🐻⬇️🏀

Binghamton

Also known as: Binghamton
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 → 1098 (#150) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +62 elo More → 1017 (#314) HCA +62 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More → +40.8 (#44) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 1.000 (#86) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +70.6 More → 1.000 (#34) NetEff +70.6
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +68.1 More → 1.000 (#19) AdjNet +68.1
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +68.0 More → 1.000 (#30) AdjNet +68.0
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 81.5 | AdjD 41.8 More → 0.974 (#40) AdjO 81.5 | AdjD 41.8
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 65.6 | AdjD 56.5 More → 0.695 (#131) AdjO 65.6 | AdjD 56.5
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 → 0.966 (#19) 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 → 0.945 (#25) Blend of Elo, BT, Margin, PythLog, PtsOD

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-03 vs SUNY Geneseo W 86 - 35

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%
Kendall Bennett - 1 22.3 16.0 7.0 0.0 1.0 0.0 0.0 9.0 15.0 - - - 55.6 0 85.7 - 66.2 55.6
Meghan Casey - 1 20.1 13.0 1.0 4.0 2.0 0.0 0.0 7.0 13.0 - - - 71.4 60.0 0 - 92.9 92.9
Bella Pucci - 1 21.2 12.0 3.0 1.0 3.0 0.0 0.0 9.0 10.0 - - - 55.6 25.0 50.0 - 60.7 61.1
Leah Middleton - 1 23.1 12.0 3.0 2.0 3.0 0.0 0.0 12.0 8.0 - - - 41.7 28.6 0 - 50.0 50.0
Yanniah Boyd - 1 20.1 10.0 5.0 2.0 2.0 0.0 3.0 9.0 7.0 - - - 44.4 40.0 0 - 55.6 55.6
Kaia Goode - 1 22.5 10.0 1.0 5.0 6.0 0.0 1.0 11.0 10.0 - - - 36.4 0.0 66.7 - 40.6 36.4
Klarissa Goode - 1 13.9 7.0 2.0 2.0 3.0 0.0 0.0 5.0 9.0 - - - 60.0 50.0 0.0 - 64.3 70.0
Ashley Redd - 1 16.0 3.0 1.0 0.0 2.0 0.0 1.0 5.0 0.0 - - - 20.0 33.3 0 - 30.0 30.0
Daysha Salgado - 1 17.5 3.0 5.0 1.0 1.0 0.0 1.0 2.0 7.0 - - - 50.0 0 50.0 - 52.1 50.0
Carletta Bennett - 1 17.5 0.0 2.0 0.0 1.0 0.0 1.0 3.0 -1.0 12 1.7 53.6 0.0 0.0 0 1.29 0.0 0.0
Leah Fowler - 1 5.8 0.0 0.0 0.0 0.0 0.0 0.0 3.0 -3.0 - - - 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