Ohio State
2026 Team Stats (32 games)
78.9
PPG
72.2
Opp
+6.7
Margin
48.7%
FG%
35.8%
3P%
78.0%
FT%
33.2
RPG
14.1
APG
10.3
TO
75.5
Pace
83.7
AdjO
65.4
AdjD
#23
Rank
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → | 1220 (#39) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1166 (#64) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1048 (#108) | HCA +109 elo |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 991 (#493) | HCA +109 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +18.1 (#24) | HCA +2.2 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +30.8 (#18) | HCA +2.5 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -7.5 (#447) | HCA +2.5 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.759 (#43) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.765 (#90) | NetEff +11.4 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.939 (#26) | AdjNet +23.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.940 (#26) | AdjNet +23.9 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.841 (#23) | AdjO 83.7 | AdjD 65.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.722 (#32) | AdjO 77.4 | AdjD 66.9 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.442 (#518) | AdjO 72.0 | AdjD 74.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.926 (#37) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.374 (#417) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. More → | 0.903 (#35) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. More → | 0.385 (#412) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1226 (#51) | RD 112 | GP 32 |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 869 (#579) | RD 350 | GP 2 |
2026 Schedule & Results
2026 Roster
Minutes by Position
The surface stays filled across the five on-court roles. Use the labels or legend to isolate how each player absorbs guard-to-big minutes.
| Player | Pos | GP | MIN | PTS | REB | AST | STL | BLK | TO | FGA | Numbers | PM | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B. Thornton
|
- | 32 | 36.5 | 20.0 | 5.0 | 3.7 | 1.2 | 0.2 | 1.3 | 12.7 | 16.1 | 147 | 5.9 | 10.2 | 55.4 | 40.5 | 82.7 | 0.83 | 67.5 | 63.1 |
J. Mobley Jr.
|
- | 29 | 31.7 | 15.4 | 2.4 | 2.9 | 0.8 | 0.1 | 1.9 | 11.6 | 8.1 | 150 | 6.8 | 9.8 | 42.6 | 41.1 | 86.7 | 1.65 | 60.1 | 56.0 |
D. Royal
|
- | 30 | 32.8 | 13.5 | 5.6 | 1.6 | 0.6 | 0.1 | 1.6 | 10.0 | 10.0 | 92 | 4.4 | 7.6 | 46.7 | 29.3 | 80.5 | 0.47 | 57.3 | 51.2 |
C. Tilly
|
C | 30 | 26.1 | 11.4 | 4.8 | 2.2 | 0.7 | 0.6 | 1.5 | 7.7 | 10.5 | 111 | 5.3 | 8.8 | 48.3 | 23.2 | 74.3 | 1.29 | 58.3 | 51.1 |
Amare Bynum
|
- | 32 | 28.5 | 9.8 | 4.9 | 1.1 | 0.6 | 0.8 | 1.1 | 7.4 | 8.7 | 42 | 1.9 | 3.2 | 51.1 | 31.8 | 73.3 | 0.13 | 59.4 | 56.8 |
B. Noel
|
F | 15 | 17.9 | 5.1 | 3.5 | 0.9 | 0.3 | 0.1 | 0.9 | 3.9 | 5.1 | 119 | 6.6 | 17.4 | 56.9 | 21.4 | 80.0 | 0.56 | 61.7 | 59.5 |
T. Chatman
|
- | 27 | 13.3 | 4.5 | 1.2 | 0.9 | 0.3 | 0.1 | 0.8 | 3.2 | 3.0 | -23 | -1.4 | -8.3 | 46.0 | 47.1 | 85.0 | 0.01 | 63.2 | 59.8 |
I. Njegovan
|
- | 29 | 11.6 | 2.7 | 3.0 | 0.7 | 0.1 | 0.4 | 0.6 | 1.7 | 4.6 | 39 | 2.2 | 8.3 | 56.0 | 66.7 | 65.5 | 0.4 | 61.3 | 58.0 |
P. Johnson
|
G | 9 | 11.4 | 2.3 | 1.0 | 0.1 | 0.1 | 0.0 | 0.4 | 2.0 | 1.1 | 9 | 0.5 | 2.0 | 33.3 | 42.9 | 66.7 | -0.04 | 47.8 | 41.7 |
G. Cupps
|
- | 31 | 11.9 | 1.7 | 1.2 | 1.0 | 0.4 | 0.0 | 0.7 | 1.3 | 2.3 | 19 | 0.9 | 2.9 | 41.0 | 26.1 | 73.7 | 0.18 | 54.9 | 48.7 |
Mathieu Grujicic
|
- | 6 | 5.5 | 1.0 | 0.8 | 0.3 | 0.2 | 0.0 | 0.2 | 1.3 | 0.8 | 19 | 3.2 | 22.9 | 12.5 | 14.3 | 42.9 | 0.14 | 27.1 | 18.8 |
C. White
|
- | 27 | 8.7 | 0.8 | 1.0 | 0.3 | 0.2 | 0.0 | 0.2 | 0.9 | 1.3 | 39 | 1.9 | 8.7 | 37.5 | 12.5 | 20.0 | 0.69 | 40.1 | 41.7 |
J. Ojianwuna
|
F | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
B. Nash
|
- | 6 | 1.3 | 0.0 | 0.0 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2 | 1 | 0.3 | 12.2 | 0 | 0 | 0 | 0.01 | 0 | 0 |
Myles Herro
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Numbers/Game vs RAPM
X-axis = Numbers/Game (PTS+REB+AST+STL+BLK-TO-FGA), Y-axis = RAPM.
Advanced: Numbers = PTS+REB+AST+STL+BLK-TO-FGA, PM = total +/-, PM/G = per game, PM/40 = per 40 minutes, RAPM = Regularized Adj Plus-Minus, TS% = True Shooting, eFG% = Effective FG