🐻⬇️🏀

Point Loma

Also known as: Point Loma
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 → 1066 (#85) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1200 (#39) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +95 elo More → 1126 (#51) HCA +95 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.8 More → +16.5 (#38) HCA +2.8
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.3 More → +7.5 (#200) HCA +3.3
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.739 (#189) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +45.6 More → 0.994 (#75) NetEff +45.6
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +15.6 More → 0.858 (#192) AdjNet +15.6
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +15.8 More → 0.862 (#190) AdjNet +15.8
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 81.4 | AdjD 69.4 More → 0.748 (#183) AdjO 81.4 | AdjD 69.4
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 77.1 | AdjD 69.3 More → 0.671 (#86) AdjO 77.1 | AdjD 69.3
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 → 0.732 (#112) 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 → 0.730 (#106) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 107 | GP 21 More → 1210 (#44) RD 107 | GP 21

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-14 @ Cal St. Dom. Hills W 90 - 82
2025-11-15 vs CSUSB W 87 - 66
2025-11-19 vs Cal St. San Marcos W 75 - 61
2025-11-22 vs Stanton W 101 - 67
2025-11-28 vs Central Wash. W 94 - 78
2025-11-29 @ Seattle Pacific L 73 - 80
2025-12-04 @ Jessup W 89 - 87
2025-12-06 @ Fresno Pacific W 85 - 63
2025-12-10 @ Biola W 74 - 70
2025-12-13 vs Dominican (CA) L 73 - 92
2025-12-20 @ Azusa Pacific L 73 - 75
2026-01-01 @ Dominican (CA) W 87 - 62
2026-01-03 @ Menlo W 74 - 51
2026-01-08 vs Jessup W 92 - 83
2026-01-10 @ CUI W 74 - 64
2026-01-13 vs Biola W 81 - 61
2026-01-17 vs Azusa Pacific W 90 - 82
2026-01-24 @ Vanguard L 67 - 76
2026-01-29 vs Chaminade W 77 - 52
2026-01-31 vs Fresno Pacific W 69 - 54
2026-02-05 vs Menlo W 91 - 68

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%
Andrew Nagy - 21 24.3 15.5 6.1 1.5 0.6 0.7 1.7 10.4 12.3 149 7.8 49.9 62.4 31.6 70.7 4.34 66.7 65.1
James Nobles - 21 27.5 11.6 4.6 1.3 0.9 0.6 1.7 7.9 9.4 110 5.5 34.8 47.6 36.1 75.6 -0.42 60.7 55.4
Andrew Hommes - 21 28.3 11.4 5.8 2.0 0.7 1.8 1.5 7.7 12.5 139 7.0 37.2 47.8 37.2 80.6 1.47 63.5 58.7
Jaden Matingou - 20 28.1 11.2 4.2 4.0 1.0 0.1 2.4 7.4 10.8 181 9.1 52.1 49.3 34.0 72.4 2.28 60.4 54.7
Tyce Paulsen - 20 28.7 10.9 3.5 2.1 1.4 0.7 1.4 7.8 9.3 70 3.7 17.9 45.2 40.2 92.1 0.23 62.7 58.3
Caden Harris - 20 20.9 8.5 2.4 1.2 0.9 0.2 1.6 7.7 3.9 70 3.9 26.6 38.3 30.1 71.4 -0.66 49.3 45.5
Jake Lifgren - 17 19.1 6.2 2.2 1.9 0.5 0.1 0.8 5.3 4.9 64 4.0 42.9 45.6 32.6 58.8 2.99 54.4 53.3
Judson Loe - 21 12.2 3.1 1.8 1.0 0.4 0.0 0.6 2.1 3.6 106 5.3 73.6 48.9 39.1 72.2 1.33 62.4 58.9
Jack Wistrcill - 21 10.0 2.5 2.5 0.8 0.2 0.2 0.4 2.3 3.5 18 0.9 19.0 39.6 25.0 61.1 0.14 47.4 43.8
David Scariano - 10 4.5 2.2 1.2 0.1 0.0 0.0 0.2 1.6 1.7 16 1.6 118.2 56.2 30.0 50.0 0.26 65.2 65.6
Demari Davis - 16 5.0 1.8 1.0 0.6 0.1 0.1 0.5 1.8 1.3 8 0.5 14.3 46.4 28.6 0.0 0.27 49.2 50.0
Nash Dunham - 5 3.8 1.4 0.2 0.2 0.4 0.0 0.4 0.8 1.0 - - - 50.0 0.0 100.0 - 65.8 50.0
Jude Harris - 11 4.9 1.1 0.2 0.3 0.1 0.0 0.4 1.5 -0.3 4 0.4 19.3 29.4 15.4 0 -0.21 35.3 35.3
Bobby Moore - 2 1.9 1.0 1.5 0.0 0.0 0.5 0.0 0.5 2.5 58 3.1 18.6 100.0 0 0 -0.52 100.0 100.0

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