Sat, Oct 18 2025
·
Week 8
·
🏟 Sun Devil Stadium
Tempe, AZ
·
Turf
·
56,232 cap
Texas Tech✈ 579 mi-2 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
73.7%
Texas Tech wins
Solid
Game Control
75.9%
Texas Tech wins
Solid
Vegas Spread
Texas Tech -7.5
O/U 52.5
DraftKings
Advanced Stats
All 4 factors agree → Texas Tech
· 83.1% ATS historically when all four align
↓ See full breakdown
Texas Tech 2025 Schedule
Texas Tech's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Texas Tech vs Arkansas-Pine Bluff | -54.5W67–7 | 63.5 | W67–7 | O | Y |
| Sat 9/6 | Texas Tech vs Kent State | -48.5W62–14 | 60.0 | W62–14 | O | N |
| Sat 9/13 | Texas Tech vs Oregon State | -24.5W45–7 | 61.5 | W45–7 | U | Y |
| Sat 9/20 | Texas Tech at Utah | +3.5W34–10 | 58.5 | W34–10 | U | Y |
| — Bye Week — | ||||||
| Sat 10/4 | Texas Tech at Houston | -13.5W35–11 | 51.5 | W35–11 | U | Y |
| Sat 10/11 | Texas Tech vs Kansas | -13.5W42–17 | 58.5 | W42–17 | O | Y |
| Sat 10/18 | Texas Tech at Arizona State | -7.5L22–26 | 52.5 | L22–26 | U | N |
| Sat 10/25 | Texas Tech vs Oklahoma State | -37.5W42–0 | 56.5 | W42–0 | U | Y |
| Sat 11/1 | Texas Tech at Kansas State | -7.5W43–20 | 51.5 | W43–20 | O | Y |
| Sat 11/8 | Texas Tech vs BYU | -13.5W29–7 | 50.5 | W29–7 | U | Y |
| Sat 11/15 | Texas Tech vs UCF | -24.5W48–9 | 48.5 | W48–9 | O | Y |
| — Bye Week — | ||||||
| Sat 11/29 | Texas Tech at West Virginia | -24.5W49–0 | 53.5 | W49–0 | U | Y |
| Sat 12/6 | Texas Tech vs BYU | -12.5W34–7 | 50.5 | W34–7 | U | Y |
| Thu 1/1 | Texas Tech vs Oregon | -1.5L0–23 | 50.5 | L0–23 | U | N |
Arizona State 2025 Schedule
Arizona State's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Arizona State vs Northern Arizona | -29.5W38–19 | 52.5 | W38–19 | O | N |
| Sat 9/6 | Arizona State at Mississippi State | -6.0L20–24 | 58.5 | L20–24 | U | N |
| Sat 9/13 | Arizona State vs Texas State | -18.5W34–15 | 61.5 | W34–15 | U | Y |
| Sat 9/20 | Arizona State at Baylor | +3.0W27–24 | 60.5 | W27–24 | U | Y |
| Fri 9/26 | Arizona State vs TCU | -2.5W27–24 | 54.5 | W27–24 | U | Y |
| — Bye Week — | ||||||
| Sat 10/11 | Arizona State at Utah | +9.5L10–42 | 44.5 | L10–42 | O | N |
| Sat 10/18 | Arizona State vs Texas Tech | +7.5W26–22 | 52.5 | W26–22 | U | Y |
| Sat 10/25 | Arizona State vs Houston | -7.0L16–24 | 46.5 | L16–24 | U | N |
| Sat 11/1 | Arizona State at Iowa State | +7.5W24–19 | 48.5 | W24–19 | U | Y |
| — Bye Week — | ||||||
| Sat 11/15 | Arizona State vs West Virginia | -10.0W25–23 | 46.5 | W25–23 | O | N |
| Sat 11/22 | Arizona State at Colorado | -7.0W42–17 | 47.5 | W42–17 | O | Y |
| Fri 11/28 | Arizona State vs Arizona | +2.0L7–23 | 48.5 | L7–23 | U | N |
| Wed 12/31 | Arizona State vs Duke | +4.0L39–42 | 49.5 | L39–42 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Texas Tech
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Texas Tech
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 · 2025 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 +1.80
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 5 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Texas Tech Edge
Texas Tech +48.4
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 6 games this season
Actual Result
CSS Battle
Arizona State
2 — 1 sequences
✗ Predicted incorrectly
GC Battle
Arizona State
63.7 — 15.5 GC score
✗ Predicted incorrectly
Game Result
Arizona State won by 4
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Texas Tech 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
23–15 (61%)
· Yr 4 at school
OC
Mack Leftwich
Yr 1
#1
DC
Shiel Wood
Yr 1
#1
Arizona State
Kenny Dillingham #1
14–11 (56%)
· Yr 3 at school
OC
Marcus Arroyo
Yr 2
#1
DC
Brian Ward
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 ✓

