Providence Friars
2026 Team Stats (26 games)
59.5
PPG
67.7
Opp
-8.2
Margin
38.7%
FG%
27.9%
3P%
68.3%
FT%
35.3
RPG
10.9
APG
16.7
TO
81.1
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 → | 971 (#452) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +13.9 (#150) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.444 (#362) | AdjO 61.1 | AdjD 63.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.736 (#182) | 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 → | 0.682 (#194) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 994 (#212) | RD 149 | GP 26 |
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. Gueye
|
G | 26 | 31.6 | 16.2 | 5.9 | 2.2 | 1.7 | 0.8 | 3.5 | 14.2 | 9.1 | 66 | 2.8 | 3.5 | 47.8 | 20.8 | 78.2 | 3.7 | 51.9 | 48.5 |
T. Brown
|
F | 26 | 26.0 | 10.3 | 6.0 | 1.1 | 1.3 | 0.2 | 1.8 | 9.3 | 7.7 | 96 | 4.8 | 10.8 | 42.0 | 18.8 | 75.6 | 2.92 | 48.2 | 42.6 |
O. Gormley
|
G | 25 | 30.7 | 9.2 | 4.1 | 3.6 | 2.7 | 0.2 | 2.2 | 7.8 | 9.8 | -20 | -0.9 | -1.0 | 41.3 | 29.5 | 79.4 | -2.65 | 51.4 | 45.9 |
P. Dunbar
|
G | 26 | 20.2 | 6.2 | 1.0 | 0.7 | 0.4 | 0.1 | 2.1 | 6.4 | -0.0 | 34 | 1.4 | 2.1 | 31.3 | 34.7 | 71.9 | -0.6 | 45.0 | 41.9 |
S. Hall
|
G | 25 | 18.5 | 4.4 | 1.4 | 0.5 | 0.5 | 0.4 | 0.9 | 3.8 | 2.5 | -28 | -1.2 | -3.8 | 35.8 | 34.2 | 64.0 | -2.36 | 51.9 | 49.5 |
P. Moody
|
G | 26 | 18.4 | 4.0 | 2.2 | 1.3 | 1.1 | 0.0 | 2.0 | 4.5 | 2.0 | 9 | 0.4 | 0.8 | 32.5 | 30.2 | 46.7 | 0.48 | 39.6 | 38.0 |
A. Dinges
|
F | 26 | 18.9 | 4.0 | 3.0 | 0.7 | 0.5 | 0.2 | 0.6 | 5.2 | 2.5 | 49 | 2.0 | 3.9 | 30.6 | 20.0 | 53.8 | 5.02 | 36.9 | 35.8 |
N. Kaysia
|
F | 20 | 17.2 | 3.2 | 4.8 | 0.4 | 0.6 | 0.7 | 1.2 | 3.9 | 4.7 | -53 | -4.4 | -10.6 | 35.1 | 16.7 | 39.1 | -1.98 | 36.7 | 35.7 |
S. Mancini
|
F | 22 | 5.6 | 1.4 | 1.3 | 0.1 | 0.0 | 0.0 | 0.5 | 1.4 | 1.0 | 20 | 0.9 | 6.3 | 35.5 | 100.0 | 44.4 | 1.65 | 39.8 | 37.1 |
A. Shields
|
F | 24 | 8.8 | 1.0 | 1.4 | 0.2 | 0.3 | 0.1 | 0.5 | 1.5 | 1.1 | -24 | -1.0 | -3.5 | 28.6 | 17.6 | 0 | -2.18 | 32.9 | 32.9 |
R. Hamburger
|
G | 23 | 9.8 | 1.0 | 0.9 | 0.3 | 0.1 | 0.2 | 0.8 | 1.2 | 0.5 | -18 | -0.9 | -4.9 | 17.9 | 0.0 | 63.6 | -1.34 | 31.8 | 17.9 |
O. Rodrigues
|
G | 6 | 4.0 | 0.7 | 0.3 | 0.0 | 0.0 | 0.0 | 0.2 | 0.7 | 0.2 | -40 | -4.0 | -24.9 | 50.0 | 0.0 | 0 | -4.2 | 50.0 | 50.0 |
E. Imafidon
|
C | 13 | 3.5 | 0.4 | 0.9 | 0.1 | 0.0 | 0.2 | 0.5 | 0.7 | 0.4 | 25 | 1.8 | 12.5 | 22.2 | 0 | 50.0 | 1.13 | 25.3 | 22.2 |
Mariana Padilla
|
G | 1 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -5 | -2.5 | -55.3 | 0 | 0 | 0 | -0.93 | 0 | 0 |
Austeja Babraitis
|
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