Le Moyne Dolphins
2026 Team Stats (30 games)
72.9
PPG
74.0
Opp
-1.1
Margin
45.6%
FG%
33.8%
3P%
71.8%
FT%
34.9
RPG
14.1
APG
13.2
TO
77.4
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 → | 960 (#587) | HCA +109 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +4.9 (#305) | HCA +2.5 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.463 (#440) | AdjO 72.2 | AdjD 73.9 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.563 (#303) | 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 → | 0.529 (#304) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 902 (#480) | RD 157 | GP 30 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
S. Jackson
|
F | 25 | 30.6 | 16.0 | 8.1 | 2.2 | 0.5 | 1.7 | 2.5 | 9.5 | 16.5 | -28 | -1.4 | -2.6 | 63.7 | 50.0 | 72.4 | 0.19 | 67.6 | 63.9 |
T. Mosquera
|
G | 30 | 31.8 | 13.2 | 5.7 | 2.3 | 1.4 | 0.6 | 2.0 | 11.3 | 9.9 | -13 | -0.6 | -0.9 | 39.3 | 35.0 | 72.0 | -0.16 | 52.9 | 49.9 |
D. Garang
|
- | 30 | 30.5 | 11.1 | 5.4 | 1.0 | 1.1 | 0.6 | 1.6 | 8.8 | 8.7 | -70 | -3.0 | -6.2 | 45.7 | 33.3 | 71.4 | -0.09 | 56.3 | 53.4 |
J. Sanders
|
G | 27 | 30.6 | 11.0 | 3.5 | 4.6 | 1.0 | 0.0 | 2.6 | 7.8 | 9.6 | -73 | -3.3 | -5.6 | 41.0 | 37.9 | 75.6 | 0.01 | 55.3 | 46.9 |
T. Rainwater
|
G | 30 | 24.1 | 9.6 | 4.3 | 1.6 | 0.6 | 0.2 | 1.8 | 5.5 | 9.1 | 31 | 1.3 | 3.2 | 57.0 | 52.5 | 65.8 | 0.04 | 66.1 | 63.3 |
S. Hincapie
|
- | 28 | 15.6 | 4.8 | 1.9 | 0.6 | 0.1 | 0.1 | 0.6 | 4.4 | 2.5 | -63 | -2.9 | -9.4 | 41.9 | 24.0 | 57.6 | -0.86 | 48.7 | 46.8 |
J. Blakley
|
G | 30 | 15.8 | 4.1 | 1.2 | 0.6 | 0.1 | 0.0 | 0.4 | 3.8 | 1.7 | -3 | -0.1 | -0.4 | 34.2 | 30.9 | 86.4 | -0.24 | 49.3 | 45.2 |
T. Roe
|
- | 17 | 7.3 | 2.9 | 1.4 | 0.3 | 0.3 | 0.1 | 0.2 | 2.6 | 2.1 | 20 | 2.0 | 39.2 | 40.9 | 32.3 | 100.0 | -0.11 | 54.6 | 52.3 |
E. Greenberg
|
- | 29 | 13.7 | 2.6 | 1.3 | 1.4 | 0.4 | 0.0 | 1.0 | 2.4 | 2.3 | 49 | 2.2 | 9.1 | 31.9 | 28.6 | 85.7 | 0.22 | 47.3 | 40.6 |
I. Nyakundi
|
F | 24 | 9.7 | 2.0 | 1.8 | 0.3 | 0.2 | 0.5 | 0.5 | 1.8 | 2.5 | -27 | -1.4 | -8.2 | 46.5 | 25.0 | 54.5 | -0.37 | 51.2 | 50.0 |
J. Lee
|
- | 16 | 5.0 | 1.4 | 0.4 | 0.2 | 0.2 | 0.0 | 0.1 | 1.1 | 1.1 | 0 | 0.0 | 0.0 | 44.4 | 33.3 | 100.0 | 0.12 | 60.9 | 58.3 |
K. Thomas
|
- | 2 | 4.0 | 1.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.5 | 1.5 | -0.5 | -28 | -1.6 | -4.0 | 33.3 | 0 | 0 | -0.31 | 33.3 | 33.3 |
S. Donnelly
|
- | 5 | 2.4 | 0.6 | 0.2 | 0.0 | 0.0 | 0.0 | 0.2 | 0.6 | 0.0 | 4 | 1.3 | 34.3 | 33.3 | 0.0 | 50.0 | -0.01 | 38.7 | 33.3 |
A. Moss
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | 22 | 11.0 | 23.9 | - | - | - | 0.01 | - | - |
N. Fouts
|
F | 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