West Virginia at Pittsburgh Week 1 College Football Matchup West Virginia at Pittsburgh Matchup - Week 1
Thu, Sep 1 2022 · Week 1 · 🏟 Acrisure Stadium Pittsburgh, PA · Turf · 68,400 cap
31 38
Final
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📊 Punt & Rally Projection
West Virginia
23
PITT -7.5
Pittsburgh
32
P&R Line Pittsburgh -8.5
P&R Total O/U 55
Confidence 86 High
Vegas Pittsburgh -7.5 · O/U 50.0
Matchup Prediction
Toss-up — no clear edge
Neither metric shows a meaningful pre-game edge in this matchup.
Momentum Control
58.4%
Lean
Game Control
50.6%
Toss-up
Vegas Spread
Pittsburgh -7.5
O/U 50.0
teamrankings
Advanced Stats
PPA + Success Rate agree → Pittsburgh · 73.9% ATS historically
↓ See full breakdown
West Virginia 2022 Schedule
West Virginia's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Thu 9/1West Virginia at Pittsburgh+7.5L31–3850.0L31–38OY
Sat 9/10West Virginia vs Kansas-14.0L42–5559.5L42–55ON
Sat 9/17West Virginia vs Towson-41.0W65–758.5W65–7OY
Thu 9/22West Virginia at Virginia Tech-2.0W33–1049.5W33–10UY
Sat 10/1West Virginia at Texas+7.5L20–3861.0L20–38UN
— Bye Week —
Thu 10/13West Virginia vs Baylor+3.0W43–4055.0W43–40OY
Sat 10/22West Virginia at Texas Tech+5.0L10–4865.5L10–48UN
Sat 10/29West Virginia vs TCU+7.0L31–4170.0L31–41ON
Sat 11/5West Virginia at Iowa State+6.5L14–3149.5L14–31UN
Sat 11/12West Virginia vs Oklahoma+8.5W23–2068.5W23–20UY
Sat 11/19West Virginia vs Kansas State+8.0L31–4854.5L31–48ON
Sat 11/26West Virginia at Oklahoma State+5.5W24–1959.5W24–19UY
Pittsburgh 2022 Schedule
Pittsburgh's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Thu 9/1Pittsburgh vs West Virginia-7.5W38–3150.0W38–31ON
Sat 9/10Pittsburgh vs Tennessee+6.0L27–3463.0L27–34UN
Sat 9/17Pittsburgh at Western Michigan-10.0W34–1346.0W34–13OY
Sat 9/24Pittsburgh vs Rhode Island-32.5W45–2455.0W45–24ON
Sat 10/1Pittsburgh vs Georgia Tech-21.5L21–2647.0L21–26UN
Sat 10/8Pittsburgh vs Virginia Tech-14.5W45–2942.0W45–29OY
— Bye Week —
Sat 10/22Pittsburgh at Louisville+1.5L10–2455.0L10–24UN
Sat 10/29Pittsburgh at North Carolina+2.5L24–4265.5L24–42ON
Sat 11/5Pittsburgh vs Syracuse-3.5W19–947.5W19–9UY
Sat 11/12Pittsburgh at Virginia-5.5W37–741.5W37–7OY
Sat 11/19Pittsburgh vs Duke-6.5W28–2649.0W28–26ON
Sat 11/26Pittsburgh at Miami-5.5W42–1643.0W42–16OY
Fri 12/30Pittsburgh vs UCLA+9.0W37–3555.0W37–35OY
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2022 season
Pittsburgh 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
→ Pittsburgh
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
West Virginia
+0.270
Pittsburgh
+0.395
Pittsburgh Edge
PPA Passing
Pass efficiency edge · Strong predictor
West Virginia
+0.324
Pittsburgh
+0.556
Pittsburgh Edge
Havoc Total
Def. disruption rate · Strong predictor
West Virginia
0.148
Pittsburgh
0.221
TFLs, sacks, PBUs, forced fumbles — higher is better
Pittsburgh Edge
Points Per Opp
Drive-finishing edge · Strong predictor
West Virginia
+7.814
Pittsburgh
+7.643
West Virginia Edge
Success Rate
Play consistency edge · Solid predictor
West Virginia
+0.796
Pittsburgh
+0.876
Pittsburgh Edge
Field Position
Avg start (lower=better) · Solid predictor
West Virginia
73.1
Pittsburgh
69.3
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Pittsburgh Edge
Advanced stats sourced from CFBD · 2022 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
West Virginia
1.2
Pittsburgh
9.1
Offense Rating
West Virginia
17.8
Pittsburgh
19.3
Defense Rating (lower = better defense)
West Virginia
16.6
Pittsburgh
10.2
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? West Virginia Edge
Avg sequences created per game
West Virginia #122
0.00
Pittsburgh #70
0.00
Avg sequences allowed per game (lower is better)
West Virginia #110
0.00
Pittsburgh #40
0.00
West Virginia +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 0 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? West Virginia Edge
Avg GC score per game (offense)
West Virginia #1
0.0
Pittsburgh #1
0.0
Avg GC score allowed per game (lower is better)
West Virginia #102
0.0
Pittsburgh #18
0.0
West Virginia +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 0 games this season
Actual Result
CSS Battle
West Virginia
1 — 2 sequences
✗ Predicted incorrectly
GC Battle
Pittsburgh
40.5 — 31.5 GC score
✗ Predicted incorrectly
Game Result
Pittsburgh won by 7
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

Both metrics agree on Pittsburgh, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.

ATS data is informational only. Past cover rates do not guarantee future results.

Coaching Matchup
West Virginia
Neal Brown #1
17–18 (49%) · Yr 4 at school
OC Graham Harrell Yr 1 #1
DC ShaDon Brown Yr 2 #1
Staff Rating
0.00 #1
Pittsburgh
Pat Narduzzi #1
53–37 (59%) · Yr 8 at school
OC Frank Cignetti Jr. Yr 1 #1
DC Randy Bates Yr 2 #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: Momentum Control is a great measure for predicting game outcome but NOT an 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: Game Control is another great measure for predicting game outcome but NOT an 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