🐻⬇️🏀

UMBC

Also known as: UMBC
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 → 1020 (#305) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1061 (#226) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +56 elo More → 1011 (#355) HCA +56 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.0 More → +30.8 (#55) HCA +3.0
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.999 (#56) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +35.6 More → 0.984 (#62) AdjNet +35.6
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +35.1 More → 0.986 (#63) AdjNet +35.1
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 95.7 | AdjD 64.7 More → 0.944 (#35) AdjO 95.7 | AdjD 64.7
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 82.0 | AdjD 71.0 More → 0.730 (#79) AdjO 82.0 | AdjD 71.0
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 → 0.896 (#32) 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 → 0.859 (#35) Blend of Elo, BT, Margin, PythLog, PtsOD

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-24 vs Notre Dame (MD) W 102 - 52

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%
Cougar Downing - 1 17.6 19.0 3.0 2.0 2.0 0.0 0.0 8.0 18.0 - - - 75.0 71.4 100.0 - 107.0 106.2
Josh Odunowo - 1 16.0 15.0 3.0 0.0 0.0 1.0 1.0 10.0 8.0 - - - 70.0 0 50.0 - 68.9 70.0
Daylon Dickerson - 1 14.3 12.0 9.0 5.0 1.0 0.0 1.0 6.0 20.0 - - - 66.7 0 80.0 - 73.2 66.7
Ace Valentine - 1 24.0 10.0 7.0 6.0 0.0 0.0 1.0 7.0 15.0 - - - 57.1 66.7 0 - 71.4 71.4
Jose Roberto Tanchyn - 1 15.1 9.0 3.0 0.0 0.0 1.0 1.0 6.0 6.0 - - - 66.7 33.3 0 - 75.0 75.0
DJ Armstrong - 1 24.0 8.0 2.0 1.0 0.0 1.0 4.0 8.0 0.0 - - - 37.5 28.6 0 - 50.0 50.0
Jake Stout - 1 8.0 8.0 1.0 0.0 0.0 0.0 1.0 4.0 4.0 - - - 75.0 50.0 100.0 - 90.1 87.5
Caden Diggs - 1 17.6 7.0 3.0 1.0 0.0 1.0 0.0 8.0 4.0 - - - 37.5 50.0 0 - 43.8 43.8
Jah'Likai King - 1 28.9 6.0 10.0 0.0 3.0 1.0 1.0 7.0 12.0 0 0.0 0.0 42.9 0.0 0 -0.19 42.9 42.9
Riley Jacobs - 1 17.9 5.0 7.0 1.0 2.0 2.0 1.0 4.0 12.0 - - - 50.0 0.0 50.0 - 51.2 50.0
Tim Eze - 1 13.4 3.0 3.0 1.0 2.0 0.0 2.0 1.0 6.0 - - - 0.0 0.0 75.0 - 54.3 0.0
Saahil Thakkar - 1 3.3 0.0 0.0 0.0 0.0 0.0 0.0 2.0 -2.0 - - - 0.0 0.0 0 - 0.0 0.0

Numbers/Game vs RAPM

Not enough players with both Numbers/Game and RAPM to plot.

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