Matchup Prediction
TCU
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
TCU entering this game.
Momentum Control
71.6%
TCU wins
Solid
Game Control
67.1%
TCU wins
Solid
Vegas Spread
TCU -3.5
O/U 66.5
DraftKings
Advanced Stats
All 4 factors agree → TCU
· 83.1% ATS historically when all four align
↓ See full breakdown
Baylor 2025 Schedule
Baylor's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/29 | Baylor vs Auburn | +1.5L24–38 | 57.5 | L24–38 | O | N |
| Sat 9/6 | Baylor at SMU | +3.0W48–45 | 65.5 | W48–45 | O | Y |
| Sat 9/13 | Baylor vs Samford | -51.5W42–7 | 65.5 | W42–7 | U | N |
| Sat 9/20 | Baylor vs Arizona State | -3.0L24–27 | 60.5 | L24–27 | U | N |
| Sat 9/27 | Baylor at Oklahoma State | -21.0W45–27 | 58.5 | W45–27 | O | N |
| Sat 10/4 | Baylor vs Kansas State | -4.5W35–34 | 59.5 | W35–34 | O | N |
| — Bye Week — | ||||||
| Sat 10/18 | Baylor at TCU | +3.5L36–42 | 66.5 | L36–42 | O | N |
| Sat 10/25 | Baylor at Cincinnati | +3.5L20–41 | 68.5 | L20–41 | U | N |
| Sat 11/1 | Baylor vs UCF | -3.0W30–3 | 58.5 | W30–3 | U | Y |
| — Bye Week — | ||||||
| Sat 11/15 | Baylor vs Utah | +9.5L28–55 | 60.5 | L28–55 | O | N |
| Sat 11/22 | Baylor at Arizona | +6.5L17–41 | 61.5 | L17–41 | U | N |
| Sat 11/29 | Baylor vs Houston | -2.5L24–31 | 57.5 | L24–31 | U | N |
TCU 2025 Schedule
TCU's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Mon 9/1 | TCU at North Carolina | -3.0W48–14 | 59.5 | W48–14 | O | Y |
| — Bye Week — | ||||||
| Sat 9/13 | TCU vs Abilene Christian | -42.5W42–21 | 60.5 | W42–21 | O | N |
| Sat 9/20 | TCU vs SMU | -6.5W35–24 | 63.5 | W35–24 | U | Y |
| Fri 9/26 | TCU at Arizona State | +2.5L24–27 | 54.5 | L24–27 | U | N |
| Sat 10/4 | TCU vs Colorado | -13.5W35–21 | 57.5 | W35–21 | U | Y |
| Sat 10/11 | TCU at Kansas State | -3.0L28–41 | 54.5 | L28–41 | O | N |
| Sat 10/18 | TCU vs Baylor | -3.5W42–36 | 66.5 | W42–36 | O | Y |
| Sat 10/25 | TCU at West Virginia | -16.5W23–17 | 55.5 | W23–17 | U | N |
| — Bye Week — | ||||||
| Sat 11/8 | TCU vs Iowa State | -7.5L17–20 | 58.5 | L17–20 | U | N |
| Sat 11/15 | TCU at BYU | +3.0L13–44 | 51.5 | L13–44 | O | N |
| Sat 11/22 | TCU at Houston | -1.5W17–14 | 55.5 | W17–14 | U | Y |
| Sat 11/29 | TCU vs Cincinnati | -3.0W45–23 | 58.5 | W45–23 | O | Y |
| Tue 12/30 | TCU vs USC | +4.5W30–27 | 56.5 | W30–27 | 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
→ TCU
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ TCU
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ TCU
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?
TCU Edge
TCU +1.40
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 5 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
TCU Edge
TCU +15.6
GC Edge (season-to-date)
Teams with this edge win 67.1% of games historically
Based on 6 games this season
Actual Result
CSS Battle
Tie
1 — 1 sequences
✗ Predicted incorrectly
GC Battle
TCU
66.9 — 10.3 GC score
✓ Predicted correctly
Game Result
TCU won by 6
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on TCU with a moderate edge in both. This is the strongest ATS signal in our backtest: teams in this situation have covered 55.8% of the time (n=113).
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Baylor
Dave Aranda #1
31–29 (52%)
· Yr 6 at school
OC
Jake Spavital
Yr 2
#1
DC
Matt Powledge
Yr 3
#1
TCU
Sonny Dykes #1
26–13 (67%)
· Yr 4 at school
OC
Kendal Briles
Yr 3
#1
DC
Andy Avalos
Yr 2
#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 ✓