I am working on a player-based projection system, similar to how Bart Torvik does it.
For now, the main projections are team-based, with the main inputs being:
1. Reversion to conference mean.
2. Coaching change factor = a fired coach results in a positive benefit, a good coach hired away produces a negative one.
3. Generic increase in performance for remaining players on roster.
It's okay, and generally mirrors some of the early subjective predictions. But we can do better.
| Player | Class | Height | Avg Minutes | Avg Points | Avg Rebounds | Avg Assists | 2025 Team |
|---|---|---|---|---|---|---|---|
| Ajia James | Jr | 6-01 | 23.2 | 7.8 | 4.0 | 0.7 | Elon |
| Aly Wadkovsky | So | 6-02 | 3.3 | 0.6 | 0.9 | 0.1 | Elon |
| Ava Leroux | Fr | 6-04 | 14.2 | 5.1 | 3.6 | 0.6 | Elon |
| Diamond Monroe | Jr | 5-10 | 18.6 | 4.8 | 2.7 | 0.4 | Elon |
| Hannah Dereje | So | 6-03 | 6.4 | 2.0 | 1.8 | 0.1 | Elon |
| Iycez Adams | Jr | 6-00 | 27.5 | 10.3 | 7.0 | 0.7 | Elon |
| Maraja Pass | Fr | 5-04 | 25.7 | 8.6 | 4.2 | 3.7 | Elon |
| Regina Walton | So | 5-03 | 22.5 | 4.4 | 1.9 | 2.3 | Elon |
| Ruby Willard | So | 5-10 | 15.3 | 2.8 | 1.6 | 0.4 | Elon |