Matchup Prediction
USC
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
USC entering this game.
Momentum Control
78.1%
USC wins
Strong
Game Control
76%
USC wins
Strong
Vegas Spread
USC -17
O/U 53.0
teamrankings
Advanced Stats
All 4 factors agree → USC
· 83.1% ATS historically when all four align
↓ See full breakdown
Stanford 2021 Schedule
Stanford's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Stanford vs Kansas State | +3.0L7–24 | 54.5 | L7–24 | U | N |
| Sat 9/11 | Stanford at USC | +17.0W42–28 | 53.0 | W42–28 | O | Y |
| Sat 9/18 | Stanford at Vanderbilt | -13.0W41–23 | 49.0 | W41–23 | O | Y |
| Sat 9/25 | Stanford vs UCLA | +4.0L24–35 | 60.5 | L24–35 | U | N |
| Sat 10/2 | Stanford vs Oregon | +8.5W31–24 | 57.5 | W31–24 | U | Y |
| Fri 10/8 | Stanford at Arizona State | +13.5L10–28 | 53.5 | L10–28 | U | N |
| Sat 10/16 | Stanford at Washington State | +1.0L31–34 | 53.0 | L31–34 | O | N |
| — Bye Week — | ||||||
| Sat 10/30 | Stanford vs Washington | -2.5L13–20 | 45.5 | L13–20 | U | N |
| Fri 11/5 | Stanford vs Utah | +10.0L7–52 | 52.0 | L7–52 | O | N |
| Sat 11/13 | Stanford at Oregon State | +12.5L14–35 | 56.5 | L14–35 | U | N |
| Sat 11/20 | Stanford vs California | +2.5L11–41 | 46.0 | L11–41 | O | N |
| Sat 11/27 | Stanford vs Notre Dame | +20.5L14–45 | 53.0 | L14–45 | O | N |
USC 2021 Schedule
USC's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | USC vs San José State | -13.5W30–7 | 61.0 | W30–7 | U | Y |
| Sat 9/11 | USC vs Stanford | -17.0L28–42 | 53.0 | L28–42 | O | N |
| Sat 9/18 | USC at Washington State | -7.0W45–14 | 61.0 | W45–14 | U | Y |
| Sat 9/25 | USC vs Oregon State | -11.0L27–45 | 62.5 | L27–45 | O | N |
| Sat 10/2 | USC at Colorado | -9.0W37–14 | 50.5 | W37–14 | O | Y |
| Sat 10/9 | USC vs Utah | -3.0L26–42 | 52.5 | L26–42 | O | N |
| — Bye Week — | ||||||
| Sat 10/23 | USC at Notre Dame | +8.0L16–31 | 59.5 | L16–31 | U | N |
| Sat 10/30 | USC vs Arizona | -22.0W41–34 | 55.5 | W41–34 | O | N |
| Sat 11/6 | USC at Arizona State | +10.0L16–31 | 61.0 | L16–31 | U | N |
| Sat 11/13 | USC at California | -2.0 | 52.5 | — | — | — |
| Sat 11/20 | USC vs UCLA | +4.5L33–62 | 66.5 | L33–62 | O | N |
| Sat 11/27 | USC vs BYU | +8.5L31–35 | 65.5 | L31–35 | O | Y |
| Sat 12/4 | USC at California | +4.5L14–24 | 57.5 | L14–24 | U | 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
→ USC
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ USC
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ USC
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?
USC Edge
USC +2.00
CSS Edge (season-to-date)
Teams with this edge win 78.1% of games historically
Based on 1 game this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
USC Edge
USC +88.8
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 1 game this season
Actual Result
CSS Battle
USC
2 — 1 sequences
✓ Predicted correctly
GC Battle
Stanford
27.6 — 59.6 GC score
✗ Predicted incorrectly
Game Result
Stanford won by 14
✗ Model missed 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
Stanford
David Shaw #1
92–37 (71%)
· Yr 11 at school
OC
Tavita Pritchard
Yr 1
#1
DC
Lance Anderson
Yr 1
#1
USC
Donte Williams #1
1–0 (100%)
· Yr 1 at school
OC
Graham Harrell
Yr 1
#1
DC
Todd Orlando
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 ✓