Presbyterian
Also known as: Presbyterian
Program History
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 → | 1018 (#235) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1015 (#273) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1014 (#286) | HCA +75 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +9.4 (#224) | HCA +3.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.998 (#80) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.956 (#147) | AdjNet +26.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.958 (#150) | AdjNet +26.0 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.803 (#167) | AdjO 70.4 | AdjD 54.9 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.578 (#202) | AdjO 64.7 | AdjD 61.3 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.679 (#198) | 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 → | 0.665 (#216) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1093 (#117) | RD 350 | GP 1 |
2026 Schedule & Results
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aminata Tal | - | 1 | 22.8 | 20.0 | 4.0 | 4.0 | 1.0 | 0.0 | 5.0 | 16.0 | 8.0 | - | - | - | 50.0 | 50.0 | 100.0 | - | 57.7 | 53.1 |
| Ja'Cia Cunningham | - | 1 | 16.6 | 19.0 | 4.0 | 3.0 | 4.0 | 0.0 | 3.0 | 10.0 | 17.0 | - | - | - | 70.0 | 50.0 | 66.7 | - | 75.2 | 75.0 |
| Allie Sykes | - | 1 | 32.8 | 15.0 | 2.0 | 0.0 | 1.0 | 1.0 | 1.0 | 11.0 | 7.0 | - | - | - | 36.4 | 44.4 | 75.0 | - | 58.8 | 54.5 |
| Ore Ogunwolere | - | 1 | 20.6 | 10.0 | 2.0 | 6.0 | 6.0 | 0.0 | 2.0 | 9.0 | 13.0 | - | - | - | 55.6 | 0 | 0 | - | 55.6 | 55.6 |
| Daniella Velez | - | 1 | 20.6 | 9.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 8.0 | 1.0 | - | - | - | 50.0 | 25.0 | 0 | - | 56.2 | 56.2 |
| Yolanda Floyd | - | 1 | 9.9 | 6.0 | 4.0 | 1.0 | 1.0 | 0.0 | 2.0 | 4.0 | 6.0 | - | - | - | 75.0 | 0 | 0 | - | 75.0 | 75.0 |
| Morgan Boyd | - | 1 | 24.1 | 5.0 | 4.0 | 3.0 | 1.0 | 1.0 | 6.0 | 6.0 | 2.0 | - | - | - | 16.7 | 0 | 75.0 | - | 32.2 | 16.7 |
| Samantha Mullock | - | 1 | 21.8 | 2.0 | 5.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 9.0 | - | - | - | 100.0 | 0 | 0 | - | 100.0 | 100.0 |
| Laetitia Kamdoum | - | 1 | 14.0 | 0.0 | 4.0 | 1.0 | 0.0 | 0.0 | 2.0 | 3.0 | 0.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Amani Williams | - | 1 | 16.7 | 0.0 | 3.0 | 2.0 | 2.0 | 0.0 | 3.0 | 2.0 | 2.0 | -6 | -2.0 | -151.6 | 0.0 | 0 | 0.0 | 0.3 | 0.0 | 0.0 |
Numbers/Game vs RAPM
Not enough players with both Numbers/Game and RAPM to plot.
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