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Tufts

Season: 2026 2025 2024 2023 2022 2020 2019 2017 2016 2015
Also known as: Tufts
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 → 1299 (#6) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1316 (#10) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +56 elo More → 1205 (#12) HCA +56 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.3 More → +15.6 (#7) HCA +2.3
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.0 More → +14.5 (#169) HCA +3.0
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.857 (#266) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +16.8 More → 0.874 (#192) AdjNet +16.8
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +18.0 More → 0.891 (#189) AdjNet +18.0
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 77.8 | AdjD 65.6 More → 0.753 (#196) AdjO 77.8 | AdjD 65.6
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 80.2 | AdjD 63.1 More → 0.825 (#15) AdjO 80.2 | AdjD 63.1
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 → 0.847 (#60) 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 → 0.849 (#43) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 104 | GP 22 More → 1358 (#5) RD 104 | GP 22

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-14 @ Babson L 79 - 83
2025-11-16 @ Endicott L 73 - 76
2025-11-18 vs Suffolk W 54 - 47
2025-11-20 vs Emerson W 84 - 50
2025-11-23 vs Yeshiva W 100 - 94
2025-11-25 @ MIT W 74 - 67
2025-11-30 @ Keene St. W 82 - 79
2025-12-03 vs Bridgewater St. W 121 - 67
2025-12-06 vs Lasell W 87 - 59
2025-12-20 @ Saint Vincent W 66 - 63
2025-12-21 vs VTSU Lyndon W 117 - 51
2025-12-31 vs Clark (MA) W 79 - 77
2026-01-03 @ WPI W 70 - 52
2026-01-09 @ Bowdoin W 81 - 69
2026-01-10 @ Colby W 88 - 66
2026-01-16 vs Williams W 65 - 36
2026-01-17 vs Middlebury W 75 - 62
2026-01-24 @ Connecticut Col. W 76 - 73
2026-01-26 vs Wentworth L 0 - 0
2026-01-30 vs Wesleyan (CT) L 61 - 68
2026-01-31 vs Trinity (CT) W 68 - 62
2026-02-06 @ Amherst L 62 - 65
2026-02-07 @ Hamilton W 102 - 71

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%
Ray Cuevas - 1 36.0 28.0 1.0 2.0 1.0 0.0 1.0 17.0 14.0 20 1.2 4.8 47.1 50.0 90.9 3.49 64.1 52.9
Scott Gyimesi - 21 30.9 15.9 9.4 2.7 1.0 0.9 1.7 11.7 16.4 188 9.9 80.4 55.5 41.9 72.9 1.58 61.4 59.2
Dylan Reilly - 12 28.1 11.5 2.9 0.6 1.0 0.4 0.6 8.6 7.2 61 5.1 47.6 42.7 41.9 70.0 0.33 61.7 60.2
Jon Medley - 16 27.5 11.1 3.7 4.2 1.2 0.7 1.9 7.6 11.3 86 5.7 39.6 43.4 28.6 68.7 3.41 55.8 49.2
Joshua Bernstein - 21 23.6 10.0 8.9 1.7 0.4 1.7 1.4 6.7 14.5 115 6.1 54.4 65.7 0 75.0 0.46 67.7 65.7
Kevin Reeves - 1 21.0 10.0 5.0 2.0 1.0 0.0 3.0 9.0 6.0 30 1.9 11.3 55.6 0 0.0 0.23 53.0 55.6
Justas Bardauskas - 1 19.0 9.0 7.0 1.0 0.0 0.0 1.0 5.0 11.0 - - - 60.0 0.0 33.3 - 50.2 60.0
Zion Watt - 21 24.5 8.7 4.4 0.8 1.7 0.8 0.7 6.9 8.9 115 6.1 58.7 39.3 38.3 71.8 -1.15 56.4 53.4
James Morakis - 17 16.5 7.4 1.4 1.7 0.2 0.0 1.7 6.7 2.2 47 2.8 74.1 38.6 17.1 70.5 0.67 46.9 41.2
Deacon Baratta - 1 3.0 6.0 1.0 0.0 0.0 0.0 0.0 2.0 5.0 - - - 100.0 100.0 0 0.45 150.0 150.0
Ricardo Nieves - 21 15.9 5.9 2.1 1.8 1.0 0.7 1.1 4.0 6.3 132 6.6 103.3 45.9 34.3 76.7 2.54 59.2 52.9
Sidney Wooten - 17 19.3 5.4 1.5 1.5 0.5 0.2 0.9 5.4 2.8 125 7.4 251.9 27.5 27.9 88.9 -1.4 44.2 36.8
Lukas Schmid - 11 7.1 4.3 1.4 0.6 0.5 0.1 0.5 3.5 2.9 87 9.7 725.0 42.1 36.8 100.0 0.41 56.6 51.3
Isaac Friedman - 9 6.7 4.2 0.3 0.2 0.1 0.0 0.6 2.7 1.7 57 7.1 475.0 58.3 64.3 33.3 0.41 75.0 77.1
Theo Liu - 4 7.1 4.0 2.0 0.5 0.5 0.2 0.8 2.5 4.0 47 15.7 616.4 60.0 50.0 50.0 0.45 68.0 70.0
Nolan Bessire - 1 19.0 4.0 5.0 1.0 0.0 0.0 0.0 3.0 7.0 -19 -1.4 -6.8 66.7 0 0 -1.0 66.7 66.7
Robbie Nyamwaya - 16 10.5 3.7 2.6 0.7 0.1 0.1 0.4 3.1 3.6 72 4.8 112.8 44.0 33.3 73.3 0.39 52.1 48.0
Ian Randall - 3 5.0 2.7 2.0 0.7 0.0 0.3 0.3 1.3 4.0 26 8.7 990.5 75.0 0 66.7 0.02 75.2 75.0
Evan Reeves - 18 7.9 2.1 1.4 0.4 0.1 0.4 0.2 1.7 2.6 18 1.1 46.7 56.7 0.0 20.0 -0.17 49.0 56.7
Griffin Linstra - 16 7.3 1.8 1.3 0.9 0.3 0.0 0.4 1.7 2.2 49 3.3 92.6 44.4 0.0 71.4 0.87 48.2 44.4
Daniel Simmons - 1 4.0 0.0 0.0 0.0 0.0 0.0 2.0 1.0 -3.0 - - - 0.0 0.0 0 - 0.0 0.0
Chris Simonds - 1 4.0 0.0 0.0 0.0 0.0 0.0 2.0 1.0 -3.0 -13 -1.6 -25.3 0.0 0.0 0 0.16 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