🐻⬇️🏀

Vassar

Season: 2026 2025 2024 2023 2022 2020 2019 2017 2016 2015
Also known as: Vassar
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 → 1175 (#42) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1168 (#54) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +56 elo More → 1098 (#97) HCA +56 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.3 More → +4.7 (#65) HCA +2.3
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.0 More → +2.7 (#304) HCA +3.0
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.470 (#491) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -6.0 More → 0.334 (#437) AdjNet -6.0
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -6.2 More → 0.325 (#437) AdjNet -6.2
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 71.4 | AdjD 76.1 More → 0.394 (#439) AdjO 71.4 | AdjD 76.1
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 72.9 | AdjD 65.8 More → 0.656 (#139) AdjO 72.9 | AdjD 65.8
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 → 0.614 (#300) 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 → 0.629 (#284) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 102 | GP 22 More → 1132 (#123) RD 102 | GP 22

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-12 @ Marist L 61 - 93
2025-11-14 vs SUNY Geneseo W 83 - 68
2025-11-15 vs Hartford W 89 - 74
2025-11-21 vs SUNY New Paltz W 77 - 56
2025-11-22 @ Mt. St. Mary (NY) W 105 - 58
2025-12-03 @ Williams L 69 - 79
2025-12-05 vs Ithaca W 88 - 85
2025-12-06 vs Hobart W 85 - 74
2025-12-30 @ Claremont-M-S L 61 - 73
2026-01-02 @ Chapman L 69 - 70
2026-01-09 vs Clarkson W 56 - 54
2026-01-10 vs St. Lawrence W 70 - 44
2026-01-16 @ RIT W 73 - 64
2026-01-17 @ Union (NY) W 76 - 74
2026-01-20 @ Skidmore W 67 - 46
2026-01-23 vs Rensselaer L 56 - 62
2026-01-24 vs Bard W 93 - 50
2026-01-30 @ St. Lawrence L 56 - 57
2026-01-31 @ Clarkson W 70 - 51
2026-02-03 vs Skidmore W 82 - 75
2026-02-06 @ Bard W 81 - 70
2026-02-07 @ Rensselaer L 58 - 61

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%
Will Householter - 1 38.0 24.0 6.0 5.0 2.0 1.0 2.0 18.0 18.0 56 3.7 33.5 50.0 60.0 75.0 2.18 60.7 58.3
Avery Lee - 9 25.8 16.8 2.8 4.0 1.0 0.0 1.9 13.0 9.7 -2 -0.3 -2.5 46.2 41.3 85.7 0.71 58.4 54.3
Shea Fitzgerald - 21 31.2 15.6 4.1 3.1 1.5 0.0 1.8 13.1 9.4 175 9.2 29.6 38.4 37.7 88.1 8.74 53.7 48.7
Parker Neuenhaus - 21 24.7 12.6 5.9 1.7 0.2 0.7 1.5 10.4 9.1 139 7.3 27.2 53.7 37.5 62.9 3.47 56.8 55.7
Joey Kennedy - 1 30.0 10.0 12.0 7.0 0.0 5.0 1.0 13.0 20.0 37 2.3 24.2 23.1 0 80.0 -0.6 32.9 23.1
Nathan Denham - 19 22.2 9.4 7.4 0.9 1.7 0.8 0.9 7.3 12.0 63 3.7 14.0 55.8 16.7 62.9 2.48 58.0 56.5
Sebastian Medina - 21 25.3 6.8 4.5 2.4 0.8 0.9 1.7 6.9 6.8 102 5.4 20.0 34.5 28.6 67.6 -3.7 44.3 40.7
Brady Karich - 1 30.0 6.0 2.0 4.0 2.0 1.0 2.0 3.0 10.0 26 2.2 107.6 100.0 0 0 -1.5 100.0 100.0
Sacha Greenberg - 21 14.0 5.8 4.0 0.5 0.1 0.3 0.4 5.2 5.1 19 1.0 7.3 40.4 28.8 77.8 -4.23 51.7 49.1
Will Gregory - 20 13.1 4.8 1.2 0.8 0.5 0.0 0.6 4.4 2.2 59 3.3 19.6 39.8 33.3 62.5 -0.94 52.4 51.7
Kreekor Karageuzian - 21 24.7 4.4 4.6 3.0 1.4 0.2 1.6 4.0 7.9 85 4.5 16.8 41.2 25.0 70.4 1.66 48.0 43.5
Kas Mirza - 14 5.1 3.1 1.1 0.3 0.1 0.0 0.2 2.6 1.8 -1 -0.1 -1.3 33.3 30.0 61.9 -2.28 47.5 41.7
Eric Zhang - 21 11.2 3.0 1.3 0.6 0.6 0.1 0.6 3.3 1.7 -9 -0.5 -3.9 35.7 21.1 42.1 -3.54 39.6 38.6
Gyasi Zinn - 21 16.7 2.5 4.4 0.6 0.3 1.1 0.7 2.5 5.9 15 0.8 5.1 48.1 0.0 27.3 0.26 46.6 48.1
James Frye - 1 10.0 2.0 6.0 0.0 0.0 0.0 1.0 3.0 4.0 14 1.4 156.3 33.3 0 0 -0.1 33.3 33.3
Kale Elmhorst - 10 5.3 1.8 0.8 0.2 0.0 0.0 0.0 2.0 0.8 1 0.1 2.0 30.0 35.7 50.0 -0.34 43.1 42.5
Noah Mann - 9 3.0 0.8 0.4 0.1 0.1 0.0 0.8 0.4 0.2 0 0.0 0.0 50.0 100.0 100.0 -0.98 71.7 62.5
Jack Moineau - 9 2.7 0.7 0.4 0.1 0.0 0.0 0.1 0.9 0.2 2 0.3 6.6 25.0 0.0 100.0 -1.01 33.8 25.0
Luke Jacobson - 1 9.0 0.0 2.0 0.0 1.0 2.0 1.0 1.0 3.0 -15 -1.4 -103.4 0.0 0 0 -0.98 0.0 0.0
Samuel Gibbs - 1 14.0 0.0 0.0 0.0 0.0 0.0 1.0 2.0 -3.0 -141 -9.4 -31.0 0.0 0 0 -2.71 0.0 0.0
JP Miranda - 1 2.9 0.0 0.0 1.0 0.0 0.0 0.0 2.0 -1.0 -6 -6.0 -83.7 0.0 0 0 -1.09 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