Edgewood
Also known as: Edgewood
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 → | 957 (#325) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 945 (#488) | HCA +95 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -12.3 (#480) | HCA +3.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.062 (#550) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.381 (#473) | AdjNet -4.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.385 (#471) | AdjNet -4.0 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.399 (#490) | AdjO 83.9 | AdjD 88.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.314 (#531) | AdjO 76.0 | AdjD 84.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.318 (#447) | 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 → | 0.312 (#464) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 902 (#353) | RD 220 | GP 1 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2026-01-19 | @ | Wis.-Parkside | L | 75 - 95 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Jack Rose | - | 1 | 29.7 | 24.0 | 2.0 | 3.0 | 0.0 | 1.0 | 1.0 | 13.0 | 16.0 | -9 | -0.6 | -8.4 | 69.2 | 40.0 | 100.0 | -0.49 | 81.3 | 76.9 |
| Andrew Soenksen | - | 1 | 29.0 | 22.0 | 18.0 | 3.0 | 1.0 | 1.0 | 0.0 | 15.0 | 30.0 | 24 | 3.4 | 106.3 | 53.3 | 33.3 | 66.7 | 1.41 | 62.4 | 60.0 |
| Logan Zahour | - | 1 | 30.0 | 21.0 | 2.0 | 2.0 | 4.0 | 0.0 | 2.0 | 13.0 | 14.0 | -18 | -1.2 | -18.3 | 61.5 | 50.0 | 100.0 | -1.62 | 75.6 | 73.1 |
| Zach Behn | - | 1 | 30.8 | 16.0 | 7.0 | 3.0 | 0.0 | 0.0 | 2.0 | 11.0 | 13.0 | 5 | 0.3 | 3.0 | 45.5 | 42.9 | 100.0 | 0.84 | 64.9 | 59.1 |
| Matas Castillo | - | 1 | 24.8 | 9.0 | 2.0 | 5.0 | 1.0 | 0.0 | 1.0 | 3.0 | 13.0 | 9 | 0.8 | 21.5 | 33.3 | 0 | 87.5 | -4.39 | 69.0 | 33.3 |
| Hudson Kirby | - | 1 | 18.7 | 3.0 | 3.0 | 0.0 | 1.0 | 1.0 | 1.0 | 5.0 | 2.0 | - | - | - | 20.0 | 0.0 | 50.0 | - | 25.5 | 20.0 |
| Sam Lootens | - | 1 | 21.6 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 3.0 | -2.0 | -6 | -1.5 | -225.0 | 0.0 | 0.0 | 0 | -0.0 | 0.0 | 0.0 |
| Liam Lubkeman | - | 1 | 15.5 | 0.0 | 3.0 | 2.0 | 0.0 | 2.0 | 0.0 | 1.0 | 6.0 | - | - | - | 0.0 | 0 | 0 | - | 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