🐻⬇️🏀

UChicago

Also known as: UChicago
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 → 1114 (#56) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1274 (#20) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +62 elo More → 1236 (#14) HCA +62 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.3 More → +22.5 (#20) HCA +2.3
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More → +23.6 (#100) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.744 (#336) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +14.1 More → 0.866 (#187) NetEff +14.1
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +30.7 More → 0.972 (#149) AdjNet +30.7
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +30.7 More → 0.974 (#150) AdjNet +30.7
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 70.6 | AdjD 51.7 More → 0.848 (#150) AdjO 70.6 | AdjD 51.7
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 62.6 | AdjD 44.6 More → 0.837 (#41) AdjO 62.6 | AdjD 44.6
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 → 0.913 (#61) 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 → 0.910 (#49) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 100 | GP 19 More → 1339 (#18) RD 100 | GP 19

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-07 @ St. Norbert W 54 - 49
2025-11-08 @ Wis.-Oshkosh L 58 - 60
2025-11-14 vs Marian (WI) W 84 - 29
2025-11-16 vs Tufts W 66 - 57
2025-11-22 vs Rose-Hulman W 85 - 54
2025-11-25 @ Carroll (WI) L 52 - 73
2025-11-29 vs Elmhurst L 0 - 0
2025-12-16 vs Ill. Wesleyan W 73 - 54
2025-12-30 vs Albion W 79 - 57
2026-01-10 vs WashU L 39 - 68
2026-01-16 @ CWRU W 52 - 44
2026-01-18 @ Carnegie Mellon W 61 - 58
2026-01-23 vs Brandeis W 57 - 36
2026-01-25 vs NYU L 55 - 67
2026-01-30 vs Rochester (NY) W 60 - 53
2026-02-01 vs Emory W 54 - 42
2026-02-06 @ Rochester (NY) W 61 - 54
2026-02-08 @ Emory L 29 - 29

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%
Annabelle Spotts - 17 29.6 11.7 6.1 1.3 0.9 0.7 2.9 10.4 7.4 90 4.7 14.1 42.6 33.3 74.5 -0.11 49.7 44.9
Chris Sanders - 17 31.3 9.5 2.6 2.0 1.4 0.4 1.8 8.6 5.6 91 4.8 13.6 41.8 30.2 80.8 1.28 51.4 48.3
Bri Simpson - 16 21.1 7.6 4.1 1.2 1.3 0.1 2.7 7.6 3.9 69 3.8 17.2 41.0 29.6 65.0 2.44 46.3 44.3
Kate Gross - 17 29.4 7.6 2.1 2.1 0.8 0.6 1.9 7.6 3.8 125 6.6 21.1 38.8 30.6 66.7 1.3 46.7 44.6
Alexis Clark - 17 15.8 6.5 4.5 0.6 0.8 0.5 1.2 6.1 5.6 80 4.2 29.3 47.6 0 75.0 0.46 50.0 47.6
Kasi Samuda - 17 22.7 6.4 8.9 1.8 0.8 0.9 1.4 5.2 12.2 110 6.1 22.0 45.5 0 72.5 1.45 51.6 45.5
Caroline Workman - 17 26.9 5.2 4.2 1.7 0.9 1.0 0.9 4.4 7.8 101 5.3 16.8 48.6 25.0 53.3 2.09 54.6 54.1
Karen Xin - 17 10.2 3.4 0.8 0.4 0.4 0.0 0.9 3.4 0.6 52 2.7 43.4 36.8 40.0 25.0 1.02 48.5 49.1
Lindsey Carter - 3 7.9 2.7 2.3 1.0 0.7 0.3 0.7 2.0 4.3 - - - 50.0 0 100.0 - 58.1 50.0
Ruiqi Liu - 16 10.4 2.2 0.9 0.6 0.2 0.2 0.7 2.6 0.8 28 1.6 30.9 29.3 20.0 100.0 0.18 40.1 35.4
Zora Burrell - 5 3.5 1.6 1.2 0.4 0.2 0.0 0.2 1.6 1.6 - - - 50.0 0.0 0.0 - 47.4 50.0
Lauren Miller - 6 3.6 1.5 0.8 0.2 0.3 0.0 0.2 0.8 1.8 14 2.0 3360.0 60.0 0.0 75.0 -0.02 66.6 60.0
Lauren Strifling - 5 7.0 1.4 2.0 0.2 0.4 0.0 0.0 2.0 2.0 - - - 30.0 14.3 0 - 35.0 35.0
Paige Lim - 1 1.8 0.0 0.0 0.0 0.0 0.0 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