Sat, Sep 9 2023
·
Week 2
·
🏟 Carter-Finley Stadium
Raleigh, NC
·
Turf
·
57,583 cap
Notre Dame✈ 574 miSame 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
80.6%
Notre Dame wins
Strong
Game Control
64.9%
Notre Dame wins
Lean
Vegas Spread
Notre Dame -7
O/U 49.5
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → Notre Dame
· 73.9% ATS historically
↓ 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 |
NC State 2023 Schedule
NC State's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/31 | NC State at UConn | -14.5W24–14 | 47.5 | W24–14 | U | N |
| Sat 9/9 | NC State vs Notre Dame | +7.0L24–45 | 49.5 | L24–45 | O | N |
| Sat 9/16 | NC State vs VMI | -42.5W45–7 | 51.0 | W45–7 | O | N |
| Fri 9/22 | NC State at Virginia | -8.5W24–21 | 47.5 | W24–21 | U | N |
| Fri 9/29 | NC State vs Louisville | +3.5L10–13 | 56.5 | L10–13 | U | Y |
| Sat 10/7 | NC State vs Marshall | -6.5W48–41 | 44.0 | W48–41 | O | Y |
| Sat 10/14 | NC State at Duke | +3.5L3–24 | 44.0 | L3–24 | U | N |
| — Bye Week — | ||||||
| Sat 10/28 | NC State vs Clemson | +9.5W24–17 | 44.5 | W24–17 | U | Y |
| Sat 11/4 | NC State vs Miami | +6.5W20–6 | 44.0 | W20–6 | U | Y |
| Sat 11/11 | NC State at Wake Forest | +0.5W26–6 | 42.5 | W26–6 | U | Y |
| Sat 11/18 | NC State at Virginia Tech | +2.5W35–28 | 40.5 | W35–28 | O | Y |
| Sat 11/25 | NC State vs North Carolina | +2.0W39–20 | 55.0 | W39–20 | O | Y |
| Thu 12/28 | NC State vs Kansas State | +3.0L19–28 | 48.5 | L19–28 | U | 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
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 · 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 +3.00
CSS Edge (season-to-date)
Teams with this edge win 80.6% of games historically
Based on 1 game this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Notre Dame Edge
Notre Dame +11.8
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 1 game this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Notre Dame. 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
13–5 (72%)
· Yr 2 at school
OC
Gerad Parker
Yr 1
#1
DC
Al Golden
Yr 2
#1
NC State
Dave Doeren #1
74–55 (58%)
· Yr 11 at school
OC
Robert Anae
Yr 1
#1
DC
Tony Gibson
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 ✓