Sat, Oct 10 2026
·
Week 6
·
🏟 Notre Dame Stadium
Notre Dame, IN
·
Turf
·
80,795 cap
Stanford✈ 1,922 mi+3 hr TZ
Preseason projection — This game has not yet been played and 2026 in-season data is not yet available.
Edges are based on 2025 full-season performance.
Confidence will increase once in-season games are logged.
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
71.6%
Notre Dame wins
Solid
Game Control
76%
Notre Dame wins
Strong
Advanced Stats
All 4 factors agree → Notre Dame
· 83.1% ATS historically when all four align
↓ See full breakdown
Stanford 2026 Schedule
Stanford's 2026 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/29 | Stanford vs Hawai'i | +5.5 | — | — | — | — |
| Fri 9/4 | Stanford vs Miami | +28 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 9/19 | Stanford at Duke | +16 | — | — | — | — |
| Sat 9/26 | Stanford vs Georgia Tech | +11 | — | — | — | — |
| Sat 10/3 | Stanford at Wake Forest | +16 | — | — | — | — |
| Sat 10/10 | Stanford at Notre Dame | +31.5 | — | — | — | — |
| Sat 10/17 | Stanford vs Elon | -15 | — | — | — | — |
| Fri 10/23 | Stanford vs NC State | +11.5 | — | — | — | — |
| Sat 10/31 | Stanford at Louisville | +22.5 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 11/14 | Stanford at Virginia Tech | +9 | — | — | — | — |
| Sat 11/21 | Stanford at California | +15 | — | — | — | — |
| Sat 11/28 | Stanford vs SMU | +20.5 | — | — | — | — |
Notre Dame 2026 Schedule
Notre Dame's 2026 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sun 9/6 | Notre Dame vs Wisconsin | -16.5 | 46.5 | — | — | — |
| Sat 9/12 | Notre Dame vs Rice | -35 | — | — | — | — |
| Sat 9/19 | Notre Dame vs Michigan State | -29.5 | — | — | — | — |
| Sat 9/26 | Notre Dame at Purdue | -28.5 | — | — | — | — |
| Sat 10/3 | Notre Dame at North Carolina | -27 | — | — | — | — |
| Sat 10/10 | Notre Dame vs Stanford | -31.5 | — | — | — | — |
| Sat 10/17 | Notre Dame at BYU | -10.5 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 10/31 | Notre Dame vs Navy | -26.5 | — | — | — | — |
| Sat 11/7 | Notre Dame vs Miami | -6.5 | — | — | — | — |
| Sat 11/14 | Notre Dame vs Boston College | -31 | — | — | — | — |
| Sat 11/21 | Notre Dame vs SMU | -14 | — | — | — | — |
| Sat 11/28 | Notre Dame at Syracuse | -29.5 | — | — | — | — |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season (prior year)
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 · 2025 season (prior year — 2026 data not yet available) ·
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 +1.17
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 2025 full season · preseason estimate
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Notre Dame Edge
Notre Dame +47.3
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 2025 full season · preseason estimate
Coaching Matchup
Stanford
Tavita Pritchard #77
0–0 (0%)
· Yr 1 at school
OC
Terry Heffernan
Yr 1
#67
DC
Kris Richard
Yr 1
#68
Notre Dame
Marcus Freeman #3
43–12 (78%)
· Yr 5 at school
OC
Mike Denbrock
Yr 3
#1
DC
Chris Ash
Yr 2
#42
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 ✓