Marshall at Penn State Week 1 College Football Matchup Marshall at Penn State Matchup - Week 1
Sat, Sep 5 2026 · Week 1 · 🏟 Beaver Stadium University Park, PA · Turf · 106,572 cap
Marshall✈ 293 miSame TZ
Preseason projection — This game has not yet been played and 2026 in-season data is not yet available. Edges are based on 2025 full-season performance. Confidence will increase once in-season games are logged.
📊 Punt & Rally Projection
Marshall
19
Penn State
38
P&R Line Penn State -19.5
P&R Total O/U 56.5
Confidence 66 Good
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
58.4%
Penn State wins
Lean
Game Control
67.1%
Penn State wins
Solid
Advanced Stats
3 factors agree (PPA + PPO + Havoc) → Penn State · 82.4% ATS historically
↓ See full breakdown
Marshall 2026 Schedule
Marshall's 2026 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/5Marshall at Penn State+19.5
Penn State 2026 Schedule
Penn State's 2026 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/5Penn State vs Marshall-19.5
Sat 9/12Penn State at Temple-15.5
Sat 9/19Penn State vs Buffalo-25
Sat 9/26Penn State vs Wisconsin-18
Fri 10/2Penn State at Northwestern-8.5
Sat 10/10Penn State vs USC+1
Sat 10/17Penn State at Michigan+4.5
— Bye Week —
Sat 10/31Penn State vs Purdue-21
Sat 11/7Penn State at Washington+4
Sat 11/14Penn State vs Minnesota-12
Sat 11/21Penn State vs Rutgers-16.5
Sat 11/28Penn State at Maryland-8.5
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2025 season (prior year)
Penn State PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Penn State
Elite · 73.9% ATS
PPA + Success Rate
Split
Metrics disagree
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Marshall #56
+0.307
Penn State #32
+0.387
Penn State Edge
PPA Passing
Pass efficiency edge · Strong predictor
Marshall #28
+0.563
Penn State #53
+0.618
Penn State Edge
Havoc Total
Def. disruption rate · Strong predictor
Marshall #67
0.157
Penn State #63
0.159
TFLs, sacks, PBUs, forced fumbles — higher is better
Penn State Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Marshall #52
+7.227
Penn State #25
+7.941
Penn State Edge
Success Rate
Play consistency edge · Solid predictor
Marshall #37
+0.863
Penn State #26
+0.851
Marshall Edge
Field Position
Avg start (lower=better) · Solid predictor
Marshall #12
67.8
Penn State #14
68.1
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Marshall Edge
Advanced stats sourced from CFBD · 2025 season (prior year — 2026 data not yet available) · 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
Marshall #91
-3.1
Penn State #26
8.8
Offense Rating
Marshall #91
13.9
Penn State #30
19.0
Defense Rating (lower = better defense)
Marshall #91
17.0
Penn State #25
10.2
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
Marshall #93
0.91
Penn State #43
1.50
Avg sequences allowed per game (lower is better)
Marshall #90
1.27
Penn State #35
0.67
Penn State +0.59
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 2025 full season · preseason estimate
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Penn State Edge
Avg GC score per game (offense)
Marshall #109
42.0
Penn State #62
54.4
Avg GC score allowed per game (lower is better)
Marshall #70
38.5
Penn State #35
29.6
Penn State +12.3
GC Edge (season-to-date)
Teams with this edge win 67.1% of games historically
Based on 2025 full season · preseason estimate
Coaching Matchup
Marshall
Tony Gibson #95
5–7 (42%) · Yr 2 at school
OC Rod Smith Yr 2 #34
DC Shannon Morrison Yr 2 #109
Staff Rating
2.65 #75
Penn State
Matt Campbell #28
0–0 (0%) · Yr 1 at school
OC Taylor Mouser Yr 1 #43
DC D’Anton Lynn Yr 1 #28
Staff Rating
3.34 #24
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