Thu, Sep 22 2022
·
Week 4
·
🏟 Lane Stadium
Blacksburg, VA
·
Turf
·
66,233 cap
West Virginia✈ 169 miSame TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors West Virginia,
while Game Control favors Virginia Tech.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
73.7%
West Virginia wins
Solid
Game Control
76%
Virginia Tech wins
Strong
Vegas Spread
West Virginia -2
O/U 49.5
teamrankings
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
West Virginia 2022 Schedule
West Virginia's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 9/1 | West Virginia at Pittsburgh | +7.5L31–38 | 50.0 | L31–38 | O | Y |
| Sat 9/10 | West Virginia vs Kansas | -14.0L42–55 | 59.5 | L42–55 | O | N |
| Sat 9/17 | West Virginia vs Towson | -41.0W65–7 | 58.5 | W65–7 | O | Y |
| Thu 9/22 | West Virginia at Virginia Tech | -2.0W33–10 | 49.5 | W33–10 | U | Y |
| Sat 10/1 | West Virginia at Texas | +7.5L20–38 | 61.0 | L20–38 | U | N |
| — Bye Week — | ||||||
| Thu 10/13 | West Virginia vs Baylor | +3.0W43–40 | 55.0 | W43–40 | O | Y |
| Sat 10/22 | West Virginia at Texas Tech | +5.0L10–48 | 65.5 | L10–48 | U | N |
| Sat 10/29 | West Virginia vs TCU | +7.0L31–41 | 70.0 | L31–41 | O | N |
| Sat 11/5 | West Virginia at Iowa State | +6.5L14–31 | 49.5 | L14–31 | U | N |
| Sat 11/12 | West Virginia vs Oklahoma | +8.5W23–20 | 68.5 | W23–20 | U | Y |
| Sat 11/19 | West Virginia vs Kansas State | +8.0L31–48 | 54.5 | L31–48 | O | N |
| Sat 11/26 | West Virginia at Oklahoma State | +5.5W24–19 | 59.5 | W24–19 | U | Y |
Virginia Tech 2022 Schedule
Virginia Tech's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/2 | Virginia Tech at Old Dominion | -6.0L17–20 | 48.5 | L17–20 | U | N |
| Sat 9/10 | Virginia Tech vs Boston College | -2.5W27–10 | 45.0 | W27–10 | U | Y |
| Sat 9/17 | Virginia Tech vs Wofford | -39.0W27–7 | 45.0 | W27–7 | U | N |
| Thu 9/22 | Virginia Tech vs West Virginia | +2.0L10–33 | 49.5 | L10–33 | U | N |
| Sat 10/1 | Virginia Tech at North Carolina | +9.5L10–41 | 57.0 | L10–41 | U | N |
| Sat 10/8 | Virginia Tech at Pittsburgh | +14.5L29–45 | 42.0 | L29–45 | O | N |
| Sat 10/15 | Virginia Tech vs Miami | +9.0L14–20 | 48.5 | L14–20 | U | Y |
| — Bye Week — | ||||||
| Thu 10/27 | Virginia Tech at NC State | +13.0L21–22 | 39.0 | L21–22 | O | Y |
| Sat 11/5 | Virginia Tech vs Georgia Tech | -4.0L27–28 | 40.5 | L27–28 | O | N |
| Sat 11/12 | Virginia Tech at Duke | +10.0L7–24 | 50.0 | L7–24 | U | N |
| Sat 11/19 | Virginia Tech at Liberty | +10.5W23–22 | 46.0 | W23–22 | U | Y |
| Sat 11/26 | Virginia Tech vs Virginia | -1.5 | 40.0 | — | — | — |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2022 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
Split
Metrics disagree
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 · 2022 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?
West Virginia Edge
West Virginia +1.00
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 2 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Virginia Tech Edge
Virginia Tech +29.3
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 3 games this season
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
West Virginia
Neal Brown #1
17–18 (49%)
· Yr 4 at school
OC
Graham Harrell
Yr 1
#1
DC
ShaDon Brown
Yr 2
#1
Virginia Tech
Brent Pry #1
0–0 (0%)
· Yr 1 at school
OC
Tyler Bowen
Yr 1
#1
DC
Chris Marve
Yr 1
#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 ✓