Forecasting 2018 NFL Rookie WR Success: 3-Year Model

Forecasting 2018 NFL Rookie WR Success: 3-Year Model

By Kevin Zatloukal (4for4 Contributor), last update May 16, 2018

Kevin Zatloukal's picture

Kevin is a Ph.D. computer scientist. His doctoral work at MIT was focused on quantum algorithms. During the fantasy offseason, he teaches computer science at the University of Washington, his alma mater.

Follow Kevin Zatloukal on Twitter: @kczat.

A new season means a new class of rookie wide receivers attempting to break into the league and into our fantasy lineups. In this article, we will discuss some of the key receivers to focus on going into the 2018 season.

For readers in standard (redraft) leagues, we can keep this short: none of these rookies are likely to be important during key parts of your 2018 draft. While some could provide depth for you at the position, none are likely to finish in the top 36 this season.


Click Here to Read Forecasting 2018 Rookie Running Backs


Readers in dynasty or keeper leagues, on the other hand, need to consider the prospects for these receivers not only in 2018 but also in future years. Furthermore, such leagues usually have a rookie-only draft each year, where fantasy managers pick rookies to add to their rosters, necessitating a study of these players.

D.J. Moore, now of the Carolina Panthers, looks like the top prospect in this year's class, but he is also likely to be the first receiver taken in rookie drafts—going somewhere in the mid-first round. Given the number of top-tier running backs in this class, I'd almost certainly be taking an RB at that cost. Below, I'll focus my attention on receivers who can be acquired later in drafts, at a discount to their true value.

By the way, if you’re in a dynasty league, you should definitely check out all the content from our friends over at Dynasty League Football. They have much more information on all of the rookies I talk about below.

Forecasting Wide Receiver Success

I built a statistical model two years ago that predicted the odds of a rookie receiver having a top-36 season in one of their first three years in the NFL. That model needed only draft position and career market share of team yards from scrimmage in order to achieve high accuracy over past seasons. Last year, I added a machine learning (ML) model. Combining different models with similar individual accuracy typically leads to more accurate forecasts due to a wisdom-of-crowds effect. The combined odds I give below are a weighted average of these two different models.

Hopefully, you followed last year's advice and grabbed Kenny Golladay or Cooper Kupp, two of our top three targets. Both were available late in rookie drafts and hugely out-performed their draft position. (The other of the top three targets, Zay Jones, had a rough year, but still has a chance to be a success in the league.)

Below you will find a table showing some receivers who are well-poised to do the same this year, and my breakdown of five rookie receivers...

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2018

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