Stony Brook
2026 Team Stats (29 games)
70.0
PPG
69.4
Opp
+0.6
Margin
42.2%
FG%
34.8%
3P%
72.8%
FT%
34.4
RPG
12.7
APG
11.3
TO
76.5
Pace
70.8
AdjO
75.2
AdjD
#227
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 → | 980 (#199) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 928 (#234) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 992 (#475) | HCA +109 elo |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 926 (#633) | HCA +109 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -4.5 (#231) | HCA +2.2 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +8.8 (#244) | HCA +2.5 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +4.3 (#317) | HCA +2.5 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.430 (#221) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.878 (#56) | NetEff +21.0 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.320 (#237) | AdjNet -6.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.317 (#237) | AdjNet -6.6 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.401 (#227) | AdjO 70.8 | AdjD 75.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.488 (#297) | AdjO 71.2 | AdjD 71.7 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.465 (#428) | AdjO 67.0 | AdjD 68.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.658 (#244) | 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 → | 0.498 (#348) | 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 → | 0.616 (#250) | 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 → | 0.476 (#346) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1026 (#214) | RD 148 | GP 29 |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 845 (#623) | RD 147 | GP 32 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
E. Pratt
|
G | 27 | 33.6 | 18.5 | 4.8 | 3.3 | 1.1 | 0.3 | 2.9 | 16.0 | 9.1 | 27 | 1.2 | 1.7 | 42.5 | 31.5 | 74.4 | -0.1 | 51.8 | 47.9 |
Andrej Shoshkikj
|
- | 29 | 26.6 | 11.2 | 2.7 | 2.4 | 1.5 | 0.2 | 1.8 | 7.8 | 8.3 | 39 | 1.7 | 3.7 | 51.1 | 46.2 | 96.2 | -0.0 | 65.2 | 60.7 |
R. Brown III
|
G | 29 | 30.1 | 10.4 | 3.2 | 1.3 | 0.4 | 0.1 | 1.1 | 9.1 | 5.4 | 186 | 9.3 | 13.5 | 36.7 | 36.2 | 84.9 | 1.55 | 52.7 | 48.9 |
C. O'Connor
|
G | 8 | 26.2 | 7.5 | 2.5 | 1.8 | 0.9 | 0.6 | 1.5 | 5.0 | 6.8 | 40 | 3.6 | 10.2 | 55.0 | 28.6 | 80.0 | 0.03 | 64.4 | 60.0 |
R. Goods
|
F | 29 | 24.2 | 6.9 | 5.7 | 2.0 | 1.0 | 0.5 | 1.4 | 6.1 | 8.6 | 21 | 0.9 | 1.9 | 40.1 | 30.8 | 52.3 | -0.36 | 48.6 | 46.9 |
Ethan Simmon
|
- | 25 | 16.0 | 5.9 | 1.3 | 0.4 | 0.4 | 0.2 | 0.4 | 4.4 | 3.5 | 14 | 0.7 | 2.9 | 45.5 | 38.9 | 69.0 | -0.49 | 60.3 | 58.2 |
Tomas Valentiny
|
- | 29 | 19.4 | 5.0 | 3.6 | 0.8 | 0.3 | 0.3 | 0.5 | 4.4 | 5.0 | 25 | 1.1 | 2.7 | 39.5 | 33.3 | 62.1 | 0.06 | 50.8 | 48.8 |
Jonah Butler
|
- | 27 | 12.7 | 4.2 | 1.9 | 0.6 | 0.9 | 0.3 | 0.6 | 3.4 | 3.9 | 47 | 2.2 | 10.2 | 40.9 | 32.1 | 80.0 | 0.43 | 54.8 | 50.5 |
Q. Gorman
|
F | 28 | 17.7 | 3.9 | 3.4 | 0.8 | 0.5 | 0.9 | 0.6 | 3.0 | 5.9 | 4 | 0.2 | 0.4 | 45.9 | 33.3 | 69.2 | -0.17 | 56.0 | 52.9 |
O. Kojenets
|
- | 29 | 10.6 | 2.9 | 3.2 | 0.4 | 0.2 | 0.6 | 0.7 | 2.6 | 4.0 | 22 | 1.0 | 4.9 | 38.2 | 0 | 59.1 | -0.23 | 44.0 | 38.2 |
T. Onyekonwu
|
- | 19 | 8.8 | 1.7 | 0.6 | 0.7 | 0.5 | 0.0 | 0.5 | 2.1 | 0.9 | 21 | 1.3 | 8.9 | 27.5 | 21.7 | 85.7 | -0.16 | 38.3 | 33.8 |
L. Nahar
|
F | 6 | 4.3 | 1.3 | 0.5 | 0.2 | 0.2 | 0.0 | 0.2 | 1.3 | 0.7 | 8 | 2.0 | 49.7 | 25.0 | 33.3 | 100.0 | 0.05 | 45.0 | 37.5 |
Liam Dagostino
|
- | 3 | 4.0 | 1.0 | 2.3 | 0.0 | 0.0 | 0.0 | 0.3 | 1.0 | 2.0 | - | - | - | 33.3 | 0.0 | 50.0 | - | 38.7 | 33.3 |
Jake Harbatkin
|
- | 3 | 4.0 | 0.7 | 0.7 | 0.7 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | - | - | - | 33.3 | 0.0 | 0 | - | 33.3 | 33.3 |
Andrew Okafor
|
- | 3 | 3.7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 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