Matchup Prediction
Iowa
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Iowa entering this game.
Momentum Control
61.3%
Iowa wins
Lean
Game Control
64.9%
Iowa wins
Lean
Vegas Spread
Iowa -4
O/U 40.5
DraftKings
Advanced Stats
All 4 factors agree → Iowa
· 83.1% ATS historically when all four align
↓ See full breakdown
Iowa 2024 Schedule
Iowa's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Iowa vs Illinois State | -29.5 | — | — | — | — |
| Sat 9/7 | Iowa vs Iowa State | -3.0L19–20 | 35.0 | L19–20 | O | N |
| Sat 9/14 | Iowa vs Troy | -23.5W38–21 | 39.5 | W38–21 | O | N |
| Sat 9/21 | Iowa at Minnesota | -3.0W31–14 | 34.5 | W31–14 | O | Y |
| — Bye Week — | ||||||
| Sat 10/5 | Iowa at Ohio State | +17.0L7–35 | 46.0 | L7–35 | U | N |
| Sat 10/12 | Iowa vs Washington | -2.5W40–16 | 41.5 | W40–16 | O | Y |
| Sat 10/19 | Iowa at Michigan State | -7.0L20–32 | 39.5 | L20–32 | O | N |
| Sat 10/26 | Iowa vs Northwestern | -16.5W40–14 | 38.5 | W40–14 | O | Y |
| Sat 11/2 | Iowa vs Wisconsin | -2.5W42–10 | 40.0 | W42–10 | O | Y |
| Fri 11/8 | Iowa at UCLA | -6.5L17–20 | 44.5 | L17–20 | U | N |
| — Bye Week — | ||||||
| Sat 11/23 | Iowa at Maryland | -4.0W29–13 | 40.5 | W29–13 | O | Y |
| Fri 11/29 | Iowa vs Nebraska | -3.5W13–10 | 41.5 | W13–10 | U | N |
| Mon 12/30 | Iowa vs Missouri | +1.0L24–27 | 41.0 | L24–27 | O | N |
Maryland 2024 Schedule
Maryland's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Maryland vs UConn | -19.0W50–7 | 45.5 | W50–7 | O | Y |
| Sat 9/7 | Maryland vs Michigan State | -7.5L24–27 | 44.5 | L24–27 | O | N |
| Sat 9/14 | Maryland at Virginia | +2.5W27–13 | 55.5 | W27–13 | U | Y |
| Sat 9/21 | Maryland vs Villanova | -22.5W38–20 | 46.5 | W38–20 | O | N |
| Sat 9/28 | Maryland at Indiana | +7.5L28–42 | 50.0 | L28–42 | O | N |
| — Bye Week — | ||||||
| Fri 10/11 | Maryland vs Northwestern | -11.0L10–37 | 45.0 | L10–37 | O | N |
| Sat 10/19 | Maryland vs USC | +6.5W29–28 | 56.5 | W29–28 | O | Y |
| Sat 10/26 | Maryland at Minnesota | +6.0L23–48 | 45.0 | L23–48 | O | N |
| — Bye Week — | ||||||
| Sat 11/9 | Maryland at Oregon | +24.0L18–39 | 58.0 | L18–39 | U | Y |
| Sat 11/16 | Maryland vs Rutgers | -4.5L17–31 | 54.5 | L17–31 | U | N |
| Sat 11/23 | Maryland vs Iowa | +4.0L13–29 | 40.5 | L13–29 | O | N |
| Sat 11/30 | Maryland at Penn State | +26.5L7–44 | 50.5 | L7–44 | O | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Iowa
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Iowa
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Iowa
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 · 2024 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?
Iowa Edge
Iowa +0.78
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 9 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Iowa Edge
Iowa +14.9
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 10 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Iowa 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
Iowa
Kirk Ferentz #1
196–119 (62%)
· Yr 26 at school
OC
Tim Lester
Yr 1
#1
DC
Phil Parker
Yr 3
#1
Maryland
Mike Locksley #1
29–33 (47%)
· Yr 6 at school
OC
Josh Gattis
Yr 2
#1
DC
Aazaar Abdul-Rahim
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 ✓