🐻⬇️🏀

DeSales

Also known as: DeSales
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 → 1020 (#196) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1123 (#109) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +62 elo More → 1183 (#34) HCA +62 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.3 More → +11.2 (#86) HCA +2.3
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More → +11.1 (#201) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.936 (#214) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +13.5 More → 0.885 (#176) NetEff +13.5
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +19.5 More → 0.905 (#210) AdjNet +19.5
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +18.9 More → 0.905 (#211) AdjNet +18.9
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 63.7 | AdjD 53.1 More → 0.724 (#220) AdjO 63.7 | AdjD 53.1
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 60.8 | AdjD 47.6 More → 0.768 (#78) AdjO 60.8 | AdjD 47.6
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 → 0.837 (#115) 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 → 0.838 (#109) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 96 | GP 21 More → 1258 (#41) RD 96 | GP 21

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-08 vs Gettysburg L 60 - 63
2025-11-09 @ Mary Washington W 81 - 59
2025-11-15 vs Saint Vincent W 65 - 55
2025-11-19 vs Rowan L 38 - 43
2025-11-22 @ Muhlenberg W 62 - 50
2025-11-24 @ Moravian W 66 - 46
2025-12-16 vs Scranton L 48 - 74
2025-12-29 @ CCNY W 92 - 22
2025-12-30 @ Lehman W 72 - 42
2026-01-10 @ Delaware Valley W 52 - 45
2026-01-14 @ Lebanon Valley W 46 - 33
2026-01-17 @ Stevens L 51 - 56
2026-01-21 vs Arcadia W 54 - 45
2026-01-24 vs Misericordia W 74 - 38
2026-01-28 @ King's (PA) W 62 - 59
2026-01-31 vs Delaware Valley W 73 - 48
2026-02-04 vs Lebanon Valley W 49 - 43
2026-02-07 @ FDU-Florham W 66 - 47

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%
Lindsay Bednarek - 18 24.9 14.0 3.3 2.3 1.8 0.3 1.9 12.6 7.2 95 5.0 30.6 44.7 33.3 69.0 2.79 49.0 44.9
Mikaili Donmoyer - 18 28.9 10.9 3.8 1.9 1.6 0.1 2.0 12.1 4.2 100 5.3 25.4 30.9 28.3 72.1 2.01 41.8 38.2
Aubrey Pollard - 18 25.5 9.6 7.7 0.5 1.1 0.1 1.0 8.3 9.7 41 2.2 15.1 52.3 0.0 42.1 -0.42 51.9 52.3
Kayla Ishigami - 18 17.0 6.9 1.7 1.1 1.1 0.0 1.5 6.8 2.5 53 2.8 27.8 35.0 37.3 76.2 1.55 46.9 43.9
Sammi White - 18 32.9 4.6 7.2 1.9 1.4 2.2 1.2 5.7 10.6 126 6.3 32.0 39.2 0.0 25.0 4.48 38.7 39.2
Keara McCaffrey - 16 8.3 3.2 1.3 0.1 0.3 0.1 0.4 2.9 1.8 51 3.0 53.5 43.5 0 61.1 -0.12 47.3 43.5
Marissa Laverghetta - 1 13.0 3.0 2.0 1.0 1.0 0.0 0.0 4.0 3.0 116 6.1 35.2 25.0 0.0 100.0 1.32 33.8 25.0
Lillirose Lang - 15 9.1 2.3 0.6 0.7 0.9 0.1 1.1 3.6 -0.2 21 1.2 49.8 25.9 22.7 100.0 0.13 31.9 30.6
Mia Soto - 4 4.6 2.2 1.2 0.5 0.2 0.0 0.2 2.0 2.0 4 0.8 157.4 50.0 50.0 0 0.13 56.2 56.2
Emma O'Hare - 6 4.5 2.2 0.8 0.2 0.2 0.0 0.2 0.8 2.3 28 4.7 1101.6 40.0 33.3 80.0 0.13 69.1 50.0
Emma Pyne - 10 9.4 1.8 1.7 0.5 0.5 0.0 0.5 2.2 1.8 44 4.4 85.8 27.3 23.1 75.0 1.1 37.9 34.1
Julia Kowalski - 15 10.4 1.6 1.4 0.6 0.6 0.0 0.4 2.1 1.7 7 0.5 9.2 28.1 13.3 66.7 0.23 34.6 31.2
Mia Stock - 14 7.5 0.9 1.5 0.5 0.2 0.3 0.5 1.6 1.3 39 2.8 28.3 21.7 0.0 75.0 1.41 26.3 21.7
Mackenzie Gordos - 9 3.8 0.7 0.1 0.3 0.2 0.0 0.3 0.6 0.4 10 1.0 120.0 40.0 50.0 0 -0.03 60.0 60.0

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