Michigan Tech
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 → | 1076 (#80) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1160 (#43) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +14.3 (#62) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.518 (#354) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.461 (#233) | NetEff -1.3 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.904 (#200) | AdjNet +19.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.914 (#200) | AdjNet +20.0 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.772 (#194) | AdjO 71.4 | AdjD 58.0 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Isabella Lenz | - | 29 | 33.8 | 14.2 | 4.0 | 2.6 | 1.1 | 0.7 | 2.2 | 12.4 | 8.1 | 37 | 1.3 | 1.3 | 41.5 | 36.6 | 87.0 | -0.05 | 52.6 | 48.2 |
| Kendall Standfest | - | 29 | 29.6 | 11.7 | 7.9 | 2.0 | 0.8 | 0.5 | 2.2 | 10.5 | 10.2 | 56 | 1.4 | 1.5 | 41.6 | 36.0 | 70.1 | 0.74 | 50.0 | 46.7 |
| Janie Tormanen | - | 22 | 23.5 | 10.2 | 5.7 | 1.1 | 0.7 | 0.4 | 2.1 | 7.9 | 8.1 | 101 | 3.3 | 4.0 | 56.6 | 30.8 | 60.0 | 1.44 | 58.8 | 57.8 |
| Alyssa Wypych | - | 29 | 27.2 | 9.0 | 4.4 | 1.0 | 0.7 | 0.3 | 1.8 | 8.4 | 5.3 | 60 | 1.5 | 1.8 | 39.1 | 32.0 | 82.0 | 0.54 | 49.4 | 45.5 |
| Maja Kozlowska | - | 25 | 17.3 | 7.5 | 3.4 | 0.5 | 0.2 | 0.5 | 2.0 | 5.8 | 4.4 | -5 | -0.1 | -0.3 | 53.5 | 0 | 77.3 | -0.04 | 57.5 | 53.5 |
| Emma Anderson | - | 27 | 19.3 | 4.9 | 4.3 | 1.2 | 0.6 | 0.4 | 0.8 | 4.6 | 6.1 | 32 | 1.2 | 2.2 | 40.7 | 26.9 | 93.3 | 0.16 | 50.9 | 48.0 |
| Ella Mason | - | 29 | 12.2 | 4.5 | 1.1 | 0.5 | 0.3 | 0.1 | 0.8 | 4.5 | 1.2 | -18 | -0.5 | -0.8 | 35.9 | 19.7 | 92.6 | -0.03 | 45.8 | 40.5 |
| Dani Nuest | - | 28 | 25.2 | 4.2 | 2.4 | 2.6 | 0.9 | 0.0 | 1.4 | 5.1 | 3.5 | 106 | 2.9 | 3.7 | 31.2 | 24.7 | 41.2 | 0.59 | 38.6 | 38.2 |
| Kloe Zentkowski | - | 25 | 11.7 | 2.2 | 2.0 | 0.5 | 0.2 | 0.1 | 0.9 | 2.4 | 1.8 | 26 | 0.8 | 1.8 | 35.6 | 31.2 | 80.0 | -0.21 | 43.4 | 39.8 |
| Brittney Mislivecek | - | 20 | 5.7 | 1.1 | 0.7 | 0.2 | 0.1 | 0.1 | 0.2 | 1.4 | 0.5 | 46 | 2.7 | 8.3 | 25.0 | 11.1 | 75.0 | 0.42 | 33.3 | 26.8 |
| Kaitlyn Maxwell | - | 27 | 3.5 | 1.0 | 0.4 | 0.1 | 0.1 | 0.0 | 0.3 | 1.1 | 0.4 | -9 | -0.4 | -1.6 | 31.0 | 18.2 | 75.0 | -0.24 | 40.0 | 34.5 |
| Maggie Napont | - | 23 | 0.8 | 0.2 | 0.2 | 0.0 | 0.0 | 0.0 | 0.2 | 0.1 | 0.1 | - | - | - | 66.7 | 0 | 0.0 | - | 51.5 | 66.7 |
| Kaisa Salani | - | 24 | 0.7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Soraya Timms | - | 6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 12 | 1.1 | 1.2 | 0 | 0 | 0 | 0.73 | 0 | 0 |
| Maryellen Trewhella | - | 7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 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