Sat, Oct 29 2022
·
Week 9
·
🏟 Jones AT&T Stadium
Lubbock, TX
·
Turf
·
60,862 cap
Baylor✈ 310 miSame TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Texas Tech,
while Game Control favors Baylor.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Texas Tech wins
Lean
Game Control
75.9%
Baylor wins
Solid
Vegas Spread
Texas Tech -1.5
O/U 61.0
teamrankings
Advanced Stats
PPA + Success Rate agree → Texas Tech
· 73.9% ATS historically
↓ See full breakdown
Baylor 2022 Schedule
Baylor's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Baylor vs UAlbany | -42.5W69–10 | 46.5 | W69–10 | O | Y |
| Sat 9/10 | Baylor at BYU | +2.5L20–26 | 54.5 | L20–26 | U | N |
| Sat 9/17 | Baylor vs Texas State | -30.0W42–7 | 53.0 | W42–7 | U | Y |
| Sat 9/24 | Baylor at Iowa State | +2.5W31–24 | 45.0 | W31–24 | O | Y |
| Sat 10/1 | Baylor vs Oklahoma State | -2.5L25–36 | 56.0 | L25–36 | O | N |
| — Bye Week — | ||||||
| Thu 10/13 | Baylor at West Virginia | -3.0L40–43 | 55.0 | L40–43 | O | N |
| Sat 10/22 | Baylor vs Kansas | -10.5W35–23 | 56.5 | W35–23 | O | Y |
| Sat 10/29 | Baylor at Texas Tech | +1.5W45–17 | 61.0 | W45–17 | O | Y |
| Sat 11/5 | Baylor at Oklahoma | +3.0W38–35 | 61.5 | W38–35 | O | Y |
| Sat 11/12 | Baylor vs Kansas State | -2.5L3–31 | 52.0 | L3–31 | U | N |
| Sat 11/19 | Baylor vs TCU | +2.0L28–29 | 58.0 | L28–29 | U | Y |
| Fri 11/25 | Baylor at Texas | +10.0L27–38 | 55.0 | L27–38 | O | N |
| Thu 12/22 | Baylor vs Air Force | -3.5L15–30 | 42.0 | L15–30 | O | N |
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 |
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?
Texas Tech Edge
Texas Tech +0.71
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 7 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Baylor Edge
Baylor +23.7
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 7 games this season
Actual Result
CSS Battle
Tie
1 — 1 sequences
✗ Predicted incorrectly
GC Battle
Baylor
9.7 — 72.5 GC score
✓ Predicted correctly
Game Result
Baylor won by 28
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
Baylor
Dave Aranda #1
14–9 (61%)
· Yr 3 at school
OC
Jeff Grimes
Yr 2
#1
DC
Ron Roberts
Yr 2
#1
Texas Tech
Joey McGuire #1
0–0 (0%)
· Yr 1 at school
OC
Zach Kittley
Yr 1
#1
DC
Tim DeRuyter
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 ✓