
2026 Dossier · Efficiency · Schedule · Churn · Market vs Model
“Ranked #3 in EPA/dropback and #47 in EPA/rush out of 138 — a pass-first offense by a wide margin.”
“The defense allowed the #9 EPA/play and created the #28 havoc rate — a genuine unit on last year's tape.”
“Returns 70% of its own 2025 EPA production and imported 86 EPA from the portal — though only 29% of a 17-player class is measurable, so that import is credited conservatively.”
“Plays the 3rd-hardest schedule in the country by average opponent rating, which is what turns a 2.32 rating into 9.3 projected wins.”
Few possessions, long ones. This offense shortens the game — fewer total drives for both teams, which drags the total down regardless of how efficient either side is.
Ranks order the field by size, not by quality — 1st in plays per game means the most snaps, which is an identity, not an advantage. Points per drive allowed is ranked 1 = stingiest. These are the same pace and per-drive efficiency inputs the totals model uses to project this team's scoring.
Ball State (-1.90)-43.1
@ Texas (1.49)-4.2
Kent State (-1.27)-41.8
Illinois (0.92)-30.1
@ Iowa (1.14)-17.0
Maryland (0.25)-34.0
@ Indiana (2.15)-1.1
@ USC (1.28)-7.7
Oregon (2.06)-11.7
Northwestern (0.68)-16.6
@ Nebraska (0.67)-9.7
Michigan (0.93)-20.9Spread column is the model's projected line for this team (negative = favored). Opponent rating in parentheses.
CORE rates this team 4.9 points better than our model does. Its situational baseline and regularized schedule network credited context our opponent adjustment did not — our projection may be starting this team too low.
Points created minus allowed per 100 qualifying plays, opponent-adjusted. FCS games, garbage time, overtime and special teams excluded — 734 offensive and 594 defensive plays qualified. Held as a cross-check only: as a prior for the next season it tested worse than SP+, so it never feeds a projection.
Bar labels are the percent of simulations finishing with that win total.
Only 29% of this class is measurable — the EPA feed covers offensive skill players only, so defenders and linemen show no production. The rating adjustment is shrunk toward neutral rather than counting them as zero.
Ryan DayContinuitySame head coach as 2025 — no coaching-change adjustment to this team's rating.
9th season at Ohio State · since 2018
82-1287%
Hired Dec 4, 2018
Follows Urban Meyer (2012-2018, 83-9, 11.9 wins a year)
Level he coached at
Lateral move · Big Ten ranked #2 of 11 in 2025 conference strength; Big Ten ranked #2 of 11 in 2025 — a lateral move.
Lg = his conference's strength rank that season, SOS = his own schedule's rank in FBS (1 = hardest), T25 = ranked opponents faced. Both measured from opponents' actual results.
As favorite · straight up
105 of 105 games carried a line · since 2015
Career · 2018+
82-12
At Ohio State
82-12
ATS
57-44-456%
Coaching Accolades
Avg line at home
-26.454 g
Avg line on road
-16.634 g
Last five seasons · overall
Since 2015
Arthur SmithNew hire2025: Offensive Coordinator at Pittsburgh Steelers
First year with Ryan Day — no prior season together on record.
Last coordinated at Pittsburgh Steelers (2025) — no cached unit table for that season yet.
Jim KnowlesReturningReturning for 2026 · ran this unit in 2025
Worked under Ryan Day at Ohio State in 2025 — a carried-over pairing, not a new one.
Ohio State 2025 · ranks among 136 FBS units · conf ranks within the Big Ten
Teams coming off 10+ regular-season wins lose 2.2 wins on average the following year, and 73% decline outright. The market prices last year's record; the model prices the regression.
189 team-seasons, 2014-2025 · n=189 · avg next-season change -2.2 wins
A regular season with one loss or none is the hardest thing in the sport to run back: 69% of those teams won fewer games the next year, giving back 2.1 wins on average.
67 team-seasons, 2014-2025 · n=67 · avg next-season change -2.1 wins
Records regress, but dominance mostly doesn't: of 167 teams that outscored opponents by 14+ per game, 75% won at least 8 games again. Buy margin, not record.
167 team-seasons, 2014-2025 · n=167 · avg next-season change -1.4 wins
Defense is the stickiest input in the model: 68% of the 110 teams that allowed 18 or fewer points per game won at least 8 games the next season, even through coaching and roster turnover.
110 team-seasons, 2014-2025 · n=110 · avg next-season change -1.0 wins
Twenty-point average margins are earned, not lucky: 79% of those 68 team-seasons won 9+ games again. This is the one profile worth paying up for in August.
68 team-seasons, 2014-2025 · n=68 · avg next-season change -1.2 wins
Since 2019, 79% of 11-win teams declined the next season, giving back 2.8 wins on average. Roster churn hits the top of the sport hardest — the guys who won those games get drafted or bought.
53 team-seasons, 2019-2025 · portal era · n=53 · avg next-season change -2.8 wins
Dominance sets a floor even through roster churn: since 2019, 79% of the 145 teams that outscored opponents by 10+ per game won at least 7 games again. Their unders are the worst-priced side on the board.
145 team-seasons, 2019-2025 · portal era · n=145 · avg next-season change -1.5 wins
The 10,000-run simulation puts Ohio State at 9.3 wins (10th–90th percentile: 8–11), with a 83.4% playoff rate and 30.2% to win the national title. It plays the #3 schedule, and model confidence sits at 0.43 — preseason numbers on a projected roster, not a sharp in-season line.
Pushes are excluded from the cover rate. Cover margin is points beyond the number, game-weighted — a record can hide whether those covers were comfortable or by a half point.