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Mercy

Also known as: Mercy
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 โ†’ 671 (#295) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ†’ 699 (#295) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +95 elo More โ†’ 772 (#599) HCA +95 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.7 More โ†’ -11.6 (#290) HCA +2.7
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.3 More โ†’ -14.2 (#495) HCA +3.3
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ†’ 0.129 (#290) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +30.1 More โ†’ 0.969 (#136) NetEff +30.1
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -18.7 More โ†’ 0.104 (#294) AdjNet -18.7
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -18.6 More โ†’ 0.102 (#294) AdjNet -18.6
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 73.4 | AdjD 88.7 More โ†’ 0.199 (#295) AdjO 73.4 | AdjD 88.7
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 67.8 | AdjD 80.0 More โ†’ 0.247 (#566) AdjO 67.8 | AdjD 80.0
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 โ†’ 0.169 (#547) 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 โ†’ 0.169 (#560) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 114 | GP 20 More โ†’ 617 (#515) RD 114 | GP 20

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-14 @ Holy Family L 85 - 96
2025-11-15 @ Jefferson L 58 - 89
2025-11-19 vs Felician L 55 - 82
2025-11-22 @ Chestnut Hill L 66 - 80
2025-11-26 @ Bryant - Incomplete score
2025-11-30 @ East Stroudsburg L 92 - 98
2025-12-03 @ Staten Island L 79 - 90
2025-12-06 vs Dist. Columbia W 91 - 86
2025-12-09 vs Adelphi L 55 - 77
2025-12-12 vs Daemen L 65 - 83
2025-12-14 vs D'Youville W 103 - 98
2025-12-18 @ Goldey-Beacom L 74 - 96
2025-12-21 @ Franklin Pierce L 75 - 92
2026-01-02 vs Southern Conn. St. L 76 - 79
2026-01-11 @ Roberts Wesleyan L 64 - 84
2026-01-14 @ Dist. Columbia L 61 - 63
2026-01-17 vs Staten Island L 98 - 103
2026-01-21 vs Queens (NY) L 61 - 69
2026-01-24 @ Molloy - Incomplete score
2026-01-31 @ St. Thomas Aquinas L 65 - 84
2026-02-08 vs Roberts Wesleyan - Incomplete score
2026-02-13 @ Daemen L 60 - 86
2026-02-15 @ D'Youville L 60 - 65
2026-02-18 @ Queens (NY) L 69 - 82
2026-02-22 vs Molloy L 73 - 84
2026-02-25 vs Caldwell W 82 - 71
2026-02-28 vs St. Thomas Aquinas L 80 - 95

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 GP PM/G PM/40 FG% 3P% FT% RAPM TS% eFG%
Kohen Rowbatham - 24 35.6 20.5 3.7 2.7 1.1 0.2 3.6 19.3 5.2 - - - - 40.8 30.4 67.3 - 48.0 44.9
TJ Holloway - 22 35.2 15.3 5.3 2.0 0.5 0.3 2.8 13.9 6.6 - - - - 36.3 31.9 83.2 - 47.9 41.2
Jordan Trahan - 22 34.0 15.0 6.3 2.0 2.5 0.4 3.0 12.6 10.6 - - - - 42.1 24.5 57.6 - 48.3 44.4
Ashton Pratt - 22 27.1 7.3 2.8 1.4 1.1 0.2 1.1 7.1 4.7 - - - - 38.5 34.5 78.6 - 47.8 44.6
Derek Long - 8 15.5 6.5 1.5 0.9 1.5 0.0 1.5 6.2 2.6 - - - - 40.0 36.4 80.0 - 49.8 48.0
Christopher Nana - 22 13.2 3.0 2.5 0.5 0.2 0.4 0.5 2.3 3.8 - - - - 54.9 33.3 90.0 - 60.5 56.9
Tyrell Miller - 24 18.9 2.8 5.0 0.2 0.9 2.0 1.0 2.8 7.2 - - - - 44.8 0 26.9 - 42.7 44.8
James Connolly - 25 12.2 2.6 2.2 0.4 0.3 0.2 0.4 2.0 3.3 - - - - 48.0 37.5 66.7 - 54.9 51.0
Joshua Naklen - 19 11.2 2.4 1.6 0.9 0.5 0.1 0.7 2.7 2.0 - - - - 33.3 28.6 90.0 - 40.6 35.3
Daniel Boateng - 20 10.0 2.0 2.2 0.2 0.1 0.0 0.7 1.6 2.2 - - - - 33.3 15.8 78.9 - 48.4 37.9
Jeffrey Mulhern - 21 10.1 1.9 2.1 0.1 0.1 0.0 0.4 2.3 1.5 - - - - 29.2 27.8 66.7 - 37.5 34.4
Thomas Mandell - 9 5.3 1.0 0.3 0.2 0.2 0.0 0.2 0.9 0.7 - - - - 37.5 60.0 0 - 56.2 56.2

Numbers/Game vs RAPM

Not enough players with both Numbers/Game and RAPM to plot.

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