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
50.6%
—
Toss-up
Vegas Spread
Marshall -3.5
O/U 46.5
teamrankings
Advanced Stats
All 4 factors agree → Marshall
· 83.1% ATS historically when all four align
↓ See full breakdown
Marshall 2021 Schedule
Marshall's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Marshall at Navy | -3.5W49–7 | 46.5 | W49–7 | O | Y |
| Sat 9/11 | Marshall vs North Carolina Central | -42.5W44–10 | 53.5 | W44–10 | O | N |
| Sat 9/18 | Marshall vs East Carolina | -11.0L38–42 | 58.5 | L38–42 | O | N |
| Thu 9/23 | Marshall at App State | +7.0L30–31 | 59.0 | L30–31 | O | Y |
| Sat 10/2 | Marshall at Middle Tennessee | -11.0L28–34 | 66.0 | L28–34 | U | N |
| Sat 10/9 | Marshall vs Old Dominion | -21.5W20–13 | 62.0 | W20–13 | U | N |
| Fri 10/15 | Marshall at North Texas | -11.0W49–21 | 66.5 | W49–21 | O | Y |
| — Bye Week — | ||||||
| Sat 10/30 | Marshall vs Florida International | -21.5W38–0 | 64.0 | W38–0 | U | Y |
| Sat 11/6 | Marshall at Florida Atlantic | -1.0W28–13 | 58.0 | W28–13 | U | Y |
| Sat 11/13 | Marshall vs UAB | -4.5L14–21 | 55.5 | L14–21 | U | N |
| Sat 11/20 | Marshall at Charlotte | -14.0W49–28 | 62.0 | W49–28 | O | Y |
| Sat 11/27 | Marshall vs Western Kentucky | +1.0L21–53 | 75.5 | L21–53 | U | N |
| Sat 12/18 | Marshall vs Louisiana | +4.0L21–36 | 55.5 | L21–36 | O | N |
Navy 2021 Schedule
Navy's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Navy vs Marshall | +3.5L7–49 | 46.5 | L7–49 | O | N |
| Sat 9/11 | Navy vs Air Force | +6.0L3–23 | 40.0 | L3–23 | U | N |
| — Bye Week — | ||||||
| Sat 9/25 | Navy at Houston | +20.0L20–28 | 47.0 | L20–28 | O | Y |
| Sat 10/2 | Navy vs UCF | +15.0W34–30 | 52.5 | W34–30 | O | Y |
| Sat 10/9 | Navy vs SMU | +13.5L24–31 | 57.0 | L24–31 | U | Y |
| Thu 10/14 | Navy at Memphis | +11.0L17–35 | 55.5 | L17–35 | U | N |
| Sat 10/23 | Navy vs Cincinnati | +28.5L20–27 | 49.5 | L20–27 | U | Y |
| Fri 10/29 | Navy at Tulsa | +11.0W20–17 | 46.0 | W20–17 | U | Y |
| Sat 11/6 | Navy at Notre Dame | +21.0L6–34 | 47.5 | L6–34 | U | N |
| — Bye Week — | ||||||
| Sat 11/20 | Navy vs East Carolina | +3.5L35–38 | 46.0 | L35–38 | O | Y |
| Sat 11/27 | Navy at Temple | -13.5W38–14 | 42.0 | W38–14 | O | Y |
| — Bye Week — | ||||||
| Sat 12/11 | Navy at Army | -7.0W17–13 | 35.5 | W17–13 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2021 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 · 2021 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?
Marshall Edge
Marshall +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 0 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Marshall Edge
Marshall +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 0 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Navy, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Marshall
Charles Huff #1
2–1 (67%)
· Yr 1 at school
OC
Tim Cramsey
Yr 1
#1
DC
Lance Guidry
Yr 1
#1
Navy
Ken Niumatalolo #1
101–69 (59%)
· Yr 15 at school
OC
Vacant
Yr 1
#1
DC
Brian Newberry
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: 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 ✓