Lipscomb
Also known as: Lipscomb
Program History
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1055 (#231) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1013 (#343) | HCA +62 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +28.4 (#78) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 1.000 (#43) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 1.000 (#43) | NetEff +70.5 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.999 (#36) | AdjNet +62.0 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 1.000 (#40) | AdjNet +60.8 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.986 (#16) | AdjO 92.4 | AdjD 45.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.682 (#141) | AdjO 66.9 | AdjD 58.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.903 (#64) | 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 → | 0.865 (#86) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1089 (#177) | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Taylor Bowen | - | 1 | 15.6 | 18.0 | 10.0 | 3.0 | 0.0 | 0.0 | 0.0 | 9.0 | 22.0 | - | - | - | 77.8 | 0.0 | 66.7 | - | 77.3 | 77.8 |
| Molly Heard | - | 1 | 16.4 | 17.0 | 2.0 | 5.0 | 0.0 | 0.0 | 0.0 | 7.0 | 17.0 | - | - | - | 71.4 | 33.3 | 85.7 | - | 84.3 | 78.6 |
| Hannah Richardson | - | 1 | 18.2 | 14.0 | 8.0 | 3.0 | 1.0 | 0.0 | 0.0 | 11.0 | 15.0 | - | - | - | 45.5 | 33.3 | 75.0 | - | 54.9 | 50.0 |
| Maris Zurliene | - | 1 | 23.6 | 13.0 | 9.0 | 1.0 | 3.0 | 1.0 | 4.0 | 11.0 | 12.0 | - | - | - | 54.5 | 50.0 | 0 | - | 59.1 | 59.1 |
| Olivia Vinson | - | 1 | 26.9 | 13.0 | 8.0 | 1.0 | 1.0 | 0.0 | 1.0 | 11.0 | 11.0 | - | - | - | 36.4 | 60.0 | 50.0 | - | 50.9 | 50.0 |
| McKayla Miller | - | 1 | 15.5 | 8.0 | 3.0 | 3.0 | 2.0 | 2.0 | 3.0 | 3.0 | 12.0 | 96 | 5.1 | 47.6 | 100.0 | 100.0 | 0 | 2.85 | 133.3 | 133.3 |
| Addison Melton | - | 1 | 19.6 | 8.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 6.0 | 4.0 | - | - | - | 50.0 | 50.0 | 0.0 | - | 58.1 | 66.7 |
| Hope Counts | - | 1 | 26.7 | 6.0 | 9.0 | 3.0 | 6.0 | 3.0 | 0.0 | 8.0 | 19.0 | - | - | - | 37.5 | 0.0 | 0 | - | 37.5 | 37.5 |
| Elena Bertrand | - | 1 | 14.9 | 6.0 | 0.0 | 3.0 | 1.0 | 0.0 | 1.0 | 4.0 | 5.0 | - | - | - | 25.0 | 50.0 | 100.0 | - | 56.4 | 37.5 |
| Taylor Holt | - | 1 | 22.8 | 2.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 5.0 | 0.0 | - | - | - | 20.0 | 0.0 | 0 | - | 20.0 | 20.0 |
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