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Furman

Season: 2026 2023 2018 2015 2014
Also known as: Furman
Program History

Model Outputs

2025-2026
Catalog

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 → 1088 (#172) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +62 elo More → 1027 (#260) HCA +62 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More → +62.3 (#6) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 1.000 (#94) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +41.3 More → 0.992 (#104) AdjNet +41.3
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +40.4 More → 0.993 (#106) AdjNet +40.4
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 92.0 | AdjD 57.6 More → 0.958 (#73) AdjO 92.0 | AdjD 57.6
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 86.9 | AdjD 57.0 More → 0.938 (#6) AdjO 86.9 | AdjD 57.0
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 → 0.967 (#18) 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 → 0.957 (#19) Blend of Elo, BT, Margin, PythLog, PtsOD

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-12-30 vs Brevard W 110 - 54

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%
Clare Coyle - 1 20.0 18.0 10.0 3.0 1.0 1.0 1.0 13.0 19.0 - - - 61.5 0 66.7 - 62.8 61.5
Lauren Bailey - 1 24.4 15.0 0.0 2.0 1.0 0.0 0.0 10.0 8.0 - - - 50.0 50.0 0 - 75.0 75.0
Alyssa Ervin - 1 21.9 13.0 3.0 2.0 3.0 2.0 2.0 8.0 13.0 - - - 37.5 20.0 66.7 - 54.3 43.8
Raina McGowens - 1 23.5 13.0 7.0 0.0 3.0 0.0 0.0 12.0 11.0 - - - 41.7 0.0 50.0 - 44.4 41.7
Sophia Pearl - 1 18.7 12.0 2.0 5.0 1.0 0.0 1.0 9.0 10.0 - - - 44.4 66.7 0 - 66.7 66.7
Kyraha Parnell - 1 19.5 10.0 4.0 3.0 5.0 0.0 0.0 5.0 17.0 - - - 80.0 0 100.0 - 85.0 80.0
Samaria Taylor - 1 14.0 7.0 2.0 2.0 4.0 0.0 0.0 7.0 8.0 -30 -2.5 -28.9 28.6 0.0 50.0 -1.48 36.3 28.6
Chantelle Stuart - 1 17.6 6.0 4.0 6.0 1.0 1.0 3.0 4.0 11.0 - - - 75.0 0 0 - 75.0 75.0
Brooklyn King - 1 16.8 5.0 6.0 0.0 2.0 1.0 2.0 8.0 4.0 - - - 25.0 33.3 0.0 - 28.2 31.2
Tyriana Berry - 1 8.5 4.0 6.0 0.0 1.0 1.0 1.0 3.0 8.0 - - - 66.7 0 0 - 66.7 66.7
Channing Warren - 1 9.2 4.0 1.0 1.0 0.0 1.0 0.0 3.0 4.0 - - - 66.7 0 0 - 66.7 66.7
Hilary Englert - 1 6.0 3.0 1.0 0.0 0.0 0.0 0.0 1.0 3.0 - - - 100.0 100.0 0 - 150.0 150.0

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