🐻⬇️🏀

Dartmouth

Also known as: Dartmouth
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 → 1033 (#226) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1048 (#266) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +56 elo More → 990 (#526) HCA +56 elo
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.0 More → +32.3 (#47) HCA +3.0
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 1.000 (#29) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +33.5 More → 0.980 (#82) AdjNet +33.5
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +33.9 More → 0.985 (#67) AdjNet +33.9
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 89.1 | AdjD 61.2 More → 0.927 (#56) AdjO 89.1 | AdjD 61.2
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 90.0 | AdjD 70.0 More → 0.860 (#10) AdjO 90.0 | AdjD 70.0
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 → 0.899 (#28) 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 → 0.884 (#24) Blend of Elo, BT, Margin, PythLog, PtsOD

2026 Schedule & Results

Date Vs/At Opponent Result Score
2026-01-01 vs Elms W 107 - 43

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%
Anton Strelnikov - 1 9.5 16.0 6.0 0.0 0.0 1.0 0.0 10.0 13.0 - - - 70.0 0.0 100.0 - 73.5 70.0
Niko Abusara - 1 26.2 13.0 5.0 3.0 0.0 0.0 2.0 10.0 9.0 - - - 60.0 0.0 100.0 - 62.3 60.0
Brandon Mitchell-Day - 1 18.9 12.0 11.0 1.0 0.0 3.0 2.0 8.0 17.0 - - - 62.5 100.0 0 - 75.0 75.0
Shanon Simango - 1 11.4 12.0 3.0 0.0 0.0 0.0 0.0 5.0 10.0 - - - 80.0 0.0 57.1 - 74.3 80.0
Cameron McNamee - 1 24.1 10.0 7.0 5.0 3.0 0.0 0.0 8.0 17.0 - - - 37.5 28.6 100.0 - 56.3 50.0
Tyler Garrett - 1 17.1 9.0 11.0 3.0 0.0 1.0 2.0 7.0 15.0 - - - 57.1 25.0 0 - 64.3 64.3
Cameron Hiatt - 1 29.9 9.0 2.0 9.0 1.0 0.0 1.0 6.0 14.0 - - - 50.0 50.0 0 - 75.0 75.0
Connor Amundsen - 1 14.1 8.0 2.0 1.0 0.0 0.0 1.0 7.0 3.0 - - - 42.9 33.3 100.0 - 53.8 50.0
Jackson Munro - 1 17.4 8.0 4.0 4.0 0.0 0.0 0.0 4.0 12.0 - - - 100.0 0 0 - 100.0 100.0
Kareem Thomas - 1 22.1 8.0 3.0 1.0 0.0 1.0 1.0 5.0 7.0 72 4.2 16.3 40.0 33.3 75.0 3.8 59.2 50.0
Patrick Tivnan Jr. - 1 9.3 2.0 3.0 1.0 0.0 0.0 0.0 1.0 5.0 -26 -2.0 -67.5 100.0 0 0 -0.47 100.0 100.0

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