Matchup Prediction
Maryland
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Maryland entering this game.
Momentum Control
73.7%
Maryland wins
Solid
Game Control
75.9%
Maryland wins
Solid
Vegas Spread
Maryland -7
O/U 61.5
teamrankings
Advanced Stats
PPA + Success Rate agree → Maryland
· 73.9% ATS historically
↓ See full breakdown
Maryland 2021 Schedule
Maryland's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Maryland vs West Virginia | +2.5W30–24 | 56.0 | W30–24 | U | Y |
| Sat 9/11 | Maryland vs Howard | -48.5W62–0 | 56.0 | W62–0 | O | Y |
| Fri 9/17 | Maryland at Illinois | -7.0W20–17 | 61.5 | W20–17 | U | N |
| Sat 9/25 | Maryland vs Kent State | -13.0W37–16 | 71.5 | W37–16 | U | Y |
| Fri 10/1 | Maryland vs Iowa | +3.0L14–51 | 47.5 | L14–51 | O | N |
| Sat 10/9 | Maryland at Ohio State | +22.0L17–66 | 71.5 | L17–66 | O | N |
| — Bye Week — | ||||||
| Sat 10/23 | Maryland at Minnesota | +4.0L16–34 | 53.0 | L16–34 | U | N |
| Sat 10/30 | Maryland vs Indiana | -3.5W38–35 | 48.0 | W38–35 | O | N |
| Sat 11/6 | Maryland vs Penn State | +10.0L14–31 | 56.5 | L14–31 | U | N |
| Sat 11/13 | Maryland at Michigan State | +11.5L21–40 | 60.0 | L21–40 | O | N |
| Sat 11/20 | Maryland vs Michigan | +16.0L18–59 | 58.5 | L18–59 | O | N |
| Sat 11/27 | Maryland at Rutgers | +2.0W40–16 | 53.0 | W40–16 | O | Y |
| Wed 12/29 | Maryland vs Virginia Tech | -4.0W54–10 | 55.0 | W54–10 | O | Y |
Illinois 2021 Schedule
Illinois's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/28 | Illinois vs Nebraska | +6.5W30–22 | 52.0 | W30–22 | U | Y |
| Sat 9/4 | Illinois vs UTSA | -4.5L30–37 | 52.0 | L30–37 | O | N |
| Sat 9/11 | Illinois at Virginia | +10.5L14–42 | 57.0 | L14–42 | U | N |
| Fri 9/17 | Illinois vs Maryland | +7.0L17–20 | 61.5 | L17–20 | U | Y |
| Sat 9/25 | Illinois at Purdue | +10.5L9–13 | 53.5 | L9–13 | U | Y |
| Sat 10/2 | Illinois vs Charlotte | -10.0W24–14 | 54.0 | W24–14 | U | N |
| Sat 10/9 | Illinois vs Wisconsin | +12.5L0–24 | 42.0 | L0–24 | U | N |
| — Bye Week — | ||||||
| Sat 10/23 | Illinois at Penn State | +24.5W20–18 | 46.0 | W20–18 | U | Y |
| Sat 10/30 | Illinois vs Rutgers | +1.5L14–20 | 41.5 | L14–20 | U | N |
| Sat 11/6 | Illinois at Minnesota | +14.5W14–6 | 44.5 | W14–6 | U | Y |
| — Bye Week — | ||||||
| Sat 11/20 | Illinois at Iowa | +12.0L23–33 | 37.5 | L23–33 | O | Y |
| Sat 11/27 | Illinois vs Northwestern | -7.0W47–14 | 45.0 | W47–14 | O | Y |
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
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Maryland
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?
Maryland Edge
Maryland +1.67
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Maryland Edge
Maryland +42.4
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 3 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Maryland 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
Maryland
Mike Locksley #1
9–17 (35%)
· Yr 3 at school
OC
Dan Enos
Yr 1
#1
DC
Brian Williams
Yr 1
#1
Illinois
Bret Bielema #1
1–3 (25%)
· Yr 1 at school
OC
Tony Petersen
Yr 1
#1
DC
Ryan Walters
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 ✓