Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Maryland,
while Game Control favors Iowa.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Maryland wins
Lean
Game Control
64.9%
Iowa wins
Lean
Vegas Spread
Iowa -3.0
O/U 47.5
Bovada
Advanced Stats
PPA + Success Rate agree → Maryland
· 73.9% ATS historically
↓ See full breakdown
Iowa 2021 Schedule
Iowa's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Iowa vs Indiana | -3.5W34–6 | 45.5 | W34–6 | U | Y |
| Sat 9/11 | Iowa at Iowa State | +4.0W27–17 | 45.0 | W27–17 | U | Y |
| Sat 9/18 | Iowa vs Kent State | -22.0W30–7 | 55.5 | W30–7 | U | Y |
| Sat 9/25 | Iowa vs Colorado State | -24.0W24–14 | 43.5 | W24–14 | U | N |
| Fri 10/1 | Iowa at Maryland | -3.0W51–14 | 47.5 | W51–14 | O | Y |
| Sat 10/9 | Iowa vs Penn State | -2.5W23–20 | 41.0 | W23–20 | O | Y |
| Sat 10/16 | Iowa vs Purdue | -11.0L7–24 | 42.5 | L7–24 | U | N |
| — Bye Week — | ||||||
| Sat 10/30 | Iowa at Wisconsin | +3.0L7–27 | 35.5 | L7–27 | U | N |
| Sat 11/6 | Iowa at Northwestern | -11.5W17–12 | 40.5 | W17–12 | U | N |
| Sat 11/13 | Iowa vs Minnesota | -4.0W27–22 | 37.5 | W27–22 | O | Y |
| Sat 11/20 | Iowa vs Illinois | -12.0W33–23 | 37.5 | W33–23 | O | N |
| Fri 11/26 | Iowa at Nebraska | +1.5W28–21 | 41.0 | W28–21 | O | Y |
| Sat 12/4 | Iowa vs Michigan | +12.0L3–42 | 43.5 | L3–42 | O | N |
| Sat 1/1 | Iowa vs Kentucky | +3.0L17–20 | 43.5 | L17–20 | U | Y |
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 |
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 +0.92
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Iowa Edge
Iowa +14.7
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 4 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
CSS and GC disagree on this matchup. When the metrics split, historical cover rates are essentially random — treat this as a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Iowa
Kirk Ferentz #1
171–106 (62%)
· Yr 23 at school
OC
Brian Ferentz
Yr 1
#1
DC
Phil Parker
Yr 1
#1
Maryland
Mike Locksley #1
9–17 (35%)
· Yr 3 at school
OC
Dan Enos
Yr 1
#1
DC
Brian Williams
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 ✓