Virginia Tech at Pittsburgh Week 6 College Football Matchup Virginia Tech at Pittsburgh Matchup - Week 6
Sat, Oct 8 2022 · Week 6 · 🏟 Acrisure Stadium Pittsburgh, PA · Turf · 68,400 cap
Virginia Tech✈ 224 miSame TZ
29 45
Final
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📊 Punt & Rally Projection
Virginia Tech
13
Pittsburgh
34
P&R Line Pittsburgh -20.5
P&R Total O/U 46.5
Confidence 90 High
Vegas Pittsburgh -14.5 · O/U 42.0
Matchup Prediction
Pittsburgh has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor Pittsburgh entering this game.
Momentum Control
58.4%
Pittsburgh wins
Lean
Game Control
58.6%
Pittsburgh wins
Lean
Vegas Spread
Pittsburgh -14.5
O/U 42.0
teamrankings
Advanced Stats
All 4 factors agree → Pittsburgh · 83.1% ATS historically when all four align
↓ See full breakdown
🏠 Pittsburgh 3rd straight Home Game 🚌 Virginia Tech 2nd straight Road Game
Virginia Tech 2022 Schedule
Virginia Tech's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Fri 9/2Virginia Tech at Old Dominion-6.0L17–2048.5L17–20UN
Sat 9/10Virginia Tech vs Boston College-2.5W27–1045.0W27–10UY
Sat 9/17Virginia Tech vs Wofford-39.0W27–745.0W27–7UN
Thu 9/22Virginia Tech vs West Virginia+2.0L10–3349.5L10–33UN
Sat 10/1Virginia Tech at North Carolina+9.5L10–4157.0L10–41UN
Sat 10/8Virginia Tech at Pittsburgh+14.5L29–4542.0L29–45ON
Sat 10/15Virginia Tech vs Miami+9.0L14–2048.5L14–20UY
— Bye Week —
Thu 10/27Virginia Tech at NC State+13.0L21–2239.0L21–22OY
Sat 11/5Virginia Tech vs Georgia Tech-4.0L27–2840.5L27–28ON
Sat 11/12Virginia Tech at Duke+10.0L7–2450.0L7–24UN
Sat 11/19Virginia Tech at Liberty+10.5W23–2246.0W23–22UY
Sat 11/26Virginia Tech vs Virginia-1.540.0
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
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
Virginia Tech
+0.162
Pittsburgh
+0.348
Pittsburgh Edge
PPA Passing
Pass efficiency edge · Strong predictor
Virginia Tech
+0.226
Pittsburgh
+0.504
Pittsburgh Edge
Havoc Total
Def. disruption rate · Strong predictor
Virginia Tech
0.185
Pittsburgh
0.221
TFLs, sacks, PBUs, forced fumbles — higher is better
Pittsburgh Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Virginia Tech
+6.235
Pittsburgh
+7.701
Pittsburgh Edge
Success Rate
Play consistency edge · Solid predictor
Virginia Tech
+0.740
Pittsburgh
+0.814
Pittsburgh Edge
Field Position
Avg start (lower=better) · Solid predictor
Virginia Tech
71.6
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
Virginia Tech
5.9
Pittsburgh
9.1
Offense Rating
Virginia Tech
18.3
Pittsburgh
19.3
Defense Rating (lower = better defense)
Virginia Tech
12.4
Pittsburgh
10.2
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
Virginia Tech #87
0.00
Pittsburgh #70
0.75
Avg sequences allowed per game (lower is better)
Virginia Tech #114
1.75
Pittsburgh #40
1.00
Pittsburgh +0.75
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Pittsburgh Edge
Avg GC score per game (offense)
Virginia Tech #1
56.0
Pittsburgh #1
63.0
Avg GC score allowed per game (lower is better)
Virginia Tech #86
32.6
Pittsburgh #18
25.8
Pittsburgh +7.0
GC Edge (season-to-date)
Teams with this edge win 58.6% of games historically
Based on 5 games this season
Actual Result
CSS Battle
Pittsburgh
3 — 2 sequences
✓ Predicted correctly
GC Battle
Pittsburgh
79.2 — 9.6 GC score
✓ Predicted correctly
Game Result
Pittsburgh won by 16
✓ Model called 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
Virginia Tech
Brent Pry #1
0–0 (0%) · Yr 1 at school
OC Tyler Bowen Yr 1 #1
DC Chris Marve Yr 1 #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