Towson Tigers
2026 Team Stats (30 games)
66.2
PPG
65.8
Opp
+0.4
Margin
38.4%
FG%
30.9%
3P%
69.1%
FT%
38.5
RPG
13.1
APG
14.3
TO
83.4
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 → | 985 (#429) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +11.4 (#181) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.561 (#161) | AdjO 67.7 | AdjD 65.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.695 (#202) | 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 → | 0.673 (#199) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1030 (#197) | RD 130 | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
I. Johnston
|
G | 30 | 30.5 | 16.0 | 2.2 | 2.4 | 0.9 | 0.2 | 1.8 | 12.8 | 7.1 | -31 | -1.3 | -2.5 | 41.7 | 33.9 | 80.6 | -1.1 | 54.6 | 49.1 |
T. Shepard
|
G | 30 | 27.1 | 9.3 | 3.9 | 1.8 | 1.0 | 0.0 | 1.6 | 8.1 | 6.4 | 52 | 2.3 | 4.1 | 36.2 | 26.6 | 75.9 | 3.1 | 48.0 | 40.5 |
Z. Khalil
|
G | 26 | 28.3 | 9.2 | 3.4 | 1.5 | 0.6 | 0.5 | 2.0 | 9.0 | 4.0 | 8 | 0.3 | 0.6 | 37.3 | 29.9 | 70.7 | -0.2 | 46.0 | 42.3 |
M. Marchbanks
|
G | 15 | 16.5 | 6.9 | 2.3 | 0.7 | 0.7 | 0.1 | 0.9 | 6.7 | 3.1 | 12 | 1.5 | 8.0 | 35.6 | 35.2 | 80.0 | 1.52 | 47.9 | 45.0 |
T. Sjokvist
|
G | 30 | 24.5 | 6.8 | 2.7 | 2.9 | 0.5 | 0.1 | 2.1 | 7.3 | 3.6 | - | - | - | 34.7 | 32.8 | 52.9 | - | 45.0 | 44.5 |
V. Matulevicius
|
G | 30 | 17.1 | 5.6 | 2.3 | 1.4 | 0.6 | 0.1 | 1.2 | 5.4 | 3.3 | 15 | 0.7 | 2.0 | 39.9 | 39.1 | 33.3 | 1.59 | 47.4 | 48.2 |
S. Turner
|
G | 30 | 24.1 | 5.3 | 6.0 | 0.8 | 1.0 | 0.1 | 1.2 | 4.3 | 7.7 | -44 | -1.8 | -4.5 | 46.5 | 16.0 | 57.6 | -0.76 | 51.0 | 48.1 |
K. Morris
|
F | 30 | 19.0 | 4.5 | 6.3 | 0.6 | 1.0 | 2.0 | 1.0 | 5.1 | 8.4 | 34 | 1.5 | 1.8 | 35.9 | 20.7 | 57.6 | 3.76 | 40.3 | 37.9 |
H. Dereje
|
F | 30 | 14.3 | 4.4 | 4.4 | 0.6 | 0.2 | 0.2 | 1.5 | 4.2 | 4.1 | -15 | -0.7 | -2.1 | 42.1 | 0 | 69.4 | 1.8 | 46.2 | 42.1 |
S. Baynes
|
G | 19 | 6.4 | 1.8 | 0.6 | 0.7 | 0.5 | 0.0 | 0.4 | 1.1 | 2.3 | -31 | -1.7 | -16.2 | 45.0 | 28.6 | 77.8 | -2.51 | 60.9 | 50.0 |
A. Barnes
|
G | 20 | 5.4 | 1.6 | 0.3 | 0.4 | 0.1 | 0.0 | 0.5 | 2.1 | -0.2 | 110 | 4.4 | 5.5 | 26.2 | 20.0 | 50.0 | 3.15 | 35.8 | 34.5 |
A. Langley
|
F | 19 | 6.4 | 1.2 | 2.2 | 0.3 | 0.1 | 0.2 | 0.7 | 1.6 | 1.5 | -22 | -1.4 | -11.9 | 29.0 | 0.0 | 50.0 | -3.02 | 31.9 | 29.0 |
J. Watson
|
G | 8 | 1.4 | 0.2 | 0.0 | 0.1 | 0.1 | 0.0 | 0.0 | 0.2 | 0.2 | -3 | -0.6 | -126.3 | 50.0 | 0.0 | 0 | -0.16 | 50.0 | 50.0 |
Nadeya Regala
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Jaymee Wadey
|
F | 1 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 1.0 | -3.0 | - | - | - | 0.0 | 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