Preseason projection — This game has not yet been played and 2026 in-season data is not yet available.
Edges are based on 2025 full-season performance.
Confidence will increase once in-season games are logged.
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Arizona,
while Game Control favors TCU.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Arizona wins
Lean
Game Control
49.4%
TCU wins
Toss-up
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
TCU 2026 Schedule
TCU's 2026 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/29 | TCU vs North Carolina | -7.5 | 50.5 | — | — | — |
| Sat 9/12 | TCU vs Grambling | -29 | — | — | — | — |
| Sat 9/19 | TCU vs Arkansas State | -23.5 | — | — | — | — |
| Sat 9/26 | TCU at UCF | -3.5 | — | — | — | — |
| Sat 10/3 | TCU vs BYU | +3 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 10/17 | TCU at Baylor | -2.5 | — | — | — | — |
| Sat 10/24 | TCU vs West Virginia | -12.5 | — | — | — | — |
| Sat 10/31 | TCU vs Kansas | -8 | — | — | — | — |
| Sat 11/7 | TCU at Arizona | +6 | — | — | — | — |
| Sat 11/14 | TCU vs Kansas State | -3.5 | — | — | — | — |
| Sat 11/21 | TCU vs Utah | -0 | — | — | — | — |
| Sat 11/28 | TCU at Texas Tech | +22.5 | — | — | — | — |
Arizona 2026 Schedule
Arizona's 2026 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/5 | Arizona vs Northern Arizona | -30.5 | — | — | — | — |
| Sat 9/12 | Arizona at BYU | +5 | — | — | — | — |
| Sat 9/19 | Arizona vs Northern Illinois | -29 | — | — | — | — |
| Sat 9/26 | Arizona at Washington State | -9 | — | — | — | — |
| Sat 10/3 | Arizona vs Cincinnati | -11.5 | — | — | — | — |
| Sat 10/10 | Arizona at West Virginia | -11 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 10/24 | Arizona vs Iowa State | -6.5 | — | — | — | — |
| Sat 10/31 | Arizona at Texas Tech | +19.5 | — | — | — | — |
| Sat 11/7 | Arizona vs TCU | -6 | — | — | — | — |
| Sat 11/14 | Arizona vs Utah | -3.5 | — | — | — | — |
| Sat 11/21 | Arizona at Kansas State | -1.5 | — | — | — | — |
| Sat 11/28 | Arizona vs Arizona State | -7.5 | — | — | — | — |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season (prior year)
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 · 2025 season (prior year — 2026 data not yet available) ·
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?
Arizona Edge
Arizona +0.17
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 2025 full season · preseason estimate
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
TCU Edge
TCU +1.3
GC Edge (season-to-date)
Teams with this edge win 49.4% of games historically
Based on 2025 full season · preseason estimate
Coaching Matchup
TCU
Sonny Dykes #35
36–17 (68%)
· Yr 5 at school
OC
Gordon Sammis
Yr 1
#23
DC
Andy Avalos
Yr 3
#57
Arizona
Brent Brennan #58
13–12 (52%)
· Yr 3 at school
OC
Seth Doege
Yr 2
#33
DC
Danny Gonzales
Yr 2
#38
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 ✓