Sat, Sep 16 2023
·
Week 3
·
🏟 Faurot Field
Columbia, MO
·
Turf
·
71,168 cap
Kansas State✈ 229 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
64.9%
Kansas State wins
Lean
Vegas Spread
Kansas State -3.5
O/U 48.0
William Hill (New Jersey)
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
Kansas State 2023 Schedule
Kansas State's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Kansas State vs Southeast Missouri State | -28.5W45–0 | 56.5 | W45–0 | U | Y |
| Sat 9/9 | Kansas State vs Troy | -15.0W42–13 | 50.0 | W42–13 | O | Y |
| Sat 9/16 | Kansas State at Missouri | -3.5L27–30 | 48.0 | L27–30 | O | N |
| Sat 9/23 | Kansas State vs UCF | -6.0W44–31 | 53.5 | W44–31 | O | Y |
| — Bye Week — | ||||||
| Fri 10/6 | Kansas State at Oklahoma State | -11.5L21–29 | 53.5 | L21–29 | U | N |
| Sat 10/14 | Kansas State at Texas Tech | +1.0W38–21 | 57.0 | W38–21 | O | Y |
| Sat 10/21 | Kansas State vs TCU | -5.5W41–3 | 60.0 | W41–3 | U | Y |
| Sat 10/28 | Kansas State vs Houston | -17.5W41–0 | 61.0 | W41–0 | U | Y |
| Sat 11/4 | Kansas State at Texas | +4.0L30–33 | 49.5 | L30–33 | O | Y |
| Sat 11/11 | Kansas State vs Baylor | -20.5W59–25 | 55.5 | W59–25 | O | Y |
| Sat 11/18 | Kansas State at Kansas | -7.0W31–27 | 60.5 | W31–27 | U | N |
| Sat 11/25 | Kansas State vs Iowa State | -9.5L35–42 | 46.0 | L35–42 | O | N |
| Thu 12/28 | Kansas State vs NC State | -3.0W28–19 | 48.5 | W28–19 | U | Y |
Missouri 2023 Schedule
Missouri's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/31 | Missouri vs South Dakota | -27.0W35–10 | 44.5 | W35–10 | O | N |
| Sat 9/9 | Missouri vs Middle Tennessee | -21.0W23–19 | 47.5 | W23–19 | U | N |
| Sat 9/16 | Missouri vs Kansas State | +3.5W30–27 | 48.0 | W30–27 | O | Y |
| Sat 9/23 | Missouri vs Memphis | -6.5W34–27 | 52.0 | W34–27 | O | Y |
| Sat 9/30 | Missouri at Vanderbilt | -14.0W38–21 | 53.5 | W38–21 | O | Y |
| Sat 10/7 | Missouri vs LSU | +6.0L39–49 | 63.5 | L39–49 | O | N |
| Sat 10/14 | Missouri at Kentucky | +1.5W38–21 | 50.5 | W38–21 | O | Y |
| Sat 10/21 | Missouri vs South Carolina | -7.5W34–12 | 57.5 | W34–12 | U | Y |
| — Bye Week — | ||||||
| Sat 11/4 | Missouri at Georgia | +15.0L21–30 | 56.5 | L21–30 | U | Y |
| Sat 11/11 | Missouri vs Tennessee | +1.0W36–7 | 58.5 | W36–7 | U | Y |
| Sat 11/18 | Missouri vs Florida | -12.5W33–31 | 56.5 | W33–31 | O | N |
| Fri 11/24 | Missouri at Arkansas | -9.5W48–14 | 53.5 | W48–14 | O | Y |
| Fri 12/29 | Missouri vs Ohio State | +4.0W14–3 | 51.0 | W14–3 | U | Y |
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
Split
Metrics disagree
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?
Kansas State +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 1 game this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Kansas State Edge
Kansas State +17.8
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 2 games this season
Actual Result
CSS Battle
Tie
1 — 1 sequences
GC Battle
Kansas State
29.4 — 33.2 GC score
✓ Predicted correctly
Game Result
Missouri won by 3
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
Kansas State
Chris Klieman #1
32–21 (60%)
· Yr 5 at school
OC
Collin Klein
Yr 2
#1
DC
Joe Klanderman
Yr 3
#1
Missouri
Eliah Drinkwitz #1
20–19 (51%)
· Yr 4 at school
OC
Kirby Moore
Yr 1
#1
DC
Blake Baker
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: 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 ✓