Sat, Oct 21 2023
·
Week 8
·
🏟 Mountaineer Field at Milan Puskar Stadium
Morgantown, WV
·
Turf
·
60,000 cap
Oklahoma State✈ 962 mi+1 hr TZ
Matchup Prediction
Oklahoma State
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Oklahoma State entering this game.
Momentum Control
61.3%
Oklahoma State wins
Lean
Game Control
58.3%
Oklahoma State wins
Lean
Vegas Spread
West Virginia -3
O/U 48.0
William Hill (New Jersey)
Advanced Stats
All 4 factors agree → West Virginia
· 83.1% ATS historically when all four align
↓ See full breakdown
Oklahoma State 2023 Schedule
Oklahoma State's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Oklahoma State vs Central Arkansas | -25.5W27–13 | 59.5 | W27–13 | U | N |
| Sat 9/9 | Oklahoma State at Arizona State | -2.5W27–15 | 53.5 | W27–15 | U | Y |
| Sat 9/16 | Oklahoma State vs South Alabama | -7.0L7–33 | 49.5 | L7–33 | U | N |
| Sat 9/23 | Oklahoma State at Iowa State | +3.5L27–34 | 36.0 | L27–34 | O | N |
| — Bye Week — | ||||||
| Fri 10/6 | Oklahoma State vs Kansas State | +11.5W29–21 | 53.5 | W29–21 | U | Y |
| Sat 10/14 | Oklahoma State vs Kansas | +3.0W39–32 | 54.0 | W39–32 | O | Y |
| Sat 10/21 | Oklahoma State at West Virginia | +3.0W48–34 | 48.0 | W48–34 | O | Y |
| Sat 10/28 | Oklahoma State vs Cincinnati | -7.0W45–13 | 53.0 | W45–13 | O | Y |
| Sat 11/4 | Oklahoma State vs Oklahoma | +6.0W27–24 | 61.5 | W27–24 | U | Y |
| Sat 11/11 | Oklahoma State at UCF | -2.5L3–45 | 63.5 | L3–45 | U | N |
| Sat 11/18 | Oklahoma State at Houston | -6.5W43–30 | 56.5 | W43–30 | O | Y |
| Sat 11/25 | Oklahoma State vs BYU | -15.5W40–34 | 55.5 | W40–34 | O | N |
| Sat 12/2 | Oklahoma State vs Texas | +14.0L21–49 | 55.0 | L21–49 | O | N |
| Wed 12/27 | Oklahoma State vs Texas A&M | -4.0W31–23 | 56.0 | W31–23 | U | Y |
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 |
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
All 4 Agree
→ West Virginia
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ West Virginia
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ West Virginia
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?
Oklahoma State Edge
Oklahoma State +0.60
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 5 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Oklahoma State Edge
Oklahoma State +5.0
GC Edge (season-to-date)
Teams with this edge win 58.3% of games historically
Based on 6 games this season
Actual Result
CSS Battle
Oklahoma State
1 — 2 sequences
✓ Predicted correctly
GC Battle
Oklahoma State
23.9 — 44.6 GC score
✓ Predicted correctly
Game Result
Oklahoma State won by 14
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Oklahoma State, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Oklahoma State
Mike Gundy #1
158–76 (68%)
· Yr 19 at school
OC
Kasey Dunn
Yr 3
#1
DC
Jim Bob Clements
Yr 1
#1
West Virginia
Neal Brown #1
24–26 (48%)
· Yr 5 at school
OC
Chad Scott
Yr 1
#1
DC
ShaDon Brown
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 ✓