🐻⬇️🏀

Walsh

Season: 2026 2025 2024 2023 2022 2020 2014
Also known as: Walsh
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 → 1029 (#261) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1088 (#164) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +56 elo More → 1012 (#351) HCA +56 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.0 More → +18.5 (#135) HCA +3.0
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.970 (#207) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +30.1 More → 0.970 (#111) AdjNet +30.1
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +29.6 More → 0.970 (#118) AdjNet +29.6
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 83.5 | AdjD 61.3 More → 0.882 (#119) AdjO 83.5 | AdjD 61.3
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 80.2 | AdjD 73.7 More → 0.643 (#158) AdjO 80.2 | AdjD 73.7
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 → 0.805 (#95) 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 → 0.770 (#114) 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 → 1152 (#96) RD 350 | GP 1

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-24 vs Carnegie Mellon W 98 - 72

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%
Matthew Biddell - 1 27.4 25.0 4.0 2.0 5.0 0.0 2.0 17.0 17.0 - - - 64.7 25.0 50.0 - 69.9 70.6
Quintero Barnett - 1 27.4 25.0 4.0 2.0 5.0 0.0 2.0 17.0 17.0 - - - 64.7 25.0 50.0 - 69.9 70.6
Kobe Mitchell - 1 27.4 15.0 3.0 3.0 1.0 0.0 1.0 10.0 11.0 - - - 50.0 20.0 80.0 - 61.5 55.0
Kaleb Schaffer - 1 17.6 15.0 2.0 0.0 1.0 0.0 0.0 6.0 12.0 - - - 83.3 80.0 100.0 - 116.5 116.7
Zack Oddo - 1 27.5 11.0 3.0 1.0 1.0 0.0 2.0 5.0 9.0 - - - 60.0 50.0 60.0 - 76.4 80.0
Grady Schroeder - 1 25.9 10.0 5.0 4.0 0.0 0.0 0.0 7.0 12.0 - - - 42.9 0.0 80.0 - 54.3 42.9
Aiden Satterfield - 1 9.7 7.0 2.0 3.0 1.0 0.0 0.0 4.0 9.0 - - - 75.0 50.0 0 - 87.5 87.5
Jaden Jefferson - 1 17.7 4.0 3.0 3.0 4.0 0.0 0.0 5.0 9.0 - - - 40.0 0.0 0 - 40.0 40.0
Myers Gottfried - 1 8.2 2.0 2.0 1.0 0.0 0.0 0.0 5.0 0.0 - - - 20.0 0.0 0 - 20.0 20.0
Nate Frascone - 1 4.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - - - 0 0 0 - 0 0
Andras Lane - 1 2.2 0.0 0.0 0.0 0.0 0.0 0.0 1.0 -1.0 - - - 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