🐻⬇️🏀

Marywood

Also known as: Marywood
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 → 975 (#416) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 937 (#445) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +56 elo More → 933 (#628) HCA +56 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.3 More → -17.5 (#346) HCA +2.3
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.0 More → -19.8 (#681) HCA +3.0
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.314 (#584) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -20.1 More → 0.090 (#652) AdjNet -20.1
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -20.5 More → 0.084 (#655) AdjNet -20.5
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 70.3 | AdjD 85.6 More → 0.199 (#658) AdjO 70.3 | AdjD 85.6
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 69.7 | AdjD 82.6 More → 0.236 (#721) AdjO 69.7 | AdjD 82.6
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 → 0.190 (#669) 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 → 0.198 (#679) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 95 | GP 22 More → 928 (#446) RD 95 | GP 22

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-07 vs Clarkson W 72 - 68
2025-11-08 @ Nazareth L 86 - 98
2025-11-12 vs Keystone W 79 - 64
2025-11-19 vs Hartwick W 91 - 72
2025-11-22 vs Rosemont W 83 - 53
2025-11-24 @ American L 53 - 113
2025-12-06 @ King's (PA) W 101 - 98
2025-12-10 vs Messiah W 93 - 85
2025-12-13 @ Wilson L 70 - 76
2025-12-29 vs Kenyon L 67 - 93
2025-12-30 vs Mt. St. Mary (NY) W 85 - 71
2026-01-03 @ Haverford L 60 - 110
2026-01-07 @ Centenary (NJ) L 71 - 81
2026-01-10 vs Pratt W 84 - 80
2026-01-14 vs Gwynedd Mercy L 76 - 81
2026-01-17 vs Saint Elizabeth W 88 - 72
2026-01-21 vs Neumann W 78 - 68
2026-01-24 @ Marymount (VA) L 47 - 71
2026-01-29 @ Immaculata W 73 - 70
2026-01-31 vs Centenary (NJ) L 68 - 87
2026-02-04 @ Gwynedd Mercy L 69 - 94
2026-02-07 @ Pratt L 65 - 74

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%
Joe Macciocco - 22 25.5 13.4 2.7 3.1 1.4 0.0 2.3 10.8 7.5 -45 -2.2 -11.6 40.8 30.0 76.6 -1.82 54.3 49.6
Collin Himmelberg - 22 25.5 13.3 4.2 1.5 1.1 0.1 1.7 10.6 7.9 6 0.3 1.6 40.2 36.0 82.1 -0.8 55.4 50.6
Michel Loftin - 22 31.1 13.3 5.9 2.9 2.0 0.2 2.9 11.7 9.6 -41 -2.0 -8.7 38.4 28.1 73.4 -0.15 49.9 45.3
Andrew Quinn - 21 21.8 9.5 2.6 1.6 0.7 0.1 1.3 7.4 5.8 -27 -1.4 -8.1 46.5 36.5 84.8 -1.54 58.7 55.2
Shilo Bivins - 22 27.5 8.5 6.9 1.7 1.1 0.3 1.4 6.9 10.1 -60 -2.9 -13.7 54.3 23.3 55.2 0.26 57.1 56.6
Noah Perry - 21 20.3 5.8 1.7 1.6 0.4 0.0 2.0 6.1 1.5 58 3.1 24.8 34.4 28.0 65.0 1.6 44.6 42.6
Ty Cheney - 22 20.6 4.0 3.8 2.5 0.9 0.2 1.4 3.7 6.4 -7 -0.4 -3.4 40.7 28.6 88.2 -0.98 50.3 45.7
Austin Bausman - 3 17.5 4.0 3.7 1.7 0.0 0.0 0.3 3.7 5.3 -28 -9.3 -38.2 36.4 37.5 50.0 1.95 50.5 50.0
Pedro Lugo - 21 13.6 3.5 2.9 0.1 0.1 1.5 1.0 2.2 4.9 -8 -0.4 -3.7 50.0 14.3 63.4 -0.59 57.0 51.1
Zack Patetta - 13 7.9 2.8 1.8 0.2 0.1 0.1 0.6 2.7 1.7 -19 -1.7 -14.1 42.9 100.0 41.7 -0.31 44.7 44.3
Reece Garvin - 21 8.8 1.9 1.7 1.0 0.3 0.1 0.4 2.4 2.1 -55 -2.9 -71.9 26.0 19.5 66.7 -2.29 37.1 34.0
Robbie Logan - 4 4.5 1.8 0.5 0.2 0.0 0.0 0.2 1.2 1.0 -2 -0.7 -6.8 40.0 50.0 50.0 -0.22 59.5 60.0
Max Maslowski - 9 2.2 1.1 0.4 0.0 0.3 0.0 0.2 0.7 1.0 -16 -2.0 -685.7 50.0 0.0 100.0 -0.54 64.4 50.0
Zach Carpenter - 9 2.6 0.3 0.0 0.2 0.0 0.1 0.0 0.7 0.0 -11 -1.4 -119.5 16.7 16.7 0 -0.51 25.0 25.0
Noah Reiser - 7 2.2 0.3 0.4 0.3 0.1 0.0 0.0 0.3 0.9 -17 -2.8 -728.6 0.0 0.0 50.0 -0.54 26.6 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