Elite running backs are a precious commodity in dynasty fantasy football. Dave Caban outlines a simple way to maximize your chances of finding tomorrow’s stars.
Earlier this month I used regression tree analysis to better understand wide receiver prospect profiles. Regression trees help us to understand the mixture of attributes that tend to drive NFL performance and provide a visual way to understand how these attributes interact. I built a regression tree in that article that could be used to estimate the points per game that a WR prospect would score in his first three NFL seasons.
Since completing it, I’ve been working on a similar analysis for running backs. I’ve yet to arrive at a model I’m ready to publish, but from using a variety of training sets and workshopping different regression trees, I have identified a couple of factors that tend to be useful when considering RB prospect profiles.[1] In particular, there are two factors, that when paired together, provide very competitive hit rates in identifying backs with the potential to be elite fantasy players.
Key Statistics
A majority of the regression trees I looked at included
Footnotes
| ↑1 | Regression trees built using RB prospect data tend to overfit to the limited data available. |
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