Matchup Prediction
UCF
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
UCF entering this game.
Momentum Control
61.3%
UCF wins
Lean
Game Control
75.9%
UCF wins
Solid
Vegas Spread
Baylor -3
O/U 58.5
DraftKings
Advanced Stats
3 factors agree (PPA + PPO + Havoc) → UCF
· 82.4% ATS historically
↓ See full breakdown
UCF 2025 Schedule
UCF's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/28 | UCF vs Jacksonville State | -16.5W17–10 | 53.5 | W17–10 | U | N |
| Sat 9/6 | UCF vs North Carolina A&T | -38.0W68–7 | 51.0 | W68–7 | O | Y |
| — Bye Week — | ||||||
| Sat 9/20 | UCF vs North Carolina | -7.0W34–9 | 46.5 | W34–9 | U | Y |
| Sat 9/27 | UCF at Kansas State | +5.5L20–34 | 48.5 | L20–34 | O | N |
| Sat 10/4 | UCF vs Kansas | +4.0L20–27 | 53.5 | L20–27 | U | N |
| Sat 10/11 | UCF at Cincinnati | +10.0L11–20 | 55.5 | L11–20 | U | Y |
| Sat 10/18 | UCF vs West Virginia | -6.5W45–13 | 46.5 | W45–13 | O | Y |
| — Bye Week — | ||||||
| Sat 11/1 | UCF at Baylor | +3.0L3–30 | 58.5 | L3–30 | U | N |
| Fri 11/7 | UCF vs Houston | -1.5L27–30 | 47.5 | L27–30 | O | N |
| Sat 11/15 | UCF at Texas Tech | +24.5L9–48 | 48.5 | L9–48 | O | N |
| Sat 11/22 | UCF vs Oklahoma State | -13.5W17–14 | 47.5 | W17–14 | U | N |
| Sat 11/29 | UCF at BYU | +17.5L21–41 | 46.5 | L21–41 | O | N |
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 |
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
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ UCF
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 ·
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?
UCF Edge
UCF +0.71
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 7 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
UCF Edge
UCF +20.8
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 8 games this season
Actual Result
CSS Battle
Baylor
2 — 0 sequences
✗ Predicted incorrectly
GC Battle
Baylor
94.0 — 3.0 GC score
✗ Predicted incorrectly
Game Result
Baylor won by 27
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on UCF 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
UCF
Scott Frost #1
19–7 (73%)
· Yr 1 at school
OC
Steve Cooper
Yr 1
#1
DC
Alex Grinch
Yr 1
#1
Baylor
Dave Aranda #1
31–29 (52%)
· Yr 6 at school
OC
Jake Spavital
Yr 2
#1
DC
Matt Powledge
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 ✓