🐻⬇️🏀

Seattle Pacific

Also known as: Seattle Pacific
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 → 836 (#492) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 887 (#445) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +75 elo More → 910 (#605) HCA +75 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.8 More → -1.9 (#195) HCA +2.8
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.7 More → -8.2 (#487) HCA +3.7
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.214 (#483) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -16.3 More → 0.091 (#398) NetEff -16.3
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -2.1 More → 0.441 (#430) AdjNet -2.1
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -1.6 More → 0.452 (#430) AdjNet -1.6
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 64.5 | AdjD 65.9 More → 0.469 (#437) AdjO 64.5 | AdjD 65.9
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 59.8 | AdjD 67.8 More → 0.326 (#596) AdjO 59.8 | AdjD 67.8
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 → 0.320 (#511) 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 → 0.314 (#518) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 108 | GP 22 More → 871 (#414) RD 108 | GP 22

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-04 @ Montana L 44 - 81
2025-11-14 vs Cal State LA L 63 - 75
2025-11-15 vs Cal St. Dom. Hills W 64 - 61
2025-11-21 @ Azusa Pacific L 59 - 75
2025-11-22 @ CUI L 51 - 74
2025-11-28 @ Nova Southeastern L 69 - 88
2025-11-29 @ Palm Beach Atl. W 53 - 42
2025-12-03 vs Simon Fraser L 54 - 57
2025-12-05 vs Western Wash. L 43 - 67
2025-12-20 vs Westminster (UT) L 60 - 70
2025-12-20 @ Colorado Mesa L 55 - 86
2026-01-03 vs Mont. St. Billings L 45 - 58
2026-01-10 @ Western Ore. W 80 - 58
2026-01-15 vs Central Wash. L 56 - 88
2026-01-17 vs Northwest Nazarene L 62 - 72
2026-01-22 @ Alas. Anchorage W 101 - 98
2026-01-24 @ Alas. Fairbanks W 69 - 56
2026-01-31 @ Mont. St. Billings L 39 - 74
2026-02-05 vs Western Ore. L 64 - 75
2026-02-07 vs Saint Martin's L 47 - 67

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%
Layne Kearns - 17 31.4 14.1 5.5 2.6 1.1 0.6 3.4 12.4 8.2 -118 -6.6 -33.0 37.4 24.2 82.5 1.69 48.7 41.2
Grace Turley - 20 31.9 11.6 3.5 1.3 1.5 0.6 1.9 11.8 4.7 -151 -7.2 -26.9 30.6 24.3 83.8 1.56 43.2 36.0
Grace Leasure - 19 26.4 9.1 4.7 1.2 1.5 2.1 3.4 8.1 7.0 -36 -1.8 -11.1 44.2 21.4 84.6 0.56 50.2 45.1
Madison Rubino - 10 19.2 7.0 5.1 1.0 2.0 1.3 2.5 7.1 6.8 -45 -3.8 -24.3 39.4 33.3 65.0 0.39 43.9 40.1
Haylie-Anne Ohta - 20 33.5 6.7 4.0 3.2 2.2 0.1 3.3 6.8 6.2 -178 -8.5 -30.2 37.8 31.2 58.3 -2.51 47.4 46.7
Grace Mertes - 20 23.6 6.0 3.8 1.2 0.6 0.2 1.8 7.0 3.0 -106 -5.0 -24.2 30.2 28.3 50.0 -3.29 41.0 40.3
Cascadia Yates - 17 11.2 4.2 1.2 0.2 0.2 0.2 0.9 4.1 1.1 20 1.1 13.6 40.6 50.0 84.6 0.56 48.2 44.2
Naomi Hotchkiss - 20 10.3 2.5 3.2 0.1 0.1 0.2 0.7 3.0 2.5 -167 -8.0 -86.5 35.6 0 46.7 -3.24 37.3 35.6
Layla Senderson - 15 9.3 1.9 0.4 0.3 0.3 0.1 0.7 2.4 -0.1 -33 -2.1 -24.8 27.8 23.1 66.7 -0.55 37.5 36.1
Kara Wilson - 17 11.8 1.8 1.0 0.2 0.4 0.2 0.8 2.2 0.6 -14 -0.8 -7.7 21.1 16.7 85.7 -1.49 35.1 25.0
Jadlyn Senderson - 18 8.0 1.3 0.7 0.5 0.2 0.1 0.7 1.8 0.3 -51 -2.7 -38.6 31.2 20.0 0.0 -2.22 35.0 35.9
Julia Lavigne - 12 7.1 0.7 1.6 0.0 0.2 0.3 0.4 1.4 1.0 -53 -4.1 -49.2 17.6 0.0 33.3 -1.92 20.4 17.6
Ava Mai - 3 3.0 0.7 0.7 0.0 0.0 0.0 0.3 0.3 0.7 - - - 100.0 0 0.0 - 53.2 100.0
Pippa Krieger - 1 1.7 0.0 0.0 0.0 0.0 0.0 1.0 0.0 -1.0 - - - 0 0 0 - 0 0
Jasmine Pho - 3 4.5 0.0 0.3 0.7 0.0 0.0 0.0 0.7 0.3 -2 -0.7 -6.0 0.0 0.0 0 -0.29 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