Pittsburgh at West Virginia Week 3 College Football Matchup Pittsburgh at West Virginia Matchup - Week 3
Sat, Sep 16 2023 · Week 3 · 🏟 Mountaineer Field at Milan Puskar Stadium Morgantown, WV · Turf · 60,000 cap
6 17
Final
📊 Punt & Rally Projection
Pittsburgh
20
West Virginia
31
P&R Line West Virginia -11
P&R Total O/U 50.5
Confidence 86 High
Vegas West Virginia -2.5 · O/U 48.0
Matchup Prediction
Pittsburgh has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor Pittsburgh entering this game.
Momentum Control
73.7%
Pittsburgh wins
Solid
Game Control
58.3%
Pittsburgh wins
Lean
Vegas Spread
West Virginia -2.5
O/U 48.0
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → West Virginia · 73.9% ATS historically
↓ See full breakdown
🏠 West Virginia 2nd straight Home Game
Pittsburgh 2023 Schedule
Pittsburgh's 2023 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/2Pittsburgh vs Wofford-37.5W45–749.5W45–7OY
Sat 9/9Pittsburgh vs Cincinnati-6.5L21–2744.5L21–27ON
Sat 9/16Pittsburgh at West Virginia+2.5L6–1748.0L6–17UN
Sat 9/23Pittsburgh vs North Carolina+7.0L24–4149.5L24–41ON
Sat 9/30Pittsburgh at Virginia Tech-3.0L21–3840.0L21–38ON
— Bye Week —
Sat 10/14Pittsburgh vs Louisville+7.5W38–2144.5W38–21OY
Sat 10/21Pittsburgh at Wake Forest-3.0L17–2145.0L17–21UN
Sat 10/28Pittsburgh at Notre Dame+21.0L7–5845.5L7–58ON
Sat 11/4Pittsburgh vs Florida State+21.5L7–2450.0L7–24UY
Sat 11/11Pittsburgh vs Syracuse-4.5L13–2837.5L13–28ON
Thu 11/16Pittsburgh vs Boston College-1.0W24–1647.0W24–16UY
Sat 11/25Pittsburgh at Duke+4.5L19–3040.5L19–30ON
West Virginia 2023 Schedule
West Virginia's 2023 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/2West Virginia at Penn State+21.0L15–3848.0L15–38ON
Sat 9/9West Virginia vs Duquesne-38.5W56–1755.5W56–17OY
Sat 9/16West Virginia vs Pittsburgh-2.5W17–648.0W17–6UY
Sat 9/23West Virginia vs Texas Tech+6.0W20–1353.5W20–13UY
Sat 9/30West Virginia at TCU+14.0W24–2152.0W24–21UY
— Bye Week —
Thu 10/12West Virginia at Houston-3.0L39–4149.5L39–41ON
Sat 10/21West Virginia vs Oklahoma State-3.0L34–4848.0L34–48ON
Sat 10/28West Virginia at UCF+6.5W41–2859.5W41–28OY
Sat 11/4West Virginia vs BYU-13.0W37–748.5W37–7UY
Sat 11/11West Virginia at Oklahoma+13.5L20–5959.5L20–59ON
Sat 11/18West Virginia vs Cincinnati-4.5W42–2152.5W42–21OY
Sat 11/25West Virginia at Baylor-6.5W34–3153.5W34–31ON
Wed 12/27West Virginia vs North Carolina-4.5W30–1062.0W30–10UY
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2023 season
West Virginia PPA Edge
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
→ West Virginia
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Pittsburgh #119
+0.279
West Virginia #35
+0.383
West Virginia Edge
PPA Passing
Pass efficiency edge · Strong predictor
Pittsburgh #109
+0.414
West Virginia #55
+0.590
West Virginia Edge
Havoc Total
Def. disruption rate · Strong predictor
Pittsburgh #36
0.178
West Virginia #18
0.188
TFLs, sacks, PBUs, forced fumbles — higher is better
West Virginia Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Pittsburgh #98
+7.627
West Virginia #54
+7.442
Pittsburgh Edge
Success Rate
Play consistency edge · Solid predictor
Pittsburgh #113
+0.792
West Virginia #37
+0.845
West Virginia Edge
Field Position
Avg start (lower=better) · Solid predictor
Pittsburgh #121
73.3
West Virginia #18
68.8
Avg yards from own endzone to average start — lower is better · longer bar = better field position
West Virginia Edge
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
Pittsburgh Rated Higher
Overall Power Rating
Pittsburgh
9.1
West Virginia
1.3
Offense Rating
Pittsburgh
19.3
West Virginia
17.8
Defense Rating (lower = better defense)
Pittsburgh
10.2
West Virginia
16.5
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? Pittsburgh Edge
Avg sequences created per game
Pittsburgh #108
1.00
West Virginia #41
0.00
Avg sequences allowed per game (lower is better)
Pittsburgh #54
2.00
West Virginia #65
2.00
Pittsburgh +1.00
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 1 game this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Pittsburgh Edge
Avg GC score per game (offense)
Pittsburgh #1
45.1
West Virginia #1
35.8
Avg GC score allowed per game (lower is better)
Pittsburgh #102
46.2
West Virginia #37
55.2
Pittsburgh +9.4
GC Edge (season-to-date)
Teams with this edge win 58.3% of games historically
Based on 2 games this season
Actual Result
CSS Battle
West Virginia
1 — 0 sequences
✗ Predicted incorrectly
GC Battle
West Virginia
50.9 — 20.4 GC score
✗ Predicted incorrectly
Game Result
West Virginia won by 11
✗ Model missed it
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
Pittsburgh
Pat Narduzzi #1
63–43 (59%) · Yr 9 at school
OC Frank Cignetti Jr. Yr 2 #1
DC Randy Bates Yr 3 #1
Staff Rating
0.00 #1
West Virginia
Neal Brown #1
24–26 (48%) · Yr 5 at school
OC Chad Scott Yr 1 #1
DC ShaDon Brown Yr 3 #1
Staff Rating
0.00 #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