Pittsburgh at Virginia Week 11 College Football Matchup Pittsburgh at Virginia Matchup - Week 11
Sat, Nov 12 2022 · Week 11 · 🏟 Scott Stadium Charlottesville, VA · Turf · 61,500 cap
Pittsburgh✈ 185 miSame TZ
37 7
Final
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📊 Punt & Rally Projection
Pittsburgh
30
Virginia
15
P&R Line Pittsburgh -15
P&R Total O/U 44.5
Confidence 90 High
Vegas Pittsburgh -5.5 · O/U 41.5
Matchup Prediction
Pittsburgh has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor Pittsburgh entering this game.
Momentum Control
61.3%
Pittsburgh wins
Lean
Game Control
75.9%
Pittsburgh wins
Solid
Vegas Spread
Pittsburgh -5.5
O/U 41.5
Bovada
Advanced Stats
All 4 factors agree → Pittsburgh · 83.1% ATS historically when all four align
↓ See full breakdown
🏠 Virginia 3rd straight Home Game
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
Virginia 2022 Schedule
Virginia's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/3Virginia vs Richmond-22.5W34–1762.0W34–17UN
Sat 9/10Virginia at Illinois+4.0L3–2455.0L3–24UN
Sat 9/17Virginia vs Old Dominion-8.0W16–1452.5W16–14UN
Fri 9/23Virginia at Syracuse+9.5L20–2253.5L20–22UY
Sat 10/1Virginia at Duke+2.0L17–3855.0L17–38UN
Sat 10/8Virginia vs Louisville-1.5L17–3447.5L17–34ON
— Bye Week —
Thu 10/20Virginia at Georgia Tech+3.5W16–948.0W16–9UY
Sat 10/29Virginia vs Miami+3.0L12–1448.5L12–14UY
Sat 11/5Virginia vs North Carolina+7.0L28–3161.5L28–31UY
Sat 11/12Virginia vs Pittsburgh+5.5L7–3741.5L7–37ON
Sat 11/19Virginia vs Coastal Carolina-2.044.5
Sat 11/26Virginia at Virginia Tech+1.540.0
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
All 4 Agree
→ Pittsburgh
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Pittsburgh
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Pittsburgh
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Pittsburgh
+0.312
Virginia
+0.143
Pittsburgh Edge
PPA Passing
Pass efficiency edge · Strong predictor
Pittsburgh
+0.453
Virginia
+0.117
Pittsburgh Edge
Havoc Total
Def. disruption rate · Strong predictor
Pittsburgh
0.221
Virginia
0.152
TFLs, sacks, PBUs, forced fumbles — higher is better
Pittsburgh Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Pittsburgh
+7.380
Virginia
+6.424
Pittsburgh Edge
Success Rate
Play consistency edge · Solid predictor
Pittsburgh
+0.842
Virginia
+0.760
Pittsburgh Edge
Field Position
Avg start (lower=better) · Solid predictor
Pittsburgh
69.3
Virginia
71.8
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
Pittsburgh
9.1
Virginia
7.0
Offense Rating
Pittsburgh
19.3
Virginia
17.9
Defense Rating (lower = better defense)
Pittsburgh
10.2
Virginia
10.9
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 #70
0.88
Virginia #134
0.13
Avg sequences allowed per game (lower is better)
Pittsburgh #40
1.38
Virginia #93
1.00
Pittsburgh +0.75
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 8 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Pittsburgh Edge
Avg GC score per game (offense)
Pittsburgh #1
58.7
Virginia #1
37.5
Avg GC score allowed per game (lower is better)
Pittsburgh #18
23.8
Virginia #94
44.3
Pittsburgh +21.2
GC Edge (season-to-date)
Teams with this edge win 75.9% 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 with a large edge. Historically, dominant teams like this are fully priced into the spread — the agreed-upon team covers just 50.2% of the time. The metrics predict game control better than they beat the number.

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

Coaching Matchup
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
Virginia
Tony Elliott #1
0–0 (0%) · Yr 1 at school
OC Des Kitchings Yr 1 #1
DC John Rudzinski Yr 1 #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