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The Gut Check No. 400: WR Production Shares, ADP, and Consistency

Matt Waldman examines wide receivers that quarterbacks lean on in the passing game, including the return of his consistency data. 

Pairing statistics with insightful context can uncover fantasy value in pre-draft prep. Delivering the insightful context is the difficult part. Three data points that have potential value for fantasy owners are the percentage of targets, yards, and touchdowns that pass catchers earn from their quarterback during the year.

This week's Gut Check column will examine these three statistical outcomes for wide receivers between 2014-2016. This information will also be paired with ADP, consistency data, and other salient points that will help readers identify some of the safest options in 2017 fantasy drafts.

ABOUT CONSISTENCY DATA

I began publishing Consistency Data in 2004. What differentiates my examination of "fantasy consistency" from many is that I don't use standard deviation as the method because this stat's purpose is to measure the variance of a process. When I was posting a lot of consistency analysis in the early-to-mid 2000s, the few others who were analyzing consistent performance were valuing low standard deviations because it proved to them that the process is under control. When applied to fantasy football, standard deviation doesn't help us see the type of consistency that a fantasy owner desires from a player.

Standard deviation doesn't take into account what we really want to know: How consistently a player reaches at least the desired amount of fantasy points per game. "At least" are the two key words. Strict adherence to standard deviation as the process punishes players who score a lot more than the baseline target—even when they consistency deliver to that baseline.

For example, here's a look at the 2016's top-35 PPR wide receivers with a minimum scoring average of 10 points per game and ranked by lowest to highest standard deviation:

Lowest Standard Deviation Among 2016 PPR Wide Receivers (Minimum of 11 fantasy points per game average)

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Several of the receivers (in red and near the top) with the lowest standard deviation of fantasy points scored (yellow row) are closest to the minimum baseline average that I queried for this list. Many of the highest weekly fantasy scorers (in green and near the bottom) have the largest standard deviation scores. This is why I set tier baselines by generating average values for elite, WR1, WR2, WR3, and subpar categories based on the fantasy years in question. This method doesn't punish consistently high scoring options because their massive game in Week 4 blew their tight little standard deviation figure. 

In other words, why would you punish Julio Jones' consistency because of his 300-yard game? Consistency in our industry's context is about consistently being good—and "better" is always encouraged! 

There's nothing wrong with taking the players in red or at the top of this list at the appropriate round but standard deviation offers are limited scope to the measurement of consistent performance in fantasy football. As mentioned in my article on running backs, I will feature consistency data throughout the summer at Footballguys. 

Wide Receiver Production Shares

Before digging into consistency data, let's examine production shares between 2014-2016, including the top 36 receivers with the highest percentages of targets, yards, and touchdowns in their offenses. These are the columns highlighted in yellow, green, and blue below. 

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