Notre Dame (MD)
Model Outputs
2024-2025
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 → | 1100 (#74) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1094 (#109) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -17.0 (#335) | HCA +2.4 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.586 (#416) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.565 (#217) | NetEff +1.9 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.051 (#601) | AdjNet -25.4 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.041 (#607) | AdjNet -26.4 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.194 (#591) | AdjO 51.8 | AdjD 67.5 |
2025 Schedule & Results
2025 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Amya Durham | - | 28 | 32.8 | 12.5 | 4.3 | 2.7 | 1.6 | 0.2 | 2.6 | 14.1 | 4.6 | 20 | 0.9 | 0.8 | 32.7 | 20.9 | 67.4 | 0.1 | 40.2 | 36.3 |
| Amani Watts | - | 25 | 18.7 | 12.2 | 6.4 | 0.4 | 1.1 | 0.4 | 0.8 | 7.3 | 12.2 | 53 | 2.4 | 2.7 | 64.5 | 0 | 68.0 | 0.76 | 67.0 | 64.5 |
| Elena Rodriguez | - | 28 | 27.0 | 8.6 | 2.4 | 1.1 | 1.4 | 0.1 | 2.4 | 9.5 | 1.7 | 1 | 0.0 | 0.0 | 31.1 | 31.6 | 60.0 | -0.45 | 42.2 | 40.3 |
| Bethani Newbold | - | 28 | 29.9 | 7.5 | 5.2 | 2.6 | 1.2 | 0.0 | 3.2 | 7.3 | 6.0 | 28 | 1.3 | 1.2 | 32.4 | 21.7 | 70.5 | 0.25 | 42.5 | 34.8 |
| Allison Holman | - | 28 | 24.0 | 5.5 | 4.0 | 1.4 | 1.4 | 0.3 | 1.8 | 5.2 | 5.6 | 24 | 0.8 | 1.2 | 44.5 | 0.0 | 54.5 | -0.19 | 46.6 | 44.5 |
| Madison Simmons | - | 28 | 19.8 | 4.9 | 2.6 | 1.7 | 1.2 | 0.0 | 2.7 | 4.3 | 3.5 | -2 | -0.1 | -0.1 | 39.2 | 29.2 | 57.1 | -0.41 | 46.4 | 42.1 |
| Yasmeen Yussuf | - | 28 | 20.2 | 3.0 | 4.0 | 0.9 | 1.5 | 0.1 | 2.0 | 2.9 | 4.5 | 59 | 2.1 | 3.0 | 32.5 | 0 | 54.4 | 0.54 | 39.5 | 32.5 |
| Jadyn Forbes | - | 27 | 6.6 | 2.0 | 0.7 | 0.5 | 0.2 | 0.0 | 0.4 | 2.6 | 0.5 | 3 | 0.1 | 0.6 | 26.1 | 29.4 | 66.7 | -0.39 | 38.4 | 37.0 |
| Thalia Kayiranga | - | 26 | 7.2 | 1.7 | 1.7 | 0.2 | 0.2 | 0.2 | 0.8 | 2.0 | 1.1 | 0 | 0.0 | 0.0 | 31.4 | 0.0 | 55.0 | -0.11 | 36.0 | 31.4 |
| Hillary Howard | - | 16 | 5.1 | 1.6 | 0.9 | 0.1 | 0.2 | 0.0 | 0.4 | 2.2 | 0.1 | - | - | - | 30.6 | 0.0 | 75.0 | 0.29 | 33.1 | 30.6 |
| Kathryn Degrange | - | 4 | 17.5 | 1.2 | 3.5 | 1.2 | 0.5 | 0.2 | 1.5 | 3.2 | 2.0 | -2 | -0.2 | -0.6 | 7.7 | 0 | 75.0 | -0.04 | 16.9 | 7.7 |
| Regina Sabirova | - | 25 | 2.5 | 0.5 | 0.3 | 0.1 | 0.0 | 0.0 | 0.3 | 0.8 | -0.1 | 15 | 1.5 | 8.2 | 21.1 | 10.0 | 42.9 | -0.31 | 27.2 | 23.7 |
| Chloe Harris | - | 27 | 1.6 | 0.0 | 0.3 | 0.0 | 0.1 | 0.0 | 0.2 | 0.4 | -0.1 | 20 | 2.5 | 5.0 | 0.0 | 0.0 | 0.0 | 0.11 | 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