Sat, Sep 27 2025
·
Week 5
·
🏟 Boone Pickens Stadium
Stillwater, OK
·
Turf
·
60,218 cap
Baylor✈ 315 miSame TZ
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
49.4%
Baylor wins
Toss-up
Vegas Spread
Baylor -21
O/U 58.5
DraftKings
Advanced Stats
PPA + Success Rate agree → Baylor
· 73.9% ATS historically
↓ See full breakdown
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 |
Oklahoma State 2025 Schedule
Oklahoma State's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/28 | Oklahoma State vs UT Martin | -26.0W27–7 | 56.5 | W27–7 | U | N |
| Sat 9/6 | Oklahoma State at Oregon | +28.5L3–69 | 55.5 | L3–69 | O | N |
| — Bye Week — | ||||||
| Fri 9/19 | Oklahoma State vs Tulsa | -10.5L12–19 | 54.5 | L12–19 | U | N |
| Sat 9/27 | Oklahoma State vs Baylor | +21.0L27–45 | 58.5 | L27–45 | O | Y |
| Sat 10/4 | Oklahoma State at Arizona | +21.5L13–41 | 56.5 | L13–41 | U | N |
| Sat 10/11 | Oklahoma State vs Houston | +14.5L17–39 | 47.5 | L17–39 | O | N |
| Sat 10/18 | Oklahoma State vs Cincinnati | +23.5L17–49 | 57.5 | L17–49 | O | N |
| Sat 10/25 | Oklahoma State at Texas Tech | +37.5L0–42 | 56.5 | L0–42 | U | N |
| Sat 11/1 | Oklahoma State at Kansas | +24.5L21–38 | 54.5 | L21–38 | O | Y |
| — Bye Week — | ||||||
| Sat 11/15 | Oklahoma State vs Kansas State | +19.5L6–14 | 50.5 | L6–14 | U | Y |
| Sat 11/22 | Oklahoma State at UCF | +13.5L14–17 | 47.5 | L14–17 | U | Y |
| Sat 11/29 | Oklahoma State vs Iowa State | +13.5L13–20 | 47.5 | L13–20 | U | Y |
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
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 · 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?
Baylor +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 2 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Baylor Edge
Baylor +0.2
GC Edge (season-to-date)
Teams with this edge win 49.4% of games historically
Based on 3 games this season
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
31–29 (52%)
· Yr 6 at school
OC
Jake Spavital
Yr 2
#1
DC
Matt Powledge
Yr 3
#1
Oklahoma State
Mike Gundy #1
169–88 (66%)
· Yr 21 at school
OC
Doug Meacham
Yr 1
#1
DC
Todd Grantham
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 ✓