Sat, Sep 23 2023
·
Week 4
·
🏟 Spartan Stadium
East Lansing, MI
·
Turf
·
75,005 cap
Maryland✈ 470 miSame TZ
Matchup Prediction
Maryland
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Maryland entering this game.
Momentum Control
80.6%
Maryland wins
Strong
Game Control
64.9%
Maryland wins
Lean
Vegas Spread
Maryland -7
O/U 52.5
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → Maryland
· 73.9% ATS historically
↓ See full breakdown
Maryland 2023 Schedule
Maryland's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Maryland vs Towson | -38.5W38–6 | 55.5 | W38–6 | U | N |
| Sat 9/9 | Maryland vs Charlotte | -24.5W38–20 | 50.0 | W38–20 | O | N |
| Fri 9/15 | Maryland vs Virginia | -16.5W42–14 | 48.5 | W42–14 | O | Y |
| Sat 9/23 | Maryland at Michigan State | -7.0W31–9 | 52.5 | W31–9 | U | Y |
| Sat 9/30 | Maryland vs Indiana | -14.5W44–17 | 50.0 | W44–17 | O | Y |
| Sat 10/7 | Maryland at Ohio State | +17.0L17–37 | 56.5 | L17–37 | U | N |
| Sat 10/14 | Maryland vs Illinois | -13.5L24–27 | 52.0 | L24–27 | U | N |
| — Bye Week — | ||||||
| Sat 10/28 | Maryland at Northwestern | -14.0L27–33 | 48.5 | L27–33 | O | N |
| Sat 11/4 | Maryland vs Penn State | +8.5L15–51 | 50.5 | L15–51 | O | N |
| Sat 11/11 | Maryland at Nebraska | -1.5W13–10 | 41.5 | W13–10 | U | Y |
| Sat 11/18 | Maryland vs Michigan | +17.5L24–31 | 50.5 | L24–31 | O | Y |
| Sat 11/25 | Maryland at Rutgers | -2.0W42–24 | 45.5 | W42–24 | O | Y |
| Sat 12/30 | Maryland vs Auburn | +4.0W31–13 | 47.5 | W31–13 | U | Y |
Michigan State 2023 Schedule
Michigan State's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/1 | Michigan State vs Central Michigan | -14.0W31–7 | 45.0 | W31–7 | U | Y |
| Sat 9/9 | Michigan State vs Richmond | -29.5W45–14 | 43.5 | W45–14 | O | Y |
| Sat 9/16 | Michigan State vs Washington | +14.5L7–41 | 57.0 | L7–41 | U | N |
| Sat 9/23 | Michigan State vs Maryland | +7.0L9–31 | 52.5 | L9–31 | U | N |
| Sat 9/30 | Michigan State at Iowa | +10.0L16–26 | 36.5 | L16–26 | O | Y |
| — Bye Week — | ||||||
| Sat 10/14 | Michigan State at Rutgers | +4.0L24–27 | 38.5 | L24–27 | O | Y |
| Sat 10/21 | Michigan State vs Michigan | +25.5L0–49 | 47.0 | L0–49 | O | N |
| Sat 10/28 | Michigan State at Minnesota | +6.5L12–27 | 41.5 | L12–27 | U | N |
| Sat 11/4 | Michigan State vs Nebraska | +3.0W20–17 | 34.5 | W20–17 | O | Y |
| Sat 11/11 | Michigan State at Ohio State | +30.5L3–38 | 48.5 | L3–38 | U | N |
| Sat 11/18 | Michigan State at Indiana | +3.5W24–21 | 47.5 | W24–21 | U | Y |
| Fri 11/24 | Michigan State vs Penn State | +20.0L0–42 | 42.0 | L0–42 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2023 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 · 2023 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 +2.00
CSS Edge (season-to-date)
Teams with this edge win 80.6% of games historically
Based on 2 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Maryland Edge
Maryland +14.0
GC Edge (season-to-date)
Teams with this edge win 64.9% 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 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
24–28 (46%)
· Yr 5 at school
OC
Josh Gattis
Yr 1
#1
DC
Brian Williams
Yr 3
#1
Michigan State
Harlon Barnett #1
0–1 (0%)
· Yr 1 at school
OC
Jay Johnson
Yr 3
#1
DC
Scottie Hazelton
Yr 3
#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 ✓