Occidental
Model Outputs
2025-2026
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 → | 912 (#389) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 959 (#382) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 983 (#507) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +2.8 (#165) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +3.4 (#314) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.630 (#386) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 1.000 (#48) | NetEff +68.2 |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.551 (#344) | NetEff +1.5 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.772 (#283) | AdjNet +10.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.772 (#282) | AdjNet +10.3 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.634 (#284) | AdjO 67.7 | AdjD 61.7 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.566 (#274) | AdjO 64.3 | AdjD 61.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.556 (#334) | 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. More → | 0.569 (#322) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 989 (#327) | RD 92 | GP 22 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-17 | vs | Texas Lutheran | L | 54 - 75 |
| 2025-11-24 | @ | UC San Diego | L | 39 - 87 |
| 2025-11-30 | vs | Puget Sound | W | 60 - 58 |
| 2025-12-12 | vs | Bethesda (CA) | W | 89 - 29 |
| 2025-12-16 | vs | Westminster (MO) | W | 74 - 53 |
| 2025-12-20 | vs | Lewis & Clark | W | 64 - 45 |
| 2025-12-29 | @ | Gettysburg | L | 53 - 68 |
| 2025-12-30 | @ | Salve Regina | L | 77 - 78 |
| 2025-12-31 | vs | St. Joseph's (ME) | W | 70 - 58 |
| 2026-01-10 | @ | Caltech | W | 77 - 59 |
| 2026-01-14 | @ | Pomona-Pitzer | L | 59 - 63 |
| 2026-01-17 | vs | Cal Lutheran | L | 63 - 68 |
| 2026-01-19 | vs | Whittier | W | 73 - 67 |
| 2026-01-21 | @ | Chapman | W | 79 - 59 |
| 2026-01-24 | @ | Redlands | L | 61 - 73 |
| 2026-01-26 | vs | La Verne | W | 67 - 46 |
| 2026-01-31 | vs | Caltech | W | 69 - 44 |
| 2026-02-04 | vs | Pomona-Pitzer | L | 67 - 87 |
| 2026-02-07 | @ | La Verne | W | 65 - 57 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Paige Yasukochi | - | 19 | 30.1 | 13.6 | 4.5 | 2.1 | 1.3 | 0.8 | 1.9 | 12.6 | 7.8 | 34 | 1.7 | 21.6 | 45.8 | 31.4 | 79.3 | 1.65 | 51.2 | 49.2 |
| Ainsley Shelsta | - | 5 | 15.5 | 10.2 | 7.2 | 1.0 | 0.8 | 0.6 | 1.6 | 8.0 | 10.2 | - | - | - | 52.5 | 0 | 52.9 | - | 53.7 | 52.5 |
| Dominique Cabading | - | 19 | 27.1 | 9.5 | 5.3 | 3.7 | 1.9 | 0.2 | 2.1 | 10.2 | 8.4 | 26 | 1.3 | 15.0 | 33.0 | 22.4 | 64.3 | 0.89 | 41.4 | 37.4 |
| Dara Tokeshi | - | 19 | 33.7 | 7.5 | 1.9 | 2.4 | 1.3 | 0.2 | 0.8 | 7.7 | 4.7 | 44 | 2.2 | 23.7 | 34.9 | 27.4 | 79.3 | 1.32 | 44.7 | 40.8 |
| Emily Ko | - | 19 | 20.9 | 7.1 | 2.3 | 2.5 | 1.9 | 0.2 | 2.1 | 6.6 | 5.3 | 22 | 1.1 | 16.8 | 40.5 | 35.2 | 81.2 | -0.33 | 50.4 | 48.0 |
| Ila Giblin | - | 19 | 20.7 | 5.5 | 5.0 | 0.6 | 0.5 | 0.5 | 1.5 | 5.2 | 5.4 | 85 | 4.5 | 72.9 | 45.5 | 16.7 | 52.0 | 2.23 | 47.3 | 46.0 |
| Kayla Ikuma | - | 19 | 18.0 | 5.2 | 2.7 | 1.3 | 1.1 | 0.1 | 1.0 | 4.4 | 4.9 | 56 | 2.8 | 64.1 | 39.8 | 43.9 | 60.9 | 1.54 | 52.6 | 50.6 |
| Megan Delgado | - | 16 | 7.1 | 3.7 | 0.6 | 0.2 | 0.3 | 0.1 | 0.4 | 3.1 | 1.4 | 15 | 1.0 | 19.5 | 44.9 | 35.3 | 75.0 | -0.1 | 58.1 | 57.1 |
| Micah Elegores | - | 13 | 11.1 | 2.9 | 1.6 | 1.1 | 0.5 | 0.0 | 1.2 | 3.0 | 1.8 | 12 | 0.9 | 10.8 | 30.8 | 20.0 | 61.9 | 2.1 | 39.4 | 32.1 |
| Makena Daggett | - | 19 | 9.7 | 2.6 | 2.5 | 0.3 | 0.4 | 0.1 | 0.7 | 2.4 | 2.7 | -14 | -0.7 | -14.8 | 40.0 | 0 | 87.5 | -0.6 | 48.0 | 40.0 |
| Nicole Vanegas | - | 18 | 8.3 | 2.6 | 1.6 | 0.4 | 0.5 | 0.0 | 0.6 | 1.9 | 2.6 | 63 | 3.9 | 224.0 | 37.1 | 50.0 | 76.0 | -0.04 | 51.1 | 40.0 |
| Cristina Sepulveda | - | 9 | 7.3 | 2.1 | 0.3 | 0.8 | 0.6 | 0.0 | 0.1 | 3.0 | 0.7 | 13 | 1.9 | 45.7 | 25.9 | 27.3 | 100.0 | -0.93 | 34.1 | 31.5 |
| Lillian Spector | - | 12 | 4.7 | 0.9 | 1.7 | 0.1 | 0.2 | 0.0 | 0.3 | 1.6 | 0.9 | 29 | 2.6 | 316.4 | 26.3 | 0 | 50.0 | 0.27 | 27.7 | 26.3 |
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