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Nelson has been the league's best receiver in 2014

Nelson has been the league's best receiver in 2014

I have used the concept of Adjusted Catch Yards for a long time; that metric is the base statistic in my Greatest Wide Receivers Ever post. ACY, you may recall, is simply receiving yards with a 5-yard bonus for receptions and a 20-yard bonus for touchdowns. Why a 5-yard yard bonus for catches?

We want to give receivers credit for receptions because, all else being equal, a receiver with more receptions is providing more value because he’s likely generating more first downs.

For the last 15 years, we have data on the number of first downs a receiver produces. But this summer, we added a bit of crucial information: we now know that the value of a first down is about 9 yards. As a result, Adjusted Catch Yards can be modified to be:

Receiving Yards + 9 * First Downs + 11 * Touchdowns

Why is the variable on touchdowns changed to 11? Because a touchdown is a first down; mathematically, this is the same as keeping the value of a touchdown at 20 but changing the first downs variable to be “first downs that did not result in a touchdown.”

This year, Jordy Nelson has caught 33 passes for 459 yards and 3 touchdowns, with 24 of those catches going for first downs (and, of course, 21 going for first downs and not being a touchdown). As a result, Nelson has produced 708 Adjusted Catch Yards this year. But we don’t want to just rank receivers by Adjusted Catch Yards. One thing we can do is rank them on a per-attempt basis; while not as advanced as True Receiving Yards, this provides a relatively simple metric that everyone can understand. We start with receiving yards; then we add bonuses for first downs and touchdowns, and finally we divide the level of production by team pass opportunities. [click to continue…]

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Over the last three seasons, Calvin Johnson has caught 5,137 yards of passes. That’s an incredible amount, and the most by a player over any three-year span in NFL history. That stat by itself isn’t proof of Johnson’s greatness – after all, Detroit has thrown 2,040 passes over the last three years, also the most in any three-year span in football history. But records are not just about greatness: records are a function of era, teammates, and many more elements than pure ability.

So can Calvin Johnson break Jerry Rice’s career receiving yards record? The odds are very long that Johnson will go down in history as a better receiver than Rice, but his odds at breaking his receiving yards record – almost by definition – are a little higher. The man known as Megatron has 9,328 career receiving yards, the third most of any player through his age 28 season. That gives him a 1,462-yard lead on Rice at this age, although Johnson will have to keep up his outstanding pace for a very long time if he wants to capture the record. As the graph below shows, Johnson has had an edge on Rice in career receiving yards through every age of his career to date, but it was Rice’s work in his thirties that separated the GOAT from the pack: [click to continue…]

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James Lofton is the Yards Per Catch King

Yesterday, we looked at which quarterbacks were the best at yards per completion after adjusting for league average. Today, we’ll do the same thing for wide receivers and yards per completion.

Lofton tries to hide from the creamsicle uniforms.

Lofton tries to hide from the creamsicle uniforms.

A small tweak is necessary to the formula. You can skip down to the results section if you don’t care about the math, but I suppose most of my readers want to know what goes in the sausage. We can’t just use league-wide yards per completion rates, since that average includes receptions by non-wide receivers. One way around this is to calculate the league average YPC for wide receivers only; that’s easy to do for 2013, but less easy to do for the earlier years of NFL history when the distinction among the positions was not so clear. So, after playing around with a few different methods, I’ve decided to instead use 120% of the league average YPC rate, and give wide receivers credit for their yards over expectation using that inflated number.

For example, in 1983, James Lofton caught 58 passes for 1,300 yards for the Packers, a 22.4 YPC average. That year, the average reception went for 12.63 yards; 120% of that average is 15.2, which means we would give Lofton credit only for his yards over the product of 15.2 and 58, or 879. Since Lofton actually had 1,300 yards, he gets credit for 421 yards over expectation.

The next year, Lofton caught 62 passes for 1,361 yards (22.0). Since the average reception went for 12.66 yards, Lofton gets credit for his yards over (120% * 12.66 * 62), or 942. Lofton therefore is credited with 419 yards over expectation, nearly identical to his performance in the prior year. In fact, those were the 10th and 11th best season in NFL history by this method. [click to continue…]

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The core of the Manning era Colts

Presumably the picture that caused the NFL to consider eliminating the Pro Bowl.

Last week, I looked at the top receivers and the quarterbacks who threw it to them. Today, we flip that question around and look at which receivers the top quarterbacks threw to. I used the exact same methodology from the previous post, so please read that for the fine details.

For Peyton Manning, 20% of his career passing yards came via Marvin Harrison, and another 16% came from Reggie Wayne.  Both of those numbers will decline the longer Manning plays, of course, but for now, those players dominate his list (Dallas Clark is third at seven percent). That’s a pretty stark departure from other quarterbacks such as say, I dunno, Tom Brady.  For the Patriots signal caller, Wes Welker is his top man (13%), followed by Deion Branch (9%), Troy Brown (7%), Rob Gronkowski (7%), and then Randy Moss (5%).

The table below lists the top 7 receivers for each of the 200 quarterbacks with the most passing yards since 1960. The list is sorted by the quarterback’s career passing yards, and I have removed the percentage sign from the table to enable proper sorting.  For example, here’s how to read Brett Favre’s line.  He’s the career leader in passing yards, and played from 1992 to 2010.  His top receiver was Donald Driver (9%), followed by Antonio Freeman (9%), Robert Brooks (6%), Sterling Sharpe (5%), Bill Schroeder (5%), Ahman Green (4%), and William Henderson. [click to continue…]

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Johnson's target ratio is no joking matter

Johnson's target ratio is no joking matter.

Yards per Route Run, a metric tabulated by Pro Football Focus, is one of my favorite statistics to use to examine wide receiver performance.  To me, it’s the wide receiver version of yards per pass, as it takes production and divides that by opportunity.  However, there are some folks who prefer Yards per Target to YPRR, under the idea that a target is a better way to define an opportunity than a route.

Which view is correct?  Fortunately for our analysis, Yards per Route Run can be broken down into two metrics: Yards per Target and Targets per Route Run.  In other words, YPRR already incorporates Yards per Target, but it adjusts that statistic for Targets Per Route Run.  This makes it very easy for us to compare the two statistics: essentially, the question boils down to how valuable it is to know a receiver’s number of Targets per Route Run.

For example, Kenny Stills had the most extreme breakdown of any player in the NFL in 2013. He was off-the-charts good in yards per target (13.9), but saw targets on just 9% of his routes run last year. As a result, Stills averaged just 1.29 yards per route run, a pretty unimpressive figure.

Steve Johnson was the anti-Stills. While Johnson had the worst year of his career since becoming a Bills starter, he still managed to pull down targets on 25% of his snaps. However, he averaged only 6.3 yards target, leaving Johnson with a poor 1.56 yards per route run average. Of course, when comparing Stills’ numbers to Johnson’s, one might note that Johnson was playing with EJ Manuel and Thaddeus Lewis while Stills was playing with Drew Brees, which provides some explanation for the drastic differences between the two receivers in yards per target.1 But putting the quarterbacks issue aside, the question today is a more global one.

Since the only difference between YPRR and Y/T is the metric “targets per route run,” it’s worth asking: is Targets Per Route Run a metric worth looking at? Is it more useful than Yards per Target? Well, the word “useful” will mean different things to different people. What I’m curious about is the stickiness of each metric. And there is a pretty clear answer to that question.

Among the three metrics — YPRR, Y/T, and TPRR — it’s Targets Per Route Run that’s the most consistent from year to year. From 2007 to 2012, there were 344 wide receivers who saw at least 40 targets in Year N, and then played for the same team and saw at least 40 targets in Year N+1.2 [click to continue…]

  1. I suppose one counter to that would be that Stills was competing with Jimmy Graham, Marques Colston, and the Saints obsession with throwing passes to running backs, while Johnson was competing with Scott Chandler, Robert Woods, and Fred Jackson for targets. []
  2. While there are some issues with survivorship bias here, I’m not sure (1) how to get around them, and (2) that those concerns bias the results in a way that’s more biased towards one of the variables we’re examining than the others. []
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One of my first posts at Football Perspective was one of my favorites: the top receivers and the men who threw it to them. I like referencing that post from time to time, so I decided to update the numbers through the 2013 season.

I looked at all regular season games since 19601, and calculated the percentage of passing yards produced from each quarterback. Then, I assigned that percentage to the number of receiving yards for each receiver. For example, in this Raiders game from 1995, Vince Evans threw for 75% of the Raiders passing yards, and Jeff Hostetler was responsible for the other 25%. Therefore, since Tim Brown gained 161 yards, 121 of those yards are assigned to the “Brown-Evans” pairing and 40 to the “Brown-Hostetler” pairing. Do this for every game since 1960, and you can then assign the percentage of career receiving yards each receiver gained from each quarterback.

For example, 32% of Brown’s yards came from Rich Gannon, 26% from Hostetler, 12% from Jeff George, and 9% from Jay Schroeder. That breakdown isn’t too unique: in fact, of the six receivers with the most receiving yards since 1960, all six (including Brown) gained between 29% and 37% of their career receiving yards from their top quarterback.

The table below lists the top 7 quarterbacks for each receiver, although I only included quarterbacks who were responsible for at least five percentage of the receiver’s yards. It includes the 200 players with the most receiving yards since 1960. [click to continue…]

  1. Sorry, Don Hutson. []
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Friend-of-the-program Matt Waldman had some thoughts on the topic of wide receiver size, and then asked if I could contribute with some data. Matt posted our joint effort on his Matt’s site, but I’m reproducing it below for the Football Perspective readers. On twitter, some asked if I could do a separate study on wide receivers and weight rather than height. I’ll put that on the to-do list.


 

Matt Waldman: Stats Ministers and Their Church

I’m a fan of applying analytics to football. Those who do it best possess rigorous statistical training or are disciplined about maintaining limits with its application. Brian Burke wrote that at its core, football analytics is no different than the classic scientific method. Perhaps unsurprisingly, there are some bad scientists out there, who behave more like religious zealots than statisticians. I call them Stats Ministers. They claim objectivity when their methodology and fervor is anything but.

Stats Ministers scoff at the notion that anyone would see value in a wide receiver under a specific height and weight. They love to share how an overwhelming number of receivers above that specific height and weight mark make up the highest production tiers at the history of the position, but that narrow observation doesn’t prove the broader point that among top-tier prospects, taller wide receivers fare better than shorter ones. In fact, what the Stats Ministers ignore is that a disproportionately high number of the biggest busts were above a certain height and weight, too. Having a microphone does not mean one conducted thoughtful analysis: it could also mean one has a bully pulpit where a person with less knowledge and perspective of the subject will look at the correlation and come to the conclusion that it must be so.

However, correlation isn’t causation. Questioning why anyone would like a smaller wide receiver based on larger number of top wide receivers having size is an example of pointing to faulty ‘data backed’ points. Pointing to historical data can only get you so far: it’s not that different than the reasoning that led to Warren Moon going undrafted. That’s an extreme comparison, of course, but the structure of the argument is the same: there were very few black quarterbacks who had experienced any sort of success in the NFL, so why would Moon? Sometimes you have to shift eras to see in a clear light what “correlation isn’t causation” really looks like.

It was overwhelmingly obvious that Moon could play quarterback if you watched him. But if you’re prejudiced by past history rather than open to learning what to study on the field, then it isn’t overwhelmingly obvious. Data can help define the boundaries of risk, but when those wielding the data want to eliminate the search for the exceptional they’ve gone too far. Even as we see players get taller, stronger, and faster, wide receivers under 6’2″, 210 pounds aren’t the exception.

Analytics-minded individuals employed by NFL teams — who have backgrounds in statistics – don’t follow this line of thoughts. Those with whom I spoke acknowledged that there is an effective player archetype of the small, quick receiver. They recognize the large number of size of shorter/smaller receivers who have been impact players in the NFL that make the size argument moot: Isaac Bruce, Derrick Mason, Wes Welker, Marvin Harrison, DeSean Jackson, Torry Holt, Steve Smith, Jerry Rice, Tim Brown, Antonio Brown, Pierre Garcon, Victor Cruz, and Reggie Wayne are just a small sample of players who did not match this 6-2, 210-pound requirement.

This size/weight notion and discussion of “calibration” or what I think they actually mean–reverse regression–is also a classic statistical case of overfitting. There are too many variables and complexities to the game and the position to throw up two data points like height and weight and derive a predictive model on quality talent among receivers. The only fact about big/tall receivers is that they tend to have a large catch radius. Otherwise, there is no factual basis to assume that these players have more talent and skill.

The dangerous thing about this type of thinking is that many of these “Stats Ministers” were trained using perfect data sets in the classroom and their math is reliant on “high fit” equations. When they tackle a real world environment like football they still expect these lessons to help them when it won’t. However, there are plenty of people who are reading and buying into what they’re selling. I showed my argument above to Chase Stuart and asked him to share his thoughts. Here’s his analysis:

Chase Stuart: Analysis of the Big vs. Small WR Question

We should begin by first getting a sense of the distribution of height among wide receivers in the draft. The graph below shows the number of wide receivers selected in the first two rounds of each draft from 1970 to 2013 at each height (in inches):

wr draft ht

The distribution is somewhat like a bell curve, with the peak height being 6’1, and the curve being slightly skewed thereafter towards shorter players (more 6’0 receivers than 6’2, more 5’11 receivers than 6’3, and so on).

Now, let’s look at the number of WRs who have made three Pro Bowls since 1970:

wr pro bowl ht

The most common height for a wide receiver who has made three Pro Bowls since the AFL-NFL merger is 72 inches. And while Harold Jackson is the only wide receiver right at 5’10 to make the list, players at 71 and 69 inches are pretty well represented, too. I suppose it’s easy to forget smaller receivers, so here’s the list of wide receivers 6′0 or shorter with 3 pro bowls:

Mel Gray
Mark Duper
Mark Clayton
Gary Clark
Steve Smith
Wes Welker
Harold Jackson
Charlie Joiner
Cliff Branch
Lynn Swann
Steve Largent
Stanley Morgan
Henry Ellard
Anthony Carter
Anthony Miller
Paul Warfield
Drew Pearson
Wes Chandler
Irving Fryar
Tim Brown
Sterling Sharpe
Isaac Bruce
Rod Smith
Marvin Harrison
Hines Ward
Donald Driver
Torry Holt
Reggie Wayne
DeSean Jackson

Recent history

Now, let’s turn to players drafted since 2000. This next graph shows how many wide receivers were selected in the first two rounds of drafts from ’00 to ’13, based on height:

As you can see, the draft is skewing towards taller wide receivers in recent years. Part of that is because nearly all positions are getting bigger and taller (and faster), but the real question concerns whether this trend is overvaluing tall wide receivers.

It’s too early to grade receivers from the 2012 or 2013 classes, so let’s look at all receivers drafted in the first round between 2000 and 2011. There were 21 receivers drafted who were 6’3 or taller, compared to just 14 receivers drafted who stood six feet tall or shorter. On average, these taller receivers were drafted with the 13th pick in the draft, while the set of short receivers were selected, on average, with the 21st pick.

So we would expect the taller receivers to be better players, since they were drafted eight spots higher. But that wasn’t really the case. Both sets of players produced nearly identical receiving yards averages:

Type
Rookie
Year 2
Year 3
Short535669709
Tall567676720

Taller wide receivers have fared ever so slightly better than shorter receivers. But once you factor in draft position, that edge disappears. If you look at the ten highest drafted “short” receivers, they still were drafted later (on average, 17th overall) than the average “tall” receiver. But their three-year receiving yards line is better, reading 563-694-790. In other words, I don’t see evidence to indicate that shorter receivers, once taking draft position into account, are worse than taller receivers. If anything, the evidence points the other way, suggesting that talent evaluators are more comfortable “reaching” for a taller player who isn’t quite as good. Players like Santana Moss, Lee Evans, Percy Harvin, and Jeremy Maclin were very productive shorter picks; for some reason, it’s easy for some folks to forget the success of those shorter receivers, and also forget the failures of taller players like Charles Rogers, Mike Williams, Jonathan Baldwin, Sylvester Morris, David Terrell, Michael Jenkins, Reggie Williams, and Matt Jones.

But that’s just one way of answering the question. What I did next was run a regression using draft value using the values from my Draft Value Chart and height to predict success. If the draft was truly efficient — i.e., if height was properly being incorporated into a player’s draft position–then adding height to the regression would be useless. But if height was being improperly valued by NFL decision makers, the regression would tell us that, too.

To measure success, I used True Receiving Yards by players in their first five seasons. I jointly developed True Receiving Yards with Neil Paine (now of 538 fame), and you can read the background about it here and here.

The basic explanation is that TRY adjusts receiver numbers for era and combines receptions, receiving yards, and receiving touchdowns into one number, and adjusts for the volume of each team’s passing attack. The end result is one number that looks like receiving yards: Antonio Brown, AJ Green, Josh Gordon, Calvin Johnson, Anquan Boldin, and Demaryius Thomas all had between 1100 and 1200 TRY last year.

First, I had to isolate a sample of receivers to analyze. I decided to take 20 years of NFL drafts, looking at all players drafted between 1990 and 2009 who played in an NFL game, and their number of TRYs in their first five seasons. (Note: As will become clear at the end of this post, I have little reason to think this is an issue. But technically, I should note that I am only looking at drafted wide receivers who actually played in an NFL game. So if, for example, height is disproportionately linked to players who are drafted but fail to make it to an NFL game, that would be important to know but would be ignored in this analysis.)

To give you a sense of what type of players TRY likes, here are the top 10 leaders (in order) in True Receiving Yards accumulated during their first five seasons among players drafted between 1990 and 2009:

Randy Moss
Torry Holt
Marvin Harrison
Larry Fitzgerald
Chad Johnson
Calvin Johnson
Keyshawn Johnson
Anquan Boldin
Herman Moore
Andre Johnson

First, I ran a regression using Draft Pick Value as my sole input and True Receiving Yards as my output. The best-fit formula was:

TRY through five years = 348 + 131.3 * Draft Pick Value

That doesn’t mean much in the abstract, so let’s use an example. Keyshawn Johnson was the first pick in the draft, which gives him a draft value of 34.6. This formula projected Johnson to have 4,890 TRY through five years. In reality, he had 4,838. The R^2 in the regression was 0.60, which is pretty strong: It means draft pick is pretty strongly tied to wide receiver production, a sign that the market is pretty efficient.

Then I re-ran the formula using draft pick value *and* height as my inputs. As it turns out, the height variable was completely meaningless. The R^2 remained at 0.60, and the coefficient on the height variable was not close to significant (p=0.53) despite a large sample of 543 players.

In other words, NFL GMs were properly valuing height in the draft during this period.

In case you’re curious, the 15 biggest “overachievers” as far as TRY relative to draft position were, in order: Marques Colston, Santana Moss, Brandon Marshall, Darrell Jackson, Terrell Owens, Anquan Boldin, Antonio Freeman, Chad Johnson, Coles, Mike Wallace, Greg Jennings, Chris Chambers, Marvin Harrison, Hines Ward, and Steve Johnson.

In this sample, about 50% of the players were taller than 6-0, and only about 30% of the receivers were 5-11 or shorter. We shouldn’t necessarily expect to see a bunch of short overachievers, but I’m convinced that height was properly valued by NFL teams in the draft at least over this 20-year period. There may be fewer star receivers who are short, but that’s only because there are fewer star receiver prospects who are short. Once an NFL team puts a high grade on a short prospect, that’s pretty much all we need to know.

Of the 33 players drafted in the top 15, just one-third of them were six feet or shorter. As a group, there were a couple of big overachievers (Torry Holt, Lee Evans), some other players who did very well (Joey Galloway, Terry Glenn, and Donte Stallworth), and a few big busts (Desmond Howard, Ted Ginn, Troy Edwards, and Peter Warrick). Ike Hilliard and Mike Pritchard round out the group. But I see nothing to indicate that short receivers who are highly drafted do any worse than tall receivers who are highly drafted. It’s just that usually, the taller receiver is drafted earlier.
wr draft 2000 2013 ht

Waldman: Why the Exceptional is Valuable

Chase’s analysis echoes what I have heard from those with NFL analytics backgrounds: There are too many variables to consider with raw stats to indicate that big receivers are inherently better than small receivers and there are viable archetypes of the effective small receiver.

What concerns me about the attempts to pigeonhole player evaluation into narrower physical parameters is that if taken too far one might as well replace the word “talent” in the phrase “talent evaluation” and use “athletic” or “physical” in its place. I may be wrong, but I get the sense that some of these Stats Ministers–intentionally or otherwise–dislike the exceptional when it comes to human nature. They’re seeking a way to make scouting a plain of square holes where the square pegs fit neatly into each place.

The problem with this philosophy is that once a concept, strategy, or view becomes the “right way” it evolves into the standard convention. Once it becomes conventional, it’s considered “safe.” However this is not true in the arena of competition. If you’re seeking the conventional, you’ve limited the possibilities of finding and creating environments for the exceptional to grow.

Many players who didn’t match the ideal size for their positions and had success were difference makers on winning teams–often Super Bowl Champions. I’d argue that exceptions to the rule that succeed are often drivers of excellence:

  • Russell Wilson didn’t meet the faulty “data backed” physical prototypes for quarterback and picking this exception to the rule in the third round earned them exceptional savings to acquire or keep other players for a Super Bowl run.
  • Rod Smith was too short, too slow, a rookie at 25, and not even drafted. But like a lot of his peers I mentioned above, his production was a huge factor for his team becoming a contender. The fact he was the exception to the rule freed Denver to acquire other pieces to the puzzle.
  • Joe Montana was too small, threw a wobbly ball, and was a third-round pick who was more of a point guard than full-fledged pocket passer, but he was just the type of player Bill Walsh was seeking in an offense that changed the entire course of the game. But at the time, the west coast offense was the exception to the rule that turned the league upside down.
  • Buddy Ryan and the Bears drafted a bunch of defenders that didn’t meet physical prototypes for traditional roles in a 4-3, but the 46 defense took Chicago to Super Bowl dominance.
  • Drew Brees, Darren Sproles, and Marques Colston were exceptions to the rule. The Saints offense has been the driver for this team’s playoff and Super Bowl appearances.

I could name more, but the point isn’t to list every player. Why should I? Players who become top starters in the NFL are by very definition the exception to the rule. The only thing height gives a wide receiver is potential position on a target due to wing span, but it doesn’t help hand-eye coordination, body position, route running, comfort with physical contact, and understanding of a defense.

There are also smaller players with good arm length, leaping ability, quickness, and strength to earn similar, if not better position on a target. Even when the smaller receivers lack the same caliber of physical measurements as the bigger players, if they possess all of the other traits of a good receiver that these big athletes lack then size doesn’t matter.

There are legitimate archetypes for smaller, quick receivers with change of direction. However, there are social biases with these correlations that filter out players from the earliest stages of the game. These biases include the idea that the vast majority of these types of players are in the highest levels of football so anything different should be discouraged at the high school and college level–think white wide receivers, running backs, and cornerbacks as examples.

Players who succeed in defying these social biases and also possess the skill and persistence to overcome them. I’ve shown this video before, but physicist Neil deGrasse Tyson makes a strong point against “data backed” arguments of this nature when he answered a question posed about the small number of female and black scientists in the world. Harvard President Lawrence Summers hazarded a guess that it was genetics. Tyson’s answer is a great example why correlation isn’t causation.

The greatest irony about this specific crowd of data zealots is that they are often the first to complain about coaching tendencies that have same biases.

Maybe rookie receivers with the dimensions of Paul Richardson – or for that matter Jeremy Gallon or Odell Beckham – don’t become productive fantasy options or football players as often as bigger players based on correlating data. However, pointing to past history and scoffing at the wisdom of making an investment is like stating that it was a fact in the 15th century that dragons lie at the edge of the flat world we live in.

If you’re going to avoid investing in a player–or encourage others to do so–use good reasoning. Looking at the data is helpful, but the NFL isn’t a perfect data set. There are some data analysts writing about football that derive ideas reliant on a lot of highly fit equations that don’t work in a real world situation. However, they expect perfection and it’s not going to happen. They also behave as if data only tells the truth–and when that data lacks a fit, context, or proper application, it’s a little scary.

I want to see analytics succeed in the NFL, but like film study it’s not the answer. These two areas–when executed well–can contribute to the answer. However, the NFL–beyond some individual cases–hasn’t made significant advances in either area.

I suppose when you have a monopoly in the marketplace combined with a socialistic system for spreading the wealth owners don’t have significant motivation to become innovative with player evaluation. If they did, they’d be spending more money on making these processes rather than cycling through coaches and GMs every 3-5 years.

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Gordon smoked the defensive back on this play

Gordon smoked the defensive back on this play.

Josh Gordon led the league with 1,646 receiving yards last year. That’s impressive: perhaps even more impressive is that he did it on “only” 159 targets, meaning he averaged 10.35 yards per target.1 But the most impressive part, of course, was that he did it for the Browns. You know, the Browns, quarterbacked by a three-headed monster of Jason Campbell, Brandon Weeden, and Brian Hoyer, each of whom managed to average a around the same mediocre 6.4 yards per attempt.

Here’s another way to think of it. While Jordan Cameron was somewhat efficient (7.7 yards per target), the other three Browns to finish in the top five in Cleveland targets were Greg Little (4.7 yards per target), Chris Ogbonnaya (4.6), and Davone Bess (4.2!). And here’s yet another way to think of it: the Browns threw 681 passes last year and gained 4,372 passing yards. But 1,646 of those yards came on the 159 passes intended for Gordon. Remove those plays, and Cleveland averaged just 5.22 yards per pass attempt on passes to all other Browns last year.

That means Cleveland averaged 5.13 more yards per target on passes to Gordon in 2013 than on passes to everyone else. That’s insane, particularly over 159 targets. How insane? If we multiply those two numbers, we get a “value relative to teammates” metric: Gordon gained 816 more yards on his targets than the other Browns averaged per target. Now, in the abstract, maybe 816 doesn’t mean much to you. But it’s the most of any player since at least 1999. The table below shows the top 75 wide receivers in value relative to teammates: the columns should be self-explanatory, and the “ROT Y/A” shows the yards per attempt on passes to the rest of the team. As always, it’s fully sortable and searchable; by default, it displays only the top 25 receivers, but you can switch that by clicking on the dropdown box to the left. [click to continue…]

  1. That’s the most of any receiver with over 130 targets. It’s the second most among players with 100 targets, behind DeSean Jackson‘s 10.6 average on 126 targets. It’s the third most among players with more than 60 targets, behind Jackson and Doug Baldwin (10.7, 73). And it’s the fourth most among players with at least 40 targets, behind Jackson, Baldwin, and Kenny Stills (12.8, 50). []
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Analyzing the leaders in targets in 2013

Comparing wide receivers across teams is tricky. Pierre Garcon led the NFL in targets,1 but that’s partially because Washington didn’t have much help at wide receiver.2 Vincent Jackson was 2nd in percentage of team targets (we’ll get to who was first in a few minutes) for a similar reason: Jackson is a very good receiver, but Tampa Bay had limited weapons in 2014.3 At least in theory, the high target numbers for Garcon and Jackson should be considered in light of the fact that both teams had below-average passing offenses.

The flip side of that coin is a player like Demaryius Thomas. In 2012, while “competing” with another very good receiver in Eric Decker, Thomas saw 24.2% of Denver targets.  Last year, with the addition of Wes Welker and a breakout season from Julius Thomas, Thomas saw just 21.2% of Broncos targets. But the team’s passing game was better, so arguably Thomas should receive a “bump” in his target percentage because he played for a great offense.

That’s just in theory. The unspoken elephant in the analysis is the quarterback. It’s not just a player’s supporting cast of weapons that determines whether his team has a good or bad passing attack: Thomas obviously benefited greatly from playing with Peyton Manning, too. Regular readers may recall that last year, for each team’s leader in targets, I compared their target percentage (defined as targets divided by all team targets) to their team’s passing efficiency (defined by Adjusted Net Yards per Attempt). I thought it would be fun to perform the analysis again, even if it may make more sense in theory than in practice. Take a look: the Y-axis shows percentage of team targets, and the X-axis respects Team ANY/A. In theory, the best WR1s should be up and to the right, with the worst WR1s (or tight ends masquerading as WR1s) in the bottom left corner of the chart.

[click to continue…]

  1. All target data comes courtesy of Footballguys.com. []
  2. And in the offseason, Washington signed DeSean Jackson and Andre Roberts []
  3. And in the 2014 NFL Draft, the Bucs added Texas A&M wide receiver Mike Evans and Washington tight end Austin Seferian-Jenkins. []
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Over the last three years, Calvin Johnson has 5,137 receiving yards in 46 games.  That’s an average of 111.7 receiving yards per game, the most by any player over a three-year stretch in NFL history.  That mark comes with a bit of an asterisk, of course, as the Lions have attempted 2,040 passes since the start of the 2011 season, also an NFL record; that’s why I like using True Receiving Yards and various other WR Ranking Systems rather than just raw receiving yards.

But hey, trivia is trivia, and Johnson is the current record holder.  But prior to 2013, do you know who held the record for receiving yards per game over a three-year stretch? The answer is not Jerry Rice, or else this would be a really lame trivia question.  Rice averaged 101.0 receiving yards per game from 1993 to 1995, and is one of just three players to average over 100 receiving yards per game for a three-year stretch.  Megatron also averaged 101.4 receiving yards per game from 2010 to 2012, but he only became the 3-year king after the conclusion of the 2013 season.

Trivia hint 1 Show


Trivia hint 2 Show


Trivia hint 3 Show


Click 'Show' for the Answer Show


I suspect you’ll also be surprised to see who would is number 4 on the list of most receiving yards per game over a three-year span (counting each player only once, of course).

Trivia hint 1 Show


Trivia hint 2 Show


Trivia hint 3 Show


Click 'Show' for the Answer Show
[click to continue…]

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Green is poised for another monster year

Green is poised for another monster year.

Last year, at Footballguys.com, I looked at the best starting point for wide receiver projections. Well, I’ve re-run the numbers and come up with the best starting point for wide receiver projections in 2014.

The general philosophy is that receiving yards can be re-written using the following formula:

Receiving yards = (Receiving Yards/Target) x (Targets/Team_Pass_Att) x Team_Pass_Att.

Since each of those variables regress to the mean in different ways, we can get a more accurate projection of future receiving yards by projecting each of those three variables than by simply looking at past receiving yards. For example, here are the best fit formulas for each of those metrics:

Future Pass Attempts = 36 + (450 x Pass_Attempts/Play) + (0.255 x Offensive Plays)

Future Percentage of Targets = 6.2% + 71.3% x Past Percentage of Targets

Future Yards/Target = 5.5 + 0.29 x Past Yards/Targets

If you take a look at the three coefficients, the number of offensive plays run from year to year and the yards per target averages are not very sticky; both have coefficients of less than 0.3, which indicates a significant amount of regression to the mean. Meanwhile, percentage of targets is much, much sticker, at 71%.1

As a result, this regression really likes players like A.J. Green (5th in receiving yards in 2013, projected to be 1st in 2014), Andre Johnson (7th, 2nd) and Vincent Jackson (14th, 6th). To find out who else this metric likes and dislikes, and for a more thorough analysis, you can read the full article here.

  1. Pass attempts per play can’t be analyzed the same way, at least using the formulas presented here, but it does look as though the pass-heaviness of an offense is moderately sticky, too. And that would be even more true if we accounted for game scripts, I suppose. []
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Turnover Among Targets, Part II

Yesterday, I looked at team turnover in the passing game for every team in 2013. You can review the pretty complicated1 formula in that post, but the short version is to give each player credit for the lower of two values: his percentage of team receiving yards in Year N and his percentage of team yards in Year N-1. Today, I use that same concept to analyze team passing for every year since the merger.

And the team with the greatest receiving turnover in NFL history (even including pre-1970 teams) is the 1989 Detroit Lions. Take a look at the players who caught passes for Detroit in 1988:

Receiving
No. Age Pos G GS Rec Yds Y/R TD Y/G
82 Pete Mandley 27 PR/WR 15 14 44 617 14.0 4 41.1
33 Garry James 25 RB 16 16 39 382 9.8 2 23.9
80 Carl Bland 27 wr 16 2 21 307 14.6 2 19.2
89 Jeff Chadwick 28 WR 10 8 20 304 15.2 3 30.4
83 Gary Lee 23 KR/wr 14 6 22 261 11.9 1 18.6
30 James Jones 27 FB 14 14 29 259 8.9 0 18.5
87 Pat Carter 22 TE 15 14 13 145 11.2 0 9.7
49 Tony Paige 26 rb 16 2 11 100 9.1 0 6.3
81 Stephen Starring 27 6 0 5 89 17.8 0 14.8
38 Scott Williams 26 11 0 3 46 15.3 0 4.2
81 Mark Lewis 27 te 3 3 3 32 10.7 1 10.7
41 Paco Craig 23 8 0 2 29 14.5 0 3.6
26 Carl Painter 24 12 0 1 1 1.0 0 0.1
Team Total 26.2 16 213 2572 12.1 13 160.8

[click to continue…]

  1. While I admit to it being complicated, I think the added value in accuracy is worth the added layer of complexity; frankly, I can’t think of a simple way to calculate turnover that really captures what analysts value. []
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Turnover Among Targets, Part I

Cam may need to really be Superman in 2014

Cam may need to really be Superman in 2014.

The Carolina Panthers have experienced a lot of turnover this offseason. Steve Smith (Baltimore), Ted Ginn (Arizona), Domenik Hixon (Chicago), and Brandon LaFell (New England) are all gone. Those four players were the only wide receivers to catch a pass for Carolina in 2013, and they accounted for 59% of the Panthers receiving yards. last year. What does this mean for Cam Newton? Last August, a couple of star quarterbacks appeared to be going through some similarly significant turnover among their targets.

Tom Brady lost four of his top five targets from 2012 and the fifth was Rob Gronkowski; in retrospect, most people underestimated how big of an impact this would have on Brady’s numbers. Meanwhile, Ben Roethlisberger’s receivers were a big question mark entering the season, but a monster year from Antonio Brown prevented Roethlisberger’s numbers from tanking. As it turned out, Roethlisberger didn’t wind up having much turnover, but the quarterback who experienced the second-most turnover wound up winning the Comeback Player of the Year award.

For Carolina, I think some of the departures have been overblown. The defense should again be one of the best in the NFL, and it’s not as though the passing game was outstanding last year. Greg Olsen led the team in receptions, receiving yards, and receiving touchdowns last year, and he’ll be back in 2014. In addition, the Panthers averaged 7.4 yards per attempt on passes to Greg Olsen last year and 7.1 yards per attempt (the league average) on passes to all other players. Carolina signed Jerricho Cotchery, Jason Avant, Tiquan Underwood, and Joe Webb, should draft a receiver or two in May, and has a potential sleeper in Marvin McNutt. I think they’ll be just fine, mostly because that’s all the passing game was last year.

Since it’s still a bit early to figure out exactly how the Panthers passing game will look in 2014, I thought we could use some time this weekend to review some history. Which teams have experienced the most turnover among their targets? And how do we even measure such a thing? [click to continue…]

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In January, I calculated the AV-adjusted age of every team in 2013. In February, I looked at the production-adjusted height for each team’s receivers. Today, we combine those two ideas, and see which teams had the youngest and oldest set of targets.

To calculate the average receiving age of each team, I calculated a weighted average of the age of each player on that team, weighted by their percentage of team receiving yards. For example, Anquan Boldin caught 36.7% of all San Francisco receiving yards, and he was 32.9 years old as of September 1, 2013. Therefore, his age counts for 36.7% of the 49ers’ average receiving age. Vernon Davis, who was 29.6 on 9/1/13, caught 26.5% of the team’s receiving yards last year, so his age matters more than all other 49ers but less than Boldin’s. The table below shows the average age for each team’s receivers (which includes tight ends and running backs) in 2013, along with the percentage of team receiving yards and age as of 9/1/13 for each team’s top four receiving leaders: [click to continue…]

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Megatron at his best

Megatron at his best.

In his seven-year career, Calvin Johnson has already recorded 9,328 receiving yards. And for those curious about these sorts of things, he’s the career leader in receiving yards per game at 88.0, too. But Johnson has also benefited greatly from playing on teams that have thrown a weighted average of 635 pass attempts per season.

What is a weighted average of team pass attempts? I’m defining it as an average of pass attempts per season weighted by the number of receiving yards by that player. Why use that instead of a simple average? When thinking about whether a receiver played for a run-heavy or pass-happy team, we tend to think of that receiver during his peak years. If he caught 10 passes for 150 yards as a rookie on a very pass-happy team, that should not be given the same weight as the number of pass attempts his team produced in his best season. For example, here is how I derived the 635 attempt number for Megatron.

Twenty-one percent of his career receiving yards came in 2012, when Detroit passed 740 times (excluding sacks). Therefore, 21% of his team pass attempts average comes from that season, while 18% comes from his 2011 season, 16% from his 2013 season, and so on. In the table below, the far right column shows how we get to that 635 figure: by multiplying in each season the percentage of career receiving yards recorded by him in that season by Detroit’s Team Pass Attempts.

Yr
RecYd
TPA
Perc
TM * %
2013149263416%101.4
2012196474021.1%155.8
2011168166618%120
2010112063312%76
200998458510.5%61.7
2008133150914.3%72.6
20077565878.1%47.6
Total93284354100%635.2

There are 121 players with 7,000 career receiving yards. Unsurprisingly, Johnson has the highest weighted average number of team pass attempts, which must be recognized when fawning over his great raw totals. Marques Colston is just a hair behind Johnson, but no other player has an average of 600+ team pass attempts.

The table below contains data for all 121 players (by default, the table displays only the top 25, but you can change that). Here’s how to read it, starting with the GOAT: Jerry Rice ranks first in career receiving yards, and he played from 1985 to 2004. Rice played in 303 games, gained 22,895 receiving yards, and his teams threw a weighted average of 547 passes per season. Among these 121 players, that rank Rice as playing for the 25th highest or most pass-happy team. Rice also averaged 76 receiving yards per game, which ranks 5th among this group. [click to continue…]

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How will DeSean Jackson age?

DeSean Jackson crosses the goal line before discarding the ball

DeSean Jackson crosses the goal line before discarding the ball.

If you believe the rumors, the Eagles are desperately trying to trade wide receiver DeSean Jackson; absent an eligible suitor, and Philadelphia may even cut the three-time Pro Bowler. This is a pretty weird situation; what’s even weirder is how few tangible reasons have been given as to why the Eagles desire to remove him from the roster.

Jackson has a cap hit of $12.75M this year and $12M in each of the next two seasons; that’s obviously a significant amount, and I don’t doubt that Philadelphia feels a bit of buyer’s remorse on that contract. But reading the tea leaves indicates that a high salary cap figure is only part of the issue; unfortunately, without knowing the other reasons, it’s impossible to suggest whether a team would be wise to trade for him. This might be a Randy Moss-to-New England situation, or it could just as easily be a Santonio Holmes-to-the-Jets disaster. [click to continue…]

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Wazzup????

Wazzup????

Some quarterbacks and wide receivers just go together. Peyton Manning and Marvin Harrison. Dan Marino and Mark Clayton and Mark Duper. Joe Namath and Don Maynard. John Hadl and Lance Alworth. But quarterbacks play with lots of receivers, and receivers generally play with several quarterbacks. We don’t remember most combinations, but that doesn’t mean they were all unproductive. So I thought it might be interesting to look at every wide receiver since 1950, find his best single season in receiving yards, and record who was his team’s primary quarterback that season.

Jerry Rice’s best year came with Steve Young, not Joe Montana. Randy Moss set the touchdown record with Tom Brady, but his best year in receiving yards was with Daunte Culpepper. Lynn Swann’s best year was with Terry Bradshaw, but John Stallworth’s top season in receiving yards came with Mark Malone. James Lofton’s best season was with Lynn Dickey, Isaac Bruce’s best year was with Chris Miller, Torry Holt’s top season came with Marc Bulger, and Tim Brown’s top year was with Jeff George.

This is little more than random trivia, but this site does not have aspirations for March content higher than random trivia. In unsurprising news, 25 different players had their best season in receiving yards (minimum 300 receiving yards) while playing with Brett Favre. That includes a host of Packers, but also a couple of Jets and Vikings, too (including one future Hall of Famer).

After Favre, Marino is next with 22 players, and he’s followed by Manning and Fran Tarkenton (20). From that group, I suspect that Tarkenton might surprise some folks. That is, unless they realized that he was the career leader in passing yards when he retired and played for five years with the Giants and thirteen with Minnesota.

The table below shows every quarterback who was responsible for the peak receiving yards season of at least five different receivers (subject to the 300 yard minimum threshold). For each quarterback, I’ve also listed all of his receivers. [click to continue…]

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Meaningless receiving yards

Shorts makes a meaningful catch

Shorts makes a meaningful catch.

Which player led the league in meaningless receiving yards last year? Wait, what are meaningless receiving yards?

I am defining a meaningless receiving yard as one where:

  • On third or fourth down, a player gained fewer yards than necessary for the first down.
  • The receiving yard(s) came in a loss and when the player’s team trailed by at least 28 points.
  • The receiving yard(s) came in a loss and when the player’s team trailed by at least 21 points with fewer than 15 minutes remaining.
  • The receiving yard(s) came in a loss and when the player’s team trailed by at least 14 points with fewer than 8 minutes remaining.
  • The receiving yard(s) came in a loss and when the player’s team trailed by at least 9 points with fewer than 3 minutes remaining.

This definition is not perfect — Le’Veon Bell had a 29-yard reception on 3rd-and-30 last season against the Patriots, and then rushed for a first down on 4th-and-1 — but I think it gets us close enough to perfect that I feel comfortable using it. The results aren’t too surprising — two Jaguars ranked in the top three, separated by the player who led the league in receiving yards — but that doesn’t have to be the end of the analysis. [click to continue…]

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Jones catches another bomb

Jones catches another bomb.

In November, I noted that Chris Johnson was the career leader in average length of rushing touchdown. Since then, he’s actually dropped to number two, as his six rushing touchdowns covered “only” 84 yards in November and December. But what about the career leader in average length of receiving touchdown?

That title belongs to former Giants wide receiver Homer Jones.  A star in the late ’60s, 19 of Jones’ 36 career touchdowns went for 50 or more yards. The table below shows all 413 players to record at least 35 receiving touchdowns (including the postseason) from 1940 to 2013.  While Jones leads in average touchdown length, I think it makes more sense to sort the list by median touchdown length, although that doesn’t matter much for Jones.  For each player listed, I’ve included both their average and median touchdown length, the years they played, and a best guess at their primary position.  The table by default shows 50 entries, but you can change that; in addition, the table is fully sortable and searchable. [click to continue…]

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How Have Previous Eric Deckers Fared?

Decker learns how to run a Papa Johns franchise

Decker learns how to run a Papa John's franchise.

Just a few minutes before press time, the Jets signed Eric Decker, generally considered the best wide receiver available in free agency. But for weeks, the #hotsportstake on Eric Decker has been pretty clear: he’s a product of playing with Peyton Manning and alongside Demaryius Thomas (and Wes Welker and Julius Thomas). It would take you awhile to find a discussion of Decker’s free agent candidacy without hearing the phrase “he’s not a number one wide receiver.” This sort of analysis is obviously lazy, but it’s also a fascinating counter to an unmade argument. In the same way that Joe Namath is now an underrated quarterback, it’s fair to wonder: if so many people are calling Decker overrated, how can he be overrated?

In today’s post, I want to look at how the previous ten Eric Deckers have fared. What’s an Eric Decker? A gritty hard working player who runs great routes receiver who met each of the following criteria:

  • Finished as a top-20 fantasy wide receiver (with 1 point per 10 yards, 6 points per touchdown, 0.5 points per reception as the scoring system) in Year N
  • Was not his team’s top fantasy wide receiver in Year N
  • Played for a different team in Year N+1

[click to continue…]

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Brown was number one in 2013

Brown was number one in 2013.

Wide receiver is a notoriously difficult position to analyze using statistics. Era adjustments are arguably more important here than at any other position, but even within the same season it is not easy to compare wide receivers. Most people, myself included, would probably say that Josh Gordon or Calvin Johnson was the best wide receiver in football in 2013. Gordon, after all, led the NFL in receiving yards despite missing two games, while Johnson is well, Megatron. If you place more emphasis on other metrics, you would be interested to know that Pierre Garcon led the NFL in receptions, while Jimmy Graham led all players in receiving touchdowns (and Demaryius Thomas led all wide receivers in that statistic).

But, as you can tell from the title of this post, it was Pittsburgh’s Antonio Brown who led all players in True Receiving Yards. Regular readers are familiar with the concept of True Receiving Yards, but walking through the system with both Brown and Gordon will serve as a useful reminder.

Let’s start by recognizing that Brown’s season was special in its own right: he became the first player to record 50 receiving yards in 16 different games in a single season. He also finished 2nd in both receptions and receiving yards, so it doesn’t take much processing through the True Receiving Yards machine to vault Brown into first place. He ended the year with a 110-1499-8 stat line, while Gordon finished 2013 with 87 catches for 1,646 yards and nine scores.

The first step in the True Receiving Yards calculation is to convert each player’s stat line into a single statistic, Adjusted Catch Yards. By giving each player 5 yards for each reception and 20 yards for each touchdown, Brown is credited with 2,209 Adjusted Catch Yards and Gordon 2,261, making them the top two players in 2013 by that metric. [click to continue…]

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Yesterday, I looked at the average height of the receivers of each team in the NFL in 2013. Today, we’ll use the same method but look at every NFL team since 1950. As it turns out, the 2013 Bears rank as one of the third tallest group of receivers in history. The only thing Chicago didn’t have was a 6’8 Harold Carmichael.

The table below shows the 200 teams with the tallest average receivers since 1950. A couple of famous teams are at the top of the list, including the 2007 Super Bowl champion Giants. Eli Manning will never be confused with a hyper-accurate quarterback, so it was smart of the Giants to surround him with tall targets like Plaxico Burress, Amani Toomer, and Jeremy Shockey. The 1998-2000 Minnesota Vikings with Randy Moss, Cris Carter, Jake Reed, and Andrew Glover, all made the top 25. And before Chicago had Brandon Marshall, Alshon Jeffery and Martellus Bennett, the Bears had another trio of monster wide receivers: Harlon Hill, Bill McColl, and Jim Dooley. [click to continue…]

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Chicago's twin towers

Chicago's twin towers.

In Marc Trestman’s first year as head coach, the Chicago Bears quickly turned into one of the most explosive offenses in football. Even after losing Jay Cutler, backup quarterback Josh McCown came in and seamlessly executed Trestman’s offense.

Chicago ranked in the top 5 in passing yards, passing touchdowns, net yards per pass attempt and points, an impressive accomplishment for a franchise that seemed permanently stuck in 1958. And while the Bears have a lot of talented offensive players, the first thing that stands out to you when watching Chicago is that they look like a basketball team. I don’t write that because of the way the team throws the ball, but because the receivers actually look like basketball players. Chicago’s top three receivers are Brandon Marshall and Alshon Jeffery (each 6’4) and tight end Martellus Bennett (6’7): those are easy targets to spot for whomever is at quarterback for the Bears.

I calculated the average receiving height of each team during the 2013 NFL season by taking a weighted average of the height of each player on each team, weighted by their percentage of team receiving yards. For example, Jeffery caught 31.9% of all Chicago receiving yards, so his 76 inches counts for 31.9% of Chicago’s average height.  Bennett gained 17.1% of the team’s receiving yards, so his 79 inches counts for 17.1% of Chicago’s average height, and so on. The table below shows the average height for each team in 2013, along with the percentage of team receiving yards and height for each team’s top four receiving leaders: [click to continue…]

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Harrison actually caught this pass.

Harrison actually caught this pass.

In a couple of weeks, the newest class of the Pro Football Hall of Fame will be announced. Only five modern-era wide receivers have been selected enshrinement on their first ballot: Jerry Rice, Paul Warfield, Steve Largent, Raymond Berry, and Lance Alworth. This year, in his first year of eligibility, Marvin Harrison is one of 15 finalists for the Pro Football Hall of Fame. I suspect the majority will view Harrison as a first-ballot Hall of Famer, but there are a few minority voices who disagree.

As best as I can surmise, there are three primary reasons why Harrison shouldn’t be selected in 2014. Two of those reasons can be addressed rather easily, but let’s start with the more complicated issue to analyze.

Harrison’s numbers are inflated because of Peyton Manning

Jerry Rice is the greatest wide receiver of all time. Rice was probably better at his position than any football player has ever been at theirs. Rice might be the most dominant sportsman of his generation. Rice probably isn’t in the discussion of greatest athletes in the history of mankind, which is about the only negative thing I’m willing to say about him. All of that is important background to say, being worse than Jerry Rice is not a negative, but just a fact of life as a wide receiver.
[click to continue…]

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Josh Gordon sets two-game receiving record

Cleveland’s Josh Gordon caught 14 passes for 237 yards and a touchdown against the Steelers last week. Against the Jaguars this afternoon, Gordon caught 10 passes for 261 yards and two scores. In the process, he became the first player to ever record back-to-back 200+ yard receiving games, and set an NFL record with 498 receiving yards in two games.

The table below shows the 53 players to record 350 receiving yards in back-to-back games from 1960 to 2012. Until this year, Houston’s Andre Johnson had the modern record for receiving yards in consecutive games, set just last season. Then Calvin Johnson had 484 yards in two straight games, setting a record that stood for all of five weeks.

Player
Team
year_id
rec yds
rec
rectd
Game 1 Box
Game 2 Box
Andre JohnsonHOU2012461231BoxscoreBoxscore
Calvin JohnsonDET2011455233BoxscoreBoxscore
Chad JohnsonCIN2006450175BoxscoreBoxscore
John TaylorSFO1989448163BoxscoreBoxscore
Jerry RiceSFO1995442263BoxscoreBoxscore
Miles AustinDAL2009421164BoxscoreBoxscore
Flipper AndersonRAM1989413191BoxscoreBoxscore
Terrell OwensSFO2000412262BoxscoreBoxscore
Jerry RiceSFO1995410203BoxscoreBoxscore
Stephone PaigeKAN1986402132BoxscoreBoxscore
Frank ClarkeDAL1962400145BoxscoreBoxscore
Sonny RandleSTL1962400193BoxscoreBoxscore
Don MaynardNYJ1968394162BoxscoreBoxscore
Drew BennettTEN2004393255BoxscoreBoxscore
Lance AlworthSDG1963390182BoxscoreBoxscore
Andre JohnsonHOU2009389202BoxscoreBoxscore
Eric MouldsBUF1999387191BoxscoreBoxscore
Wes ChandlerSDG1982385175BoxscoreBoxscore
Flipper AndersonRAM1989384171BoxscoreBoxscore
Art PowellOAK1964382175BoxscoreBoxscore
Raymond BerryBAL1960381154BoxscoreBoxscore
Charley HenniganHOU1961381171BoxscoreBoxscore
Charley HenniganHOU1961380172BoxscoreBoxscore
Wes ChandlerSDG1982378144BoxscoreBoxscore
Jerry RiceSFO1989378172BoxscoreBoxscore
Wes WelkerNWE2011375253BoxscoreBoxscore
Torry HoltSTL2003374182BoxscoreBoxscore
Qadry IsmailBAL1999373134BoxscoreBoxscore
Eric MouldsBUF1998373143BoxscoreBoxscore
Glenn BassBUF1964372142BoxscoreBoxscore
Isaac BruceSTL1995372184BoxscoreBoxscore
Qadry IsmailBAL1999371113BoxscoreBoxscore
Fred BiletnikoffOAK1968370144BoxscoreBoxscore
Webster SlaughterCLE1989370123BoxscoreBoxscore
James LoftonGNB1984368163BoxscoreBoxscore
Lance RentzelDAL1967368183BoxscoreBoxscore
Isaac BruceSTL1995364192BoxscoreBoxscore
Gary ClarkWAS1986364172BoxscoreBoxscore
James LoftonGNB1984364162BoxscoreBoxscore
Jerry RiceSFO1986360163BoxscoreBoxscore
Chris ChambersMIA2005359233BoxscoreBoxscore
Henry EllardWAS1994359162BoxscoreBoxscore
Del ShofnerNYG1962359171BoxscoreBoxscore
Stephone PaigeKAN1985358113BoxscoreBoxscore
Drew BennettTEN2004357156BoxscoreBoxscore
Charlie JoinerSDG1981357130BoxscoreBoxscore
Lance AlworthSDG1967355152BoxscoreBoxscore
Roy GreenSTL1984355142BoxscoreBoxscore
Pete RetzlaffPHI1965355143BoxscoreBoxscore
Lance AlworthSDG196435393BoxscoreBoxscore
Bill GromanHOU1960353123BoxscoreBoxscore
Jimmy SmithJAX1999352192BoxscoreBoxscore
Calvin JohnsonDET2012350172BoxscoreBoxscore
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Tavon Austin’s Record Setting Day

Fisher is introduced to Tavon Austin

Fisher is introduced to Tavon Austin.

The Tavon Austin breakout game is here. First, the #8 pick in the 2013 draft returned a punt off a bounce 98 yards for a second quarter touchdown. A few minutes later, Kellen Clemens hit him for a 57-yard touchdown pass. With St. Louis up 28-0 in the third quarter, Austin caught an 81-yard touchdown.

The third score made him just the 8th player in NFL history with three touchdowns of 50+ yards in the same game, joining Chris Johnson, Qadry Ismail, Randy Moss, Freddie Solomon, Gale Sayers, Billy Cannon, and Raymond Berry. That also means Austin has 236 yards of touchdowns today, the most of any player since 1970.

In fact, that’s the second most in NFL history. The table below shows all 78 players from 1940 to 2012 who recorded at least 160 yards worth of touchdowns in a single game.
[click to continue…]

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Calvin Johnson And Getting Tackled At the One

Johnson was tackled twice at the 1 against Dallas

Johnson was tackled twice at the 1 against Dallas.

In the last two years, Calvin Johnson has been tackled at the one yard line an incredible seven times. Ronnie Brown is the only other player to record such a dubious feat even four such times since 2012, and Eric Decker, Roddy White, and Tony Gonzalez are the only other players to get tackled on three different receptions just shy of the goal line.

Johnson has the most receptions in the league over that time frame, but Wes Welker is only one catch behind him… and he has just one reception where he was tackled at the one-yard line. Of course, that’s only for data over the last year and a half.

Since 1999, 25 players have had at least seven receptions where they were tackled at the one-yard line. As it turns out, Brian Finneran fantasy owners have been the most unlucky, as Finneran was tackled seven times at the 1-yard line on 238 career receptions.
[click to continue…]

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Cowboys defense know the back of their hands like the back of Megatron's jersey

Cowboys defenders know the back of their hands like the back of Megatron's jersey.

On Sunday, Calvin Johnson picked up 329 receiving yards against the Cowboys, the second most receiving yards in a single game after Flipper Anderson’s 336 yards in 1989 against the Saints. But when I think of the greatest games by a receiver of all time, my mind instantly goes to a performance by Kansas City’s Stephone Paige in a game in December 1985 against the Chargers. Regular readers will recall that this summer, Neil Paine and I developed a statistic known as True Receiving Yards. You can see a list of the leaders in TRY since 1950 here, but today I want to apply that same methodology on the single-game level. After crunching the numbers, Paige comes in at #2, Megatron’s performance comes in at #11, and Anderson is all the way down at #26. Why? How? Glad you asked. And I’ll keep the top spot a secret for now, in case anyone wants to guess.

1) First, we convert receiving yards into Adjusted Catch Yards by giving a five-yard bonus for receptions and a 20-yard bonus for touchdowns. Johnson had 419 ACY against the Cowboys, tied with Jerry Rice (against the ’95 Vikings) for the third highest mark since 1960.  The top spot belongs to Anderson at 431 (and personal favorite Jimmy Smith holds the number two spot for his performance against the 2000 Ravens). Paige — who produced an 8-309-2 stat line — totaled 389 Adjusted Catch Yards.

2) Next, we convert back to receiving yards by multiplying each receiver’s ACY by the league average ratio of receiving yards to Adjusted Catch Yards in that season. The point of using ACY instead of receiving yards is to include things other than receiving yards, but we still want to convert back into receiving yards. In 1985, the ACY/RecYd ratio was 0.66, in ’89 it was 0.66, and through eight weeks, that number is 0.65 in 2013, so not much is changing here. After step two, Anderson is at 286.6 receiving yards, Johnson 270.9 yards, and Paige 258.0 yards.

3) The third step is the pass attempts adjustment. The league average team team this year has averaged 38.7 attempts (including sacks) in 2013, while Matthew Stafford had 49 dropbacks yesterday. This means the Lions passed 26.6% more often than the average team. So what sort of adjustment do we make? In True Receiving Yards version 2.0, we split that number in half. I tried that here, and honestly, the numbers just didn’t look right — the top of the list was almost exclusively players on teams that had 10 or 12 pass attempts in that game. So instead of contracting the difference between pass attempts and league average pass attempts by two, I’m going to do it by three. So Johnson only gets downgraded to 91.1% of his production, or 246.9 yards.

Anderson’s record-breaking performance came in overtime in a game the Rams trailed by 14 entering the fourth quarter. As a result, Jim Everett had 57 dropbacks in a time period when 34.5 attempts was the norm.  So with Los Angeles having 65.3% more attempts than the average team that year, we have to lower Anderson from 286.6 to 224.1.

Paige, meanwhile, goes far in the other direction. The Chiefs took a 35-3 second quarter lead that day — in no small part due to Paige’s touchdown receptions of 56 and 84 yards — so Kansas City was limited to just 24 dropbacks. The average number of dropbacks in ’85 was 35.1, putting the Chiefs at just 68.4% of league average. Therefore, we bump up Paige by 15.4%, vaulting him from 258 yards to 297.9.

4) The final adjustment is the era adjustment. I’m going to use a different way to incorporate era adjustments here, because while passing yards have shot through the roof, the value of a team’s #1 wide receiver has been much less volatile. So I used the following baseline for each year: the number of Adjusted Catch Yards in the Nth best receiving game, when 2N = the number of team games in that season. So in modern times, with 512 games, this means the 256th highest ACY total in that season is the baseline; in 2011 and 2012, that was 135 Adjusted Catch Yards. From 1960 to 2012, the average was 124.3.1

So what we do now is multiply each receiver’s score from step three by the baseline for that year, and divide by 124.3. I will use the same 135 as the baseline for 2013, which brings Megatron to 227. The baseline in ’89 was 130, so Anderson goes to 214.3, and in ’85, the baseline was 125, so Paige only drops to 296.2.

If you’ve made it this far, then maybe I’m not a complete idiot for putting the fine print up front. Without further ado, here are the top 2502 performances since 1960 using this formula:
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  1. Note: I was lazy, and combined the AFL and NFL. I know, I know. []
  2. Note. I excluded two games during the 1987 strike played with replacement players: Anthony Allen had 262 TRY against the Cardinals, and Steve Largent had 260 TRY in Detroit. []
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Receiving WOWY Extended Back to 1950

A WOWY Superstar.

A WOWY Superstar.

Last week, we announced that our True Receiving Yards metric has now been calculated back to 1950, so it’s only fitting that we also compute WOWY (With Or Without You) for all of those receivers as well.

Skip the paragraph after this if you don’t care about the gory mathematical details, and just know that WOWY basically answers the question: “Did a receiver’s quarterbacks play better when they threw a lot to him, or not?”

For the brave souls who care about the calculation: WOWY starts by measuring the difference between a QB’s age-adjusted Relative Adjusted Net Yards Per Attempt in a given season and his combined age-adjusted RANY/A in every other season of his career. This is computed as an average for each team’s QB corps, using a combination of QB dropbacks during the season in question and the rest of his career as the weights (the exact formula is: weight = 1/(1/drpbk_year + 1/drpbk_other)). Finally, for each receiver we compute a weighted career average of the QB WOWY scores for the teams he played on, weighted by his True Receiving Yards in each season.

At any rate, the only players who don’t get a WOWY are those who either debuted before 1950, played with a QB who debuted before 1950, or played with a QB who ever threw to a receiver who debuted before 1950. Here are the career WOWY marks (when applicable), alongside TRY, for every 3,000-TRY receiver whose career started in 1950 or later:

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Brady needs to channel another Tom (Flores) this season

Brady needs to channel another Tom (Flores) this season

As Jason Lisk and I wrote about before the season, Tom Brady and Ben Roethlisberger have become something of the poster children so far this year when it comes to veteran QBs working with inexperienced and otherwise less-than-notable receiving groups. And, lo and behold, each has put up career-low RANY/A marks through 2 games. But how do their receiving corps rank relative to those of other teams so far this year, and how do they stack up historically?

To take a stab at answering these questions, I turned to True Receiving Yards. For each player who debuted in 1950 or later, I computed their Weighted Career True Receiving Yards for every year, as of the previous season, to get a sense of how experienced/accomplished they’d been going into the season in question. Then, I calculated a weighted averaged of those numbers for every receiver on a given team, using TRY during the season in question as the weights. For example, here are the 2013 Patriots receivers:

Player
Age
Debut
TRY
% of Tm
At-the-time WCTRY
Weighted Average560.7
Julian Edelman27200913938%615.7
Danny Amendola2820097220%1541.9
Kenbrell Thompkins2520135615%0.0
Shane Vereen2420114412%110.9
Aaron Dobson2220134312%0.0
Michael Hoomanawanui25201051%278.8
James Develin25201341%0.0

The way to read that is: Julian Edelman has accounted for 38 percent of the Pats’ TRY so far. Going into the season, he had a career Weighted TRY of 615.7, so he contributes to 38% of the 2013 Pats’ weighted average with his 615.7 previous career weighted TRY; Danny Amendola contributes to 20% of the team weighted average with his 1541.9 previous career weighted TRY; etc. Multiply each guy’s previous weighted career TRYs by the percentage of the team’s 2013 TRY he contributed, and you get a cumulative weighted average of 560.7 — meaning the average TRY of a 2013 Pats receiver has been gained by a guy who had a previous career weighted TRY of 560.7.

Is that a low number? Well, here are the numbers for all of the 2013 team receiving corps (not including Thursday night’s Eagles-Chiefs tilt), inversely sorted by weighted average (asterisks indicate rookies):

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