Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors App State,
while Game Control favors Marshall.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
61.3%
App State wins
Lean
Game Control
58.6%
Marshall wins
Lean
Vegas Spread
Marshall -3
O/U 56.5
DraftKings
Advanced Stats
All 4 factors agree → Marshall
· 83.1% ATS historically when all four align
↓ See full breakdown
App State 2024 Schedule
App State's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | App State vs East Tennessee State | -35.5W38–10 | 58.5 | W38–10 | U | N |
| Sat 9/7 | App State at Clemson | +13.5L20–66 | 53.5 | L20–66 | O | N |
| Sat 9/14 | App State at East Carolina | +0.5W21–19 | 56.5 | W21–19 | U | Y |
| Thu 9/19 | App State vs South Alabama | -8.0L14–48 | 62.5 | L14–48 | U | N |
| — Bye Week — | ||||||
| Sat 10/5 | App State at Marshall | +3.0L37–52 | 56.5 | L37–52 | O | N |
| Sat 10/12 | App State at Louisiana | +10.0L24–34 | 64.0 | L24–34 | U | Y |
| — Bye Week — | ||||||
| Sat 10/26 | App State vs Georgia State | -7.5W33–26 | 59.0 | W33–26 | U | N |
| Sat 11/2 | App State vs Old Dominion | +2.5W28–20 | 58.0 | W28–20 | U | Y |
| Thu 11/7 | App State at Coastal Carolina | -1.5L24–38 | 62.5 | L24–38 | U | N |
| — Bye Week — | ||||||
| Sat 11/23 | App State vs James Madison | +7.5W34–20 | 57.5 | W34–20 | U | Y |
| Sat 11/30 | App State at Georgia Southern | +2.5L20–29 | 60.5 | L20–29 | U | N |
Marshall 2024 Schedule
Marshall's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Marshall vs Stony Brook | -32.5W45–3 | 56.5 | W45–3 | U | Y |
| Sat 9/7 | Marshall at Virginia Tech | +20.5L14–31 | 52.5 | L14–31 | U | Y |
| — Bye Week — | ||||||
| Sat 9/21 | Marshall at Ohio State | +40.0L14–49 | 57.0 | L14–49 | O | Y |
| Sat 9/28 | Marshall vs Western Michigan | -3.5W27–20 | 53.5 | W27–20 | U | Y |
| Sat 10/5 | Marshall vs App State | -3.0W52–37 | 56.5 | W52–37 | O | Y |
| Sat 10/12 | Marshall at Georgia Southern | +1.0L23–24 | 58.5 | L23–24 | U | Y |
| Thu 10/17 | Marshall vs Georgia State | -9.5W35–20 | 51.5 | W35–20 | O | Y |
| — Bye Week — | ||||||
| Sat 11/2 | Marshall vs UL Monroe | -10.5W28–23 | 48.0 | W28–23 | O | N |
| Sat 11/9 | Marshall at Southern Miss | -13.5W37–3 | 53.5 | W37–3 | U | Y |
| Sat 11/16 | Marshall vs Coastal Carolina | -7.5W31–19 | 57.0 | W31–19 | U | Y |
| Sat 11/23 | Marshall at Old Dominion | +3.0W42–35 | 51.0 | W42–35 | O | Y |
| Sat 11/30 | Marshall at James Madison | +2.5W35–33 | 52.5 | W35–33 | O | Y |
| Sat 12/7 | Marshall at Louisiana | +5.0W31–3 | 58.0 | W31–3 | U | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Marshall
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Marshall
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Marshall
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 · 2024 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?
App State Edge
App State +0.33
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Marshall Edge
Marshall +6.8
GC Edge (season-to-date)
Teams with this edge win 58.6% of games historically
Based on 4 games this season
Actual Result
CSS Battle
Tie
1 — 1 sequences
✗ Predicted incorrectly
GC Battle
Marshall
70.1 — 11.4 GC score
✓ Predicted correctly
Game Result
Marshall won by 15
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
CSS and GC disagree on this matchup. When the metrics split, historical cover rates are essentially random — treat this as a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
App State
Shawn Clark #1
35–18 (66%)
· Yr 5 at school
OC
Frank Ponce
Yr 2
#1
DC
Scott Sloan
Yr 2
#1
Marshall
Charles Huff #1
22–17 (56%)
· Yr 4 at school
OC
Seth Doege
Yr 1
#1
DC
Jason Semore
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: CSS is not a predictive 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: GS is not a predictive 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: CSS is not a predictive 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: GS is not a predictive 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 ✓