Sun, Oct 1 2023
·
Week 5
·
🏟 Lane Stadium
Blacksburg, VA
·
Turf
·
66,233 cap
Pittsburgh✈ 224 miSame TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Virginia Tech,
while Game Control favors Pittsburgh.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Virginia Tech wins
Lean
Game Control
49.4%
Pittsburgh wins
Toss-up
Vegas Spread
Pittsburgh -3
O/U 40.0
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → Virginia Tech
· 73.9% ATS historically
↓ See full breakdown
Pittsburgh 2023 Schedule
Pittsburgh's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Pittsburgh vs Wofford | -37.5W45–7 | 49.5 | W45–7 | O | Y |
| Sat 9/9 | Pittsburgh vs Cincinnati | -6.5L21–27 | 44.5 | L21–27 | O | N |
| Sat 9/16 | Pittsburgh at West Virginia | +2.5L6–17 | 48.0 | L6–17 | U | N |
| Sat 9/23 | Pittsburgh vs North Carolina | +7.0L24–41 | 49.5 | L24–41 | O | N |
| Sat 9/30 | Pittsburgh at Virginia Tech | -3.0L21–38 | 40.0 | L21–38 | O | N |
| — Bye Week — | ||||||
| Sat 10/14 | Pittsburgh vs Louisville | +7.5W38–21 | 44.5 | W38–21 | O | Y |
| Sat 10/21 | Pittsburgh at Wake Forest | -3.0L17–21 | 45.0 | L17–21 | U | N |
| Sat 10/28 | Pittsburgh at Notre Dame | +21.0L7–58 | 45.5 | L7–58 | O | N |
| Sat 11/4 | Pittsburgh vs Florida State | +21.5L7–24 | 50.0 | L7–24 | U | Y |
| Sat 11/11 | Pittsburgh vs Syracuse | -4.5L13–28 | 37.5 | L13–28 | O | N |
| Thu 11/16 | Pittsburgh vs Boston College | -1.0W24–16 | 47.0 | W24–16 | U | Y |
| Sat 11/25 | Pittsburgh at Duke | +4.5L19–30 | 40.5 | L19–30 | O | N |
Virginia Tech 2023 Schedule
Virginia Tech's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Virginia Tech vs Old Dominion | -16.0W36–17 | 48.0 | W36–17 | O | Y |
| Sat 9/9 | Virginia Tech vs Purdue | -1.5L17–24 | 49.0 | L17–24 | U | N |
| Sat 9/16 | Virginia Tech at Rutgers | +6.5L16–35 | 37.5 | L16–35 | O | N |
| Sat 9/23 | Virginia Tech at Marshall | +5.5L17–24 | 41.5 | L17–24 | U | N |
| Sat 9/30 | Virginia Tech vs Pittsburgh | +3.0W38–21 | 40.0 | W38–21 | O | Y |
| Sat 10/7 | Virginia Tech at Florida State | +23.5L17–39 | 52.5 | L17–39 | O | Y |
| Sat 10/14 | Virginia Tech vs Wake Forest | -1.5W30–13 | 48.5 | W30–13 | U | Y |
| — Bye Week — | ||||||
| Thu 10/26 | Virginia Tech vs Syracuse | -2.5W38–10 | 47.5 | W38–10 | O | Y |
| Sat 11/4 | Virginia Tech at Louisville | +9.5L3–34 | 48.5 | L3–34 | U | N |
| Sat 11/11 | Virginia Tech at Boston College | -2.5W48–22 | 48.5 | W48–22 | O | Y |
| Sat 11/18 | Virginia Tech vs NC State | -2.5L28–35 | 40.5 | L28–35 | O | N |
| Sat 11/25 | Virginia Tech at Virginia | -2.5W55–17 | 52.5 | W55–17 | O | Y |
| Wed 12/27 | Virginia Tech vs Tulane | -13.5W41–20 | 43.5 | W41–20 | O | Y |
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
→ Virginia Tech
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?
Virginia Tech Edge
Virginia Tech +0.67
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
Pittsburgh +1.9
GC Edge (season-to-date)
Teams with this edge win 49.4% of games historically
Based on 4 games this season
Actual Result
CSS Battle
Virginia Tech
1 — 0 sequences
✓ Predicted correctly
GC Battle
Virginia Tech
72.7 — 9.9 GC score
✗ Predicted incorrectly
Game Result
Virginia Tech won by 17
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
CSS and GC disagree on this matchup. When the metrics split, historical cover rates are essentially random — treat this as 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
Virginia Tech
Brent Pry #1
4–10 (29%)
· Yr 2 at school
OC
Tyler Bowen
Yr 2
#1
DC
Chris Marve
Yr 2
#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 ✓
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 ✓