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 |
|---|---|---|---|---|---|---|---|
| Amira Mabry | So | 6-00 | 29.2 | 11.4 | 6.0 | 0.7 | Tulane |
| Chiara Grattini | Jr | 5-09 | 15.0 | 2.7 | 1.4 | 1.9 | Tulane |
| Jaylee Womack | So | 5-10 | 5.1 | 1.6 | 0.2 | 0.1 | Tulane |
| Joy Madison-Key | Fr | 5-08 | 13.5 | 2.5 | 1.0 | 2.4 | Tulane |
| Kierra Middleton | Jr | 5-07 | 20.0 | 5.0 | 2.0 | 2.0 | Tulane |
| Kyren Whittington | Jr | 5-09 | 29.9 | 17.4 | 3.4 | 2.4 | Tulane |
| Lilybeth Ba | Fr | 6-03 | 2.8 | 0.2 | 0.4 | 0.0 | Tulane |
| McKenzi Carter | Jr | 6-01 | 3.1 | 0.7 | 0.7 | 0.2 | Tulane |
| Sherese Pittman | Jr | 6-02 | 28.1 | 12.6 | 7.4 | 2.1 | Tulane |