Ohio Dominican
Season:
2026
Also known as: Ohio Dominican
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 (#233) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1015 (#334) | HCA +62 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +12.8 (#181) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.955 (#196) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.850 (#240) | AdjNet +15.0 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.848 (#244) | AdjNet +14.5 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.669 (#263) | AdjO 60.8 | AdjD 53.1 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.585 (#253) | AdjO 60.0 | AdjD 56.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.733 (#179) | 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 → | 0.715 (#196) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1117 (#134) | RD 263 | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Sarah Ochs | - | 1 | 35.6 | 17.0 | 5.0 | 2.0 | 3.0 | 0.0 | 4.0 | 15.0 | 8.0 | - | - | - | 46.7 | 37.5 | 0 | - | 56.7 | 56.7 |
| Jenna Shackleford | - | 1 | 20.5 | 11.0 | 3.0 | 3.0 | 1.0 | 0.0 | 1.0 | 10.0 | 7.0 | - | - | - | 20.0 | 0.0 | 100.0 | - | 42.0 | 20.0 |
| Mackenzie Hurd | - | 1 | 29.9 | 10.0 | 10.0 | 4.0 | 2.0 | 1.0 | 3.0 | 7.0 | 17.0 | - | - | - | 71.4 | 0 | 0 | - | 71.4 | 71.4 |
| Madelyn Fearon | - | 1 | 19.9 | 6.0 | 2.0 | 0.0 | 2.0 | 0.0 | 1.0 | 9.0 | 0.0 | - | - | - | 22.2 | 28.6 | 0 | - | 33.3 | 33.3 |
| Gracie Cosgrove | - | 1 | 30.3 | 6.0 | 1.0 | 1.0 | 3.0 | 0.0 | 0.0 | 5.0 | 6.0 | - | - | - | 40.0 | 50.0 | 0 | - | 60.0 | 60.0 |
| Eve Schwemley | - | 1 | 30.8 | 5.0 | 0.0 | 0.0 | 2.0 | 0.0 | 2.0 | 8.0 | -3.0 | - | - | - | 25.0 | 20.0 | 0 | - | 31.2 | 31.2 |
| Lucy Porter | - | 1 | 7.7 | 3.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 | 2.0 | - | - | - | 33.3 | 100.0 | 0 | - | 50.0 | 50.0 |
| Jazmyn Wheeler | - | 1 | 17.1 | 2.0 | 7.0 | 1.0 | 2.0 | 1.0 | 1.0 | 6.0 | 6.0 | - | - | - | 16.7 | 0.0 | 0 | - | 16.7 | 16.7 |
| Taylor Scohy | - | 1 | 3.5 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Halle Warner | - | 1 | 4.7 | 0.0 | 3.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 3.0 | - | - | - | 0.0 | 0 | 0 | - | 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