🐻⬇️🏀

UNCW

Also known as: UNCW
Program History

Model Outputs

2025-2026
Catalog

Output is shown as model rating with league rank in parentheses when available.

Model Output Notes
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1038 (#199) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +95 elo More → 996 (#302) HCA +95 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.3 More → +8.6 (#182) HCA +3.3
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.992 (#57) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +26.9 More → 0.957 (#70) AdjNet +26.9
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +28.7 More → 0.968 (#57) AdjNet +28.7
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 100.7 | AdjD 72.0 More → 0.931 (#29) AdjO 100.7 | AdjD 72.0
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 80.2 | AdjD 74.9 More → 0.617 (#127) AdjO 80.2 | AdjD 74.9
Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.715 (#127) 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. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.670 (#157) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 350 | GP 1 More → 1088 (#130) RD 350 | GP 1

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-03 vs Mount Olive W 106 - 77

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%
Nolan Hodge - 1 26.1 21.0 5.0 2.0 1.0 1.0 0.0 14.0 16.0 - - - 57.1 66.7 33.3 - 68.5 71.4
Madison Durr - 1 21.3 18.0 5.0 4.0 0.0 0.0 1.0 6.0 20.0 - - - 66.7 100.0 90.0 - 86.5 75.0
Patrick Wessler - 1 21.7 17.0 14.0 2.0 2.0 4.0 0.0 8.0 31.0 - - - 87.5 0 60.0 - 83.3 87.5
Greedy Williams - 1 27.1 14.0 4.0 3.0 1.0 0.0 1.0 10.0 11.0 -27 -1.3 -6.5 50.0 0.0 66.7 2.7 55.4 50.0
Noah Ross - 1 27.7 13.0 3.0 3.0 0.0 0.0 0.0 6.0 13.0 - - - 66.7 0.0 71.4 - 71.6 66.7
Christian May - 1 18.4 9.0 4.0 0.0 0.0 0.0 4.0 11.0 -2.0 - - - 27.3 50.0 0 - 40.9 40.9
Gavin Walsh - 1 28.0 9.0 6.0 2.0 1.0 0.0 4.0 10.0 4.0 - - - 40.0 0.0 16.7 - 35.6 40.0
Makoi Mabor Makoi - 1 14.1 2.0 4.0 1.0 0.0 0.0 0.0 3.0 4.0 - - - 33.3 0 0 - 33.3 33.3
Makel Smith - 1 6.4 2.0 0.0 0.0 0.0 0.0 1.0 2.0 -1.0 34 1.6 7.3 50.0 0.0 0 0.2 50.0 50.0
Grady Whitt - 1 4.7 1.0 0.0 0.0 1.0 0.0 0.0 0.0 2.0 - - - 0 0 50.0 - 56.8 0
JoJo Fullwood - 1 4.7 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