Sat, Oct 1 2022
·
Week 5
·
🏟 Maryland Stadium
College Park, MD
·
Turf
·
51,802 cap
Michigan State✈ 470 miSame TZ
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
67.1%
Maryland wins
Solid
Vegas Spread
Maryland -7.5
O/U 58.5
teamrankings
Advanced Stats
PPA + Success Rate agree → Maryland
· 73.9% ATS historically
↓ See full breakdown
Michigan State 2022 Schedule
Michigan State's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/2 | Michigan State vs Western Michigan | -22.0W35–13 | 54.5 | W35–13 | U | N |
| Sat 9/10 | Michigan State vs Akron | -34.5W52–0 | 56.0 | W52–0 | U | Y |
| Sat 9/17 | Michigan State at Washington | +3.5L28–39 | 56.5 | L28–39 | O | N |
| Sat 9/24 | Michigan State vs Minnesota | +3.0L7–34 | 50.0 | L7–34 | U | N |
| Sat 10/1 | Michigan State at Maryland | +7.5L13–27 | 58.5 | L13–27 | U | N |
| Sat 10/8 | Michigan State vs Ohio State | +27.0L20–49 | 64.5 | L20–49 | O | N |
| Sat 10/15 | Michigan State vs Wisconsin | +7.0W34–28 | 49.5 | W34–28 | O | Y |
| — Bye Week — | ||||||
| Sat 10/29 | Michigan State at Michigan | +22.0L7–29 | 55.0 | L7–29 | U | Y |
| Sat 11/5 | Michigan State at Illinois | +16.5W23–15 | 41.0 | W23–15 | U | Y |
| Sat 11/12 | Michigan State vs Rutgers | -10.0W27–21 | 41.0 | W27–21 | O | N |
| Sat 11/19 | Michigan State vs Indiana | -12.0L31–39 | 47.0 | L31–39 | O | N |
| Sat 11/26 | Michigan State at Penn State | +19.0L16–35 | 54.5 | L16–35 | U | Y |
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 |
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
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 · 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?
Michigan State +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Maryland Edge
Maryland +14.2
GC Edge (season-to-date)
Teams with this edge win 67.1% of games historically
Based on 4 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 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
Michigan State
Mel Tucker #1
13–7 (65%)
· Yr 3 at school
OC
Jay Johnson
Yr 2
#1
DC
Scottie Hazelton
Yr 2
#1
Maryland
Mike Locksley #1
12–23 (34%)
· Yr 4 at school
OC
Dan Enos
Yr 2
#1
DC
Brian Williams
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: 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 ✓