Sun, Nov 26 2023
·
Week 13
·
🏟 Stanford Stadium
Stanford, CA
·
Turf
·
50,424 cap
Notre Dame✈ 1,922 mi-3 hr TZ
Matchup Prediction
Notre Dame
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Notre Dame entering this game.
Momentum Control
61.3%
Notre Dame wins
Lean
Game Control
75.9%
Notre Dame wins
Solid
Vegas Spread
Notre Dame -26.0
O/U 50.5
Bovada
Advanced Stats
All 4 factors agree → Notre Dame
· 83.1% ATS historically when all four align
↓ See full breakdown
Notre Dame 2023 Schedule
Notre Dame's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/26 | Notre Dame vs Navy | -20.5W42–3 | 49.0 | W42–3 | U | Y |
| Sat 9/2 | Notre Dame vs Tennessee State | -48.5W56–3 | 55.0 | W56–3 | O | Y |
| Sat 9/9 | Notre Dame at NC State | -7.0W45–24 | 49.5 | W45–24 | O | Y |
| Sat 9/16 | Notre Dame vs Central Michigan | -34.5W41–17 | 51.5 | W41–17 | O | N |
| Sat 9/23 | Notre Dame vs Ohio State | +3.0L14–17 | 55.5 | L14–17 | U | Y |
| Sat 9/30 | Notre Dame at Duke | -5.5W21–14 | 52.5 | W21–14 | U | Y |
| Sat 10/7 | Notre Dame at Louisville | -6.5L20–33 | 53.0 | L20–33 | U | N |
| Sat 10/14 | Notre Dame vs USC | -3.0W48–20 | 61.0 | W48–20 | O | Y |
| — Bye Week — | ||||||
| Sat 10/28 | Notre Dame vs Pittsburgh | -21.0W58–7 | 45.5 | W58–7 | O | Y |
| Sat 11/4 | Notre Dame at Clemson | -3.0L23–31 | 44.5 | L23–31 | O | N |
| — Bye Week — | ||||||
| Sat 11/18 | Notre Dame vs Wake Forest | -22.5W45–7 | 47.5 | W45–7 | O | Y |
| Sat 11/25 | Notre Dame at Stanford | -26.0W56–23 | 50.5 | W56–23 | O | Y |
| Fri 12/29 | Notre Dame vs Oregon State | -5.5W40–8 | 40.5 | W40–8 | O | Y |
Stanford 2023 Schedule
Stanford's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/1 | Stanford at Hawai'i | -2.0W37–24 | 54.0 | W37–24 | O | Y |
| Sat 9/9 | Stanford at USC | +28.5L10–56 | 70.5 | L10–56 | U | N |
| Sat 9/16 | Stanford vs Sacramento State | -7.0L23–30 | 60.5 | L23–30 | U | N |
| Sat 9/23 | Stanford vs Arizona | +13.0L20–21 | 60.0 | L20–21 | U | Y |
| Sat 9/30 | Stanford vs Oregon | +27.0L6–42 | 59.5 | L6–42 | U | N |
| — Bye Week — | ||||||
| Fri 10/13 | Stanford at Colorado | +13.0W46–43 | 59.0 | W46–43 | O | Y |
| Sat 10/21 | Stanford vs UCLA | +17.0L7–42 | 52.0 | L7–42 | U | N |
| Sat 10/28 | Stanford vs Washington | +27.5L33–42 | 62.0 | L33–42 | O | Y |
| Sat 11/4 | Stanford at Washington State | +13.0W10–7 | 59.5 | W10–7 | U | Y |
| Sat 11/11 | Stanford at Oregon State | +21.5L17–62 | 51.5 | L17–62 | O | N |
| Sat 11/18 | Stanford vs California | +6.5L15–27 | 52.5 | L15–27 | U | N |
| Sat 11/25 | Stanford vs Notre Dame | +26.0L23–56 | 50.5 | L23–56 | O | N |
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
All 4 Agree
→ Notre Dame
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Notre Dame
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Notre Dame
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?
Notre Dame Edge
Notre Dame +0.50
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 10 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Notre Dame Edge
Notre Dame +43.2
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 11 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Notre Dame 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
Notre Dame
Marcus Freeman #1
13–5 (72%)
· Yr 2 at school
OC
Gerad Parker
Yr 1
#1
DC
Al Golden
Yr 2
#1
Stanford
Troy Taylor #1
1–2 (33%)
· Yr 1 at school
OC
Troy Taylor
Yr 1
#1
DC
Bobby April III
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: 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 ✓