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 |
|---|---|---|---|---|---|---|---|
| Alden Yergey | Fr | 5-09 | 20.4 | 6.1 | 1.8 | 1.3 | Siena |
| Anajah Brown | Jr | 6-01 | 24.6 | 11.0 | 7.4 | 1.3 | Siena |
| Ciany Conyers | Fr | 5-08 | 16.8 | 4.6 | 2.1 | 0.7 | Siena |
| Constance Ogbeide | Fr | 6-01 | 1.2 | 0.0 | 0.4 | 0.1 | Siena |
| Esther Rodellar | Fr | 5-09 | 4.1 | 0.7 | 0.8 | 0.1 | Siena |
| Eszter Turi | Fr | 6-01 | 15.3 | 3.3 | 3.1 | 0.6 | Siena |
| London Gamble | So | 5-08 | 23.9 | 6.6 | 3.7 | 1.1 | Siena |
| Nikola Zdenkova | Fr | 5-09 | 7.0 | 2.4 | 0.1 | 0.4 | Siena |
| Teresa Seppala | So | 6-00 | 30.9 | 14.1 | 6.8 | 1.5 | Siena |
| Valencia Fontenelle-Posson | Jr | 5-10 | 24.7 | 9.2 | 5.0 | 1.5 | Siena |