Penn State at UCLA Week 6 College Football Matchup Penn State at UCLA Matchup - Week 6
Sat, Oct 4 2025 · Week 6 · 🏟 Rose Bowl Pasadena, CA · Turf · 92,542 cap
Penn State✈ 2,237 mi-3 hr TZ
37 42
Final
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📊 Punt & Rally Projection
Penn State
35
UCLA
16
P&R Line Penn State -19
P&R Total O/U 51.5
Confidence 90 High
Vegas Penn State -24.5 · O/U 48.5
Matchup Prediction
Penn State has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor Penn State entering this game.
Momentum Control
80.6%
Penn State wins
Strong
Game Control
75.9%
Penn State wins
Solid
Vegas Spread
Penn State -24.5
O/U 48.5
DraftKings
Advanced Stats
All 4 factors agree → Penn State · 83.1% ATS historically when all four align
↓ See full breakdown
Penn State 2025 Schedule
Penn State's 2025 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 8/30Penn State vs Nevada-45.5W46–1158.5W46–11UN
Sat 9/6Penn State vs Florida International-42.0W34–053.5W34–0UN
Sat 9/13Penn State vs Villanova-46.5W52–657.5W52–6ON
— Bye Week —
Sat 9/27Penn State vs Oregon-4.5L24–3052.5L24–30ON
Sat 10/4Penn State at UCLA-24.5L37–4248.5L37–42ON
Sat 10/11Penn State vs Northwestern-20.5L21–2246.5L21–22UN
Sat 10/18Penn State at Iowa+3.5L24–2541.5L24–25OY
— Bye Week —
Sat 11/1Penn State at Ohio State+17.5L14–3845.5L14–38ON
Sat 11/8Penn State vs Indiana+13.5L24–2750.5L24–27OY
Sat 11/15Penn State at Michigan State-7.0W28–1048.5W28–10UY
Sat 11/22Penn State vs Nebraska-7.5W37–1045.5W37–10OY
Sat 11/29Penn State at Rutgers-14.5W40–3655.5W40–36ON
Sat 12/27Penn State vs Clemson+2.5W22–1047.5W22–10UY
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
Penn State PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Penn State
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Penn State
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Penn State
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Penn State #32
+0.483
UCLA #96
+0.243
Penn State Edge
PPA Passing
Pass efficiency edge · Strong predictor
Penn State #53
+0.613
UCLA #126
+0.277
Penn State Edge
Havoc Total
Def. disruption rate · Strong predictor
Penn State #63
0.159
UCLA #130
0.120
TFLs, sacks, PBUs, forced fumbles — higher is better
Penn State Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Penn State #25
+8.925
UCLA #124
+6.317
Penn State Edge
Success Rate
Play consistency edge · Solid predictor
Penn State #26
+0.966
UCLA #75
+0.831
Penn State Edge
Field Position
Avg start (lower=better) · Solid predictor
Penn State #14
68.1
UCLA #129
73.6
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Penn State 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
Penn State Rated Higher
Overall Power Rating
Penn State
8.8
UCLA
6.6
Offense Rating
Penn State
19.0
UCLA
19.6
Defense Rating (lower = better defense)
Penn State
10.2
UCLA
12.9
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? Penn State Edge
Avg sequences created per game
Penn State #43
3.33
UCLA #89
0.75
Avg sequences allowed per game (lower is better)
Penn State #35
0.33
UCLA #119
3.00
Penn State +2.58
CSS Edge (season-to-date)
Teams with this edge win 80.6% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Penn State Edge
Avg GC score per game (offense)
Penn State #1
77.7
UCLA #1
8.0
Avg GC score allowed per game (lower is better)
Penn State #35
10.7
UCLA #132
83.2
Penn State +69.7
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 4 games this season
Actual Result
CSS Battle
UCLA
1 — 0 sequences
✗ Predicted incorrectly
GC Battle
UCLA
90.1 — 5.9 GC score
✗ Predicted incorrectly
Game Result
UCLA won by 5
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

Both metrics agree on Penn State 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
Penn State
James Franklin #1
99–41 (71%) · Yr 12 at school
OC Andy Kotelnicki Yr 2 #1
DC Jim Knowles Yr 1 #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