Sat, Nov 15 2025
·
Week 12
·
🏟 Acrisure Stadium
Pittsburgh, PA
·
Turf
·
68,400 cap
Notre Dame✈ 335 miSame TZ
Matchup Prediction
Pittsburgh
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Pittsburgh entering this game.
Momentum Control
58.4%
Pittsburgh wins
Lean
Game Control
58.6%
Pittsburgh wins
Lean
Vegas Spread
Notre Dame -12.5
O/U 55.5
DraftKings
Advanced Stats
PPA + Success Rate agree → Notre Dame
· 73.9% ATS historically
↓ See full breakdown
Notre Dame 2025 Schedule
Notre Dame's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sun 8/31 | Notre Dame at Miami | -2.5L24–27 | 53.5 | L24–27 | U | N |
| — Bye Week — | ||||||
| Sat 9/13 | Notre Dame vs Texas A&M | -7.5L40–41 | 48.5 | L40–41 | O | N |
| Sat 9/20 | Notre Dame vs Purdue | -24.5W56–30 | 51.5 | W56–30 | O | Y |
| Sat 9/27 | Notre Dame at Arkansas | -5.5W56–13 | 64.5 | W56–13 | O | Y |
| Sat 10/4 | Notre Dame vs Boise State | -21.5W28–7 | 63.5 | W28–7 | U | N |
| Sat 10/11 | Notre Dame vs NC State | -23.5W36–7 | 59.5 | W36–7 | U | Y |
| Sat 10/18 | Notre Dame vs USC | -10.5W34–24 | 60.5 | W34–24 | U | N |
| — Bye Week — | ||||||
| Sat 11/1 | Notre Dame at Boston College | -31.5W25–10 | 55.5 | W25–10 | U | N |
| Sat 11/8 | Notre Dame vs Navy | -30.5W49–10 | 54.5 | W49–10 | O | Y |
| Sat 11/15 | Notre Dame at Pittsburgh | -12.5W37–15 | 55.5 | W37–15 | U | Y |
| Sat 11/22 | Notre Dame vs Syracuse | -36.5W70–7 | 51.5 | W70–7 | O | Y |
| Sat 11/29 | Notre Dame at Stanford | -32.5W49–20 | 50.5 | W49–20 | O | N |
Pittsburgh 2025 Schedule
Pittsburgh's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Pittsburgh vs Duquesne | -39.5W61–9 | 58.5 | W61–9 | O | Y |
| Sat 9/6 | Pittsburgh vs Central Michigan | -21.5W45–17 | 48.5 | W45–17 | O | Y |
| Sat 9/13 | Pittsburgh at West Virginia | -6.5L24–31 | 54.5 | L24–31 | O | N |
| — Bye Week — | ||||||
| Sat 9/27 | Pittsburgh vs Louisville | +3.0L27–34 | 53.5 | L27–34 | O | N |
| Sat 10/4 | Pittsburgh vs Boston College | -6.5W48–7 | 54.5 | W48–7 | O | Y |
| Sat 10/11 | Pittsburgh at Florida State | +10.5W34–31 | 56.5 | W34–31 | O | Y |
| Sat 10/18 | Pittsburgh at Syracuse | -9.5W30–13 | 54.5 | W30–13 | U | Y |
| Sat 10/25 | Pittsburgh vs NC State | -5.5W53–34 | 52.5 | W53–34 | O | Y |
| Sat 11/1 | Pittsburgh at Stanford | -13.5W35–20 | 51.5 | W35–20 | O | Y |
| — Bye Week — | ||||||
| Sat 11/15 | Pittsburgh vs Notre Dame | +12.5L15–37 | 55.5 | L15–37 | U | N |
| Sat 11/22 | Pittsburgh at Georgia Tech | +2.5W42–28 | 61.5 | W42–28 | O | Y |
| Sat 11/29 | Pittsburgh vs Miami | +6.5L7–38 | 49.5 | L7–38 | U | N |
| Sat 12/27 | Pittsburgh vs East Carolina | -13.5L17–23 | 51.5 | L17–23 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
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 ·
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?
Pittsburgh Edge
Pittsburgh +0.71
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 8 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Pittsburgh Edge
Pittsburgh +5.9
GC Edge (season-to-date)
Teams with this edge win 58.6% of games historically
Based on 9 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Pittsburgh. Teams with this edge profile have covered 50.3% historically — essentially a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Notre Dame
Marcus Freeman #1
33–10 (77%)
· Yr 4 at school
OC
Mike Denbrock
Yr 2
#1
DC
Chris Ash
Yr 1
#1
Pittsburgh
Pat Narduzzi #1
72–55 (57%)
· Yr 11 at school
OC
Kade Bell
Yr 2
#1
DC
Randy Bates
Yr 3
#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 ✓