5 | L10–31 | U | N |
| Sat 9/18 | Washington vs Arkansas State | -17.5W52–3 | 58.5 | W52–3 | U | Y |
| Sat 9/25 | Washington vs California | -7.5W31–24 | 47.5 | W31–24 | O | N |
| Sat 10/2 | Washington at Oregon State | +2.5L24–27 | 57.5 | L24–27 | U | N |
| — Bye Week — | ||||||
| Sat 10/16 | Washington vs UCLA | -1.5L17–24 | 55.5 | L17–24 | U | N |
| Fri 10/22 | Washington at Arizona | -17.5W21–16 | 45.5 | W21–16 | U | N |
| Sat 10/30 | Washington at Stanford | +2.5W20–13 | 45.5 | W20–13 | U | Y |
| Sat 11/6 | Washington vs Oregon | +7.0L16–26 | 48.0 | L16–26 | U | N |
| Sat 11/13 | Washington vs Arizona State | +6.0L30–35 | 45.5 | L30–35 | O | Y |
| Sat 11/20 | Washington at Colorado | -6.5L17–20 | 43.0 | L17–20 | U | N |
| Fri 11/26 | Washington vs Washington State | -1.0L13–40 | 45.0 | L13–40 | O | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2021 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ UCLA
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ UCLA
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ UCLA
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 · 2021 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 Edge
Washington +0.33
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
UCLA Edge
UCLA +7.5
GC Edge (season-to-date)
Teams with this edge win 58.3% of games historically
Based on 5 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
UCLA
Chip Kelly #1
12–22 (35%)
· Yr 4 at school
OC
Justin Frye
Yr 1
#1
DC
Jerry Azzinaro
Yr 1
#1
Washington
Jimmy Lake #1
4–3 (57%)
· Yr 2 at school
OC
John Donovan
Yr 1
#1
DC
Ikaika Malloe
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: 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 ✓