Minnesota Golden Gophers
2026 Team Stats (31 games)
74.0
PPG
59.7
Opp
+14.3
Margin
44.5%
FG%
35.5%
3P%
75.1%
FT%
38.8
RPG
16.1
APG
11.4
TO
81.3
Pace
78.4
AdjO
49.0
AdjD
#16
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 → | 1226 (#50) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1327 (#18) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1117 (#48) | HCA +113 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +30.1 (#17) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +39.1 (#19) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.934 (#16) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.970 (#14) | NetEff +28.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.994 (#13) | AdjNet +44.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.995 (#13) | AdjNet +45.5 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.935 (#16) | AdjO 78.4 | AdjD 49.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.816 (#22) | AdjO 71.6 | AdjD 55.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.978 (#17) | 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 → | 0.967 (#18) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1330 (#15) | RD 106 | GP 31 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
T. McKinney
|
G | 27 | 27.8 | 13.0 | 3.0 | 2.6 | 2.0 | 0.6 | 1.2 | 9.9 | 10.1 | 195 | 9.8 | 14.0 | 46.8 | 35.2 | 82.4 | 5.33 | 57.7 | 52.6 |
G. Grocholski
|
G | 31 | 33.6 | 12.0 | 5.0 | 2.8 | 1.1 | 0.2 | 1.5 | 9.7 | 9.7 | 201 | 8.4 | 10.8 | 46.0 | 42.1 | 70.3 | 2.76 | 58.3 | 57.1 |
M. Braun
|
G | 31 | 34.0 | 11.7 | 4.3 | 2.5 | 1.3 | 0.6 | 1.8 | 10.4 | 8.2 | 181 | 7.5 | 9.5 | 39.3 | 35.4 | 89.8 | 0.06 | 52.2 | 48.1 |
A. Battle
|
G | 31 | 31.2 | 11.4 | 7.6 | 3.6 | 1.2 | 0.3 | 2.3 | 11.3 | 10.4 | 177 | 7.4 | 10.2 | 38.2 | 31.6 | 84.7 | 4.77 | 45.3 | 39.9 |
S. Hart
|
C | 31 | 23.8 | 11.4 | 6.4 | 1.1 | 0.5 | 0.5 | 1.4 | 8.9 | 9.6 | 117 | 4.9 | 8.8 | 55.3 | 0 | 64.5 | 0.27 | 57.2 | 55.3 |
B. Glenn
|
G | 31 | 22.4 | 6.3 | 2.6 | 1.8 | 1.2 | 0.2 | 1.0 | 6.5 | 4.6 | 101 | 4.2 | 9.6 | 39.8 | 26.2 | 64.1 | -0.63 | 44.9 | 42.5 |
F. Tonga
|
F | 31 | 12.4 | 4.4 | 3.3 | 0.7 | 0.2 | 0.2 | 1.0 | 3.0 | 4.9 | 53 | 2.2 | 10.1 | 62.8 | 0 | 65.5 | 0.45 | 64.2 | 62.8 |
M. Christian
|
G | 27 | 10.3 | 3.4 | 1.0 | 0.4 | 0.4 | 0.0 | 0.2 | 2.7 | 2.3 | - | - | - | 37.8 | 32.8 | 72.7 | - | 54.4 | 50.7 |
T. Bershers
|
F | 2 | 7.5 | 2.0 | 0.5 | 1.0 | 0.0 | 0.0 | 0.0 | 3.0 | 0.5 | 7 | 3.5 | 56.0 | 33.3 | 0.0 | 0 | -0.81 | 33.3 | 33.3 |
K. Klick
|
G | 17 | 5.7 | 1.5 | 0.8 | 0.9 | 0.2 | 0.0 | 0.6 | 1.1 | 1.6 | 62 | 5.2 | 72.1 | 50.0 | 66.7 | 62.5 | -2.5 | 58.1 | 55.6 |
N. Holloway
|
F | 25 | 5.5 | 1.4 | 1.7 | 0.2 | 0.5 | 0.0 | 0.3 | 1.5 | 2.2 | 12 | 0.6 | 5.9 | 37.8 | 0.0 | 61.5 | -1.78 | 42.1 | 37.8 |
T. Woodson
|
F | 2 | 11.0 | 1.0 | 2.0 | 0.0 | 0.5 | 0.0 | 0.5 | 2.5 | 0.5 | -1 | -0.5 | -4.7 | 20.0 | 0.0 | 0.0 | -1.02 | 17.0 | 20.0 |
B. Senden
|
G | 14 | 3.3 | 0.6 | 0.5 | 0.4 | 0.1 | 0.0 | 0.1 | 0.4 | 1.1 | 17 | 1.9 | 36.2 | 40.0 | 33.3 | 50.0 | -1.2 | 52.4 | 50.0 |
Z. Bershers
|
C | 10 | 2.3 | 0.6 | 0.4 | 0.2 | 0.0 | 0.2 | 0.0 | 0.6 | 0.8 | - | - | - | 33.3 | 33.3 | 0 | - | 50.0 | 50.0 |
M. Heyer
|
F | 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