American University Eagles
2026 Team Stats (28 games)
55.2
PPG
66.3
Opp
-11.1
Margin
35.7%
FG%
26.8%
3P%
74.6%
FT%
34.3
RPG
11.6
APG
14.5
TO
75.5
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 → | 849 (#572) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -3.4 (#342) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.303 (#558) | AdjO 57.4 | AdjD 66.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.303 (#386) | 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 → | 0.286 (#409) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 739 (#570) | RD 148 | GP 28 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
C. Tuhy
|
F | 28 | 32.4 | 11.8 | 11.3 | 1.4 | 1.0 | 1.1 | 2.2 | 10.9 | 13.5 | -39 | -1.7 | -2.0 | 40.5 | 33.0 | 74.2 | 0.96 | 49.4 | 46.1 |
M. Driscoll
|
G | 28 | 33.0 | 11.1 | 2.9 | 2.4 | 1.2 | 0.1 | 2.0 | 11.2 | 4.5 | -48 | -2.1 | -2.4 | 35.0 | 29.9 | 78.5 | -0.35 | 45.4 | 41.4 |
M. Moore-Nicholson
|
G | 28 | 28.2 | 10.6 | 2.8 | 1.0 | 0.6 | 0.1 | 2.4 | 10.2 | 2.5 | -59 | -2.6 | -3.3 | 34.1 | 33.7 | 80.0 | -1.35 | 45.6 | 39.7 |
A. Rescifina
|
G | 28 | 27.2 | 5.9 | 3.6 | 1.3 | 0.6 | 0.1 | 1.6 | 5.1 | 4.8 | -12 | -0.5 | -0.8 | 41.3 | 13.3 | 79.2 | 1.88 | 49.3 | 42.7 |
L. Nogues
|
G | 19 | 22.8 | 4.8 | 2.0 | 2.1 | 1.2 | 0.2 | 2.5 | 5.3 | 2.5 | -25 | -2.1 | -4.4 | 32.7 | 26.9 | 54.5 | 0.43 | 41.6 | 39.6 |
G. Koepke
|
F | 13 | 12.5 | 4.4 | 2.6 | 0.8 | 0.3 | 0.5 | 0.8 | 4.5 | 3.3 | -4 | -0.7 | -2.2 | 41.4 | 33.3 | 80.0 | 0.6 | 45.7 | 42.2 |
L. Salazar
|
G | 27 | 25.6 | 3.4 | 1.9 | 2.4 | 0.4 | 0.0 | 1.8 | 4.6 | 1.8 | -54 | -2.3 | -3.2 | 24.2 | 21.0 | 64.7 | -2.52 | 35.4 | 33.1 |
E. Pingree
|
F | 19 | 9.9 | 3.3 | 1.5 | 0.3 | 0.1 | 0.2 | 0.6 | 3.1 | 1.7 | -36 | -2.4 | -8.4 | 44.1 | 29.2 | 50.0 | -1.59 | 50.4 | 50.0 |
E. Archer
|
G | 28 | 11.6 | 2.7 | 2.5 | 0.2 | 0.2 | 0.1 | 0.5 | 2.7 | 2.6 | -13 | -0.6 | -1.6 | 30.7 | 15.6 | 72.7 | -0.77 | 41.9 | 34.0 |
K. Greyvensteyn
|
G | 23 | 12.3 | 2.0 | 1.3 | 0.6 | 0.3 | 0.0 | 0.5 | 2.1 | 1.7 | -17 | -1.0 | -3.4 | 39.6 | 24.2 | 0.0 | -0.08 | 47.5 | 47.9 |
M. Bolesky
|
G | 18 | 6.3 | 0.7 | 0.7 | 0.4 | 0.1 | 0.0 | 0.4 | 1.2 | 0.2 | 15 | 0.9 | 4.6 | 23.8 | 8.3 | 50.0 | 1.63 | 27.4 | 26.2 |
A. Jude
|
G | 10 | 6.9 | 0.5 | 0.2 | 0.2 | 0.2 | 0.0 | 0.1 | 1.3 | -0.3 | 4 | 0.4 | 3.1 | 15.4 | 14.3 | 0 | 0.8 | 19.2 | 19.2 |
V. Sheng
|
G | 2 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2 | 0.7 | 10.9 | 0 | 0 | 0 | 0.23 | 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