Matchup Prediction
Nebraska
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Nebraska entering this game.
Momentum Control
61.3%
Nebraska wins
Lean
Game Control
75.9%
Nebraska wins
Solid
Vegas Spread
UCLA -1.5
O/U 45.5
DraftKings
Advanced Stats
All 4 factors agree → Nebraska
· 83.1% ATS historically when all four align
↓ See full breakdown
Nebraska 2025 Schedule
Nebraska's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/28 | Nebraska vs Cincinnati | -6.5W20–17 | 52.5 | W20–17 | U | N |
| Sat 9/6 | Nebraska vs Akron | -34.0W68–0 | 47.5 | W68–0 | O | Y |
| Sat 9/13 | Nebraska vs Houston Christian | -48.5W59–7 | 58.5 | W59–7 | O | Y |
| Sat 9/20 | Nebraska vs Michigan | +1.5L27–30 | 47.5 | L27–30 | O | N |
| — Bye Week — | ||||||
| Sat 10/4 | Nebraska vs Michigan State | -12.5W38–27 | 48.5 | W38–27 | O | N |
| Sat 10/11 | Nebraska at Maryland | -7.0W34–31 | 47.5 | W34–31 | O | N |
| Fri 10/17 | Nebraska at Minnesota | -7.0L6–24 | 47.5 | L6–24 | U | N |
| Sat 10/25 | Nebraska vs Northwestern | -7.5W28–21 | 44.5 | W28–21 | O | N |
| Sat 11/1 | Nebraska vs USC | +4.5L17–21 | 59.5 | L17–21 | U | Y |
| Sat 11/8 | Nebraska at UCLA | +1.5W28–21 | 45.5 | W28–21 | O | Y |
| — Bye Week — | ||||||
| Sat 11/22 | Nebraska at Penn State | +7.5L10–37 | 45.5 | L10–37 | O | N |
| Fri 11/28 | Nebraska vs Iowa | +5.5L16–40 | 38.5 | L16–40 | O | N |
| Wed 12/31 | Nebraska vs Utah | +13.5L22–44 | 51.5 | L22–44 | O | N |
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 |
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
→ Nebraska
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Nebraska
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Nebraska
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?
Nebraska Edge
Nebraska +0.75
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 8 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Nebraska Edge
Nebraska +30.6
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 8 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Nebraska 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
Nebraska
Matt Rhule #1
11–13 (46%)
· Yr 3 at school
OC
Dana Holgorsen
Yr 1
#1
DC
John Butler
Yr 1
#1
UCLA
DeShaun Foster #1
5–7 (42%)
· Yr 2 at school
OC
Tino Sunseri
Yr 1
#1
DC
Ikaika Malloe
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: 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 ✓