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 |
---|---|---|---|---|---|---|---|
Alexis Davis | Fr | 6-00 | 26.0 | 7.8 | 6.3 | 0.5 | Buffalo |
Ariana Seawell | Jr | 6-02 | 19.1 | 10.7 | 6.0 | 0.4 | Buffalo |
Ella Take | Fr | 5-11 | 1.5 | 0.5 | 0.2 | 0.0 | Buffalo |
Ida Jonsson Ojala | Jr | 6-02 | 4.4 | 0.8 | 0.9 | 0.3 | Buffalo |
Jaylin Hartman | Fr | 6-02 | 3.7 | 0.0 | 0.6 | 0.3 | Buffalo |
Jessica Wangolo | Fr | 5-07 | 6.4 | 0.2 | 0.4 | 0.4 | Buffalo |
Katie Burton | Jr | 5-09 | 2.0 | 0.5 | 0.0 | 0.0 | Buffalo |
Kirsten Lewis-Williams | Fr | 5-10 | 33.1 | 11.8 | 5.2 | 2.8 | Buffalo |
Lani Cornfield | Jr | 5-06 | 27.6 | 6.8 | 2.9 | 3.8 | Buffalo |
Paula Lopez | Fr | 5-08 | 13.8 | 2.0 | 1.3 | 0.7 | Buffalo |
Sitota Gines | Jr | 5-10 | 10.2 | 2.0 | 1.6 | 0.7 | Buffalo |
Terah Harness | Jr | 5-09 | 3.6 | 0.6 | 0.6 | 0.2 | Buffalo |