2017 NFL Draft: Advanced Stats for the Senior Wide Receivers
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Since we began working on wide receivers with the birth of RotoViz in 2013, we’ve written hundreds of articles on the position. Most of them arrive at the same conclusion: Understanding age-adjusted market share production allows you to hack the NFL’s evaluation process and get tremendous bargains at the position. This was the message of Jon Moore’s Phenom Index, RotoDoc’s rookie WR model, Kevin Cole’s regression tree analysis, and my research that led to the selection of Stefon Diggs as last year’s breakout star. In Part 1, I mentioned some of the components likely to be included in the machine-learning model RotoDoc and Josh Hermsmeyer are currently building. Before we get to that point, it’s helpful to build a solid foundation. In this series, I will attempt to present the career raw and market share production of the 2017 class in an apples-to-apples format. Each experience sub-group will get their own article.