Sat, Oct 29 2022
·
Week 9
·
🏟 Jack Trice Stadium
Ames, IA
·
Turf
·
61,500 cap
Oklahoma✈ 513 miSame TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Iowa State,
while Game Control favors Oklahoma.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Iowa State wins
Lean
Game Control
64.9%
Oklahoma wins
Lean
Vegas Spread
Oklahoma -1.5
O/U 58.0
teamrankings
Advanced Stats
PPA + Success Rate agree → Oklahoma
· 73.9% ATS historically
↓ See full breakdown
Oklahoma 2022 Schedule
Oklahoma's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Oklahoma vs UTEP | -31.0W45–13 | 58.0 | W45–13 | U | Y |
| Sat 9/10 | Oklahoma vs Kent State | -33.5W33–3 | 73.0 | W33–3 | U | N |
| Sat 9/17 | Oklahoma at Nebraska | -10.5W49–14 | 65.5 | W49–14 | U | Y |
| Sat 9/24 | Oklahoma vs Kansas State | -13.5L34–41 | 53.0 | L34–41 | O | N |
| Sat 10/1 | Oklahoma at TCU | -5.0L24–55 | 69.5 | L24–55 | O | N |
| Sat 10/8 | Oklahoma vs Texas | +7.5L0–49 | 65.0 | L0–49 | U | N |
| Sat 10/15 | Oklahoma vs Kansas | -10.5W52–42 | 66.0 | W52–42 | O | N |
| — Bye Week — | ||||||
| Sat 10/29 | Oklahoma at Iowa State | -1.5W27–13 | 58.0 | W27–13 | U | Y |
| Sat 11/5 | Oklahoma vs Baylor | -3.0L35–38 | 61.5 | L35–38 | O | N |
| Sat 11/12 | Oklahoma at West Virginia | -8.5L20–23 | 68.5 | L20–23 | U | N |
| Sat 11/19 | Oklahoma vs Oklahoma State | -7.0W28–13 | 67.5 | W28–13 | U | Y |
| Sat 11/26 | Oklahoma at Texas Tech | -2.0L48–51 | 65.5 | L48–51 | O | N |
| Thu 12/29 | Oklahoma vs Florida State | +10.5L32–35 | 67.0 | L32–35 | U | Y |
Iowa State 2022 Schedule
Iowa State's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Iowa State vs Southeast Missouri State | -33.5W42–10 | 54.5 | W42–10 | U | N |
| Sat 9/10 | Iowa State at Iowa | +3.5W10–7 | 39.0 | W10–7 | U | Y |
| Sat 9/17 | Iowa State vs Ohio | -20.0W43–10 | 48.0 | W43–10 | O | Y |
| Sat 9/24 | Iowa State vs Baylor | -2.5L24–31 | 45.0 | L24–31 | O | N |
| Sat 10/1 | Iowa State at Kansas | -3.5L11–14 | 59.0 | L11–14 | U | N |
| Sat 10/8 | Iowa State vs Kansas State | +1.0L9–10 | 45.0 | L9–10 | U | Y |
| Sat 10/15 | Iowa State at Texas | +15.5L21–24 | 48.5 | L21–24 | U | Y |
| — Bye Week — | ||||||
| Sat 10/29 | Iowa State vs Oklahoma | +1.5L13–27 | 58.0 | L13–27 | U | N |
| Sat 11/5 | Iowa State vs West Virginia | -6.5W31–14 | 49.5 | W31–14 | U | Y |
| Sat 11/12 | Iowa State at Oklahoma State | -2.5L14–20 | 47.5 | L14–20 | U | N |
| Sat 11/19 | Iowa State vs Texas Tech | -3.5L10–14 | 47.5 | L10–14 | U | N |
| Sat 11/26 | Iowa State at TCU | +9.5L14–62 | 46.0 | L14–62 | 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
→ Oklahoma
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?
Iowa State Edge
Iowa State +0.29
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 7 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Oklahoma Edge
Oklahoma +11.4
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 7 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
Oklahoma
Brent Venables #1
0–0 (0%)
· Yr 1 at school
OC
Jeff Lebby
Yr 1
#1
DC
Todd Bates
Yr 1
#1
Iowa State
Matt Campbell #1
42–32 (57%)
· Yr 7 at school
OC
Tom Manning
Yr 2
#1
DC
Jon Heacock
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 ✓