Long Island University Sharks
2026 Team Stats (29 games)
71.2
PPG
62.7
Opp
+8.5
Margin
42.4%
FG%
34.1%
3P%
73.7%
FT%
38.2
RPG
14.0
APG
16.2
TO
83.9
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 → | 1117 (#47) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +3.9 (#274) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.560 (#163) | AdjO 68.7 | AdjD 66.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.628 (#232) | 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 → | 0.626 (#219) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1053 (#170) | RD 123 | GP 29 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
K. Toure
|
F | 28 | 29.5 | 19.3 | 10.1 | 3.0 | 2.0 | 1.4 | 4.2 | 14.8 | 16.9 | 192 | 8.3 | 14.3 | 47.8 | 36.4 | 79.5 | 4.44 | 55.4 | 49.3 |
J. Williams
|
G | 22 | 28.4 | 13.6 | 6.7 | 1.8 | 0.8 | 0.3 | 1.8 | 9.8 | 11.6 | -14 | -0.6 | -1.0 | 47.2 | 41.8 | 74.4 | -0.89 | 59.9 | 56.0 |
S. Akridge
|
G | 29 | 31.9 | 9.4 | 2.1 | 3.3 | 1.2 | 0.2 | 1.6 | 8.6 | 6.1 | 154 | 7.0 | 12.1 | 36.8 | 33.7 | 77.5 | -0.23 | 51.2 | 48.6 |
K. Gaines
|
G | 28 | 20.7 | 8.8 | 6.1 | 1.1 | 0.8 | 0.4 | 1.5 | 7.4 | 8.4 | 107 | 4.9 | 9.6 | 48.3 | 28.6 | 60.3 | 1.97 | 52.1 | 49.8 |
J. Reed
|
G | 2 | 19.5 | 8.5 | 2.5 | 2.5 | 1.5 | 0.0 | 2.0 | 9.0 | 4.0 | 21 | 10.5 | 284.7 | 44.4 | 25.0 | 0 | 0.28 | 47.2 | 47.2 |
H. Humphrey
|
G | 29 | 25.4 | 8.2 | 2.1 | 0.9 | 1.0 | 0.2 | 1.9 | 7.2 | 3.3 | 178 | 8.1 | 15.6 | 37.1 | 35.3 | 75.6 | 0.26 | 51.6 | 48.3 |
L. Molnárová
|
F | 18 | 21.1 | 7.1 | 3.8 | 1.1 | 0.4 | 0.1 | 1.6 | 6.3 | 4.5 | 91 | 4.5 | 10.8 | 42.1 | 33.3 | 77.8 | -1.85 | 52.1 | 49.6 |
L. Nuñez
|
F | 29 | 19.8 | 4.2 | 2.3 | 1.1 | 0.4 | 1.3 | 0.7 | 4.3 | 4.3 | - | - | - | 33.9 | 32.9 | 73.3 | - | 46.3 | 44.4 |
C. Wiley
|
G | 29 | 19.6 | 3.6 | 1.6 | 1.1 | 0.6 | 0.2 | 1.5 | 2.7 | 3.0 | 125 | 6.0 | 19.8 | 43.0 | 20.0 | 64.2 | -0.34 | 51.3 | 44.9 |
I. Tanedo
|
G | 26 | 15.0 | 2.5 | 0.8 | 1.2 | 0.3 | 0.0 | 1.7 | 2.3 | 0.9 | 10 | 0.5 | 1.3 | 37.3 | 30.8 | 72.7 | -3.32 | 46.6 | 40.7 |
S. Diallo Toure
|
C | 9 | 8.8 | 2.0 | 3.1 | 0.2 | 0.2 | 0.3 | 1.2 | 1.4 | 3.2 | 41 | 3.4 | 21.2 | 30.8 | 0 | 83.3 | -2.24 | 49.2 | 30.8 |
C. Nuñez
|
F | 19 | 5.7 | 0.7 | 0.9 | 0.2 | 0.0 | 0.4 | 0.6 | 1.4 | 0.2 | - | - | - | 19.2 | 8.3 | 66.7 | - | 23.8 | 21.2 |
K. Klaer
|
F | 5 | 3.6 | 0.4 | 1.8 | 0.2 | 0.0 | 0.2 | 0.0 | 0.6 | 2.0 | - | - | - | 33.3 | 0 | 0 | - | 33.3 | 33.3 |
Kennady Gordon
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | 143 | 7.2 | 13.1 | - | - | - | 3.11 | - | - |
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