🐻⬇️🏀

Lewis & Clark

Also known as: Lewis & Clark
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 → 846 (#514) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 837 (#509) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +62 elo More → 873 (#634) HCA +62 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.4 More → -4.3 (#266) HCA +2.4
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More → -2.5 (#401) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.172 (#603) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -1.4 More → 0.454 (#372) NetEff -1.4
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -26.2 More → 0.022 (#542) NetEff -26.2
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -13.7 More → 0.172 (#503) AdjNet -13.7
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -13.6 More → 0.166 (#501) AdjNet -13.6
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 59.6 | AdjD 67.8 More → 0.321 (#493) AdjO 59.6 | AdjD 67.8
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 63.6 | AdjD 66.0 More → 0.444 (#491) AdjO 63.6 | AdjD 66.0
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 → 0.401 (#454) 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 → 0.396 (#459) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 100 | GP 22 More → 805 (#491) RD 100 | GP 22

2026 Schedule & Results

Date Vs/At Opponent Result Score
2025-11-09 vs Pacific (OR) - Incomplete score
2025-11-15 vs Schreiner - Incomplete score
2025-11-16 vs Northwest (WA) - Incomplete score
2025-11-22 vs Walla Walla - Incomplete score
2025-11-25 vs Corban - Incomplete score
2025-11-30 @ Warner Pacific - Incomplete score
2025-12-15 vs Concordia Chicago - Incomplete score
2025-12-20 @ Occidental - Incomplete score
2026-01-10 @ Pacific (OR) - Incomplete score
2026-01-13 vs Northwest Indian - Incomplete score
2026-01-16 vs Whitman - Incomplete score
2026-01-17 vs Whitworth - Incomplete score
2026-01-23 @ Willamette - Incomplete score
2026-01-24 vs Linfield - Incomplete score
2026-01-30 vs Pacific Lutheran - Incomplete score
2026-01-31 vs Puget Sound - Incomplete score
2026-02-06 vs Pacific (OR) - Incomplete score
2026-02-07 @ George Fox - Incomplete score

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%
Kaitlen Carns - 17 29.3 13.1 3.9 2.5 1.4 0.1 2.5 8.2 10.2 -56 -2.8 -9.8 42.4 34.7 90.6 1.66 61.2 48.6
Lauryn Frederickson - 13 27.8 12.1 8.5 1.3 1.5 0.5 1.4 12.3 10.2 -68 -4.2 -31.9 33.1 24.0 92.9 -0.28 44.0 36.9
Hailey Perez - 16 21.0 8.6 1.9 0.6 0.7 0.0 1.3 8.1 2.4 -44 -2.3 -12.0 31.8 28.7 57.1 -1.57 44.6 40.7
Lilly Jordan - 15 26.3 6.9 2.6 1.1 0.7 0.0 1.2 7.1 3.0 -100 -5.6 -31.8 34.9 31.2 69.2 -1.97 46.1 44.3
Ali McCauley - 13 22.2 6.4 3.2 1.5 0.6 0.1 1.8 7.4 2.7 -60 -3.8 -17.3 32.3 28.6 72.2 -0.35 39.9 36.5
Madilyn Palosi - 4 17.2 5.2 3.5 1.0 1.0 0.2 1.0 7.2 2.8 -30 -7.5 -52.2 27.6 20.0 100.0 -3.94 35.7 34.5
Divinity Singleton - 17 20.3 5.0 4.4 0.6 0.6 0.3 0.6 5.4 4.8 -46 -2.3 -12.5 32.6 30.8 84.0 0.17 41.3 34.8
Lillian Morlan - 2 9.2 5.0 2.0 0.0 0.0 0.0 1.0 5.0 1.0 - - - 50.0 0 0 - 50.0 50.0
Kaela Guidry - 14 14.0 4.9 4.7 0.2 0.3 0.6 2.1 5.4 3.2 -50 -3.6 -23.1 41.3 0.0 41.2 -3.6 41.8 41.3
Ky Roussin - 17 11.8 3.6 2.4 0.7 1.1 0.1 1.1 3.1 3.8 -8 -0.4 -3.3 44.2 0.0 64.0 0.72 49.2 44.2
DJ Kendrick - 17 15.4 3.5 3.3 0.6 0.7 0.0 1.1 3.8 3.3 -52 -2.6 -15.9 29.7 9.1 64.5 -0.33 38.0 30.5
Tatiana Rebanal - 14 15.2 2.9 1.4 0.9 0.8 0.0 1.3 3.9 0.6 -71 -3.9 -24.7 27.3 28.6 25.0 -3.9 34.2 34.5
Isabella Bernard - 5 6.6 2.0 1.2 0.0 0.2 0.2 0.2 2.4 1.0 -9 -1.3 -70.4 33.3 33.3 0 -2.15 41.7 41.7
Madelyn Sanchez - 13 8.8 1.8 0.9 0.6 0.2 0.0 0.8 2.4 0.3 40 2.9 29.0 29.0 26.1 0 2.97 38.7 38.7
Anna Chang - 3 5.3 1.3 0.3 0.0 0.3 0.0 0.3 2.7 -1.0 - - - 25.0 0.0 0 - 25.0 25.0
Kinnedy Scott - 6 9.2 1.2 3.0 0.5 0.5 0.0 1.0 1.5 2.7 21 2.6 37.3 33.3 0.0 11.1 0.02 27.0 33.3

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