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 -28
O/U 65.0
teamrankings
Advanced Stats
All 4 factors agree → Maryland
· 83.1% ATS historically when all four align
↓ See full breakdown
Maryland 2022 Schedule
Maryland's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Maryland vs Buffalo | -24.0W31–10 | 66.0 | W31–10 | U | N |
| Sat 9/10 | Maryland at Charlotte | -28.0W56–21 | 65.0 | W56–21 | O | Y |
| Sat 9/17 | Maryland vs SMU | -3.0W34–27 | 74.0 | W34–27 | U | Y |
| Sat 9/24 | Maryland at Michigan | +17.0L27–34 | 66.0 | L27–34 | U | Y |
| Sat 10/1 | Maryland vs Michigan State | -7.5W27–13 | 58.5 | W27–13 | U | Y |
| Sat 10/8 | Maryland vs Purdue | -3.0L29–31 | 59.5 | L29–31 | O | N |
| Sat 10/15 | Maryland at Indiana | -11.0W38–33 | 63.0 | W38–33 | O | N |
| Sat 10/22 | Maryland vs Northwestern | -14.0W31–24 | 51.0 | W31–24 | O | N |
| — Bye Week — | ||||||
| Sat 11/5 | Maryland at Wisconsin | +5.0L10–23 | 47.5 | L10–23 | U | N |
| Sat 11/12 | Maryland at Penn State | +10.5L0–30 | 56.5 | L0–30 | U | N |
| Sat 11/19 | Maryland vs Ohio State | +26.5L30–43 | 62.5 | L30–43 | O | Y |
| Sat 11/26 | Maryland vs Rutgers | -14.5W37–0 | 48.5 | W37–0 | U | Y |
| Fri 12/30 | Maryland vs NC State | +2.5W16–12 | 45.0 | W16–12 | U | Y |
Charlotte 2022 Schedule
Charlotte's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/27 | Charlotte at Florida Atlantic | +7.0L13–43 | 60.0 | L13–43 | U | N |
| Fri 9/2 | Charlotte vs William & Mary | -4.5L24–41 | 52.0 | L24–41 | O | N |
| Sat 9/10 | Charlotte vs Maryland | +28.0L21–56 | 65.0 | L21–56 | O | N |
| Sat 9/17 | Charlotte at Georgia State | +19.5W42–41 | 64.0 | W42–41 | O | Y |
| Sat 9/24 | Charlotte at South Carolina | +23.5L20–56 | 66.5 | L20–56 | O | N |
| Sat 10/1 | Charlotte vs UTEP | +3.5L35–41 | 56.0 | L35–41 | O | N |
| — Bye Week — | ||||||
| Sat 10/15 | Charlotte at UAB | +21.5L20–34 | 65.0 | L20–34 | U | Y |
| Sat 10/22 | Charlotte vs Florida International | -14.0L15–34 | 63.5 | L15–34 | U | N |
| Sat 10/29 | Charlotte at Rice | +15.0W56–23 | 61.0 | W56–23 | O | Y |
| Sat 11/5 | Charlotte vs Western Kentucky | +14.5L7–59 | 72.5 | L7–59 | U | N |
| Sat 11/12 | Charlotte at Middle Tennessee | +10.0L14–24 | 67.0 | L14–24 | U | Y |
| Sat 11/19 | Charlotte vs Louisiana Tech | +2.0W26–21 | 66.5 | W26–21 | U | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2022 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Maryland
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Maryland
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 · 2022 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 +1.00
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 1 game this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Maryland Edge
Maryland +86.9
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 2 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
12–23 (34%)
· Yr 4 at school
OC
Dan Enos
Yr 2
#1
DC
Brian Williams
Yr 2
#1
Charlotte
Will Healy #1
14–17 (45%)
· Yr 4 at school
OC
Mark Carney
Yr 2
#1
DC
Greg Brown
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 ✓