🐻⬇️🏀

Milwaukee

Season: 2026 2025 2024
Also known as: Milwaukee
Program History

Model Outputs

2025-2026 latest available
Catalog

No materialized model snapshot for 2024 yet, so this section is showing the latest available team-model rows.

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 → 1178 (#67) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +62 elo More → 1054 (#173) HCA +62 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More → +36.5 (#55) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.991 (#150) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +37.0 More → 0.994 (#82) NetEff +37.0
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +52.9 More → 0.998 (#71) AdjNet +52.9
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +52.5 More → 0.998 (#74) AdjNet +52.5
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 76.7 | AdjD 44.9 More → 0.948 (#87) AdjO 76.7 | AdjD 44.9
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 71.3 | AdjD 53.2 More → 0.837 (#39) AdjO 71.3 | AdjD 53.2
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 → 0.946 (#30) 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 → 0.934 (#32) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 292 | GP 1 More → 1142 (#113) RD 292 | GP 1

2024 Schedule & Results

Date Vs/At Opponent Result Score
2023-11-21 vs Edgewood W 70 - 50

2024 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%
Kendall Nead - 1 30.0 20.0 5.0 1.0 1.0 0.0 5.0 20.0 2.0 - - - 45.0 16.7 100.0 - 48.9 47.5
Kamy Peppler - 1 37.0 12.0 3.0 6.0 4.0 0.0 1.0 9.0 15.0 - - - 44.4 33.3 100.0 0.12 60.7 55.6
Jorey Buwalda - 1 24.0 12.0 6.0 1.0 0.0 0.0 4.0 6.0 9.0 - - - 83.3 0.0 100.0 - 87.2 83.3
Angie Cera - 1 26.0 11.0 2.0 1.0 1.0 0.0 1.0 10.0 4.0 - - - 40.0 0.0 100.0 - 48.6 40.0
Jada Donaldson - 1 37.0 8.0 6.0 6.0 2.0 0.0 1.0 9.0 12.0 - - - 44.4 0.0 0 - 44.4 44.4
Anna Lutz - 1 18.0 4.0 7.0 0.0 0.0 0.0 1.0 6.0 4.0 - - - 16.7 0.0 100.0 - 29.1 16.7
Jada Williams - 1 12.0 3.0 5.0 0.0 2.0 0.0 1.0 4.0 5.0 -75 -6.8 -9.7 25.0 0.0 50.0 0.24 30.7 25.0
Vanessa Jurewicz - 1 5.0 0.0 1.0 0.0 0.0 1.0 0.0 2.0 0.0 - - - 0.0 0.0 0 - 0.0 0.0
Justina Hernandez - 1 5.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 -1.0 7 1.4 2.0 0.0 0 0 0.08 0.0 0.0
Lior Halevi - 1 3.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 -1.0 - - - 0.0 0 0 - 0.0 0.0
Kalvina Eubanks - 1 1.0 0.0 2.0 0.0 0.0 0.0 0.0 1.0 1.0 - - - 0.0 0.0 0 0.05 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