Sat, Nov 30 2024
·
Week 14
·
🏟 Jones AT&T Stadium
Lubbock, TX
·
Turf
·
60,862 cap
West Virginia✈ 1,281 mi-1 hr TZ
Matchup Prediction
Texas Tech
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Texas Tech entering this game.
Momentum Control
58.4%
Texas Tech wins
Lean
Game Control
58.6%
Texas Tech wins
Lean
Vegas Spread
Texas Tech -2.5
O/U 61.5
ESPN Bet
Advanced Stats
PPA + Success Rate agree → Texas Tech
· 73.9% ATS historically
↓ See full breakdown
West Virginia 2024 Schedule
West Virginia's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | West Virginia vs Penn State | +7.5L12–34 | 48.0 | L12–34 | U | N |
| Sat 9/7 | West Virginia vs UAlbany | -38.5W49–14 | 53.5 | W49–14 | O | N |
| Sat 9/14 | West Virginia at Pittsburgh | -2.5L34–38 | 60.5 | L34–38 | O | N |
| Sat 9/21 | West Virginia vs Kansas | -1.5W32–28 | 56.0 | W32–28 | O | Y |
| — Bye Week — | ||||||
| Sat 10/5 | West Virginia at Oklahoma State | +2.5W38–14 | 65.0 | W38–14 | U | Y |
| Sat 10/12 | West Virginia vs Iowa State | +3.0L16–28 | 54.0 | L16–28 | U | N |
| Sat 10/19 | West Virginia vs Kansas State | +2.5L18–45 | 56.5 | L18–45 | O | N |
| Sat 10/26 | West Virginia at Arizona | +5.5W31–26 | 51.5 | W31–26 | O | Y |
| — Bye Week — | ||||||
| Sat 11/9 | West Virginia at Cincinnati | +5.5W31–24 | 54.5 | W31–24 | O | Y |
| Sat 11/16 | West Virginia vs Baylor | +2.0L35–49 | 60.0 | L35–49 | O | N |
| Sat 11/23 | West Virginia vs UCF | +3.0W31–21 | 60.0 | W31–21 | U | Y |
| Sat 11/30 | West Virginia at Texas Tech | +2.5L15–52 | 61.5 | L15–52 | O | N |
| Tue 12/17 | West Virginia vs Memphis | +5.0L37–42 | 60.0 | L37–42 | O | Y |
Texas Tech 2024 Schedule
Texas Tech's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Texas Tech vs Abilene Christian | -34.5W52–51 | 58.5 | W52–51 | O | N |
| Sat 9/7 | Texas Tech at Washington State | -2.5L16–37 | 64.5 | L16–37 | U | N |
| Sat 9/14 | Texas Tech vs North Texas | -10.5W66–21 | 70.5 | W66–21 | O | Y |
| Sat 9/21 | Texas Tech vs Arizona State | -4.5W30–22 | 58.5 | W30–22 | U | Y |
| Sat 9/28 | Texas Tech vs Cincinnati | -3.0W44–41 | 60.0 | W44–41 | O | N |
| Sat 10/5 | Texas Tech at Arizona | +6.0W28–22 | 64.0 | W28–22 | U | Y |
| — Bye Week — | ||||||
| Sat 10/19 | Texas Tech vs Baylor | -4.5L35–59 | 56.0 | L35–59 | O | N |
| Sat 10/26 | Texas Tech at TCU | +5.0L34–35 | 66.0 | L34–35 | O | Y |
| Sat 11/2 | Texas Tech at Iowa State | +13.5W23–22 | 55.0 | W23–22 | U | Y |
| Sat 11/9 | Texas Tech vs Colorado | +5.0L27–41 | 62.0 | L27–41 | O | N |
| — Bye Week — | ||||||
| Sat 11/23 | Texas Tech at Oklahoma State | -5.0W56–48 | 63.5 | W56–48 | O | Y |
| Sat 11/30 | Texas Tech vs West Virginia | -2.5W52–15 | 61.5 | W52–15 | O | Y |
| Fri 12/27 | Texas Tech vs Arkansas | -3.5L26–39 | 52.5 | L26–39 | O | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 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
→ Texas 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 · 2024 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?
Texas Tech Edge
Texas Tech +0.50
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 10 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Texas Tech Edge
Texas Tech +7.3
GC Edge (season-to-date)
Teams with this edge win 58.6% of games historically
Based on 11 games this season
Actual Result
CSS Battle
Texas Tech
5 — 0 sequences
✓ Predicted correctly
GC Battle
Texas Tech
80.8 — 6.4 GC score
✓ Predicted correctly
Game Result
Texas Tech won by 37
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Texas Tech. 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
West Virginia
Neal Brown #1
31–29 (52%)
· Yr 6 at school
OC
Chad Scott
Yr 2
#1
DC
ShaDon Brown
Yr 3
#1
Texas Tech
Joey McGuire #1
15–11 (58%)
· Yr 3 at school
OC
Zach Kittley
Yr 3
#1
DC
Tim DeRuyter
Yr 3
#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 ✓

