The Stats Room: Zman's WR Projection Model
The Stats Room: Zman's WR Projection Model

This article is part of our The Stats Room series.

After creating a basic projection model for quarterbacks (The Zman's), I've moved onto wide receivers. Truthfully, I wanted an easier task with just a few stats on which to concentrate. The projections for wide receivers stabilize quickly and need to be regressed quite a bit less than the quarterbacks. These projections can give a person a good read on their talent level. The key now is figuring out how each team's targets will get distributed.

These projections have no team context information. They are bare bones for now. They were created in the image of Marcels in which Tom Tango did baseball players.



As Tom describes it, "... uses as little intelligence as possible. So, that's the allusion to the monkey."



I went with the same approach with just a tad more detail in the weights and regression. The basic procedure was to take a three-year weighted sample, regress the data as needed and then add an aging factor. I did not project playing time, which I'll discuss later. 

Compared to the quarterbacks (and running backs, which I've started), the wide receiver stats are not regressed as much. There is more distinction between the good and bad wide receivers. Their job is to just to catch the ball and run. They are less reliant on those around them. That said, here are the categories I projected:

Note: I stayed away from lumping tight ends with wide receivers to see if there are any major differences. I will eventually

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ABOUT THE AUTHOR
Jeff Zimmerman
Zimmerman writes analytics-focused baseball and football articles for RotoWire. He is a three-time FSWA award winner, including the Football Writer of the Year and Best Football Print Article awards in 2016. The 2017 Tout Wars Mixed Auction champion and 2016 Tout Wars Head-to-Head champ, Zimmerman also contributes to FanGraphs.com, BaseballHQ and Baseball America.
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