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 |
---|---|---|---|---|---|---|---|
Ashlynn Shade | Fr | 5-10 | 31.1 | 10.8 | 3.6 | 1.4 | UConn |
Azzi Fudd | Jr | 5-11 | 30.0 | 11.0 | 2.5 | 2.5 | UConn |
Caroline Ducharme | Jr | 6-02 | 14.2 | 4.0 | 2.0 | 0.5 | UConn |
Ice Brady | So | 6-03 | 17.1 | 4.5 | 3.2 | 1.1 | UConn |
KK Arnold | Fr | 5-09 | 29.8 | 8.6 | 3.1 | 3.2 | UConn |
Qadence Samuels | Fr | 6-00 | 11.6 | 4.6 | 2.4 | 0.4 | UConn |