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
76%
UNLV wins
Strong
Vegas Spread
UCLA -2.5
O/U 54.5
Bovada
Advanced Stats
All 4 factors agree → UNLV
· 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 |
UNLV 2025 Schedule
UNLV's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/23 | UNLV vs Idaho State | -30.5W38–31 | 67.0 | W38–31 | O | N |
| Fri 8/29 | UNLV vs Sam Houston | -13.5W38–21 | 58.5 | W38–21 | O | Y |
| Sat 9/6 | UNLV vs UCLA | +2.5W30–23 | 54.5 | W30–23 | U | Y |
| — Bye Week — | ||||||
| Sat 9/20 | UNLV at Miami (OH) | -2.5W41–38 | 49.5 | W41–38 | O | Y |
| — Bye Week — | ||||||
| Sat 10/4 | UNLV at Wyoming | -4.5W31–17 | 50.5 | W31–17 | U | Y |
| Sat 10/11 | UNLV vs Air Force | -7.0W51–48 | 65.5 | W51–48 | O | N |
| Sat 10/18 | UNLV at Boise State | +12.5L31–56 | 60.5 | L31–56 | O | N |
| — Bye Week — | ||||||
| Sat 11/1 | UNLV vs New Mexico | -3.5L35–40 | 61.5 | L35–40 | O | N |
| Sat 11/8 | UNLV at Colorado State | -5.5W42–10 | 60.5 | W42–10 | U | Y |
| Sat 11/15 | UNLV vs Utah State | -4.5W29–26 | 68.5 | W29–26 | U | N |
| Fri 11/21 | UNLV vs Hawai'i | -2.5W38–10 | 64.5 | W38–10 | U | Y |
| Sat 11/29 | UNLV at Nevada | -7.5W42–17 | 53.0 | W42–17 | O | Y |
| Fri 12/5 | UNLV at Boise State | +6.0L21–38 | 60.0 | L21–38 | U | N |
| Tue 12/23 | UNLV vs Ohio | -6.5L10–17 | 64.5 | L10–17 | U | N |
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
→ UNLV
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ UNLV
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ UNLV
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 +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 1 game this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
UNLV Edge
UNLV +60.1
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 2 games this season
Actual Result
CSS Battle
UNLV
3 — 2 sequences
GC Battle
UNLV
89.9 — 5.3 GC score
✓ Predicted correctly
Game Result
UNLV won by 7
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on UNLV 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
UCLA
DeShaun Foster #1
5–7 (42%)
· Yr 2 at school
OC
Tino Sunseri
Yr 1
#1
DC
Ikaika Malloe
Yr 2
#1
UNLV
Dan Mullen #1
0–0 (0%)
· Yr 1 at school
OC
Corey Dennis
Yr 1
#1
DC
Zach Anrett
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 ✓