Sat, Oct 8 2022
·
Week 6
·
🏟 Boone Pickens Stadium
Stillwater, OK
·
Turf
·
60,218 cap
Texas Tech✈ 323 miSame 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
71.6%
Oklahoma State wins
Solid
Game Control
76%
Oklahoma State wins
Strong
Vegas Spread
Oklahoma State -11
O/U 66.0
teamrankings
Advanced Stats
PPA + Success Rate agree → Texas Tech
· 73.9% ATS historically
↓ See full breakdown
Texas Tech 2022 Schedule
Texas Tech's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Texas Tech vs Murray State | -38.0W63–10 | 64.0 | W63–10 | O | Y |
| Sat 9/10 | Texas Tech vs Houston | -3.5W33–30 | 62.5 | W33–30 | O | N |
| Sat 9/17 | Texas Tech at NC State | +10.5L14–27 | 55.5 | L14–27 | U | N |
| Sat 9/24 | Texas Tech vs Texas | +7.0W37–34 | 60.0 | W37–34 | O | Y |
| Sat 10/1 | Texas Tech at Kansas State | +7.5L28–37 | 56.0 | L28–37 | O | N |
| Sat 10/8 | Texas Tech at Oklahoma State | +11.0L31–41 | 66.0 | L31–41 | O | Y |
| — Bye Week — | ||||||
| Sat 10/22 | Texas Tech vs West Virginia | -5.0W48–10 | 65.5 | W48–10 | U | Y |
| Sat 10/29 | Texas Tech vs Baylor | -1.5L17–45 | 61.0 | L17–45 | O | N |
| Sat 11/5 | Texas Tech at TCU | +8.5L24–34 | 69.0 | L24–34 | U | N |
| Sat 11/12 | Texas Tech vs Kansas | -3.5W43–28 | 63.5 | W43–28 | O | Y |
| Sat 11/19 | Texas Tech at Iowa State | +3.5W14–10 | 47.5 | W14–10 | U | Y |
| Sat 11/26 | Texas Tech vs Oklahoma | +2.0W51–48 | 65.5 | W51–48 | O | Y |
| Wed 12/28 | Texas Tech vs Ole Miss | +4.5W42–25 | 73.0 | W42–25 | U | Y |
Oklahoma State 2022 Schedule
Oklahoma State's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 9/1 | Oklahoma State vs Central Michigan | -20.5W58–44 | 58.0 | W58–44 | O | N |
| Sat 9/10 | Oklahoma State vs Arizona State | -12.0W34–17 | 58.5 | W34–17 | U | Y |
| Sat 9/17 | Oklahoma State vs Arkansas-Pine Bluff | -54.5W63–7 | 64.5 | W63–7 | O | Y |
| — Bye Week — | ||||||
| Sat 10/1 | Oklahoma State at Baylor | +2.5W36–25 | 56.0 | W36–25 | O | Y |
| Sat 10/8 | Oklahoma State vs Texas Tech | -11.0W41–31 | 66.0 | W41–31 | O | N |
| Sat 10/15 | Oklahoma State at TCU | +5.0L40–43 | 69.5 | L40–43 | O | Y |
| Sat 10/22 | Oklahoma State vs Texas | +6.5W41–34 | 58.5 | W41–34 | O | Y |
| Sat 10/29 | Oklahoma State at Kansas State | +2.5L0–48 | 57.5 | L0–48 | U | N |
| Sat 11/5 | Oklahoma State at Kansas | +3.0L16–37 | 59.5 | L16–37 | U | N |
| Sat 11/12 | Oklahoma State vs Iowa State | +2.5W20–14 | 47.5 | W20–14 | U | Y |
| Sat 11/19 | Oklahoma State at Oklahoma | +7.0L13–28 | 67.5 | L13–28 | U | N |
| Sat 11/26 | Oklahoma State vs West Virginia | -5.5L19–24 | 59.5 | L19–24 | U | N |
| Tue 12/27 | Oklahoma State vs Wisconsin | +5.0L17–24 | 45.0 | L17–24 | U | N |
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
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 · 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?
Oklahoma State Edge
Oklahoma State +1.27
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?
Oklahoma State Edge
Oklahoma State +46.3
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 4 games this season
Actual Result
CSS Battle
Oklahoma State
2 — 1 sequences
✓ Predicted correctly
GC Battle
Oklahoma State
59.7 — 19.8 GC score
✓ Predicted correctly
Game Result
Oklahoma State won by 10
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Oklahoma State 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
Texas Tech
Joey McGuire #1
0–0 (0%)
· Yr 1 at school
OC
Zach Kittley
Yr 1
#1
DC
Tim DeRuyter
Yr 1
#1
Oklahoma State
Mike Gundy #1
149–69 (68%)
· Yr 18 at school
OC
Kasey Dunn
Yr 2
#1
DC
Derek Mason
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 ✓