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Ursinus Bears

Season: 2026 2025 2024 2023 2022 2020 2019 2017 2016 2015
Also known as: Ursinus Bears
Program History

Model Outputs

2025-2026 latest available
Catalog

No materialized model snapshot for 2024 yet, so this section is showing the latest available team-model rows.

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 → 1058 (#162) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1050 (#261) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +56 elo More → 1050 (#174) HCA +56 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.3 More → -0.5 (#126) HCA +2.3
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.0 More → -0.1 (#352) HCA +3.0
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.594 (#405) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +4.9 More → 0.653 (#35) NetEff +4.9
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -3.7 More → 0.395 (#403) AdjNet -3.7
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -4.0 More → 0.386 (#401) AdjNet -4.0
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 76.8 | AdjD 79.8 More → 0.433 (#406) AdjO 76.8 | AdjD 79.8
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 80.6 | AdjD 75.9 More → 0.607 (#206) AdjO 80.6 | AdjD 75.9
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 → 0.568 (#341) 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 → 0.583 (#333) 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 → 1104 (#169) RD 96 | GP 21

2024 Schedule & Results

Date Vs/At Opponent Result Score
2023-11-08 vs FDU-Florham L 0 - 0
2023-11-11 @ TCNJ L 68 - 86
2023-11-15 @ Widener L 73 - 86
2023-11-18 vs Rosemont W 92 - 54
2023-11-21 @ Franklin & Marshall L 59 - 71
2023-11-28 vs Haverford W 91 - 85
2023-12-02 @ McDaniel L 70 - 72
2023-12-06 @ Swarthmore L 66 - 82
2023-12-20 vs Ohio Northern L 51 - 83
2023-12-21 @ Carthage W 83 - 75
2023-12-30 @ Goucher W 90 - 64
2024-01-06 @ Johns Hopkins L 58 - 91
2024-01-09 vs Washington Col. W 97 - 60
2024-01-11 vs Dickinson W 74 - 68
2024-01-13 @ Gettysburg L 50 - 59
2024-01-17 vs Muhlenberg L 72 - 75
2024-01-20 vs McDaniel W 81 - 63
2024-01-25 @ Haverford W 77 - 66
2024-01-27 vs Johns Hopkins L 70 - 83
2024-01-31 vs Franklin & Marshall W 67 - 65
2024-02-03 @ Washington Col. W 59 - 57
2024-02-06 vs Swarthmore L 63 - 69
2024-02-10 vs Gettysburg W 78 - 59
2024-02-14 @ Muhlenberg W 80 - 67
2024-02-17 @ Dickinson L 55 - 66
2024-02-21 @ Swarthmore L 65 - 80

2024 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%
Trevor Wall - 24 31.1 19.9 3.3 2.5 1.0 0.1 2.8 15.7 8.4 -5 -1.2 -3.1 46.8 28.7 78.9 0.35 55.6 50.7
Nick Nocito - 23 23.5 10.7 3.0 2.1 0.5 0.1 2.7 8.5 5.1 76 5.1 58.9 40.3 33.0 76.5 0.49 54.2 49.2
Marlin Wise - 24 25.4 8.8 5.4 2.1 0.6 1.0 1.8 6.2 10.1 -26 -6.5 -18.0 49.7 40.8 71.0 0.61 60.1 56.4
Mohamed Toure - 25 20.4 8.3 4.2 0.4 0.7 0.6 0.8 6.5 6.9 98 6.5 75.0 42.0 32.6 86.0 0.77 56.2 50.6
Cole Grubbs - 24 22.8 6.7 6.2 1.3 0.3 1.8 1.3 4.5 10.5 -12 -3.0 -11.2 56.5 0 69.1 0.42 60.5 56.5
Luke Nieman - 24 18.9 6.7 2.2 0.3 0.9 0.2 1.0 5.4 4.0 13 0.9 11.8 42.3 37.6 69.6 0.15 57.5 55.8
Jaiden Jakubowski - 24 20.9 4.2 3.3 1.2 0.6 0.1 1.2 4.2 4.1 -5 -1.2 -5.9 42.0 17.9 44.0 0.17 45.0 44.5
Beau Everett - 24 17.7 3.4 1.8 1.6 1.0 0.0 0.8 2.6 4.4 -1 -0.2 -2.0 41.9 15.4 73.0 0.02 51.7 43.5
Matthew Field - 23 12.3 3.0 2.3 0.7 0.3 0.1 0.9 1.8 3.7 64 4.3 84.3 39.0 0.0 73.5 0.17 54.3 39.0
Patrick Downes - 23 4.3 1.3 0.4 0.2 0.0 0.1 0.4 1.0 0.6 - - - 52.2 35.3 20.0 - 61.5 65.2
Michael Farley - 24 3.7 0.6 0.3 0.3 0.0 0.2 0.1 0.9 0.4 - - - 33.3 0.0 33.3 - 33.6 33.3
Luke Trotta - 21 1.4 0.4 0.3 0.1 0.0 0.0 0.1 0.7 -0.0 - - - 20.0 0.0 75.0 - 26.8 20.0
Will Allain - 21 1.0 0.1 0.1 0.1 0.0 0.0 0.1 0.1 0.1 - - - 33.3 0.0 0 - 33.3 33.3
Graham Eilberg - 23 0.6 0.0 0.1 0.0 0.0 0.0 0.0 0.1 -0.1 - - - 0.0 0.0 0 - 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