Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Kansas,
while Game Control favors Duke.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Kansas wins
Lean
Game Control
75.9%
Duke wins
Solid
Vegas Spread
Kansas -7.5
O/U 66.0
Bovada
Advanced Stats
PPA + Success Rate agree → Duke
· 73.9% ATS historically
↓ See full breakdown
Duke 2022 Schedule
Duke's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/2 | Duke vs Temple | -9.5W30–0 | 51.5 | W30–0 | U | Y |
| Sat 9/10 | Duke at Northwestern | +10.0W31–23 | 56.5 | W31–23 | U | Y |
| Sat 9/17 | Duke vs North Carolina A&T | -30.5W49–20 | 53.0 | W49–20 | O | N |
| Sat 9/24 | Duke at Kansas | +7.5L27–35 | 66.0 | L27–35 | U | N |
| Sat 10/1 | Duke vs Virginia | -2.0W38–17 | 55.0 | W38–17 | U | Y |
| Sat 10/8 | Duke at Georgia Tech | -3.5L20–23 | 54.0 | L20–23 | U | N |
| Sat 10/15 | Duke vs North Carolina | +7.0L35–38 | 70.0 | L35–38 | O | Y |
| Sat 10/22 | Duke at Miami | +10.0W45–21 | 59.0 | W45–21 | O | Y |
| — Bye Week — | ||||||
| Fri 11/4 | Duke at Boston College | -11.5W38–31 | 47.0 | W38–31 | O | N |
| Sat 11/12 | Duke vs Virginia Tech | -10.0W24–7 | 50.0 | W24–7 | U | Y |
| Sat 11/19 | Duke at Pittsburgh | +6.5L26–28 | 49.0 | L26–28 | O | Y |
| Sat 11/26 | Duke vs Wake Forest | +3.0W34–31 | 67.0 | W34–31 | U | Y |
| Wed 12/28 | Duke vs UCF | -3.5W30–13 | 63.0 | W30–13 | U | Y |
Kansas 2022 Schedule
Kansas's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/2 | Kansas vs Tennessee Tech | -30.5W56–10 | 62.0 | W56–10 | O | Y |
| Sat 9/10 | Kansas at West Virginia | +14.0W55–42 | 59.5 | W55–42 | O | Y |
| Sat 9/17 | Kansas at Houston | +8.5W48–30 | 58.0 | W48–30 | O | Y |
| Sat 9/24 | Kansas vs Duke | -7.5W35–27 | 66.0 | W35–27 | U | Y |
| Sat 10/1 | Kansas vs Iowa State | +3.5W14–11 | 59.0 | W14–11 | U | Y |
| Sat 10/8 | Kansas vs TCU | +7.0L31–38 | 70.0 | L31–38 | U | Y |
| Sat 10/15 | Kansas at Oklahoma | +10.5L42–52 | 66.0 | L42–52 | O | Y |
| Sat 10/22 | Kansas at Baylor | +10.5L23–35 | 56.5 | L23–35 | O | N |
| — Bye Week — | ||||||
| Sat 11/5 | Kansas vs Oklahoma State | -3.0W37–16 | 59.5 | W37–16 | U | Y |
| Sat 11/12 | Kansas at Texas Tech | +3.5L28–43 | 63.5 | L28–43 | O | N |
| Sat 11/19 | Kansas vs Texas | +9.0L14–55 | 63.5 | L14–55 | O | N |
| Sat 11/26 | Kansas at Kansas State | +11.5L27–47 | 62.0 | L27–47 | O | N |
| Wed 12/28 | Kansas vs Arkansas | +1.5L53–55 | 70.5 | L53–55 | O | N |
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
→ Duke
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?
Kansas Edge
Kansas +0.67
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?
Duke Edge
Duke +22.1
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 3 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
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
Duke
Mike Elko #1
0–0 (0%)
· Yr 1 at school
OC
Kevin Johns
Yr 1
#1
DC
Robb Smith
Yr 1
#1
Kansas
Lance Leipold #1
2–10 (17%)
· Yr 2 at school
OC
Andy Kotelnicki
Yr 2
#1
DC
Brian Borland
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 ✓