Long Island University Sharks
2022 Team Stats (4 games)
52.5
PPG
59.8
Opp
-7.3
Margin
35.8%
FG%
25.3%
3P%
56.8%
FT%
35.3
RPG
9.5
APG
18.5
TO
81.3
Pace
Model Outputs
2021-2022
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 → | 1040 (#186) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1014 (#227) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +5.8 (#309) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.846 (#57) | - |
2022 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2021-11-24 | vs | Manhattan Jaspers | L | 52 - 61 |
| 2021-12-13 | @ | Columbia Lions | L | 55 - 65 |
| 2022-03-03 | @ | Bryant Bulldogs | W | 48 - 47 |
| 2022-03-07 | @ | Wagner Seahawks | L | 55 - 66 |
2022 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B. Thomas
|
G | 4 | 32.5 | 15.2 | 6.8 | 1.8 | 3.0 | 0.0 | 3.8 | 14.2 | 8.8 | - | - | - | 38.6 | 27.3 | 91.7 | 0.18 | 49.0 | 43.9 |
E. O'Brien
|
G | 4 | 26.0 | 9.5 | 1.5 | 0.5 | 1.5 | 0.0 | 3.5 | 9.0 | 0.5 | -107 | -5.3 | -29.8 | 38.9 | 33.3 | 30.0 | 0.27 | 47.0 | 48.6 |
E. Russell
|
F | 2 | 21.5 | 7.0 | 5.5 | 1.0 | 0.5 | 0.5 | 0.5 | 9.5 | 4.5 | 26 | 2.6 | 15.8 | 31.6 | 0.0 | 66.7 | 0.41 | 34.4 | 31.6 |
K. Taylor
|
G | 4 | 23.0 | 7.0 | 3.2 | 3.0 | 1.2 | 0.2 | 3.2 | 4.2 | 7.2 | 37 | 1.0 | 6.0 | 76.5 | 0 | 50.0 | 1.6 | 74.6 | 76.5 |
S. Sanford
|
G | 2 | 25.0 | 6.5 | 0.5 | 0.5 | 1.5 | 0.0 | 1.0 | 9.0 | -1.0 | - | - | - | 27.8 | 27.3 | 0 | 0.05 | 36.1 | 36.1 |
A. Flynn
|
F | 2 | 22.5 | 6.0 | 4.0 | 0.5 | 0.0 | 1.5 | 1.5 | 7.0 | 3.5 | - | - | - | 35.7 | 25.0 | 50.0 | -0.0 | 40.3 | 39.3 |
K. Bell
|
F | 4 | 21.0 | 4.8 | 4.8 | 1.0 | 1.0 | 0.5 | 1.2 | 7.0 | 3.8 | - | - | - | 25.0 | 0 | 62.5 | 0.53 | 30.1 | 25.0 |
D. Grim
|
G | 4 | 24.8 | 3.8 | 2.2 | 1.2 | 1.2 | 0.5 | 1.0 | 5.2 | 2.8 | - | - | - | 28.6 | 18.2 | 50.0 | 0.27 | 34.3 | 33.3 |
Z. Hache
|
G | 4 | 13.2 | 2.0 | 4.2 | 0.8 | 0.8 | 0.0 | 1.5 | 3.5 | 2.8 | - | - | - | 28.6 | 0.0 | 0.0 | 0.05 | 26.1 | 28.6 |
T. Eke
|
F | 4 | 8.2 | 0.5 | 1.5 | 0.0 | 0.2 | 0.5 | 1.2 | 0.8 | 0.8 | -113 | -4.9 | -28.4 | 33.3 | 0 | 0 | -0.06 | 33.3 | 33.3 |
C. Gray
|
G | 3 | 10.7 | 0.0 | 2.0 | 0.0 | 1.3 | 0.0 | 0.3 | 0.0 | 3.0 | 0 | 0.0 | 0.0 | 0 | 0 | 0 | 0.6 | 0 | 0 |
M. Perkins
|
F | 2 | 4.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | -0.61 | 0 | 0 |
D. Butler-Worley
|
F | 2 | 7.0 | 0.0 | 0.5 | 0.5 | 0.0 | 0.0 | 0.5 | 1.5 | -1.0 | - | - | - | 0.0 | 0.0 | 0 | 0.46 | 0.0 | 0.0 |
D. Carter
|
C | 1 | 4.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | -8 | -0.7 | -4.3 | 0.0 | 0.0 | 0 | 0.58 | 0.0 | 0.0 |
M. Whiteside
|
F | 1 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -1.0 | - | - | - | 0.0 | 0 | 0 | 0.01 | 0.0 | 0.0 |
T. Copeland
|
G | 1 | 4.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | - | - | - | 0 | 0 | 0 | -0.54 | 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