Michigan Wolverines
2026 Team Stats (35 games)
82.3
PPG
62.6
Opp
+19.7
Margin
46.3%
FG%
33.2%
3P%
68.9%
FT%
40.3
RPG
17.0
APG
14.5
TO
90.2
Pace
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1176 (#11) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +45.4 (#7) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.884 (#7) | AdjO 76.6 | AdjD 54.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.988 (#6) | 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 → | 0.982 (#7) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1415 (#6) | RD 97 | GP 35 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
O. Olson
|
G | 35 | 31.1 | 18.9 | 6.1 | 2.5 | 1.8 | 0.5 | 2.0 | 15.0 | 12.7 | 3 | 0.2 | 0.2 | 46.8 | 30.5 | 81.0 | 0.58 | 55.5 | 50.5 |
S. Swords
|
G | 34 | 33.9 | 14.6 | 4.2 | 2.4 | 1.6 | 0.2 | 2.0 | 13.3 | 7.8 | 82 | 3.9 | 4.4 | 40.6 | 34.0 | 77.0 | 3.3 | 52.0 | 49.9 |
J. Holloway
|
G | 35 | 28.8 | 12.3 | 4.1 | 4.8 | 1.5 | 0.2 | 2.8 | 10.3 | 9.8 | - | - | - | 43.1 | 34.4 | 77.8 | - | 53.5 | 49.3 |
T. Delfosse
|
G | 35 | 19.3 | 8.7 | 4.7 | 0.9 | 0.6 | 0.5 | 1.2 | 6.2 | 8.0 | 35 | 1.6 | 3.1 | 50.5 | 32.8 | 72.7 | 0.72 | 59.6 | 55.5 |
A. Sofilkanich
|
F | 35 | 18.3 | 7.7 | 4.2 | 0.7 | 0.7 | 1.1 | 1.3 | 6.0 | 7.1 | 61 | 2.8 | 4.8 | 54.0 | 0.0 | 56.6 | 2.7 | 55.4 | 54.0 |
B. Quarles Daniels
|
G | 35 | 25.5 | 5.9 | 5.4 | 2.8 | 2.5 | 0.2 | 1.5 | 4.9 | 10.4 | 33 | 1.5 | 2.6 | 48.0 | 0.0 | 60.9 | -0.15 | 51.2 | 48.0 |
K. Dudley
|
G | 34 | 18.9 | 5.8 | 3.9 | 1.0 | 1.2 | 0.3 | 1.3 | 4.8 | 6.1 | 66 | 3.1 | 6.2 | 54.3 | 25.0 | 36.7 | 2.99 | 53.1 | 54.6 |
M. Mathurin
|
G | 25 | 9.0 | 3.5 | 0.7 | 0.5 | 0.5 | 0.1 | 1.0 | 2.5 | 1.9 | -34 | -2.3 | -7.2 | 46.0 | 38.9 | 84.2 | -2.63 | 61.7 | 57.1 |
M. Brown
|
G | 30 | 12.3 | 2.5 | 1.3 | 1.2 | 0.5 | 0.2 | 0.8 | 1.9 | 2.9 | 163 | 7.1 | 9.9 | 37.9 | 36.1 | 65.4 | 3.88 | 53.3 | 49.1 |
A. Crockett
|
F | 29 | 7.3 | 2.3 | 1.4 | 0.5 | 0.4 | 0.1 | 0.5 | 2.1 | 2.0 | 7 | 0.4 | 1.7 | 39.3 | 31.0 | 62.5 | -0.47 | 51.1 | 50.0 |
C. Byars
|
F | 15 | 3.3 | 1.8 | 1.0 | 0.1 | 0.1 | 0.1 | 0.3 | 1.2 | 1.5 | -33 | -3.3 | -32.4 | 50.0 | 0 | 52.9 | -3.31 | 53.0 | 50.0 |
A. VanTimmeren
|
F | 21 | 4.3 | 1.7 | 1.1 | 0.2 | 0.1 | 0.1 | 0.1 | 1.4 | 1.8 | -2 | -0.2 | -1.5 | 55.2 | 0.0 | 50.0 | -0.78 | 55.4 | 55.2 |
J. Fields
|
F | 18 | 2.7 | 0.9 | 0.7 | 0.2 | 0.3 | 0.2 | 0.2 | 0.8 | 1.3 | -31 | -2.8 | -38.5 | 50.0 | 0 | 33.3 | -2.15 | 47.3 | 50.0 |
A. Dunbar
|
F | 7 | 1.4 | 0.0 | 0.1 | 0.0 | 0.1 | 0.0 | 0.0 | 0.3 | 0.0 | -7 | -1.2 | -29.8 | 0.0 | 0 | 0 | -0.31 | 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