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 |
---|---|---|---|---|---|---|---|
Alarice Gooden | So | 5-07 | 7.1 | 3.3 | 0.9 | 0.4 | Hofstra |
Emma Von Essen | So | 5-09 | 27.0 | 11.6 | 3.0 | 1.1 | Hofstra |
Kassidy Thompson | Fr | 5-10 | 9.1 | 1.9 | 2.1 | 0.4 | Hofstra |
Kayley Joseph-Bernard | So | 6-00 | 8.8 | 1.6 | 2.2 | 0.8 | Hofstra |
Micaela Carter | Fr | 5-06 | 14.2 | 2.2 | 1.2 | 1.0 | Hofstra |
Onna Brown | Fr | 5-11 | 5.4 | 1.7 | 0.5 | 0.2 | Hofstra |
Tionna Baker | Jr | 5-06 | 14.0 | 3.5 | 3.3 | 0.6 | Hofstra |