🐻⬇️🏀

UAB

Season: 2026 2023 2022
Also known as: UAB
Program History

Model Outputs

2025-2026
Catalog

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

Model Output Notes
Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → 1025 (#282) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1090 (#156) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +56 elo More → 1004 (#421) HCA +56 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.0 More → +43.1 (#13) HCA +3.0
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 1.000 (#41) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +39.7 More → 0.990 (#44) AdjNet +39.7
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +39.5 More → 0.991 (#44) AdjNet +39.5
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 98.4 | AdjD 64.6 More → 0.956 (#26) AdjO 98.4 | AdjD 64.6
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 86.2 | AdjD 72.1 More → 0.782 (#41) AdjO 86.2 | AdjD 72.1
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 → 0.940 (#9) 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 → 0.912 (#13) Blend of Elo, BT, Margin, PythLog, PtsOD

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-17 vs Rhodes W 112 - 56

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%
Chance Westry - 1 18.2 21.0 6.0 3.0 4.0 0.0 2.0 13.0 19.0 - - - 61.5 50.0 75.0 - 71.1 69.2
Daniel Rivera - 1 29.2 20.0 15.0 4.0 1.0 2.0 0.0 13.0 29.0 -33 -3.3 -137.7 53.8 50.0 50.0 0.62 57.5 57.7
Dayjaun Anderson - 1 18.0 13.0 4.0 2.0 3.0 0.0 0.0 13.0 9.0 45 2.1 11.4 46.2 12.5 0.0 5.42 48.4 50.0
Jacob Meyer - 1 20.6 12.0 2.0 1.0 1.0 1.0 0.0 7.0 10.0 - - - 71.4 50.0 100.0 - 80.6 78.6
KyeRon Lindsay-Martin - 1 21.3 11.0 14.0 0.0 0.0 1.0 2.0 9.0 15.0 - - - 33.3 0 100.0 - 49.1 33.3
Salim London - 1 24.1 10.0 5.0 3.0 1.0 0.0 2.0 7.0 10.0 - - - 42.9 100.0 50.0 - 57.1 57.1
Ahmad Robinson - 1 15.5 9.0 1.0 3.0 2.0 0.0 0.0 5.0 10.0 14 1.0 46.7 60.0 100.0 100.0 0.09 82.7 80.0
Lance Carr - 1 4.8 4.0 0.0 0.0 0.0 0.0 0.0 2.0 2.0 - - - 100.0 0 0 - 100.0 100.0
Evan Chatman - 1 22.6 4.0 7.0 0.0 2.0 0.0 0.0 5.0 8.0 - - - 40.0 0.0 0 - 40.0 40.0
Ari Gooch - 1 14.1 4.0 2.0 4.0 4.0 0.0 1.0 4.0 9.0 - - - 25.0 0.0 100.0 - 41.0 25.0
Quaran McPherson - 1 9.6 4.0 3.0 0.0 0.0 0.0 1.0 6.0 0.0 - - - 33.3 0.0 0 - 33.3 33.3
Joey Kahn - 1 2.1 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 - - - 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