Wide Receiver Consistency

In several of my WR and TE tier articles this year, I have used consistency or lack thereof as a reason why a particular player is or is not meeting his contract expectations. However, “Player A is consistent and Player B is not” without supporting analysis isn’t a very strong argument. Today, I would like to explore two methods of determining a player’s consistency: median statistics and frequency of hitting specific milestones.

My earlier posts on receivers and tight ends looked at production when averaged over 16 games. While it is important to look at season totals, a significant missing piece was what to do with players like Marvin Jones who started the season hot, then cooled off significantly. Jones’ 2016 totals should look good when viewed as one number, but the Lions are really getting several games at amazing value and several games where they’re getting well below market value.

Method #1: Median Statistics

First, I’ll look at median statistics. For most players, median touchdowns will either be 0 or 1, so I am instead looking at how many games have at least 1 touchdown. For catches and yards, I’m looking at the true median: if a player has played in 11 games, I’m looking at how he performed in his 6th best game.

To determine an approximate median game for each of the Wide Receiver Tiers. I looked at the 2014-2016 games for each receiver currently in those tiers. The smallest sample size was Tier 2 receivers at 330 games.

Click here for a more detailed analysis of how each tier was determined. The short version is: Tier 1 includes players on contracts with APY over $14M, Tier 2 is $10M-$11.5M, Tier 3 is $6M-$8M, and Tier 4 is $3M-$5M. Tier 4 receivers are not included in this article. I included both Antonio Brown and TY Hilton in the Tier 1 group even though their contracts are not at that level yet. Brown’s inclusion should be obvious. Hilton’s contract is between Tier 1 and Tier 2. I bumped him up into Tier 1 for this exercise because his production this year is closer to Tier 1 than Tier 2.

Tier 1Median TargetsMedian CatchesMedian YardsGames with TD
Julio Jones11710638%
Antonio Brown1189751%
Demaryius Thomas1168740%
AJ Green967847%
TY Hilton957733%
Alshon Jeffery857240%
Dez Bryant847255%

Another way to read this data is: “In 50% of AJ Green’s games, he will catch 6 or more passes” or “In 50% of Green’s games, he will accumulate less than 78 yards”.

Quick Observations on Tier 1:

  • Antonio Brown and Dez Bryant stick out in terms of touchdowns as both score at least 1 touchdown in over 50% of their games.
  • Julio Jones has been excellent over the past few years in terms of yardage. Over the past three seasons, he has been more likely than not to end a game with more than 106 yards.
Tier 2Median TargetsMedian CatchesMedian YardsGames with TD
Jordy Nelson968367%
Emmanuel Sanders967531%
Larry Fitzgerald966227%
Keenan Allen965826%
Randall Cobb755838%
Jeremy Maclin845744%
Doug Baldwin645133%
Allen Hurns744638%
Vincent Jackson734416%

Quick Observations on Tier 2:

  • Jordy Nelson is as consistent as a Tier 1 WR and his touchdown consistency is almost unbelievable: he has scored in 21 of his past 27 games.
  • If Nelson’s touchdown rate is removed, the group’s combined rate becomes 32%.
Tier 3Median TargetsMedian CatchesMedian YardsGames with TD
Brandon Marshall1066850%
Eric Decker856258%
Golden Tate865723%
Marvin Jones645426%
Pierre Garcon745126%
DeSean Jackson645137%
Michael Crabtree854937%
Mike Wallace644633%
Torrey Smith523837%
Travis Benjamin533719%
Mohamed Sanu432819%

Quick Observations on Tier 3:

  • Both of the Jets’ receivers, Marshall and Decker, are outliers in terms of touchdowns. The remaining receivers score a touchdown in only 28% of their games.
  • Both Marshall and Decker have median games that look closer to Tier 2 (Catches and Yards) or Tier 1 (Touchdowns) than Tier 3.
  • Some of the receivers at the bottom of this list are ones considered to be deep threats (Benjamin, Smith, Wallace). These players are just as likely to have a 30 yard day as a 130 yard day.
  • Sanu is in his first year as a presumed starter after several years in a time share in Cincinnati, so the above chart may be short-selling his production.

As expected, Tier 1 receivers have median games that are better that Tier 2 receivers who have better median games than Tier 3 receivers. One way I attempted to quantify this into a grade was to consider the difference between a player’s game averages and a player’s median game. Players with a lower score (less difference) are more consistent.

Method #2: Milestones

A second way to look at consistency is the frequency with which players hit specific milestones. For catches, I used milestones of <5, 5-7, 8-9, and 10+ catches, for yards, I used <50, 50-74, 75-99, and 100+, and for touchdowns, I used 0, 1, 2, and 3+.

My expectation was that a Tier 1 receiver will total 100 yards in a game more often than 75, 75 more often than 50, etc. A Tier 2 receiver should total 100 yards less often than a Tier 1 receiver but more often than a Tier 3 receiver. The same principles apply to catches and touchdowns.

The total counts for each tier are shown below along with the graphical representation of the percentage of games when those milestones are achieved.



The results for catches and yards are pretty much in line with what should be expected: Tier 1 receivers have games with more catches and yards with better consistency than Tier 2 or Tier 3 receivers. A Tier 1 receiver will have 50 or more yards in 75% of games while Tier 2 and 3 receivers will only pass 50 yards in 61% and 48% of their games. Tier 1 receivers have 5 or more receptions in 68% of games while Tier 2 and 3 receivers have 5 or more receptions in 53% and 40% of their games.

Summary and Final Quick Thoughts

This analysis is meant to be used in conjunction with season-long averages. If two players have near-identical annual production, but one is more consistent, that player should be compensated higher within the same Tier.

I am aware that in some games Tier 1 receivers are used as decoys. This is most often cited when discussing Julio Jones. I haven’t done enough research to determine if one player receives significant different treatment than others of the same tier, so I haven’t considered that in today’s post.

Please leave a note in the comments section below if you believe I missed something related to either of these two methods or if I missed a method entirely.

  • hanskim2016

    Question about the part regarding decoys. For simplification sake, let’s use an extreme example to illustrate the point: What if for the rest of the year, Julio Jones were to be used as a decoy and draw double teams, etc. and he had zero production from a traditional statistics standpoint, and yet somehow Sanu now scores 3 TDs a game. How would the player/agent and the team evaluate that type of activity as performance and then in turn, compensation for both Jones and Sanu?

    I assume this is definitely a meta/gray zone that I’m sure the agents start to work their spin magic and sell snake oil… Anyone have any thoughts?