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Drew Brees and Spreading It Around

In 2016, Odell Beckham gained 34% of all Giants receiving yards, the highest share in the NFL. For 31 of 32 teams, at least one player gained 20% of their team’s receiving yards, but for the Bills, Robert Woods led the team in receiving despite being responsible for only 19% of Buffalo’s receiving yards.

But since Drew Brees came to the Saints in 2006, no team has spread it around more than New Orleans. On average, Brees’ leading receiving has been responsible for only 22% of the Saints receiving yards each year. The table below shows the average percentage of team receiving yards gained by the top receiver (RB, WR, or TE) for each team in each season over the last 11 years. The Falcons, buoyed by long runs of success by Roddy White and then Julio Jones, have been the most WR1-heavy passing game, while the Saints have been the most diverse:


In yesterday’s post, I discussed how second-year wideout Michael Thomas is in a great position to produce monster stats.  This appears to be the only thing holding him back: Brees has shown a consistent preference for spreading the ball around.  The question now becomes whether or not the disparity between Thomas and the rest of the passing game is significant enough to change that equation.

Last year, Brandin Cooks was responsible for just 22.3% of the Saints receiving yards, which ranked 26th among all top receivers last year. In 2015, Cooks had 21.9% of the Saints receiving pie, which ranked 28th. The table below shows the percentage of the receiving pie, and where that ranked among the league as a whole, for the Saints top receiver in each year since 2006.

YearLeading ReceiverRkPerc
2006Marques Colston2722.4%
2007Marques Colston2127.2%
2008Lance Moore3118.3%
2009Marques Colston2623.9%
2010Marques Colston2622.1%
2011Jimmy Graham1923.8%
2012Marques Colston2422.2%
2013Jimmy Graham2423.5%
2014Kenny Stills3218.8%
2015Brandin Cooks2821.9%
2016Brandin Cooks2622.3%

What do you think? Any other fun thoughts on what to do with this type of data, or other ways (better ways?) to measure how much quarterbacks spread it around?

  • Quinton White

    I find this to be a fun and interesting way to capture QB styles.

    If you wanted to incorporate more than just the #1 guy, then you could sum up the squared shares for all a QBs receivers. For example, say a QB threw to 7 guys, and the first guy caught 30% of the yards and the second 20% and the remaining 5 guys each caught 10%, then he would have a concentration index of .3^2 + .2^2 + .1^2 + .1^2 + .1^2 + .1^2 + .1^2 = .18. The higher the number, the more concentrated the passer is. The max is 1 (Brees threw all his passes to Cooks then 1^2 = 1). If he threw 10% to ten guys each, then the index would be .1. This is one way economists measure how concentrated industries are.

    • Richie

      Interesting concept. Hope I can remember it later. I feel like I could have used this before.

    • Adam

      This is a very good idea. Maybe you should write a guest post…

      • Quinton White

        Thanks! I’d be happy to write a guest post if Chase was interested. I’d probably need a primer on where he gets the data

    • Richie

      Just to try the method, I calculated the Squared Shares for each of Brees’ years with the Saints:

      Year SqShare

      2011 0.157
      2012 0.156
      2016 0.152
      2009 0.149
      2007 0.145
      2013 0.142
      2006 0.137
      2015 0.137
      2014 0.128
      2010 0.126
      2008 0.119

      • Joseph Holley

        Wow–thanks for the math work. Curiously, how many places did you use for the percentages? Did you use every receiver, or just the top ~10? (Counting that 1 yd TD to the 6th OL that comes in as the 3rd TE would be a pain!) I wonder if we were comparing QB seasons, would 3 decimal places be enough? What would be the upper bounds of realism? .250? What would be ridiculously low? .100? I agree that this deserves more study and a guest post.

        • Richie

          I only rounded the final summation. I used every player who had at least 1 receiving yard (so I left out anybody who had zero or negative yards. In hindsight, I should have included everybody who had a catch, but it shouldn’t make much difference.).

          • Quinton White

            Thanks for taking it that extra step and doing some calculations!

  • Joseph Holley

    As a Saints fan, I have to weigh in. The point this article makes is exactly what makes the Saints’ offense dangerous. However, overall, the #31 Jags in chart 1 show a lack of talent/continuity at the pass-catching (and QB) positions.
    If your “WR1” has ~1,100 yds, and your WR2 has ~850 yds, and your TE/WR3 has ~600 yds, with your 4th & 5th leading receivers (by yds) have 400 yds, you have a dangerous team–because your QB spreads the ball around to whoever is open. If your percentages are low b/c 15 players have over 100 yds receiving for the year, you probably lack some star power or had some injuries.

  • LightsOut85

    I’m not surprised to see the Chargers as low on the list as they are; our fans have always felt Rivers was adept at spreading it around.

    I wonder how much the rankings would change if it measured literally spreading passes around – the % of total team targets by each leading receiver.

  • Kaedwon

    Any reason to use yardage rather than targets? After all, Brees doesn’t control what a receiver does with the ball once he’s thrown it. I doubt the overall conclusion would change much, but targets seem more relevant to the spread-it-around argument.l

    • Joseph Holley

      I wonder if it is harder to get reliable data on the targets. Some sites might count throw-aways (esp. where the QB is obviously avoiding the sack and just trying to get it “in the area” to avoid intentional grounding), where others wouldn’t. How do you count a Hail-Mary?
      IMO, if you use yards like Richie did, or targets, you probably need a cutoff, like 5 targets or 20 yds.

    • Richie

      I thought about that a bit.

      Targets would tell us who a QB is trying to get the ball to.

      Yardage tells us how much the actual production is spread out.

      I’m guessing there wouldn’t be huge differences, but they do tell slightly different stories.