Maryland at UCLA Week 8 College Football Matchup Maryland at UCLA Matchup - Week 8
Sat, Oct 18 2025 · Week 8 · 🏟 Rose Bowl Pasadena, CA · Turf · 92,542 cap
Maryland✈ 2,291 mi-3 hr TZ
Away
17 20
Final
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📊 Punt & Rally Projection
Maryland
26
UCLA
25
P&R Line Maryland -1.5
P&R Total O/U 50.5
Confidence 90 High
Vegas UCLA -3.5 · O/U 52.5
Matchup Prediction
Maryland has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor Maryland entering this game.
Momentum Control
61.3%
Maryland wins
Lean
Game Control
75.9%
Maryland wins
Solid
Vegas Spread
UCLA -3.5
O/U 52.5
Bovada
Advanced Stats
All 4 factors agree → Maryland · 83.1% ATS historically when all four align
↓ See full breakdown
Maryland 2025 Schedule
Maryland's 2025 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 8/30Maryland vs Florida Atlantic-16.5W39–757.5W39–7UY
Fri 9/5Maryland vs Northern Illinois-17.0W20–944.5W20–9UN
Sat 9/13Maryland vs Towson-28.5W44–1753.5W44–17ON
Sat 9/20Maryland at Wisconsin+10.5W27–1044.5W27–10UY
— Bye Week —
Sat 10/4Maryland vs Washington+5.5L20–2452.5L20–24UY
Sat 10/11Maryland vs Nebraska+7.0L31–3447.5L31–34OY
Sat 10/18Maryland at UCLA+3.5L17–2052.5L17–20UY
— Bye Week —
Sat 11/1Maryland vs Indiana+21.0L10–5550.5L10–55ON
Sat 11/8Maryland at Rutgers+1.5L20–3556.5L20–35UN
Sat 11/15Maryland at Illinois+15.5L6–2451.5L6–24UN
Sat 11/22Maryland vs Michigan+14.0L20–4546.5L20–45ON
Sat 11/29Maryland vs Michigan State+4.0L28–3849.5L28–38ON
UCLA 2025 Schedule
UCLA's 2025 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 8/30UCLA vs Utah+6.5L10–4350.5L10–43ON
Sat 9/6UCLA at UNLV-2.5L23–3054.5L23–30UN
Fri 9/12UCLA vs New Mexico-15.5L10–3552.5L10–35UN
— Bye Week —
Sat 9/27UCLA at Northwestern+6.0L14–1745.5L14–17UY
Sat 10/4UCLA vs Penn State+24.5W42–3748.5W42–37OY
Sat 10/11UCLA at Michigan State+7.0W38–1351.5W38–13UY
Sat 10/18UCLA vs Maryland-3.5W20–1752.5W20–17UN
Sat 10/25UCLA at Indiana+26.5L6–5653.5L6–56ON
— Bye Week —
Sat 11/8UCLA vs Nebraska-1.5L21–2845.5L21–28ON
Sat 11/15UCLA at Ohio State+33.5L10–4846.5L10–48ON
Sat 11/22UCLA vs Washington+10.5L14–4851.5L14–48ON
Sat 11/29UCLA at USC+21.0L10–2959.0L10–29UY
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2025 season
Maryland PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Maryland
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Maryland
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Maryland
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Maryland #85
+0.401
UCLA #96
+0.259
Maryland Edge
PPA Passing
Pass efficiency edge · Strong predictor
Maryland #77
+0.560
UCLA #126
+0.258
Maryland Edge
Havoc Total
Def. disruption rate · Strong predictor
Maryland #104
0.141
UCLA #130
0.120
TFLs, sacks, PBUs, forced fumbles — higher is better
Maryland Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Maryland #100
+7.999
UCLA #124
+6.582
Maryland Edge
Success Rate
Play consistency edge · Solid predictor
Maryland #100
+0.904
UCLA #75
+0.861
Maryland Edge
Field Position
Avg start (lower=better) · Solid predictor
Maryland #54
70.5
UCLA #129
73.6
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Maryland Edge
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
UCLA Rated Higher
Overall Power Rating
Maryland
4.5
UCLA
6.6
Offense Rating
Maryland
17.5
UCLA
19.6
Defense Rating (lower = better defense)
Maryland
13.0
UCLA
12.9
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? Maryland Edge
Avg sequences created per game
Maryland #94
1.60
UCLA #89
1.00
Avg sequences allowed per game (lower is better)
Maryland #120
1.20
UCLA #119
2.00
Maryland +0.60
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 6 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Maryland Edge
Avg GC score per game (offense)
Maryland #1
74.2
UCLA #1
31.9
Avg GC score allowed per game (lower is better)
Maryland #80
15.8
UCLA #132
59.3
Maryland +42.3
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 6 games this season
Actual Result
CSS Battle
UCLA
1 — 0 sequences
✗ Predicted incorrectly
GC Battle
UCLA
46.6 — 23.8 GC score
✗ Predicted incorrectly
Game Result
UCLA won by 3
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

Both metrics agree on Maryland 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
Maryland
Mike Locksley #1
33–41 (45%) · Yr 7 at school
OC Pep Hamilton Yr 1 #1
DC Brian Williams Yr 2 #1
Staff Rating
0.00 #1
UCLA
DeShaun Foster #1
5–7 (42%) · Yr 2 at school
OC Tino Sunseri Yr 1 #1
DC Ikaika Malloe Yr 2 #1
Staff Rating
0.00 #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