San Francisco Dons
2026 Team Stats (31 games)
68.8
PPG
67.3
Opp
+1.5
Margin
41.0%
FG%
29.1%
3P%
68.6%
FT%
40.4
RPG
16.1
APG
18.1
TO
88.2
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 → | 1028 (#155) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +13.2 (#158) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.550 (#173) | AdjO 66.2 | AdjD 64.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.774 (#149) | 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 → | 0.740 (#150) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1089 (#147) | RD 107 | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
C. Edokpaigbe
|
G | 31 | 33.3 | 18.0 | 4.5 | 1.5 | 1.5 | 0.6 | 2.5 | 13.1 | 10.4 | -101 | -4.4 | -5.4 | 50.4 | 31.6 | 76.2 | 0.56 | 58.5 | 53.5 |
A. Cargol
|
G | 31 | 32.0 | 9.7 | 3.5 | 4.6 | 1.2 | 0.0 | 3.3 | 8.8 | 7.0 | -80 | -3.5 | -4.4 | 36.1 | 34.5 | 70.8 | -0.56 | 48.1 | 43.4 |
M. Neira
|
G | 31 | 25.6 | 9.2 | 3.9 | 2.0 | 1.6 | 0.1 | 2.1 | 9.9 | 4.7 | -39 | -1.7 | -2.6 | 32.5 | 30.0 | 72.4 | 0.66 | 44.3 | 42.7 |
N. Tausova
|
F | 31 | 24.4 | 7.4 | 4.3 | 1.6 | 1.5 | 0.4 | 1.9 | 7.3 | 6.0 | 6 | 0.3 | 0.4 | 40.0 | 27.4 | 61.3 | 1.43 | 48.2 | 46.9 |
N. Mourio
|
F | 31 | 22.1 | 7.3 | 7.1 | 2.2 | 0.8 | 0.3 | 2.8 | 6.8 | 8.2 | - | - | - | 45.7 | 0.0 | 67.3 | - | 48.7 | 45.7 |
P. Tirado
|
G | 16 | 18.9 | 5.9 | 1.6 | 1.2 | 1.1 | 0.1 | 1.3 | 5.2 | 3.3 | -19 | -1.1 | -2.6 | 45.2 | 36.4 | 85.7 | -0.96 | 54.0 | 52.4 |
M. McIntyre
|
G | 31 | 19.2 | 4.7 | 4.1 | 2.0 | 1.0 | 0.0 | 1.4 | 4.7 | 5.8 | -93 | -4.0 | -9.7 | 41.8 | 19.6 | 55.6 | -3.8 | 46.6 | 45.2 |
M. Ugwah
|
F | 22 | 13.7 | 4.2 | 2.5 | 0.7 | 0.6 | 0.5 | 1.5 | 4.0 | 3.0 | -16 | -1.6 | -3.9 | 42.7 | 0 | 61.5 | 0.62 | 45.8 | 42.7 |
O. Williams
|
G | 20 | 10.4 | 2.6 | 1.8 | 0.3 | 0.2 | 0.2 | 0.6 | 3.4 | 1.2 | -45 | -3.2 | -14.5 | 32.8 | 7.1 | 87.5 | -0.89 | 36.9 | 33.6 |
S. Castro
|
F | 26 | 9.5 | 2.5 | 2.9 | 0.5 | 0.2 | 0.2 | 0.7 | 2.7 | 2.8 | -54 | -3.0 | -12.9 | 32.9 | 0 | 51.4 | -2.08 | 37.5 | 32.9 |
N. Ferrara Horne
|
F | 24 | 10.5 | 1.9 | 1.5 | 0.3 | 0.4 | 0.4 | 0.8 | 1.8 | 2.0 | 5 | 0.3 | 2.0 | 41.9 | 36.4 | 50.0 | -1.54 | 47.6 | 46.5 |
A. Pateman
|
G | 14 | 5.8 | 1.6 | 0.6 | 0.2 | 0.1 | 0.0 | 0.5 | 1.8 | 0.2 | 12 | 1.2 | 15.2 | 36.0 | 23.1 | 40.0 | -0.3 | 42.3 | 42.0 |
S. Priestley
|
F | 12 | 4.6 | 1.2 | 0.8 | 0.2 | 0.2 | 0.0 | 0.1 | 0.8 | 1.6 | 5 | 0.5 | 8.0 | 33.3 | 0.0 | 66.7 | -0.84 | 49.0 | 33.3 |
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