Iona Gaels
2023 Team Stats (5 games)
57.6
PPG
61.8
Opp
-4.2
Margin
46.3%
FG%
35.9%
3P%
56.7%
FT%
27.6
RPG
14.0
APG
20.0
TO
74.0
Pace
Model Outputs
2022-2023
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 → | 1061 (#158) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 991 (#246) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +5.3 (#315) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.438 (#207) | - |
2023 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2022-12-13 | vs | Bethune-Cookman Wildcats | W | 60 - 57 |
| 2023-03-08 | vs | Mount St. Mary's Mountaineers | W | 39 - 37 |
| 2023-03-10 | vs | Siena Saints | W | 67 - 66 |
| 2023-03-11 | vs | Manhattan Jaspers | W | 73 - 60 |
| 2023-03-18 | @ | Duke Blue Devils | L | 49 - 89 |
2023 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
J. Camilion
|
G | 5 | 36.2 | 14.6 | 6.8 | 4.2 | 2.8 | 1.2 | 3.6 | 14.2 | 11.8 | - | - | - | 42.3 | 36.4 | 62.5 | - | 49.0 | 47.9 |
K. Athias
|
C | 5 | 35.4 | 13.8 | 8.0 | 5.6 | 0.8 | 2.0 | 5.6 | 10.4 | 14.2 | - | - | - | 63.5 | 0 | 37.5 | - | 62.1 | 63.5 |
K. Mager
|
G | 5 | 36.6 | 11.2 | 2.6 | 1.0 | 0.4 | 0.2 | 0.8 | 8.8 | 5.8 | - | - | - | 43.2 | 36.8 | 100.0 | - | 61.2 | 59.1 |
N. Otkhmezuri
|
G | 5 | 21.6 | 6.8 | 2.0 | 0.6 | 0.0 | 0.0 | 1.0 | 5.8 | 2.6 | - | - | - | 41.4 | 47.4 | 100.0 | - | 57.7 | 56.9 |
J. Gomez
|
G | 4 | 31.8 | 5.0 | 1.5 | 0.8 | 1.5 | 0.2 | 2.2 | 5.2 | 1.5 | - | - | - | 42.9 | 18.2 | 0 | - | 47.6 | 47.6 |
T. Hodge-Carr
|
G | 5 | 23.6 | 4.2 | 3.0 | 0.6 | 1.2 | 0.2 | 3.2 | 5.4 | 0.6 | - | - | - | 37.0 | 0.0 | 20.0 | - | 36.0 | 37.0 |
I. Lipinski
|
F | 5 | 7.6 | 1.8 | 1.2 | 0.6 | 0.2 | 0.2 | 0.4 | 1.4 | 2.2 | - | - | - | 57.1 | 0 | 50.0 | - | 57.1 | 57.1 |
N. Givon
|
G | 3 | 8.0 | 1.3 | 0.3 | 0.0 | 0.0 | 0.0 | 1.0 | 0.7 | 0.0 | - | - | - | 50.0 | 0 | 100.0 | - | 69.4 | 50.0 |
M. Cenis
|
G | 3 | 11.3 | 0.7 | 0.7 | 1.3 | 1.0 | 0.0 | 1.7 | 1.0 | 1.0 | - | - | - | 33.3 | 0 | 0 | - | 33.3 | 33.3 |
P. Oborilova
|
F | 3 | 3.3 | 0.0 | 0.3 | 0.0 | 0.0 | 0.0 | 0.7 | 0.3 | -0.7 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
Numbers/Game vs RAPM
Not enough players with both Numbers/Game and RAPM to plot.
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