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Pacific (OR)

Also known as: Pacific (OR)
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 → 935 (#353) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1026 (#288) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +62 elo More → 900 (#611) HCA +62 elo
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +62 elo More → 818 (#671) HCA +62 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.3 More → +8.4 (#104) HCA +2.3
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More → -2.6 (#405) HCA +2.9
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More → -8.5 (#481) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.622 (#390) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +2.3 More → 0.578 (#335) NetEff +2.3
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +9.0 More → 0.739 (#301) AdjNet +9.0
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +8.8 More → 0.739 (#300) AdjNet +8.8
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 66.1 | AdjD 60.8 More → 0.618 (#289) AdjO 66.1 | AdjD 60.8
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 59.5 | AdjD 62.6 More → 0.430 (#504) AdjO 59.5 | AdjD 62.6
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 54.8 | AdjD 62.4 More → 0.334 (#587) AdjO 54.8 | AdjD 62.4
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 → 0.350 (#494) Blend of Elo, BT, Margin, PythLog, PtsOD
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 → 0.245 (#569) 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 → 0.356 (#498) 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 → 0.249 (#573) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 118 | GP 29 More → 840 (#465) RD 118 | GP 29
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 155 | GP 5 More → 687 (#544) RD 155 | GP 5

2026 Schedule & Results

Date Vs/At Opponent Result Score
2026-01-24 vs Willamette L 55 - 65
2026-01-27 @ Linfield L 51 - 61
2026-01-30 vs Whitworth L 44 - 69
2026-01-31 vs Whitman L 62 - 66
2026-02-06 @ Lewis & Clark L 51 - 65

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%
Shaade Williams - 5 26.7 11.8 4.8 0.4 0.6 0.4 2.2 13.6 2.2 -68 -3.1 -17.7 30.9 16.0 86.7 -1.55 39.5 33.8
Lindsay Barden - 5 30.8 8.8 4.4 3.6 1.4 0.0 3.4 9.0 5.8 -101 -4.6 -22.6 42.2 14.3 71.4 -0.56 45.8 43.3
Sydney Esperanza - 5 28.2 8.6 8.0 1.8 0.6 0.0 1.6 8.6 8.8 -18 -0.8 -4.2 37.2 12.5 66.7 -0.06 43.3 38.4
Jamysen Yates - 5 17.3 6.6 3.0 1.0 0.8 0.0 2.0 5.0 4.4 -7 -0.4 -3.0 44.0 44.4 63.6 3.16 55.3 52.0
Ava Cook - 5 25.8 4.6 3.2 0.8 1.2 0.6 1.4 4.6 4.4 -70 -3.2 -21.3 43.5 20.0 100.0 -1.37 48.2 45.7
Brookelynn Burke - 5 16.8 4.0 2.2 0.6 0.2 0.0 1.0 5.2 0.8 -47 -2.1 -20.3 26.9 28.6 0 -2.86 38.5 38.5
Karina Franco - 5 27.2 3.4 5.6 0.6 0.8 1.4 2.0 8.0 1.8 -67 -3.2 -17.4 20.0 0.0 100.0 -0.96 21.0 20.0
Camryn Ngo - 5 12.5 3.2 0.0 0.6 0.6 0.0 0.6 1.8 2.0 4 0.2 2.7 66.7 66.7 0 0.29 88.9 88.9
Kami Carmean - 5 3.4 1.0 0.6 0.2 0.0 0.0 0.2 2.0 -0.4 -16 -0.9 -28.8 20.0 16.7 0 0.13 25.0 25.0
Baylie Voile - 1 3.8 1.0 1.0 1.0 0.0 0.0 0.0 1.0 2.0 -13 -1.2 -34.1 0.0 0.0 50.0 2.43 26.6 0.0
Tiare Arquero - 3 5.6 0.7 0.7 0.3 0.0 0.0 0.7 1.0 0.0 9 0.9 14.5 33.3 0 0 0.78 33.3 33.3
Victoria Prochazka - 5 5.4 0.0 0.6 0.0 0.0 0.0 0.6 0.6 -0.6 1 0.0 0.7 0.0 0 0 0.2 0.0 0.0
Alynn Crooms - 1 3.8 0.0 1.0 0.0 0.0 0.0 0.0 0.0 1.0 1 0.2 5.1 0 0 0 -0.5 0 0
Iya- Lin Betteridge - 1 5.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 -1.0 -3 -0.3 -10.9 0.0 0.0 0 -0.88 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