Sat, Nov 28 2026
·
Week 13
·
🏟 Ohio Stadium
Columbus, OH
·
Turf
·
104,944 cap
Michigan✈ 160 miSame TZ
Preseason projection — This game has not yet been played and 2026 in-season data is not yet available.
Edges are based on 2025 full-season performance.
Confidence will increase once in-season games are logged.
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
71.6%
Ohio State wins
Solid
Game Control
67.1%
Ohio State wins
Solid
Advanced Stats
PPA + Success Rate agree → Ohio State
· 73.9% ATS historically
↓ See full breakdown
Michigan 2026 Schedule
Michigan's 2026 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/5 | Michigan vs Western Michigan | -21 | — | — | — | — |
| Sat 9/12 | Michigan vs Oklahoma | +1 | — | — | — | — |
| Sat 9/19 | Michigan vs UTEP | -30.5 | — | — | — | — |
| Sat 9/26 | Michigan vs Iowa | -2.5 | — | — | — | — |
| Sat 10/3 | Michigan at Minnesota | -9 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 10/17 | Michigan vs Penn State | -4.5 | — | — | — | — |
| Sat 10/24 | Michigan vs Indiana | +11 | — | — | — | — |
| Sat 10/31 | Michigan at Rutgers | -13.5 | — | — | — | — |
| Sat 11/7 | Michigan vs Michigan State | -20.5 | — | — | — | — |
| Sat 11/14 | Michigan at Oregon | +12 | — | — | — | — |
| Sat 11/21 | Michigan vs UCLA | -11.5 | — | — | — | — |
| Sat 11/28 | Michigan at Ohio State | +15.5 | — | — | — | — |
Ohio State 2026 Schedule
Ohio State's 2026 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/5 | Ohio State vs Ball State | -38 | — | — | — | — |
| Sat 9/12 | Ohio State at Texas | +0.5 | — | — | — | — |
| Sat 9/19 | Ohio State vs Kent State | -36.5 | — | — | — | — |
| Sat 9/26 | Ohio State vs Illinois | -20.5 | — | — | — | — |
| Sat 10/3 | Ohio State at Iowa | -10.5 | — | — | — | — |
| Sat 10/10 | Ohio State vs Maryland | -28 | — | — | — | — |
| Sat 10/17 | Ohio State at Indiana | +3 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 10/31 | Ohio State at USC | -9 | — | — | — | — |
| Sat 11/7 | Ohio State vs Oregon | -6 | — | — | — | — |
| Sat 11/14 | Ohio State vs Northwestern | -28 | — | — | — | — |
| Sat 11/21 | Ohio State at Nebraska | -20.5 | — | — | — | — |
| Sat 11/28 | Ohio State vs Michigan | -15.5 | — | — | — | — |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season (prior year)
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 · 2025 season (prior year — 2026 data not yet available) ·
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 +1.08
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 2025 full season · preseason estimate
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Ohio State Edge
Ohio State +19.4
GC Edge (season-to-date)
Teams with this edge win 67.1% of games historically
Based on 2025 full season · preseason estimate
Coaching Matchup
Michigan
Kyle Whittingham #22
0–0 (0%)
· Yr 1 at school
OC
Jason Beck
Yr 1
#10
DC
Jay Hill
Yr 1
#11
Ohio State
Ryan Day #1
82–12 (87%)
· Yr 8 at school
OC
Arthur Smith
Yr 1
#67
DC
Matt Patricia
Yr 2
#27
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 ✓