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
58.3%
UCF wins
Lean
Vegas Spread
UCF -2
O/U 65.0
William Hill (New Jersey)
Advanced Stats
All 4 factors agree → Kansas
· 83.1% ATS historically when all four align
↓ See full breakdown
UCF 2023 Schedule
UCF's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/31 | UCF vs Kent State | -35.0W56–6 | 54.0 | W56–6 | O | Y |
| Sat 9/9 | UCF at Boise State | -3.0W18–16 | 58.5 | W18–16 | U | N |
| Sat 9/16 | UCF vs Villanova | -26.5W48–14 | 54.0 | W48–14 | O | Y |
| Sat 9/23 | UCF at Kansas State | +6.0L31–44 | 53.5 | L31–44 | O | N |
| Sat 9/30 | UCF vs Baylor | -8.0L35–36 | 56.5 | L35–36 | O | N |
| Sat 10/7 | UCF at Kansas | -2.0L22–51 | 65.0 | L22–51 | O | N |
| — Bye Week — | ||||||
| Sat 10/21 | UCF at Oklahoma | +17.0L29–31 | 67.5 | L29–31 | U | Y |
| Sat 10/28 | UCF vs West Virginia | -6.5L28–41 | 59.5 | L28–41 | O | N |
| Sat 11/4 | UCF at Cincinnati | -3.5W28–26 | 59.5 | W28–26 | U | N |
| Sat 11/11 | UCF vs Oklahoma State | +2.5W45–3 | 63.5 | W45–3 | U | Y |
| Sat 11/18 | UCF at Texas Tech | +2.0L23–24 | 59.0 | L23–24 | U | Y |
| Sat 11/25 | UCF vs Houston | -15.5W27–13 | 61.5 | W27–13 | U | N |
| Fri 12/22 | UCF vs Georgia Tech | -6.0L17–30 | 66.5 | L17–30 | U | N |
Kansas 2023 Schedule
Kansas's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/1 | Kansas vs Missouri State | -32.5W48–17 | 60.5 | W48–17 | O | N |
| Fri 9/8 | Kansas vs Illinois | -3.5W34–23 | 57.5 | W34–23 | U | Y |
| Sat 9/16 | Kansas at Nevada | -28.5W31–24 | 58.0 | W31–24 | U | N |
| Sat 9/23 | Kansas vs BYU | -9.0W38–27 | 55.5 | W38–27 | O | Y |
| Sat 9/30 | Kansas at Texas | +15.5L14–40 | 61.0 | L14–40 | U | N |
| Sat 10/7 | Kansas vs UCF | +2.0W51–22 | 65.0 | W51–22 | O | Y |
| Sat 10/14 | Kansas at Oklahoma State | -3.0L32–39 | 54.0 | L32–39 | O | N |
| — Bye Week — | ||||||
| Sat 10/28 | Kansas vs Oklahoma | +7.0W38–33 | 66.5 | W38–33 | O | Y |
| Sat 11/4 | Kansas at Iowa State | +2.5W28–21 | 53.0 | W28–21 | U | Y |
| Sat 11/11 | Kansas vs Texas Tech | -3.5L13–16 | 61.5 | L13–16 | U | N |
| Sat 11/18 | Kansas vs Kansas State | +7.0L27–31 | 60.5 | L27–31 | U | Y |
| Sat 11/25 | Kansas at Cincinnati | -7.5W49–16 | 59.5 | W49–16 | O | Y |
| Tue 12/26 | Kansas vs UNLV | -8.0W49–36 | 64.5 | W49–36 | 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
All 4 Agree
→ Kansas
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Kansas
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Kansas
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?
UCF Edge
UCF +0.25
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
UCF Edge
UCF +6.2
GC Edge (season-to-date)
Teams with this edge win 58.3% of games historically
Based on 5 games this season
Actual Result
CSS Battle
Kansas
2 — 0 sequences
✗ Predicted incorrectly
GC Battle
Kansas
81.7 — 6.4 GC score
✗ Predicted incorrectly
Game Result
Kansas won by 29
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on UCF. Teams with this edge profile have covered 50.3% historically — essentially a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
UCF
Gus Malzahn #1
21–9 (70%)
· Yr 3 at school
OC
Darin Hinshaw
Yr 1
#1
DC
David Gibbs
Yr 2
#1
Kansas
Lance Leipold #1
11–17 (39%)
· Yr 3 at school
OC
Andy Kotelnicki
Yr 3
#1
DC
Brian Borland
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 ✓