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 |
---|---|---|---|---|---|---|---|
Amiya Carroll | So | 5-11 | 2.0 | 0.2 | 0.8 | 0.0 | Monmouth |
Antonia Panayides | Jr | 5-07 | 4.2 | 0.2 | 0.1 | 0.2 | Monmouth |
Diamond Wiggins | Fr | 5-10 | 4.0 | 0.5 | 2.0 | 0.4 | Monmouth |
Divine Dibula | Fr | 6-01 | 10.0 | 2.7 | 3.4 | 0.3 | Monmouth |
Ella Farrelly | So | 6-01 | 17.4 | 3.5 | 3.8 | 0.4 | Monmouth |
Isabella Murray | Fr | 5-09 | 1.3 | 0.0 | 0.0 | 0.0 | Monmouth |
Rosalie Mercille | Fr | 5-09 | 16.3 | 6.4 | 2.0 | 0.9 | Monmouth |