Sun, Oct 1 2023
·
Week 5
·
🏟 Amon G. Carter Stadium
Fort Worth, TX
·
Turf
·
45,000 cap
West Virginia✈ 1,080 mi-1 hr TZ
Matchup Prediction
TCU
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
TCU entering this game.
Momentum Control
71.6%
TCU wins
Solid
Game Control
76%
TCU wins
Strong
Vegas Spread
TCU -14
O/U 52.0
William Hill (New Jersey)
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
West Virginia 2023 Schedule
West Virginia's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | West Virginia at Penn State | +21.0L15–38 | 48.0 | L15–38 | O | N |
| Sat 9/9 | West Virginia vs Duquesne | -38.5W56–17 | 55.5 | W56–17 | O | Y |
| Sat 9/16 | West Virginia vs Pittsburgh | -2.5W17–6 | 48.0 | W17–6 | U | Y |
| Sat 9/23 | West Virginia vs Texas Tech | +6.0W20–13 | 53.5 | W20–13 | U | Y |
| Sat 9/30 | West Virginia at TCU | +14.0W24–21 | 52.0 | W24–21 | U | Y |
| — Bye Week — | ||||||
| Thu 10/12 | West Virginia at Houston | -3.0L39–41 | 49.5 | L39–41 | O | N |
| Sat 10/21 | West Virginia vs Oklahoma State | -3.0L34–48 | 48.0 | L34–48 | O | N |
| Sat 10/28 | West Virginia at UCF | +6.5W41–28 | 59.5 | W41–28 | O | Y |
| Sat 11/4 | West Virginia vs BYU | -13.0W37–7 | 48.5 | W37–7 | U | Y |
| Sat 11/11 | West Virginia at Oklahoma | +13.5L20–59 | 59.5 | L20–59 | O | N |
| Sat 11/18 | West Virginia vs Cincinnati | -4.5W42–21 | 52.5 | W42–21 | O | Y |
| Sat 11/25 | West Virginia at Baylor | -6.5W34–31 | 53.5 | W34–31 | O | N |
| Wed 12/27 | West Virginia vs North Carolina | -4.5W30–10 | 62.0 | W30–10 | U | Y |
TCU 2023 Schedule
TCU's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | TCU vs Colorado | -20.5L42–45 | 59.5 | L42–45 | O | N |
| Sat 9/9 | TCU vs Nicholls | -41.5W41–6 | 59.5 | W41–6 | U | N |
| Sat 9/16 | TCU at Houston | -7.5W36–13 | 64.0 | W36–13 | U | Y |
| Sat 9/23 | TCU vs SMU | -7.0W34–17 | 63.5 | W34–17 | U | Y |
| Sat 9/30 | TCU vs West Virginia | -14.0L21–24 | 52.0 | L21–24 | U | N |
| Sat 10/7 | TCU at Iowa State | -6.5L14–27 | 52.5 | L14–27 | U | N |
| Sat 10/14 | TCU vs BYU | -5.0W44–11 | 52.5 | W44–11 | O | Y |
| Sat 10/21 | TCU at Kansas State | +5.5L3–41 | 60.0 | L3–41 | U | N |
| — Bye Week — | ||||||
| Thu 11/2 | TCU at Texas Tech | +2.5L28–35 | 59.5 | L28–35 | O | N |
| Sat 11/11 | TCU vs Texas | +13.0L26–29 | 56.0 | L26–29 | U | Y |
| Sat 11/18 | TCU vs Baylor | -13.0W42–17 | 62.0 | W42–17 | U | Y |
| Fri 11/24 | TCU at Oklahoma | +12.5L45–69 | 66.5 | L45–69 | O | N |
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
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 · 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?
TCU Edge
TCU +1.00
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
TCU Edge
TCU +27.8
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 4 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on TCU 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
West Virginia
Neal Brown #1
24–26 (48%)
· Yr 5 at school
OC
Chad Scott
Yr 1
#1
DC
ShaDon Brown
Yr 3
#1
TCU
Sonny Dykes #1
15–3 (83%)
· Yr 2 at school
OC
Kendal Briles
Yr 1
#1
DC
Joe Gillespie
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 ✓