Sat, Sep 18 2021
·
Week 3
·
🏟 Ohio Stadium
Columbus, OH
·
Turf
·
104,944 cap
Tulsa✈ 750 mi+1 hr TZ
Matchup Prediction
Ohio State
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Ohio State entering this game.
Momentum Control
58.4%
Ohio State wins
Lean
Game Control
58.6%
Ohio State wins
Lean
Vegas Spread
Ohio State -24.5
O/U 60.5
teamrankings
Advanced Stats
PPA + Success Rate agree → Ohio State
· 73.9% ATS historically
↓ See full breakdown
Tulsa 2021 Schedule
Tulsa's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 9/2 | Tulsa vs UC Davis | -22.0L17–19 | 54.5 | L17–19 | U | N |
| Sat 9/11 | Tulsa at Oklahoma State | +11.5L23–28 | 51.0 | L23–28 | U | Y |
| Sat 9/18 | Tulsa at Ohio State | +24.5L20–41 | 60.5 | L20–41 | O | Y |
| Sat 9/25 | Tulsa vs Arkansas State | -14.5W41–34 | 65.0 | W41–34 | O | N |
| Fri 10/1 | Tulsa vs Houston | -3.0L10–45 | 54.0 | L10–45 | O | N |
| Sat 10/9 | Tulsa vs Memphis | -3.0W35–29 | 60.5 | W35–29 | O | Y |
| Sat 10/16 | Tulsa at South Florida | -7.5W32–31 | 56.0 | W32–31 | O | N |
| — Bye Week — | ||||||
| Fri 10/29 | Tulsa vs Navy | -11.0L17–20 | 46.0 | L17–20 | U | N |
| Sat 11/6 | Tulsa at Cincinnati | +22.5L20–28 | 56.0 | L20–28 | U | Y |
| Sat 11/13 | Tulsa at Tulane | -3.0W20–13 | 55.5 | W20–13 | U | Y |
| Sat 11/20 | Tulsa vs Temple | -22.0W44–10 | 50.5 | W44–10 | O | Y |
| Sat 11/27 | Tulsa at SMU | +6.0W34–31 | 63.0 | W34–31 | O | Y |
| Mon 12/20 | Tulsa vs Old Dominion | -7.5W30–17 | 55.0 | W30–17 | U | Y |
Ohio State 2021 Schedule
Ohio State's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 9/2 | Ohio State at Minnesota | -14.0W45–31 | 62.0 | W45–31 | O | N |
| Sat 9/11 | Ohio State vs Oregon | -14.5L28–35 | 65.0 | L28–35 | U | N |
| Sat 9/18 | Ohio State vs Tulsa | -24.5W41–20 | 60.5 | W41–20 | O | N |
| Sat 9/25 | Ohio State vs Akron | -48.5W59–7 | 66.5 | W59–7 | U | Y |
| Sat 10/2 | Ohio State at Rutgers | -15.0W52–13 | 58.0 | W52–13 | O | Y |
| Sat 10/9 | Ohio State vs Maryland | -22.0W66–17 | 71.5 | W66–17 | O | Y |
| — Bye Week — | ||||||
| Sat 10/23 | Ohio State at Indiana | -21.0W54–7 | 59.0 | W54–7 | O | Y |
| Sat 10/30 | Ohio State vs Penn State | -18.5W33–24 | 60.5 | W33–24 | U | N |
| Sat 11/6 | Ohio State at Nebraska | -14.0W26–17 | 68.5 | W26–17 | U | N |
| Sat 11/13 | Ohio State vs Purdue | -19.0W59–31 | 65.5 | W59–31 | O | Y |
| Sat 11/20 | Ohio State vs Michigan State | -19.5W56–7 | 70.5 | W56–7 | U | Y |
| Sat 11/27 | Ohio State at Michigan | -6.5L27–42 | 63.5 | L27–42 | O | N |
| Sat 1/1 | Ohio State vs Utah | -4.5W48–45 | 64.5 | W48–45 | O | N |
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
→ Ohio State
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?
Ohio State Edge
Ohio State +0.50
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 2 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Ohio State Edge
Ohio State +10.9
GC Edge (season-to-date)
Teams with this edge win 58.6% of games historically
Based on 2 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Ohio State. Teams with this edge profile have covered 50.3% historically — essentially a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Tulsa
Philip Montgomery #1
31–43 (42%)
· Yr 7 at school
OC
Philip Montgomery
Yr 1
#1
DC
Joseph Gillespie
Yr 1
#1
Ohio State
Ryan Day #1
25–3 (89%)
· Yr 3 at school
OC
Kevin Wilson
Yr 1
#1
DC
Kerry Coombs
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 ✓

