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
64.9%
Maryland wins
Lean
Vegas Spread
Rutgers -1.5
O/U 56.5
DraftKings
Advanced Stats
3 factors agree (PPA + PPO + Havoc) → Maryland
· 82.4% ATS historically
↓ See full breakdown
Maryland 2025 Schedule
Maryland's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Maryland vs Florida Atlantic | -16.5W39–7 | 57.5 | W39–7 | U | Y |
| Fri 9/5 | Maryland vs Northern Illinois | -17.0W20–9 | 44.5 | W20–9 | U | N |
| Sat 9/13 | Maryland vs Towson | -28.5W44–17 | 53.5 | W44–17 | O | N |
| Sat 9/20 | Maryland at Wisconsin | +10.5W27–10 | 44.5 | W27–10 | U | Y |
| — Bye Week — | ||||||
| Sat 10/4 | Maryland vs Washington | +5.5L20–24 | 52.5 | L20–24 | U | Y |
| Sat 10/11 | Maryland vs Nebraska | +7.0L31–34 | 47.5 | L31–34 | O | Y |
| Sat 10/18 | Maryland at UCLA | +3.5L17–20 | 52.5 | L17–20 | U | Y |
| — Bye Week — | ||||||
| Sat 11/1 | Maryland vs Indiana | +21.0L10–55 | 50.5 | L10–55 | O | N |
| Sat 11/8 | Maryland at Rutgers | +1.5L20–35 | 56.5 | L20–35 | U | N |
| Sat 11/15 | Maryland at Illinois | +15.5L6–24 | 51.5 | L6–24 | U | N |
| Sat 11/22 | Maryland vs Michigan | +14.0L20–45 | 46.5 | L20–45 | O | N |
| Sat 11/29 | Maryland vs Michigan State | +4.0L28–38 | 49.5 | L28–38 | O | N |
Rutgers 2025 Schedule
Rutgers's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/28 | Rutgers vs Ohio | -11.5W34–31 | 46.5 | W34–31 | O | N |
| Sat 9/6 | Rutgers vs Miami (OH) | -15.5W45–17 | 45.5 | W45–17 | O | Y |
| Sat 9/13 | Rutgers vs Norfolk State | -44.5W60–10 | 56.5 | W60–10 | O | Y |
| Fri 9/19 | Rutgers vs Iowa | +2.5L28–38 | 46.5 | L28–38 | O | N |
| Sat 9/27 | Rutgers at Minnesota | +3.5L28–31 | 51.5 | L28–31 | O | Y |
| — Bye Week — | ||||||
| Fri 10/10 | Rutgers at Washington | +9.5L19–38 | 62.5 | L19–38 | U | N |
| Sat 10/18 | Rutgers vs Oregon | +17.5L10–56 | 62.5 | L10–56 | O | N |
| Sat 10/25 | Rutgers at Purdue | +2.5W27–24 | 60.5 | W27–24 | U | Y |
| Sat 11/1 | Rutgers at Illinois | +13.5L13–35 | 63.5 | L13–35 | U | N |
| Sat 11/8 | Rutgers vs Maryland | -1.5W35–20 | 56.5 | W35–20 | U | Y |
| — Bye Week — | ||||||
| Sat 11/22 | Rutgers at Ohio State | +29.0L9–42 | 54.0 | L9–42 | U | N |
| Sat 11/29 | Rutgers vs Penn State | +14.5L36–40 | 55.5 | L36–40 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season
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
→ Maryland
Elite · 73.9% ATS
PPA + Success Rate
Split
Metrics disagree
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 · 2025 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?
Maryland Edge
Maryland +0.02
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 8 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Maryland Edge
Maryland +18.9
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 9 games this season
Actual Result
CSS Battle
Rutgers
1 — 0 sequences
✗ Predicted incorrectly
GC Battle
Rutgers
56.3 — 26.5 GC score
✗ Predicted incorrectly
Game Result
Rutgers won by 15
✗ 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 solid GC edge. Teams with this profile have covered 53.0% of the time historically (n=330) — a mild lean.
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
Rutgers
Greg Schiano #1
26–33 (44%)
· Yr 6 at school
OC
Kirk Ciarrocca
Yr 3
#1
DC
Robb Smith
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: 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 ✓
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 ✓