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 |
---|---|---|---|---|---|---|---|
Janae Kent | Fr | 6-01 | 7.7 | 1.6 | 0.8 | 0.4 | Texas A&M |
Janiah Barker | So | 6-04 | 26.0 | 12.2 | 7.6 | 1.4 | Texas A&M |
Kylie Marshall | Fr | 5-11 | 3.3 | 0.9 | 0.8 | 0.3 | Texas A&M |
Solè Williams | Fr | 5-09 | 12.3 | 5.0 | 1.1 | 0.8 | Texas A&M |
Sydney Bowles | So | 6-00 | 14.5 | 3.5 | 2.0 | 0.9 | Texas A&M |
Tineya Hylton | Jr | 5-07 | 14.1 | 4.1 | 1.9 | 1.7 | Texas A&M |
Vanessa Saidu | Fr | 6-02 | 3.3 | 1.7 | 0.9 | 0.0 | Texas A&M |