Matchup Prediction
Baylor
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Baylor entering this game.
Momentum Control
58.4%
Baylor wins
Lean
Game Control
50.6%
Baylor wins
Toss-up
Vegas Spread
Baylor -3
O/U 58.5
DraftKings
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
Houston 2023 Schedule
Houston's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Houston vs UTSA | +2.5W17–14 | 59.5 | W17–14 | U | Y |
| Sat 9/9 | Houston at Rice | -7.5L41–43 | 51.0 | L41–43 | O | N |
| Sat 9/16 | Houston vs TCU | +7.5L13–36 | 64.0 | L13–36 | U | N |
| Sat 9/23 | Houston vs Sam Houston | -11.5W38–7 | 37.0 | W38–7 | O | Y |
| Sat 9/30 | Houston at Texas Tech | +8.5L28–49 | 52.0 | L28–49 | O | N |
| — Bye Week — | ||||||
| Thu 10/12 | Houston vs West Virginia | +3.0W41–39 | 49.5 | W41–39 | O | Y |
| Sat 10/21 | Houston vs Texas | +24.0L24–31 | 60.5 | L24–31 | U | Y |
| Sat 10/28 | Houston at Kansas State | +17.5L0–41 | 61.0 | L0–41 | U | N |
| Sat 11/4 | Houston at Baylor | +3.0W25–24 | 58.5 | W25–24 | U | Y |
| Sat 11/11 | Houston vs Cincinnati | -3.5L14–24 | 53.5 | L14–24 | U | N |
| Sat 11/18 | Houston vs Oklahoma State | +6.5L30–43 | 56.5 | L30–43 | O | N |
| Sat 11/25 | Houston at UCF | +15.5L13–27 | 61.5 | L13–27 | U | Y |
Baylor 2023 Schedule
Baylor's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Baylor vs Texas State | -26.5L31–42 | 58.5 | L31–42 | O | N |
| Sat 9/9 | Baylor vs Utah | +7.0L13–20 | 46.5 | L13–20 | U | Y |
| Sat 9/16 | Baylor vs Long Island University | -44.0W30–7 | 54.0 | W30–7 | U | N |
| Sat 9/23 | Baylor vs Texas | +17.5L6–38 | 49.5 | L6–38 | U | N |
| Sat 9/30 | Baylor at UCF | +8.0W36–35 | 56.5 | W36–35 | O | Y |
| Sat 10/7 | Baylor vs Texas Tech | +2.5L14–39 | 59.5 | L14–39 | U | N |
| — Bye Week — | ||||||
| Sat 10/21 | Baylor at Cincinnati | +2.5W32–29 | 51.5 | W32–29 | O | Y |
| Sat 10/28 | Baylor vs Iowa State | +3.0L18–30 | 47.0 | L18–30 | O | N |
| Sat 11/4 | Baylor vs Houston | -3.0L24–25 | 58.5 | L24–25 | U | N |
| Sat 11/11 | Baylor at Kansas State | +20.5L25–59 | 55.5 | L25–59 | O | N |
| Sat 11/18 | Baylor at TCU | +13.0L17–42 | 62.0 | L17–42 | U | N |
| Sat 11/25 | Baylor vs West Virginia | +6.5L31–34 | 53.5 | L31–34 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2023 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
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 · 2023 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?
Baylor Edge
Baylor +0.38
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 +0.9
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 8 games this season
Actual Result
CSS Battle
Baylor
1 — 0 sequences
✓ Predicted correctly
GC Battle
Houston
13.2 — 64.5 GC score
✗ Predicted incorrectly
Game Result
Houston won by 1
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Baylor, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Houston
Dana Holgorsen #1
28–22 (56%)
· Yr 5 at school
OC
Dana Holgorsen
Yr 1
#1
DC
Doug Belk
Yr 3
#1
Baylor
Dave Aranda #1
21–18 (54%)
· Yr 4 at school
OC
Jeff Grimes
Yr 3
#1
DC
Matt Powledge
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 ✓