Matchup Prediction
Toss-up — no clear edge
Neither metric shows a meaningful pre-game edge in this matchup.
Momentum Control
58.4%
—
Lean
Game Control
58.3%
Baylor wins
Lean
Vegas Spread
Utah -14.5
O/U 52.5
ESPN Bet
Advanced Stats
PPA + Success Rate agree → Baylor
· 73.9% ATS historically
↓ See full breakdown
Baylor 2024 Schedule
Baylor's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Baylor vs Tarleton State | -33.5W45–3 | 53.5 | W45–3 | U | Y |
| Sat 9/7 | Baylor at Utah | +14.5L12–23 | 52.5 | L12–23 | U | Y |
| Sat 9/14 | Baylor vs Air Force | -17.5W31–3 | 40.5 | W31–3 | U | Y |
| Sat 9/21 | Baylor at Colorado | +2.5L31–38 | 52.5 | L31–38 | O | N |
| Sat 9/28 | Baylor vs BYU | -3.0L28–34 | 47.0 | L28–34 | O | N |
| Sat 10/5 | Baylor at Iowa State | +13.0L21–43 | 45.0 | L21–43 | O | N |
| — Bye Week — | ||||||
| Sat 10/19 | Baylor at Texas Tech | +4.5W59–35 | 56.0 | W59–35 | O | Y |
| Sat 10/26 | Baylor vs Oklahoma State | -7.0W38–28 | 64.5 | W38–28 | O | Y |
| Sat 11/2 | Baylor vs TCU | -2.5W37–34 | 64.0 | W37–34 | O | Y |
| — Bye Week — | ||||||
| Sat 11/16 | Baylor at West Virginia | -2.0W49–35 | 60.0 | W49–35 | O | Y |
| Sat 11/23 | Baylor at Houston | -7.0W20–10 | 51.0 | W20–10 | U | Y |
| Sat 11/30 | Baylor vs Kansas | +2.5W45–17 | 62.5 | W45–17 | U | Y |
| Tue 12/31 | Baylor vs LSU | -3.0L31–44 | 62.5 | L31–44 | O | N |
Utah 2024 Schedule
Utah's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/29 | Utah vs Southern Utah | -37.5W49–0 | 55.5 | W49–0 | U | Y |
| Sat 9/7 | Utah vs Baylor | -14.5W23–12 | 52.5 | W23–12 | U | N |
| Sat 9/14 | Utah at Utah State | -20.5W38–21 | 43.5 | W38–21 | O | N |
| Sat 9/21 | Utah at Oklahoma State | -1.0W22–19 | 53.5 | W22–19 | U | Y |
| Sat 9/28 | Utah vs Arizona | -7.5L10–23 | 47.0 | L10–23 | U | N |
| — Bye Week — | ||||||
| Fri 10/11 | Utah at Arizona State | -6.0L19–27 | 46.5 | L19–27 | U | N |
| Sat 10/19 | Utah vs TCU | -3.0L7–13 | 52.0 | L7–13 | U | N |
| Sat 10/26 | Utah at Houston | -4.5L14–17 | 36.0 | L14–17 | U | N |
| — Bye Week — | ||||||
| Sat 11/9 | Utah vs BYU | +3.5L21–22 | 40.5 | L21–22 | O | Y |
| Sat 11/16 | Utah at Colorado | +13.5L24–49 | 43.5 | L24–49 | O | N |
| Sat 11/23 | Utah vs Iowa State | +6.5L28–31 | 42.5 | L28–31 | O | Y |
| Fri 11/29 | Utah at UCF | +9.5W28–14 | 45.5 | W28–14 | 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
→ Baylor
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?
Baylor Edge
Baylor +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 0 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Baylor Edge
Baylor +6.5
GC Edge (season-to-date)
Teams with this edge win 58.3% of games historically
Based on 1 game this season
Actual Result
CSS Battle
Utah
2 — 1 sequences
✗ Predicted incorrectly
GC Battle
Utah
89.5 — 4.6 GC score
✗ Predicted incorrectly
Game Result
Utah won by 11
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
CSS and GC disagree on this matchup. When the metrics split, historical cover rates are essentially random — treat this as a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Baylor
Dave Aranda #1
23–25 (48%)
· Yr 5 at school
OC
Jake Spavital
Yr 1
#1
DC
Matt Powledge
Yr 2
#1
Utah
Kyle Whittingham #1
162–79 (67%)
· Yr 20 at school
OC
Andy Ludwig
Yr 3
#1
DC
Morgan Scalley
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: CSS is not a predictive 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: GS is not a predictive 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: CSS is not a predictive 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: GS is not a predictive 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 ✓