🐻⬇️🏀

Wyoming

Also known as: Wyoming
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 → 1015 (#243) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1017 (#267) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +75 elo More → 1014 (#283) HCA +75 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.7 More → +9.0 (#228) HCA +3.7
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.997 (#83) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +43.8 More → 0.994 (#61) AdjNet +43.8
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +43.8 More → 0.995 (#62) AdjNet +43.8
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 72.6 | AdjD 46.9 More → 0.912 (#67) AdjO 72.6 | AdjD 46.9
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 63.9 | AdjD 59.3 More → 0.604 (#165) AdjO 63.9 | AdjD 59.3
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 → 0.736 (#147) 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 → 0.721 (#154) 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 → 1047 (#210) RD 350 | GP 1

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-25 vs Chadron St. W 75 - 38

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%
Malene Pedersen - 1 24.7 26.0 6.0 3.0 1.0 0.0 0.0 16.0 20.0 - - - 68.8 57.1 0 - 81.2 81.2
Henna Sandvik - 1 29.5 12.0 2.0 3.0 1.0 0.0 2.0 12.0 4.0 - - - 50.0 0.0 0 - 50.0 50.0
Payton Muma - 1 19.7 9.0 3.0 3.0 0.0 0.0 2.0 6.0 7.0 - - - 66.7 33.3 0 - 75.0 75.0
Heidur Karlsdottir - 1 6.3 6.0 2.0 0.0 0.0 1.0 1.0 4.0 4.0 - - - 75.0 0 0 - 75.0 75.0
Lana Beslic - 1 21.5 6.0 7.0 6.0 0.0 0.0 4.0 4.0 11.0 - - - 75.0 0 0 - 75.0 75.0
Logann Alvar - 1 20.6 6.0 5.0 0.0 2.0 0.0 0.0 6.0 7.0 - - - 50.0 0.0 0 - 50.0 50.0
Jane Rumpf - 1 9.9 5.0 2.0 1.0 2.0 1.0 1.0 4.0 6.0 - - - 25.0 25.0 100.0 - 51.2 37.5
Aurore Eyango - 1 11.0 4.0 3.0 1.0 0.0 0.0 1.0 4.0 3.0 - - - 0.0 0 100.0 - 34.7 0.0
Liv Blomkvist - 1 13.1 1.0 3.0 0.0 0.0 2.0 0.0 1.0 5.0 - - - 0.0 0 50.0 - 26.6 0.0
Madi Symons - 1 19.0 0.0 3.0 2.0 0.0 0.0 2.0 4.0 -1.0 - - - 0.0 0.0 0 - 0.0 0.0
Peyton Wohlford - 1 19.9 0.0 5.0 2.0 1.0 0.0 1.0 3.0 4.0 - - - 0.0 0.0 0 - 0.0 0.0
Katie Harrington - 1 4.9 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

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