Depth and Passer-adjusted Catch Rates

| April 21, 2014

Kenny-Stills-2As is the case with many football statistics, a player’s catch rate can be distorted by a variety of variables. The main two are the player’s offensive role and the ability of his quarterback.

Today, I’m going to normalize each player’s catch rate based on these two factors. I’ll be adjusting for the depth of each target seen by the player and the completion percentage of the quarterback who made each throw.

I’m going to start with catch rates adjusted only by depth. This is fairly obvious, but the idea here is that players who tend to see a lot of targets deep down field will have a much lower catch rate and vice versa. By calculating each receiver’s expected catch rate, we’ll be able to better distinguish the league’s best and worst ball-catchers.

Our first chart shows the players who exceeded their expected catch rate (again, based only on depth this time) by the largest margins during the 2013 season. Note that only players who saw 50 or more targets are included in this study.

Rk Receiver Targ Rec aDOT  C% Exp C%  +/-
1 Kenny Stills 50 35 16.9 70% 54% 16%
2 Danny Woodhead 89 81 1.8 91% 78% 13%
3 Pierre Thomas 82 77 -1.7 94% 82% 12%
4 Timothy Wright 72 54 9.4 75% 64% 11%
5 Doug Baldwin 88 63 11.4 72% 61% 11%
6 Delanie Walker 79 60 8.8 76% 65% 11%
7 Jordy Nelson 128 92 11.4 72% 61% 11%
8 DeSean Jackson 125 85 14.3 68% 58% 10%
9 Jordan Cameron 108 79 9.9 73% 63% 10%
10 Heath Miller 74 58 6.5 78% 69% 9%
11 Keenan Allen 113 79 11.1 70% 61% 9%
12 Marques Colston 125 88 10.9 70% 61% 9%
13 Jacquizz Rodgers 58 52 -0.3 90% 81% 9%
14 Julio Jones 57 41 10.4 72% 63% 9%
15 Greg Olsen 108 77 9.8 71% 63% 8%
16 Lance Moore 61 41 11.8 67% 60% 8%
17 Tony Gonzalez 115 83 8.8 72% 65% 8%
18 Marvin Jones 88 59 12.2 67% 60% 8%
19 Darren Sproles 95 80 1.7 84% 77% 8%
20 Nate Burleson 51 39 6.4 76% 69% 7%

The 70 percent catch rate Kenny Stills put up as a rookie is even more impressive when you consider that no player in this sample had a higher average depth of target (aDOT). Of his 50 targets, 15 had a depth of at least 20 yards. Stills caught six for 340 yards and five scores. On targets inside 20 yards, he caught a ridiculous 29 of 35 targets (83 percent). Stills only dropped one pass on the season. As we’ll see later, Drew Brees under center helped boost Stills’ catch rate, but not by a ton.

When you consider that he has one of the lowest catch rates and highest aDOTs in our first chart, DeSean Jackson’s presence at No. 8 overall is quite interesting. Jackson was exceptional in his first campaign under Chip Kelly. Despite a hefty 14.3 aDOT, Jackson hauled in 68 percent of his targets. That’s almost exactly 10 percentage points above expected. Jackson was nothing short of exceptional near the line of scrimmage. He caught 47 of 52 targets (90 percent) when positioned behind or within 7 yards of the line of scrimmage. Jackson hauled in 10 of 21 targets (48 percent) when the depth was at least 30 yards down field. Much has been made about how the loss of Jackson’s field-stretching ability will hurt the Eagles’ offense, but this helps explain the team’s addition of Darren Sproles. Consider that Sproles hauled in 76 of 87 targets (87 percent) when behind or within 8 yards of the end zone last season. Sproles caught 45 of 51 targets (88 percent) when in the 0-to-10-yard range.

The next chart shows the players who fell short of their expected catch rates by the largest margins.

Rk Receiver Targ Rec aDOT  C% Exp C%  +/-
141 Davone Bess 83 42 6.1 51% 70% -19%
140 Santonio Holmes 55 23 13.0 42% 58% -16%
139 Kenbrell Thompkins 72 32 12.6 44% 59% -15%
138 Greg Little 88 41 11.8 47% 60% -14%
137 Chris Givens 77 34 13.8 44% 58% -14%
136 T.J. Graham 55 23 16.1 42% 55% -13%
135 Kris Durham 82 38 12.4 46% 59% -13%
134 Darrius Heyward-Bey 58 29 10.8 50% 62% -12%
133 Marcel Reece 53 32 4.9 60% 72% -11%
132 Santana Moss 77 42 8.8 55% 65% -10%
131 Stephen Hill 51 24 14.7 47% 57% -10%
130 Chris Ogbonnaya 70 48 1.0 69% 79% -10%
129 Steve Johnson 95 52 9.3 55% 64% -10%
128 Vincent Jackson 156 78 13.3 50% 58% -8%
127 Bilal Powell 50 36 0.1 72% 80% -8%
126 Dallas Clark 51 31 6.9 61% 68% -8%
125 Andre Holmes 52 25 14.7 48% 55% -7%
124 Reggie Bush 76 54 1.1 71% 78% -7%
123 Jerome Simpson 96 48 14.4 50% 57% -7%
122 Tavon Austin 65 40 7.7 62% 68% -7%

Davone Bess was a competent possession receiver while in Miami, but was downright dreadful in his first season in Cleveland. Bess barely caught half his targets despite primarily operating near the line of scrimmage. Bess actually caught all five of his targets at or behind the line of scrimmage, but hauled in only 25 of 55 in the 1-to-7-yard range. The Browns cut Bess earlier this offseason and will replace him in the slot with Andrew Hawkins. Hawkins has a career 80 percent catch rate on targets within 9 yards of the line of scrimmage.

An undrafted free agent signing by New England last season, Kenbrell Thompkins received an absurd amount of hype. Unsurprisingly, he failed to live up to it. Thompkins caught only 32 of his 72 targets (44 percent) despite a 12.6 aDOT. He managed only 13 receptions on 39 targets 10-plus yards down field. Thompkins is already on the bubble for the team’s 2014 53-man roster.

Our next two charts are very similar to the first two, but this time we’re adjusting for the influence the passer had on the play. Common sense tells us catch rates will be influenced quite a bit if Peyton Manning is a team’s quarterback instead of Mark Sanchez.

This chart shows the players who exceeded their aDOT and passer-adjusted expected catch rates by the largest margins last season.

Rk Receiver Targ Rec aDOT  C% Exp C%  +/-
1 Jordan Cameron 108 79 9.9 73% 59% 14%
2 Timothy Wright 72 54 9.4 75% 62% 13%
3 Kenny Stills 50 35 16.9 70% 58% 12%
4 Doug Baldwin 88 63 11.4 72% 62% 10%
5 Delanie Walker 79 60 8.8 76% 66% 9%
6 Pierre Thomas 82 77 -1.7 94% 86% 8%
7 Danny Woodhead 89 81 1.8 91% 83% 8%
8 DeSean Jackson 125 85 14.3 68% 60% 8%
9 Rod Streater 94 60 11.9 64% 56% 7%
10 Heath Miller 74 58 6.5 78% 71% 7%
11 Nate Burleson 51 39 6.4 76% 69% 7%
12 Scott Chandler 79 53 8.3 67% 60% 7%
13 Jeremy Kerley 63 43 9.0 68% 61% 7%
14 Jordan Reed 60 45 6.9 75% 68% 7%
15 Greg Olsen 108 77 9.8 71% 64% 7%
16 Jordy Nelson 128 92 11.4 72% 65% 7%
17 Marvin Jones 88 59 12.2 67% 60% 7%
18 Anquan Boldin 150 101 10.3 67% 61% 7%
19 David Nelson 56 36 11.4 64% 58% 7%
20 Julian Edelman 168 121 8.5 72% 66% 6%

Entering 2013, we knew Jordan Cameron was a physical freak with a high ceiling. Finally positioned as a starter, he turned those skills into one of the top receiving performances of the year by a tight end. Cameron ranks out as having the best catch rate in the NFL when aDOT and quarterback play are factored in. Based on my math, Cleveland’s poor quarterback play cost him four percentage points off his catch rate. Couple that with his 9.9 aDOT and Cameron’s 73 percent catch rate was 14 percentage points above expected. Cameron caught 45 of 55 (82 percent) targets in the 0-to-8-yard range. Only 25 and with the Cleveland offense improving around him, Cameron is a rising star.

Bucs’ tight end Tim Wright shows up in the Top 4 of both “good” lists we’ve seen. Wright caught 54 of his 72 targets as a rookie. More of a receiver than a tight end, his 9.4 aDOT was on the high side at the position. Wright only saw one target behind the line of scrimmage, instead doing most of his damage in the intermediate range. He hauled in all 20 of his targets in the 0-to-5-yard range and caught of 5 of 6 balls thrown 19 yards or deeper down field. Tampa Bay added Brandon Myers this offseason, but new offensive coordinator will have a hard time keeping Wright off the field on passing downs.

Finally, we have the players who fell short of their aDOT and quarterback-adjusted expected catch rates by the largest margins.

Rk Receiver Targ Rec aDOT  C% Exp C%  +/-
141 Davone Bess 83 42 6.1 51% 67% -16%
140 Kenbrell Thompkins 72 32 12.6 44% 59% -14%
139 Kris Durham 82 38 12.4 46% 59% -13%
138 Santonio Holmes 55 23 13.0 42% 54% -12%
137 Chris Givens 77 34 13.8 44% 56% -12%
136 Greg Little 88 41 11.8 47% 57% -11%
135 Darrius Heyward-Bey 58 29 10.8 50% 60% -10%
134 Le’Veon Bell 62 45 0.7 73% 82% -9%
133 Reggie Bush 76 54 1.1 71% 79% -8%
132 Marcel Reece 53 32 4.9 60% 68% -8%
131 Santana Moss 77 42 8.8 55% 62% -8%
130 T.J. Graham 55 23 16.1 42% 49% -7%
129 Chris Ogbonnaya 70 48 1.0 69% 75% -7%
128 Stephen Hill 51 24 14.7 47% 53% -6%
127 Jason Avant 77 43 11.3 56% 62% -6%
126 Jerome Simpson 96 48 14.4 50% 56% -6%
125 Tavon Austin 65 40 7.7 62% 67% -5%
124 Aaron Dobson 74 39 14.1 53% 58% -5%
123 Vincent Jackson 156 78 13.3 50% 55% -5%
122 Steve Johnson 95 52 9.3 55% 59% -5%

Le’Veon Bell wasn’t even in the aDOT-only version of this list, so his ranking of eighth-worst is worth a look. Bell’s aDOT was less than 1 yard down field, but he managed only 54 receptions on 62 targets. Bell’s catch rate was nine percent points below expected. He actually did alright on short targets, hauling in 35 of 41 looks (85 percent) with 1 yard of the line of scrimmage. OC Todd Haley had him run a few deeper routes, however, which turned out poorly. Bell caught zero of six targets nine-plus yards down field. Bell was competent as an “innings eater” as a rookie, but he’ll need to be more effective if he hopes to hold LeGarrette Blount off in Pittsburgh.

Detroit’s addition of Golden Tate looks even prettier when you realize just how poorly Kris Durham performed last season. On the field for 84 percent of Detroit’s snaps, Durham was an offensive fixture opposite Calvin Johnson. He wasn’t very good, hauling in only 38 of 82 targets (46 percent) despite a middle-of-the-pack 12.4 aDOT. Durham racked up 44 targets 10-plus yards down field, but caught only 13 (30 percent). Durham is likely ticketed for No. 4 or 5 duties in 2014.

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Follow Mike Clay on Twitter: @MikeClayNFL

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Editor’s Note: Be sure to check out our new Mock and Companion Draft Tool! Utilizing our updated player projections, run a quick mock draft and see where this year’s crop of free agents are coming off the board in early fantasy football drafts.

  • Jason Williams

    Cleveland Wide Receivers. Good Grief.

  • Robin Strick

    Hey Mike,
    Players who exceeded their aDOT from my count 7 TEs, 2 RBs, and 13WRs and in the top 10 only 4 WRs. From a fantasy pov this could be beneficial to see per position or even separating the rankings between guys who have an aDOT 9yds seems useful if you want to overlap postions? A side note, 5 of the top 20 who exceeded their catch rate are Saints and we have none from Denver.

    Imho, (sort of a generic rant) most of the comparisons done by the various writers
    (i.e. “Pass Blocking By TimeToThrow”, “ElusiveRatings”, etc) here at PFF compares players seasonal stats in a “linear” fashion (lots of extrapolation). While these are all great articles and I know are extremely time consuming to collect the data. The comparisons/rankings at times seem a little too straightforward. Like ranking #8 ZachStrief’s 547pb attempts to Armstead(#4) 132pb attempts or for ranking YAC ADP(#5) with 279att and D.Brown(#1) with 109att and less than 1 foot separating these two. Give D.Brown another 170 attempts and see if his YAC stays 1’ more than ADP if so he prob would not be going as a backup to SanDiego. Should you extrapolate that if Armstead is in on another 410 pass attempts he would be .1% ahead of Strief in that ranking? Armstead started only 2 games and Strief started 15games so ranking them in the same list doesnt seem like we are comparing “apples to apples”.

    Perhaps either there could be additional weighting given when ranking players to those who when active are involved in say >70% of their teams plays, or simply create 2 ranking lists one for starters and the other for the situational/subs/backup type players.

    • LightsOut85

      I definitely agree with your “rant”. I guess, the easy solution would be for you to “do your own ranking” (ie: ignore those low-end sample size people) & just hope that others do the same (in terms of hoping for logical football discussion).

      Rankings can present issues even with all-large sample sizes, if you don’t examine how different the values actually are (made-up ex: 3 & 15 would seem pretty far apart, but the value you’re ranking them on could not be that far apart (2.72 & 2.68, if that were yards/route-run it’d be just short of 1.5 inches difference). One way to “fix” this (if you have access to all the data, like the premium subscription) is to calculate how many standard-deviations each value is from the median.

  • Fusue Vue

    How about adjusted drop rate? Are deeper “catchable” passes harder to catch?