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
76%
TCU wins
Strong
Vegas Spread
TCU -16.5
O/U 52.0
DraftKings
Advanced Stats
PPA + Success Rate agree → TCU
· 73.9% ATS historically
↓ See full breakdown
Houston 2024 Schedule
Houston's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Houston vs UNLV | -3.0L7–27 | 56.0 | L7–27 | U | N |
| Sat 9/7 | Houston at Oklahoma | +27.5L12–16 | 48.5 | L12–16 | U | Y |
| Sat 9/14 | Houston vs Rice | -3.5W33–7 | 43.5 | W33–7 | U | Y |
| Sat 9/21 | Houston at Cincinnati | +4.0L0–34 | 47.5 | L0–34 | U | N |
| Sat 9/28 | Houston vs Iowa State | +16.0L0–20 | 43.0 | L0–20 | U | N |
| Fri 10/4 | Houston at TCU | +16.5W30–19 | 52.0 | W30–19 | U | Y |
| — Bye Week — | ||||||
| Sat 10/19 | Houston vs Kansas | +4.5L14–42 | 45.5 | L14–42 | O | N |
| Sat 10/26 | Houston vs Utah | +4.5W17–14 | 36.0 | W17–14 | U | Y |
| Sat 11/2 | Houston vs Kansas State | +12.5W24–19 | 46.5 | W24–19 | U | Y |
| — Bye Week — | ||||||
| Fri 11/15 | Houston at Arizona | +1.0L3–27 | 46.5 | L3–27 | U | N |
| Sat 11/23 | Houston vs Baylor | +7.0L10–20 | 51.0 | L10–20 | U | N |
| Sat 11/30 | Houston at BYU | +9.5L18–30 | 39.5 | L18–30 | O | N |
TCU 2024 Schedule
TCU's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/30 | TCU at Stanford | -8.0W34–27 | 58.5 | W34–27 | O | N |
| Sat 9/7 | TCU vs Long Island University | -45.5W45–0 | 56.5 | W45–0 | U | N |
| Sat 9/14 | TCU vs UCF | -1.5L34–35 | 61.5 | L34–35 | O | N |
| Sat 9/21 | TCU at SMU | -1.0L42–66 | 58.5 | L42–66 | O | N |
| Sat 9/28 | TCU vs Kansas | +1.5W38–27 | 58.5 | W38–27 | O | Y |
| Fri 10/4 | TCU vs Houston | -16.5L19–30 | 52.0 | L19–30 | U | N |
| — Bye Week — | ||||||
| Sat 10/19 | TCU at Utah | +3.0W13–7 | 52.0 | W13–7 | U | Y |
| Sat 10/26 | TCU vs Texas Tech | -5.0W35–34 | 66.0 | W35–34 | O | N |
| Sat 11/2 | TCU at Baylor | +2.5L34–37 | 64.0 | L34–37 | O | N |
| Sat 11/9 | TCU vs Oklahoma State | -10.5W38–13 | 68.5 | W38–13 | U | Y |
| — Bye Week — | ||||||
| Sat 11/23 | TCU vs Arizona | -10.5W49–28 | 60.0 | W49–28 | O | Y |
| Sat 11/30 | TCU at Cincinnati | -2.5W20–13 | 58.5 | W20–13 | U | Y |
| Sat 12/28 | TCU vs Louisiana | -9.5W34–3 | 61.0 | W34–3 | U | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 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
→ 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 · 2024 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 +1.00
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
TCU Edge
TCU +25.2
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 5 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on TCU 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
Houston
Willie Fritz #1
0–0 (0%)
· Yr 1 at school
OC
Kevin Barbay
Yr 1
#1
DC
Shiel Wood
Yr 1
#1
TCU
Sonny Dykes #1
18–9 (67%)
· Yr 3 at school
OC
Kendal Briles
Yr 2
#1
DC
Andy Avalos
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 ✓