Sat, Oct 11 2025
·
Week 7
·
🏟 Spartan Stadium
East Lansing, MI
·
Turf
·
75,005 cap
UCLA✈ 1,901 mi+3 hr TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors UCLA,
while Game Control favors Michigan State.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
61.3%
UCLA wins
Lean
Game Control
76%
Michigan State wins
Strong
Vegas Spread
Michigan State -7
O/U 51.5
DraftKings
Advanced Stats
All 4 factors agree → Michigan State
· 83.1% ATS historically when all four align
↓ See full breakdown
UCLA 2025 Schedule
UCLA's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | UCLA vs Utah | +6.5L10–43 | 50.5 | L10–43 | O | N |
| Sat 9/6 | UCLA at UNLV | -2.5L23–30 | 54.5 | L23–30 | U | N |
| Fri 9/12 | UCLA vs New Mexico | -15.5L10–35 | 52.5 | L10–35 | U | N |
| — Bye Week — | ||||||
| Sat 9/27 | UCLA at Northwestern | +6.0L14–17 | 45.5 | L14–17 | U | Y |
| Sat 10/4 | UCLA vs Penn State | +24.5W42–37 | 48.5 | W42–37 | O | Y |
| Sat 10/11 | UCLA at Michigan State | +7.0W38–13 | 51.5 | W38–13 | U | Y |
| Sat 10/18 | UCLA vs Maryland | -3.5W20–17 | 52.5 | W20–17 | U | N |
| Sat 10/25 | UCLA at Indiana | +26.5L6–56 | 53.5 | L6–56 | O | N |
| — Bye Week — | ||||||
| Sat 11/8 | UCLA vs Nebraska | -1.5L21–28 | 45.5 | L21–28 | O | N |
| Sat 11/15 | UCLA at Ohio State | +33.5L10–48 | 46.5 | L10–48 | O | N |
| Sat 11/22 | UCLA vs Washington | +10.5L14–48 | 51.5 | L14–48 | O | N |
| Sat 11/29 | UCLA at USC | +21.0L10–29 | 59.0 | L10–29 | U | Y |
Michigan State 2025 Schedule
Michigan State's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/29 | Michigan State vs Western Michigan | -18.5W23–6 | 49.5 | W23–6 | U | N |
| Sat 9/6 | Michigan State vs Boston College | -3.5W42–40 | 45.5 | W42–40 | O | N |
| Sat 9/13 | Michigan State vs Youngstown State | -23.5W41–24 | 55.5 | W41–24 | O | N |
| Sat 9/20 | Michigan State at USC | +18.5L31–45 | 55.5 | L31–45 | O | Y |
| — Bye Week — | ||||||
| Sat 10/4 | Michigan State at Nebraska | +12.5L27–38 | 48.5 | L27–38 | O | Y |
| Sat 10/11 | Michigan State vs UCLA | -7.0L13–38 | 51.5 | L13–38 | U | N |
| Sat 10/18 | Michigan State at Indiana | +26.5L13–38 | 49.5 | L13–38 | O | Y |
| Sat 10/25 | Michigan State vs Michigan | +13.5L20–31 | 47.5 | L20–31 | O | Y |
| Sat 11/1 | Michigan State at Minnesota | +4.5L20–23 | 44.5 | L20–23 | U | Y |
| — Bye Week — | ||||||
| Sat 11/15 | Michigan State vs Penn State | +7.0L10–28 | 48.5 | L10–28 | U | N |
| Sat 11/22 | Michigan State at Iowa | +17.5L17–20 | 43.0 | L17–20 | U | Y |
| Sat 11/29 | Michigan State vs Maryland | -4.0W38–28 | 49.5 | W38–28 | O | 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
All 4 Agree
→ Michigan State
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Michigan State
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Michigan State
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?
UCLA Edge
UCLA +0.30
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?
Michigan State Edge
Michigan State +22.1
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 5 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
UCLA
DeShaun Foster #1
5–7 (42%)
· Yr 2 at school
OC
Tino Sunseri
Yr 1
#1
DC
Ikaika Malloe
Yr 2
#1
Michigan State
Jonathan Smith #1
5–7 (42%)
· Yr 2 at school
OC
Brian Lindgren
Yr 2
#1
DC
Joe Rossi
Yr 2
#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 ✓