In light of the Patriots nearly breaking the NFL record for plays, and the promise of up-tempo offenses in Philadelphia (under Chip Kelly) and Denver (Adam Gase), it’s easy to think that the number of plays run per team is about to reach historic levels. But that seems really unlikely.

The graph below shows the number of plays run per team game for each season since 1950. The total number of plays run is in blue for the NFL; I also added the same data for the AFL in red. As you can see, the number of plays per team game has been relatively steady over the last 64 years, but the high-water marks were the early ’50s and most of the 1980s.

In addition to plays run, the graph also shows:

• The number of rushing plays per team game in green, a number that’s obviously on the decline.
• The number of completions per team game in black, which has risen as the number of runs has declined.
• The number of incomplete passes per team game in orange. Incomplete passes stop the clock, so I thought we might see something interesting there. How’s this for trivia: there were 13.5 incomplete passes per team game in 2012, the same number that existed in 1948! While 1948 is off the graph, you can see that the number of incomplete passes per game has been remarkably consistent throughout NFL history. In fact, the average from 1950 to 2012 is 13.5 incompletions per game, and the league average was 13.5 +/- one incompletion in over 80% of the seasons since 1950.
• The number of sacks per team game is in purple, a number that has also stayed very consistent over time. Only three times since 1950 has the league average been less than two sacks per game or more than three sacks per game.

Last off-season, I produced an exhaustive analysis of fumble recovery rates. With 13 years of play-by-play data at my disposal, I thought it would be worthwhile to take a closer look at interceptions. You can skip to the results section if you like, but let me start with a few disclaimers.

Interceptions are tricky to analyze. Interception rates are very inconsistent from year to year, so much so that completion percentage alone may be a better predictor of future interception rate than actual interception rate. But putting aside randomness, there are two other big factors that determine interception rates: the score in the game and the length of the throw.

Just about every quarterback will throw more interceptions when his team is trailing in the fourth quarter. Situation plays a huge role in football, and that’s true when it comes to interception rates, too. Similarly, quarterbacks are much more likely to be intercepted on deep passes than short ones. One thing I wanted to look at was how much league-wide interception rates varied over a wide range of circumstances.

Unfortunately, there still is a bit of bias in the data. The best quarterbacks are most likely to be winning and the worst quarterbacks are most likely to be losing. That means to the extent that trailing teams throw more interceptions than leading teams, the results are probably slightly overstated. Still, I think getting a sense of the league baseline over hundreds of thousands of throw — even if not evenly distributed — can be a useful exercise.

The Results

From 2000 to 2012, there were 6,689 interceptions thrown. Here’s the breakdown with respect to the points differential (i.e., points scored minus points allowed) for the offensive team immediately before the interception. For example, teams trailing by more than four touchdowns have thrown 110 interceptions over the last 13 regular seasons. That accounts for 1.6% of all interceptions thrown over that time period:
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At Footballguys.com, I explain why fantasy football owners need to understand the concept of regression to the mean. Readers of this blog probably don’t need the long background, but you might enjoy some of the graphs at the end. For example, this is the distribution of yards per carry in Year N and yards per carry in Year N+1:

You can read the full article here.

Over at Footballguys.com, I identified which quarterback statistics are repeatable and which ones are most likely to regress to the mean. I also ran a regression using touchdown length as my input and future touchdowns as my output.

From 1990 to 2011, 188 different quarterbacks started at least 14 games and thrown 300+ passes in one year, and then attempted at least 300 passes for the same team the next season. After analyzing the lengths of each touchdown pass for those quarterbacks, I discovered the following:

• For every one-yard touchdown pass in Year N, expect 0.70 touchdowns in Year N+1
• For every two-to-five-yard touchdown pass in Year N, expect 0.56 touchdowns in Year N+2
• For every six-to-ten-yard touchdown pass in Year N, expect 0.77 touchdowns in Year N+2
• For every 11-to-20-yard touchdown pass in Year N, expect 0.70 touchdowns in Year N+2
• For every 21-to-30-yard touchdown pass in Year N, expect 0.22 touchdowns in Year N+2
• For every 31-to-50-yard touchdown pass in Year N, expect 0.33 touchdowns in Year N+2
• For every 50+ yard touchdown pass in Year N, expect 0.33 touchdowns in Year N+2

If a team throws touchdowns from inside the red zone, that reveals an offensive philosophy that is good for your fantasy quarterback. On the other hand, 21+ yard touchdowns might make the highlight feels, but are very unpredictable from year to year. What does that mean for 2013?

You can view the full article here.

Seven years ago, Doug wrote this post analyzing wide receivers by team receiving yards. That post was overdue for an update for three reasons: (1) it was written seven years ago; (2) Doug only went back to 1978, while we now can go back to 1932; and (3) I think using Adjusted Catch Yards (which gives receivers 5 additional yards for every reception and 20 additional yards for every touchdown) is better than just using receiving yards.

For every year of every receiver’s career, I computed the percentage of his team’s Adjusted Catch Yards that he accounted for. I then averaged together each receiver’s 6 best six seasons according to that metric, and ignored all wide receivers who have played in fewer than six seasons. The results are listed below for the 161 receivers to hit the 25% mark, along with the six years selected for each receiver. As always, you can use the search box to find your favorite receiver, and the table is sortable, too.
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Over at Footballguys.com, I analyzed how the fantasy value of quarterbacks, running backs, wide receivers, and tight ends have changed since 1990. The NFL is a very different beast than it was 23 years ago, but you might be surprised to see what that means for fantasy football. To measure value, I examined the VBD curves for each of the four major positions in fantasy football.

For those unfamiliar with VBD, you can read Joe Bryant’s landmark article here. The guiding principle is that the value of a player is determined not by the number of points he scores but by how much he outscores his peers at his particular position. This means that in a league that starts 12 quarterbacks, each quarterback’s VBD score is the difference between his fantasy points and the fantasy points scored by the 12th best quarterback. The cut-offs at the other positions are 12, 24, and 36, for tight ends, running backs, and wide receivers, respectively.

The NFL in 2013 won’t closely resemble how the league looked in 1990, but what does that mean for fantasy football? To determine that, we need to see if VBD has evolved with the rest of the football statistics. Let’s start with a graph displaying number of fantasy points scored by the last starter at each position since 1990. As you can see, quarterback scoring has risen significantly over the last two decades, and the production of the 12th tight end has nearly doubled over that time period.

You can see the full article here.

Twenty quarterbacks started all sixteen games last season:

Eli Manning
Tony Romo
Andrew Luck
Russell Wilson
Peyton Manning
Matthew Stafford
Sam Bradford
Aaron Rodgers
Matt Schaub
Ryan Tannehill
Matt Ryan
Christian Ponder
Drew Brees
Ryan Fitzpatrick
Tom Brady
Josh Freeman
Cam Newton
Philip Rivers
Joe Flacco
Andy Dalton

Mark Sanchez started 15 games for the Jets, but was benched for the week 16 game against the Chargers.  Carson Palmer (ribs/chest) and Brandon Weeden (shoulder) were each injured in week 16, causing them to sit out week 17 (although Weeden probably could have played if the game meant anything.) In addition, Jay Cutler (concussion) and Robert Griffin III (knee) each missed one — but only one — game due to injury. ^[1]Griffin was on the injury report twice for head injuries but did not miss a start due to concussions.  As for the other seven teams:
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It’s no secret that Bill Belichick’s Patriots ran an up-tempo offense last year: Tom Brady and crew ran 1,191 offensive plays in 2012, just eight shy of tying the record set by the Drew Bledsoe Patriots in 1994. With versatile players like Aaron Hernandez, Rob Gronkowski, and Danny Woodhead, New England was capable of running out of multiple formations without changing personnel and uses that flexibility to prevent defenses from substituting players based on down and distance. As a result, New England ran 31 more plays than any other team and 101 more plays than any other team that had a positive Game Scripts average. We would expect some teams with negative Game Scripts — especially when they have Matthew Stafford and Andrew Luck — to run a lot of plays late in games as they play catch up, which makes the Patriots’ offensive play numbers even more impressive.

New England ran an offensive play every 24.9 seconds, the highest rate in the league. The Saints were second at 26.1, which makes sense: New Orleans also has an MVP quarterback and versatile weapons at tight end (Jimmy Graham) and running back (Darren Sproles). You might be a little surprised to see Joe Flacco’s Ravens come in at #3 in play tempo, but the Ravens finished in the bottom five last year in time of possession. The Eagles will be running a high-octane offense under Chip Kelly in 2013, but Philadelphia already ranked fourth in tempo last year.

Here’s how to read the table below. In 2012, the Patriots ranked 1st in tempo (i.e., seconds per play). New England had an average Time of Possession of 30:56 and ran 1,191 offensive plays, an average of one play every 24.9 seconds. The Patriots Game Script average was 7.7, and New England ran 21.3% of their plays in the 1st quarter, 24.9% in the 2nd quarter, 27% in the 3rd quarter, 25.8% in the 4th quarter, and 0.9% in overtime.
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Earlier this week, I posted the Game Scripts for each team this season and in each game. After spending the time to calculate the Game Scripts — i.e., the average margin of lead or deficit over the course of every game — it involved minimal extra effort to measure the percentage of time each team spent with the lead, tied, or trailing. So that’s what I’ve done for you today. ^[1]One note: I’ve noticed I made one minor mistake, which I do not have the energy to spend to fix. If a team scored first in overtime and then stopped the opponent on the ensuing drive, I did … Continue reading

It’s not surprising to see the Patriots #1 in minutes spent with the lead: New England ranked first in Game Scripts score and in points differential. But the #2 team might surprise you. One reason the Vikings were so successful basing their offense around Adrian Peterson was because the team held the lead 59% of the time. You may recall the Vikings week 1 victory against the Jaguars, when Christian Ponder led Minnesota from behind to steal the win; that was an extreme outlier. In the team’s other nine victories, the Vikings held the lead for at least 45 minutes in each game. On the other hand, Minnesota led for less than 25 minutes in all seven of their losses.

The table below shows the percentage of the time each team spent leading, tied, or trailing. I’ve also included their respective ranks in each category.
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Last year, I introduced the concepts of Game Scripts. There are 3600 seconds in every game: the Game Script is the average score over each of those 3600 seconds. For reference, you can check out this list of the top single-seasons of all-time.

Did you know that the Patriots ranked 20th in pass/run ratio last year? Without the concept of Game Scripts, we can’t put that in proper context. New England actually ranked second in the league in rush attempts last season, a result based on two factors: the Patriots ran an incredible 1,191 plays last year and on average, the team was winning by over a touchdown in each game.

Here are the 2012 Game Script scores for each team, which represent the average lead held by the team in every second of every regular season game from last year:
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As most of you know, I also write for Footballguys.com, what I consider to be the best place around for fantasy football information. If you’re interested in fantasy football or like reading about regression analysis, you can check out my article over at Footballguys on how to derive a better starting point for running back projections:

Most people will use last year’s statistics (or a three-year weighted average) as the starting point for their 2013 projections. From there, fantasy players modify those numbers up or down based on factors such as talent, key off-season changes, player development, risk of injury, etc. But in this article, I’m advocating that you use something besides last year’s numbers as your starting point.

There is a way to improve on last year’s numbers without introducing any subjective reasoning. When you base a player’s fantasy projections off of his fantasy stats from last year, you are implying that all fantasy points are created equally. But that’s not true: a player with 1100 yards and 5 touchdowns is different than a runner with 800 yards and 10 touchdowns.

Fantasy points come from rushing yards, rushing touchdowns, receptions, receiving yards, and receiving touchdowns. Since some of those variables are more consistent year to year than others, your starting fantasy projections should reflect that fact.

The Fine Print: How to Calculate Future Projections

There is a method that allows you to take certain metrics (such as rush attempts and yards per carry) to predict a separate variable (like future rushing yards). It’s called multivariate linear regression. If you’re a regression pro, great. If not, don’t sweat it — I won’t bore you with any details. Here’s the short version: I looked at the 600 running backs to finish in the top 40 in each season from 1997 to 2011. I then eliminated all players who did not play for the same team in the following season. I chose to use per-game statistics (pro-rated to 16 games) instead of year-end results to avoid having injuries complicated the data set (but I have removed from the sample every player who played in fewer than 10 games).

So what did the regression tell us about the five statistics that yield fantasy points? A regression informs you about both the “stickiness” of the projection — i.e., how easy it is to predict the future variable using the statistics we fed into the formula — and the best formula to make those projections. Loosely speaking, the R^2 number below tells us how easy that metric is to predict, and a higher number means that statistic is easier to predict. Without further ado, in ascending order of randomness, from least to most random, here is how to predict 2013 performance for each running back based on his 2012 statistics:

You can read the full article here.

The Packers have gone 43 consecutive regular season games without having a 100-yard rusher. Not coincidentally, Green Bay drafted Alabama’s Eddie Lacy and UCLA’s Johnathan Franklin in the draft last weekend, hoping that one of those players can bolster the team’s rushing attack.

Brandon Jackson rushed for 115 yards in an overtime loss against the Redskins on October 10, 2010. How long ago was that? Washington’s quarterback that day was Donovan McNabb. Two months later, Jackson rushed for 99 yards in a loss in Foxboro, and Ryan Grant had 92 rushing yards in a September victory in Chicago in 2011, but no Packer has hit the century mark in a regular season game since October 10th, 2010. (It’s worth noting that James Starks rushed for 123 yards in a playoff victory against the Eagles in the 2010 playoffs, but NFL game streaks routinely exclude postseason performances.)

The table below lists all teams since 1960 to go at least 32 games without a 100-yard rusher. Here’s how the second row of the table reads: The Washington Redskins went 72 games without a 100-yard rusher. The team’s last 100-yard rusher came in a game on December 17, 1961, and the streak finally ended on September 24, 1967. The player to break the streak was Bobby Mitchell, and you can see the boxscore from that game in the final column.
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Only three players in NFL history have been responsible for half of their team’s receiving touchdowns over a six-year period: Don Hutson, Jerry Rice, and Hugh Taylor. You probably don’t know much about Taylor, the Washington Redskins star receiver who played from 1947 to 1954. In his first game in the NFL, he caught 8 passes for 212 yards and 3 touchdowns, giving him the record for receiving yards in a player’s first game that stood until 2003.  In his last game, he caught five passes for 106 yards and three touchdowns.  In between those games, he was a star receiver on one of the worst teams in the NFL.  Despite the short career, Taylor came in at #63 on my list of the best receivers of all time. His most impressive season came in 1952, when he was responsible for 45% of the Redskins’ receiving yards and produced the 52nd-best season ever by a wide receiver.

At 6’4, Taylor was one of the tallest receivers of his era, but at only 194 pounds, he was also very deserving of his nickname: Bones. Taylor made up for his skinny physique with a long stride that enabled him to get behind defenders.  I spoke with T.J. Troup, an NFL historian who has coached wide receivers at the college and high school levels, for his thoughts on Taylor. Troup owns a significant amount of NFL film from the late ’40s and ’50s, making him the perfect source for this subject.  He described Taylor to me as one of the best home-run threats of his day, with a playing style similar to other long-striders like Harlon Hill, Don Maynard, and Lance Alworth. The numbers certainly back that up.

The table below shows all receivers who were responsible for at least 39% of a team’s receiving touchdowns over a six-year period.  Note that several receivers would show up multiple times on this list, so for players like Hutson, I’ve limited them to their single best six-year stretch. Taylor’s stretch from ’49 to ’54 ranks second on the list:

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[House-keeping note: I’ve added the Salary Cap Calculator to the gray header tabs at the top of each page, so you can now easily get there no matter what page you’re on at Football Perspective.]

A quick look at Arian Foster‘s statistics over the last three years paints a picture of a player in decline:

Foster’s declined in rushing yards per game and yards per carry over the last two years, while his value in the receiving game fell off a cliff in 2012. One could reasonably conclude that Foster simply isn’t the same player he used to be, and that he could drop off even more in 2013.  But while the traditional statistics tell one story, what do the advanced metrics say?
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Good bit of trivia from my buddy Scott Kacsmar: there were 71 interceptions returned for touchdowns in 2012, the highest number in NFL history. Another interesting fact about the 2012 season: just 2.6 interceptions were thrown per 100 attempts, the lowest figure in NFL history.

We already know that the league-wide interception rate has been rapidly decreasing for years, but the significant increase in interceptions returned for touchdowns per interception is an under-reported story. Last year was the year of the Pick Six, but the Pick Six rate (INTs returned for touchdowns per interception) has been on the rise for several years. The graph below shows both the interception rate (100*INTs/Att) in blue (and measured against the left vertical axis) and the Pick Six rate (100*INT TDs/INT) in red (and measured against the right vertical axis):

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Few get the statheads talking like Danny Amendola. Bill Barnwell wrote a free-agent book on Amendola in March, where he presented Amendola in the best possible light. Barnwell noted that over the last four years, Bradford has completed 66.5% of his passes aimed at Amendola compared to just 56.8% to all other targets. Barnwell further argued that since Amendola was much more productive in St. Louis than Wes Welker was in Miami, there is a good chance Amendola sees a big, Tom Brady-induced spike when he moves to New England, too.

Scott Kacsmar takes a slightly different view. First, the pro-Amendola argument: since 2010, the Rams are 12-15-1 (.446) when Amendola plays and 4-16 (.200) when he is out. Kacsmar also shows that the Rams averaged 18.9 PPG, 5.8 yards per pass attempt, and 312 yards per game, along with a 5.9% sack rate, in games with Amendola, versus averages of just 12.6, 5.6, 296, and 8.1%, respectively, in games that St. Louis played without Amendola. On the negative side, Kacsmar focused on Amendola’s miserable 8.81 yards-per-reception average, the lowest in history by a wide receiver with at least 100 receptions (by a pretty large margin). Another reason not to be impressed with Amendola’s high catch rate is that 29% of his receptions were “failed completions” ^[1]These are plays where the player fails to gain a minimum percentage of yards towards a first down (45 percent on first down, 60 percent on second down and 100 percent on third/fourth down. according to Kacsmar.

Amendola is a unique player in the same sense that Darren Sproles isn’t a traditional running back or Tim Tebow isn’t a traditional quarterback. Amendola’s a wide receiver, but he doesn’t operate the way wide receivers have for much of NFL history. According to Pro Football Focus, Amendola was in the slot on 85% of his routes over the last four years; that’s an enormous number, as even Wes Welker ran routes out of the slot on “only” 73.8% of his routes over that time period.
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The craziness continues, with Wes Welker signing with the Denver Broncos being the big story of day two of the league year. The Patriots responded by signing Danny Amendola, the least surprising move since Brandon Lloyd joined Josh McDaniels in New England last year. Arguably the biggest move so far this week has been Mike Wallace joining Dolphins, while Greg Jennings still seems likely to move on from Green Bay. Throw in Percy Harvin to Seattle and Anquan Boldin to San Francisco, and we’re seeing a lot of movement among the top receivers this year. Which gives me an opportunity to do a quick data dump on the best receivers to ever switch teams.

In some ways, it’s hard to find a comparable receiver to Welker. He’s been so productive for so long that it’s easy to be unimpressed with the 118 catches, 1,354 yards, and six touchdowns he had last year, but no receiver had ever switched teams after catching more than 101 catches in a season. Only two receivers — Muhsin Muhammad and Yancey Thigpen — gained more receiving yards in a season than Welker did in 2012 and then played for a new team the next year.

But Welker’s amazingly unique numbers are a product of playing in a very pass-friendly environment on a team that threw 641 passes last year. To compare players across systems and eras, I came up with a wide receiver ranking system last month. That will allow us to look at the best receivers to switch teams and not just the ones from the last couple of decades. For some perspective, Welker ranked 8th among wide receivers last season, although that’s without any Tom Brady-adjustment.

The table below contains a lot of information. It shows receivers who added over 200 yards of value over average in Year N and then played for a new team in Year N+1. For each player, I’ve listed his old team, his age in Year N, some traditional statistics, the amount of value added by the receiver, and his rank among wide receivers. Then starting in the “N+1 tm” category, we see his new team, his statistics in the new season, how much value he added in Year N+1 and his rank in that season.
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On Monday, I argued that target data has some predictive value. I wanted to update that post with a few observations.

Wide Receiver Targets

In the original post, I looked at year-to-year data for all players with at least 500 receiving yards in Year N and at least 8 games played for the same team in Years N and N+1. But it makes more sense to limit the sample to only wide receivers if we want to predict how wide receivers project in the next season.

There are 554 pairs of wide receiver seasons that meet the above criteria. ^[1]I have again pro-rated all seasons to sixteen games. The best fit formula to project future receptions based on prior receptions and prior targets is:

Year N+1 Receptions = 14.0 + 0.547 * Yr_N_Rec + 0.124 * Yr_N_Tar

The R^2 is 0.39, and while the receptions variable is statistically significant by any measure, the targets variable just barely qualifies (p = 0.044) as such. Still, this tells us that for every 8 additional targets a receiver sees in Year N, we can expect one more reception in Year N+1, holding his number of receptions equal.

If we want to project receiving yards instead of receptions, we get:

Year N+1 Receiving Yards = 180.3 + 0.434 * Yr_N_RecYd + 2.55 * Yr_N_Tar

The R^2 is 0.33, implying a slightly less strong relationships, which makes sense: yards are more variable to large outliers than receptions, so you would expect receiving yards to be slightly harder to predict. Another interesting note: the targets variable here is statistically significant at the p = 0.0003 level, and as expected, the receiving yards variable is statistically significant at all levels. Holding receiving yards equal, a receiver would need an additional 19 targets to increase his projected number of receiving yards by 50, so the practical effect may not be all that large.

Addressing the multicollinearity problem
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Reggie Wayne led the NFL in targets last year, but that’s a little misleading since the Colts ranked 6th in pass attempts. As a percentage of team targets, Wayne ranked second in the league, but he was a distant number two to Brandon Marshall, who saw two out of every five Bears passes in 2013.

But that doesn’t make him the best receiver. It was easier for Marshall to receive a high number of targets because the rest of the Chicago supporting cast was weak, so Jay Cutler consistently looked Marshall’s way. Chicago ranked 25th last year in Adjusted Net Yards per Attempt, so essentially we have a player on a bad passing offense receiving a ton of targets. It’s not all that obvious how you compare a player like that to Roddy White, who deserves credit for being in a great passing offense but loses targets because of the presence of Julio Jones and Tony Gonzalez (of course, without them, would Matt Ryan start looking like Jay Cutler?)

I identified the leader in targets for each team, and then calculated the percentage of team targets each leading receiver had in 2012. The table below lists that percentage on the Y-Axis; the X-Axis represents the number of ANY/A that player’s team averaged. Someone like Marshall (represented by the first four letters of his last name and the first two letters of his first name, MarsBr) will therefore be high and to the left, while Randall Cobb is low and to the right:

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In 2007, Doug Drinen and I wrote a pair of articles discussing our views on targets. I’m working on a wide receiver project this off-season, and a complete discussion of receiving statistics includes a discussion of targets.

Let me start with the prevailing few: targets are important, and if two receivers have the same production on a different number of targets, the one who produced on fewer targets is better/more valuable. Similarly, if all else is equal, the receiver with a higher catch rate — calculated as catches/target — is the better/more valuable one.

There are some problems with the prevailing view. By placing targets in the denominator of a formula, we’re implying that targets are a bad thing, or at a minimum, an opportunity wasted. But targets aren’t like pass attempts. Pro Football Focus has a stat called yards per pass route run, and that actually is the receiver version of yards per pass attempt. ^[1]Unfortunately, yards per pass route run is not going to help us if we want to grade receivers on a historical basis.

But targets don’t help identify the player who deserves blame: on a random incomplete pass, assume three receivers are running routes, and one of them is targeted. Absent a drop, I have a hard time saying that of the three wide receivers, the targeted one did the worst of the three. If we grade a receiver by his yards per route run, each receiver is equally penalized with one route run on the play; if we grade a receiver by yards per target, the two wide receivers that did not get open are not penalized, while the one that was targeted is penalized. That seems fundamentally wrong to me.

Here’s another problem: In a broad sense, the player with more targets (or percentage of his team’s targets) is in a very real sense a bigger part of his team’s offense. Either he’s open more often, or the quarterback is throwing in his direction even when he’s not open (whether because the coaches call more plays for him or because he’s earned the quarterback’s trust). In any event, the target itself is an indicator of quality, and penalizing a player — which is what you do when you place targets in the denominator — for an event that is highly correlated with quality is not something I’m comfortable doing.
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NFL.com posted an article yesterday looking at the strength of schedule for each team in 2013. We have known each team’s opponents since the end of the regular season, and while the full schedule won’t come out until April, it’s simple to calculate a team’s strength of schedule for 2013. Usually, the media reports this by looking at the win-loss record of each opponent from the prior season. Here are the projected SOSs for each team next season:

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Just a guess, but I think that question will be asked quite a few times over the next couple of weeks. While the inanity of the discussion that usually follows that question is not something I wish to emulate, there’s no particular reason not to take an in-depth look at Flacco’s career. The table below shows Flacco’s performance in six key metrics — all relative to league average (1.00) — for each season of his career:

As you can see, with the exception of his great interception rate — which justifies its own post during this pre-Super Bowl period — Flacco’s career performance has been rather average. His touchdown rate, like those of many quarterbacks, has bounced up and down throughout his career. His sack rate was below average during his first three years, improved significantly in 2011, and landed right at the league average in 2012.

In the three main statistics — Y/A, NY/A, and ANY/A — Flacco has consistently finished in a tight window around the league average. His ANY/A has been slightly better than his NY/A thanks to that lofty interception rate, but suffice it to say Joe Flacco is, and has been for years, a league average quarterback.

If we look at ESPN’s Total QBR, Flacco ranked 27th as a rookie in 2008, 15th in 2009, and 12th in 2010, signaling a young quarterback improving and on the rise. In 2011, he ranked 14th, perhaps signaling a leveling off, and then this past season, he finished 25th. The positive spin would be that he’s a league-average quarterback, and the negative one (at least prior to this post-season) would have been that he was regressing.

On the other hand, here is how Flacco has performed in the playoffs in each game, as measured by AY/A:

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Last weekend, I looked at career rushing stats in wins and losses, and yesterday, I did the same for quarterbacks. Today we will check out the splits for receivers.

I looked at all games, including playoffs, from 1960 to 2011, for all players with at least 4,000 receiving yards over that time period. The table below lists the following information for each player:

– His first year (or 1960, if he played before 1960) and his last year (or 2011, if still active)
– All the franchises he played for (which you can search for in the search box)
– His number of career wins, and his career receptions, receiving yards, yards per reception, and receiving yards per game in wins
– His number of career losses, and his career receptions, receiving yards, yards per reception, and receiving yards per game in losses

You might be surprised to see Andre Johnson at the top of the list, but his career average should decline the longer he plays; that said, 2012 didn’t drop his numbers. On the flip side, Calvin Johnson moves up into the #2 slot; part of that was due to a great season (although Detroit didn’t get many wins) and part of that was due to Randy Moss slipping. Larry Fitzgerald comes up high on the list for the same reason as both Johnsons, although it’s often easy to forget how great Fitzgerald can be thanks to his current situation.

The table is sorted by receiving yards per game in wins:

Rk	Player	Years	Teams	Pos	Win	Rec_W	Yd_W	YPR_W	Y/G_W	Loss	Rec_L	Yd_L	YPR_L	Y/G_L
1	Andre Johnson	2003--2011	htx	WR	52	325	4739	14.58	91.1	72	394	5118	12.99	71.1
2	Randy Moss	1998--2010	min-rai-nwe-oti	WR	114	597	9960	16.68	87.4	93	404	5763	14.26	62
3	Michael Irvin	1988--1999	dal	WR	106	560	9133	16.31	86.2	62	277	4086	14.75	65.9
4	Larry Fitzgerald	2004--2011	crd	WR	59	352	5021	14.26	85.1	71	383	5299	13.84	74.6
5	Calvin Johnson	2007--2011	det	WR	23	113	1929	17.07	83.9	54	265	4154	15.68	76.9
6	Lance Alworth	1962--1972	sdg-dal	FL-WR	83	360	6872	19.09	82.8	42	172	3094	17.99	73.7
7	Jerry Rice	1985--2004	sfo-rai-sea	WR	207	1099	16909	15.39	81.7	118	598	8173	13.67	69.3
8	Art Powell	1960--1968	nyj-rai-buf-min	SE-WR	51	244	4160	17.05	81.6	45	215	3477	16.17	77.3
9	Jimmy Smith	1995--2005	jax	WR	96	512	7829	15.29	81.6	80	390	5105	13.09	63.8
10	Torry Holt	1999--2009	ram-jax	WR	93	486	7416	15.26	79.7	89	481	6596	13.71	74.1
11	Charley Hennigan	1960--1966	oti	WR	44	209	3501	16.75	79.6	40	201	3213	15.99	80.3
12	Steve Smith	2001--2011	car	WR	75	390	5898	15.12	78.6	84	356	5162	14.5	61.5
13	Del Shofner	1960--1967	ram-nyg	E	41	165	3213	19.47	78.4	31	86	1224	14.23	39.5
14	Dwayne Bowe	2007--2011	kan	WR	25	118	1948	16.51	77.9	49	238	2979	12.52	60.8
15	Don Maynard	1960--1973	nyj-crd	WR-HB	79	298	6150	20.64	77.8	76	305	5091	16.69	67
16	Terrell Owens	1996--2010	sfo-phi-dal-buf-cin	WR	131	655	10127	15.46	77.3	95	477	6558	13.75	69
17	Marvin Harrison	1996--2008	clt	WR	125	723	9649	13.35	77.2	81	444	5814	13.09	71.8
18	Sterling Sharpe	1988--1994	gnb	WR	52	292	3937	13.48	75.7	62	314	4426	14.1	71.4
19	DeSean Jackson	2008--2011	phi	WR	39	149	2934	19.69	75.2	25	93	1364	14.67	54.6
20	Wesley Walker	1977--1989	nyj	WR	73	272	5485	20.17	75.1	71	185	3195	17.27	45
21	Herman Moore	1991--2001	det	WR	63	314	4712	15.01	74.8	77	383	4936	12.89	64.1
22	Charlie Brown	1982--1987	was-atl	WR	42	177	3134	17.71	74.6	21	71	1014	14.28	48.3
23	Sonny Randle	1960--1968	crd-sfo-dal	E-WR	45	178	3330	18.71	74	45	155	2187	14.11	48.6
24	Greg Jennings	2006--2011	gnb	WR	61	279	4493	16.1	73.7	34	151	2243	14.85	66
25	Reggie Wayne	2001--2011	clt	WR	122	639	8938	13.99	73.3	63	306	3898	12.74	61.9
26	John Jefferson	1978--1985	sdg-gnb-cle	WR	54	238	3953	16.61	73.2	44	131	2091	15.96	47.5
27	Terry Glenn	1996--2007	nwe-gnb-dal	WR	79	379	5686	15	72	61	246	3574	14.53	58.6
28	Darnay Scott	1994--2002	cin-dal	WR	40	171	2852	16.68	71.3	77	237	3341	14.1	43.4
29	Buddy Dial	1960--1966	pit-dal	SE-FL	35	112	2494	22.27	71.3	31	110	2050	18.64	66.1
30	Isaac Bruce	1994--2009	ram-sfo	WR	114	529	8119	15.35	71.2	110	539	7848	14.56	71.3
31	Gary Clark	1985--1995	was-crd-mia	WR	107	484	7609	15.72	71.1	66	273	4073	14.92	61.7
32	Carl Pickens	1992--2000	cin-oti	WR	39	212	2746	12.95	70.4	84	328	4383	13.36	52.2
33	Homer Jones	1964--1970	nyg-cle	SE-WR	32	91	2240	24.62	70	47	131	2573	19.64	54.7
34	Marques Colston	2006--2011	nor	WR	61	313	4260	13.61	69.8	32	181	2608	14.41	81.5
35	Cris Carter	1987--2002	phi-min-mia	WR	132	701	9185	13.1	69.6	101	463	5584	12.06	55.3
36	Al Toon	1985--1992	nyj	WR	48	251	3336	13.29	69.5	58	287	3551	12.37	61.2
37	Anquan Boldin	2003--2011	crd-rav	WR	65	332	4482	13.5	69	67	405	5188	12.81	77.4
38	Pete Retzlaff	1960--1966	phi	WR-TE	42	155	2889	18.64	68.8	42	181	2807	15.51	66.8
39	Chad Ochocinco	2001--2011	cin-nwe	WR	74	350	5084	14.53	68.7	89	419	6049	14.44	68
40	Steve Largent	1976--1989	sea	WR	99	419	6797	16.22	68.7	106	423	6726	15.9	63.5
41	Raymond Berry	1960--1967	clt	E	57	263	3911	14.87	68.6	32	149	1978	13.28	61.8
42	Gary Garrison	1966--1977	sdg-oti	WR-SE	55	192	3764	19.6	68.4	63	201	3557	17.7	56.5
43	Darrell Jackson	2000--2008	sea-sfo-den	WR	61	282	4147	14.71	68	63	258	3488	13.52	55.4
44	Mike Quick	1982--1990	phi	WR	39	142	2645	18.63	67.8	57	216	3664	16.96	64.3
45	James Lofton	1978--1993	gnb-rai-buf-ram-phi	WR	109	395	7387	18.7	67.8	115	402	7254	18.04	63.1
46	Rob Moore	1990--1999	nyj-crd	WR	59	269	3998	14.86	67.8	94	374	5572	14.9	59.3
47	Fred Barnett	1990--1997	phi-mia	WR	59	243	3977	16.37	67.4	38	136	1668	12.26	43.9
48	Kellen Winslow	1979--1987	sdg	TE	58	320	3908	12.21	67.4	55	249	3213	12.9	58.4
49	George Sauer	1965--1970	nyj	SE-WR	45	172	3019	17.55	67.1	30	137	1977	14.43	65.9
50	Joe Horn	1996--2007	kan-nor-atl	WR	71	319	4739	14.86	66.7	77	285	4055	14.23	52.7
51	Otis Taylor	1965--1974	kan	WR-FL	75	265	4985	18.81	66.5	41	146	2323	15.91	56.7
52	Mark Duper	1983--1992	mia	WR	88	324	5839	18.02	66.4	55	219	3625	16.55	65.9
53	Bob Hayes	1965--1975	dal-sfo	SE-WR	87	268	5679	21.19	65.3	41	126	2128	16.89	51.9
54	Steve Watson	1979--1987	den	WR	63	223	4112	18.44	65.3	39	147	2314	15.74	59.3
55	Roddy White	2005--2011	atl	WR	62	296	4032	13.62	65	53	256	3535	13.81	66.7
56	Rod Smith	1995--2006	den	WR	121	575	7865	13.68	65	64	323	4384	13.57	68.5
57	Flipper Anderson	1988--1995	ram-clt	WR	34	99	2204	22.26	64.8	58	175	3323	18.99	57.3
58	Eddie Brown	1985--1991	cin	WR	53	175	3431	19.61	64.7	51	197	2802	14.22	54.9
59	Wes Welker	2004--2011	sdg-mia-nwe	WR	86	509	5554	10.91	64.6	45	194	2110	10.88	46.9
60	Derrick Alexander	1994--2002	cle-rav-kan-min	WR	48	167	3092	18.51	64.4	69	251	3909	15.57	56.7
61	Andre Reed	1985--2000	buf-was	WR	134	599	8621	14.39	64.3	106	437	5806	13.29	54.8
62	Antonio Gates	2003--2011	sdg	TE	80	375	5124	13.66	64.1	53	257	3108	12.09	58.6
63	Wes Chandler	1978--1988	nor-sdg-sfo	WR	61	234	3894	16.64	63.8	84	348	5419	15.57	64.5
64	Anthony Miller	1988--1997	sdg-den-dal	WR	71	272	4512	16.59	63.5	82	332	4773	14.38	58.2
65	Al Denson	1964--1971	den-min	WR-TE	25	89	1581	17.76	63.2	49	163	2608	16	53.2
66	Antonio Freeman	1995--2003	gnb-phi	WR	95	375	5978	15.94	62.9	41	155	2096	13.52	51.1
67	Lee Evans	2004--2011	buf-rav	WR	51	174	3203	18.41	62.8	67	211	2874	13.62	42.9
68	Plaxico Burress	2000--2011	pit-nyg-nyj	WR	95	385	5923	15.38	62.3	57	202	2969	14.7	52.1
69	Santana Moss	2001--2011	nyj-was	WR	74	285	4606	16.16	62.2	88	387	4963	12.82	56.4
70	Brandon Marshall	2006--2011	den-mia	WR	43	214	2676	12.5	62.2	48	280	3571	12.75	74.4
71	Keyshawn Johnson	1996--2006	nyj-tam-dal-car	WR	92	447	5691	12.73	61.9	82	406	5449	13.42	66.5
72	Joey Galloway	1995--2010	sea-dal-tam-nwe-was	WR	85	321	5205	16.21	61.2	107	393	5904	15.02	55.2
73	Muhsin Muhammad	1996--2009	car-chi	WR	105	477	6407	13.43	61	96	413	5589	13.53	58.2
74	Henry Ellard	1983--1998	ram-was-nwe	WR	99	343	6040	17.61	61	125	492	8079	16.42	64.6
75	Tommy McDonald	1960--1968	phi-dal-ram-atl-cle	WR-HB	49	166	2979	17.95	60.8	61	222	3493	15.73	57.3
76	Anthony Carter	1985--1995	min-det	WR	80	293	4853	16.56	60.7	62	233	3535	15.17	57
77	Art Monk	1980--1995	was-nyj-phi	WR	142	631	8609	13.64	60.6	95	378	5174	13.69	54.5
78	Red Phillips	1960--1967	ram-min	E	24	94	1455	15.48	60.6	53	214	3147	14.71	59.4
79	Roger Carr	1974--1983	clt-sea-sdg	WR	40	110	2425	22.05	60.6	60	163	2681	16.45	44.7
80	Paul Flatley	1963--1970	min-atl	WR-FL	34	117	2061	17.62	60.6	55	179	2742	15.32	49.9
81	David Boston	1999--2005	crd-sdg-mia	WR	27	109	1626	14.92	60.2	47	206	3073	14.92	65.4
82	Ernest Givins	1986--1995	oti-jax	WR	75	320	4516	14.11	60.2	80	311	4473	14.38	55.9
83	Dwight Clark	1979--1987	sfo	WR	81	343	4872	14.2	60.1	46	216	2648	12.26	57.6
84	Santonio Holmes	2006--2011	pit-nyj	WR	57	211	3425	16.23	60.1	38	152	2212	14.55	58.2
85	Paul Warfield	1964--1977	cle-mia	WR-SE	115	340	6892	20.27	59.9	47	132	2497	18.92	53.1
86	Laveranues Coles	2000--2009	nyj-was-cin	WR	71	323	4253	13.17	59.9	81	378	4638	12.27	57.3
87	Jimmy Orr	1960--1970	pit-clt	WR	73	219	4372	19.96	59.9	38	119	2119	17.81	55.8
88	Elbert Dubenion	1960--1967	buf	WR-HB	53	159	3172	19.95	59.8	42	127	2075	16.34	49.4
89	Ken Burrough	1970--1981	nor-oti	WR	67	222	3977	17.91	59.4	80	204	3230	15.83	40.4
90	Stephone Paige	1983--1991	kan	WR	57	180	3361	18.67	59	63	203	3089	15.22	49
91	Todd Christensen	1980--1988	rai	TE-FB	66	306	3888	12.71	58.9	41	186	2342	12.59	57.1
92	Louis Lipps	1984--1992	pit-nor	WR	48	169	2827	16.73	58.9	63	204	3376	16.55	53.6
93	Jeff Graham	1991--2001	pit-chi-nyj-phi-sdg	WR	57	222	3345	15.07	58.7	85	335	5064	15.12	59.6
94	Harold Jackson	1969--1983	phi-ram-nwe-min-sea	WR-FL	100	296	5864	19.81	58.6	84	292	4835	16.56	57.6
95	Tim Brown	1988--2004	rai-tam	WR	135	562	7907	14.07	58.6	127	577	7608	13.19	59.9
96	Tony Martin	1990--2001	mia-sdg-atl	WR	103	369	6031	16.34	58.6	76	267	3732	13.98	49.1
97	John Stallworth	1974--1987	pit	WR	103	361	6023	16.68	58.5	58	230	3687	16.03	63.6
98	Eric Martin	1985--1994	nor-kan	WR	85	315	4969	15.77	58.5	68	253	3396	13.42	49.9
99	Stanley Morgan	1977--1990	nwe-clt	WR	99	298	5787	19.42	58.5	86	278	5250	18.88	61
100	Alfred Jenkins	1975--1983	atl	WR	50	170	2903	17.08	58.1	60	196	3571	18.22	59.5
101	Jason Witten	2003--2011	dal	TE	77	381	4457	11.7	57.9	67	343	3745	10.92	55.9
102	Kellen Winslow Jr.	2004--2011	cle-tam	TE	34	153	1967	12.86	57.9	58	284	2869	10.1	49.5
103	Braylon Edwards	2005--2011	cle-nyj-sfo	WR	48	172	2759	16.04	57.5	57	184	2884	15.67	50.6
104	Cris Collinsworth	1981--1988	cin	WR	60	216	3446	15.95	57.4	48	222	3606	16.24	75.1
105	Gene A. Washington	1969--1979	sfo-det	WR-SE	60	178	3445	19.35	57.4	69	210	3535	16.83	51.2
106	John Gilliam	1967--1977	nor-crd-min-atl	WR-FL	69	206	3947	19.16	57.2	70	176	3017	17.14	43.1
107	Chris Burford	1960--1967	kan	SE-WR	52	205	2971	14.49	57.1	38	157	2292	14.6	60.3
108	Max McGee	1960--1967	gnb	E	57	177	3244	18.33	56.9	19	56	1067	19.05	56.2
109	Charlie Joiner	1969--1986	oti-cin-sdg	WR	114	404	6476	16.03	56.8	114	375	6132	16.35	53.8
110	Tony Hill	1977--1986	dal	WR	97	335	5508	16.44	56.8	46	190	3098	16.31	67.3
111	Bernie Casey	1961--1968	sfo-ram	FB-WR	45	162	2547	15.72	56.6	44	160	2331	14.57	53
112	Charley Taylor	1964--1977	was	WR-RB	87	341	4918	14.42	56.5	70	297	4071	13.71	58.2
113	Javon Walker	2002--2009	gnb-den-rai	WR	45	157	2537	16.16	56.4	38	123	1760	14.31	46.3
114	Jerry Butler	1979--1986	buf	WR	38	139	2139	15.39	56.3	47	146	2285	15.65	48.6
115	Carlos Carson	1980--1989	kan-phi	WR	50	147	2809	19.11	56.2	63	203	3444	16.97	54.7
116	Webster Slaughter	1986--1998	cle-oti-kan-nyj-sdg	WR	76	276	4265	15.45	56.1	84	314	4243	13.51	50.5
117	Hines Ward	1998--2011	pit	WR	145	684	8129	11.88	56.1	83	393	4996	12.71	60.2
118	Gail Cogdill	1960--1970	det-atl	SE-WR	54	172	3023	17.58	56	53	164	2431	14.82	45.9
119	Johnny Morris	1960--1967	chi	FL-HB	51	189	2847	15.06	55.8	37	141	1794	12.72	48.5
120	Chris Chambers	2001--2010	mia-sdg-kan	WR	74	273	4127	15.12	55.8	76	291	3928	13.5	51.7
121	Cliff Branch	1972--1984	rai	WR	129	401	7184	17.92	55.7	49	170	2739	16.11	55.9
122	Andre Rison	1989--2000	clt-atl-cle-jax-gnb-kan-rai	WR	92	361	5120	14.18	55.7	92	411	5500	13.38	59.8
123	Reggie Rucker	1970--1981	dal-nyg-nwe-cle	WR	70	235	3890	16.55	55.6	79	215	3234	15.04	40.9
124	Eddie Kennison	1996--2007	ram-nor-chi-den-kan	WR	75	245	4163	16.99	55.5	102	306	4232	13.83	41.5
125	Antonio Bryant	2002--2009	dal-cle-sfo-tam	WR	40	148	2217	14.98	55.4	64	225	3472	15.43	54.3
126	Donald Driver	1999--2011	gnb	WR	115	471	6368	13.52	55.4	76	313	4367	13.95	57.5
127	Marty Booker	1999--2009	chi-mia-atl	WR	57	242	3153	13.03	55.3	85	299	3568	11.93	42
128	Yancey Thigpen	1992--2000	pit-oti	WR	67	227	3701	16.3	55.2	33	121	1800	14.88	54.5
129	Tony Gonzalez	1997--2011	kan-atl	TE	122	562	6723	11.96	55.1	116	603	6772	11.23	58.4
130	Vance Johnson	1985--1995	den	WR	70	269	3856	14.33	55.1	51	183	2520	13.77	49.4
131	Curtis Conway	1993--2004	chi-sdg-nyj-sfo	WR	61	232	3359	14.48	55.1	97	369	4952	13.42	51.1
132	Roy Jefferson	1965--1976	pit-clt-was	WR-SE	78	251	4265	16.99	54.7	72	217	3494	16.1	48.5
133	Fred Biletnikoff	1965--1978	rai	WR-FL	136	475	7424	15.63	54.6	46	148	2137	14.44	46.5
134	Lionel Taylor	1960--1968	den-oti	WR	31	136	1691	12.43	54.5	71	405	5153	12.72	72.6
135	Vincent Jackson	2005--2011	sdg	WR	63	194	3429	17.68	54.4	33	107	1828	17.08	55.4
136	Jim Colclough	1960--1968	nwe	E	49	148	2666	18.01	54.4	45	112	1874	16.73	41.6
137	Carroll Dale	1960--1973	ram-gnb-min	WR-TE	91	245	4949	20.2	54.4	73	211	3660	17.35	50.1
138	Dave Parks	1964--1973	sfo-nor-oti	WR-TE	31	107	1681	15.71	54.2	67	215	3424	15.93	51.1
139	Shannon Sharpe	1990--2003	den-rav	TE	131	534	7100	13.3	54.2	69	343	3774	11	54.7
140	Ben Hawkins	1966--1973	phi	WR	28	75	1517	20.23	54.2	57	171	2945	17.22	51.7
141	Eric Moulds	1996--2007	buf-htx-oti	WR	89	344	4803	13.96	54	100	435	5512	12.67	55.1
142	Isaac Curtis	1973--1984	cin	WR	79	226	4263	18.86	54	75	203	3022	14.89	40.3
143	Brian Blades	1988--1998	sea	WR	66	268	3556	13.27	53.9	78	318	4142	13.03	53.1
144	Lynn Swann	1974--1982	pit	WR	94	302	5054	16.74	53.8	32	80	1300	16.25	40.6
145	Deion Branch	2002--2011	nwe-sea	WR	94	367	5048	13.75	53.7	51	197	2383	12.1	46.7
146	Sammy White	1976--1985	min	WR	68	211	3646	17.28	53.6	61	188	2893	15.39	47.4
147	Kevin House	1980--1987	tam-ram	WR	30	89	1608	18.07	53.6	70	218	3693	16.94	52.8
148	Haywood Jeffires	1987--1996	oti-nor	WR	65	272	3483	12.81	53.6	68	304	3364	11.07	49.5
149	Roy Green	1979--1992	crd-phi	WR	76	239	4066	17.01	53.5	104	318	4826	15.18	46.4
150	Ahmad Rashad	1972--1982	crd-buf-min	WR	71	271	3769	13.91	53.1	67	236	3295	13.96	49.2
151	Amani Toomer	1996--2008	nyg	WR	110	403	5831	14.47	53	89	307	4232	13.79	47.6
152	Bobby Mitchell	1960--1968	cle-was	WR-HB	52	175	2750	15.71	52.9	62	263	4192	15.94	67.6
153	Bill Brooks	1986--1996	clt-buf-was	WR	74	278	3910	14.06	52.8	85	332	4403	13.26	51.8
154	Harold Carmichael	1971--1984	phi-dal	WR-TE	82	279	4306	15.43	52.5	99	333	5001	15.02	50.5
155	Drew Pearson	1973--1983	dal	WR	121	391	6350	16.24	52.5	50	165	2577	15.62	51.5
156	Lance Rentzel	1965--1974	min-dal-ram	WR-FL	66	180	3458	19.21	52.4	42	94	1544	16.43	36.8
157	Irving Fryar	1984--2000	nwe-mia-phi-was	WR	119	398	6230	15.65	52.4	135	477	6845	14.35	50.7
158	Bert Emanuel	1994--2001	atl-tam-mia-nwe-det	WR	44	158	2300	14.56	52.3	52	202	2683	13.28	51.6
159	Keenan McCardell	1992--2007	cle-jax-tam-sdg-was	WR	123	495	6428	12.99	52.3	87	443	5567	12.57	64
160	Aaron Thomas	1961--1970	sfo-nyg	TE-SE	35	87	1828	21.01	52.2	55	170	2665	15.68	48.5
161	Mark Clayton	1983--1993	mia-gnb	WR	102	336	5303	15.78	52	65	278	4178	15.03	64.3
162	Jake Reed	1992--2002	min-nor	WR	72	251	3742	14.91	52	62	225	3666	16.29	59.1
163	Roy E. Williams	2004--2011	det-dal-chi	WR	46	161	2388	14.83	51.9	66	237	3386	14.29	51.3
164	Henry Marshall	1976--1987	kan	WR	58	188	2982	15.86	51.4	84	234	3635	15.53	43.3
165	John Taylor	1987--1995	sfo	WR	94	302	4825	15.98	51.3	35	91	1507	16.56	43.1
166	Ricky Sanders	1986--1995	was-atl	WR	80	286	4105	14.35	51.3	57	228	2889	12.67	50.7
167	Alvin Harper	1991--1997	dal-tam-was	WR	56	139	2871	20.65	51.3	29	76	1257	16.54	43.3
168	Frank Clarke	1960--1967	dal	E	37	112	1887	16.85	51	51	149	2959	19.86	58
169	Marcus Robinson	1998--2006	chi-rav-min	WR	47	160	2394	14.96	50.9	55	172	2441	14.19	44.4
170	T.J. Houshmandzadeh	2001--2011	cin-sea-rav-rai	WR	57	253	2893	11.43	50.8	81	370	4286	11.58	52.9
171	Drew Hill	1979--1993	ram-oti-atl	WR	103	334	5220	15.63	50.7	105	339	5152	15.2	49.1
172	Michael Jackson	1991--1998	cle-rav	WR	39	127	1969	15.5	50.5	62	234	3556	15.2	57.4
173	Willie Davis	1992--1998	kan-oti	WR	61	183	3073	16.79	50.4	44	119	1669	14.03	37.9
174	Boyd Dowler	1960--1971	gnb-was	FL-SE	102	324	5112	15.78	50.1	40	119	1600	13.45	40
175	Derrick Mason	1997--2011	oti-rav-nyj-htx	WR	141	542	7053	13.01	50	97	450	5609	12.46	57.8
176	Johnnie Morton	1994--2005	det-kan-sfo	WR	75	267	3746	14.03	49.9	97	368	5092	13.84	52.5
177	Mark Carrier	1987--1998	tam-cle-car	WR	64	212	3188	15.04	49.8	102	366	5668	15.49	55.6
178	Danny Abramowicz	1967--1974	nor-sfo	E	30	97	1494	15.4	49.8	74	255	3884	15.23	52.5
179	Wayne Chrebet	1995--2005	nyj	WR	69	263	3435	13.06	49.8	81	336	4199	12.5	51.8
180	Dave Kocourek	1960--1968	sdg-mia-rai	TE-FL	55	157	2727	17.37	49.6	37	98	1509	15.4	40.8
181	Ed McCaffrey	1991--2003	nyg-sfo-den	WR	106	380	5212	13.72	49.2	58	227	2764	12.18	47.7
182	Michael Westbrook	1995--2002	was-cin	WR	39	135	1914	14.18	49.1	42	144	2361	16.4	56.2
183	Lionel Manuel	1984--1990	nyg	WR	50	143	2444	17.09	48.9	33	103	1740	16.89	52.7
184	Gary Collins	1962--1971	cle	WR	80	240	3877	16.15	48.5	42	95	1497	15.76	35.6
185	Robert Brooks	1992--2000	gnb-den	WR	67	226	3244	14.35	48.4	36	128	1683	13.15	46.8
186	Frank Sanders	1995--2003	crd-rav	WR	48	178	2323	13.05	48.4	80	336	4528	13.48	56.6
187	Jerry Porter	2000--2008	rai-jax	WR	38	116	1839	15.85	48.4	62	197	2573	13.06	41.5
188	Mel Gray	1971--1982	crd	WR	65	167	3113	18.64	47.9	78	188	3545	18.86	45.4
189	Tim McGee	1986--1994	cin-was	WR	53	145	2526	17.42	47.7	69	183	2737	14.96	39.7
190	Frank Lewis	1971--1983	pit-buf	WR	86	229	4098	17.9	47.7	58	190	3114	16.39	53.7
191	Bernard Berrian	2004--2011	chi-min	WR	58	178	2761	15.51	47.6	52	143	1827	12.78	35.1
192	Sean Dawkins	1993--2001	clt-nor-sea-jax	WR	54	173	2566	14.83	47.5	78	290	3960	13.66	50.8
193	Willie Gault	1983--1993	chi-rai	WR	98	227	4653	20.5	47.5	58	127	2479	19.52	42.7
194	Dallas Clark	2003--2011	clt	TE	88	358	4175	11.66	47.4	36	133	1559	11.72	43.3
195	Jessie Hester	1985--1995	rai-atl-clt-ram	WR	49	133	2318	17.43	47.3	73	241	3548	14.72	48.6
196	Michael Haynes	1988--1997	atl-nor	WR	52	155	2459	15.86	47.3	81	280	4288	15.31	52.9
197	Haven Moses	1968--1981	buf-den	WR-SE	82	199	3856	19.38	47	90	253	4425	17.49	49.2
198	Jackie Smith	1963--1978	crd-dal	TE	84	226	3950	17.48	47	77	235	3696	15.73	48
199	Mark Jackson	1986--1994	den-nyg-clt	WR	74	205	3472	16.94	46.9	53	159	2491	15.67	47
200	Terance Mathis	1990--2002	nyj-atl-pit	WR	86	299	4002	13.38	46.5	114	419	5206	12.42	45.7
201	Bob Chandler	1971--1981	buf-rai	WR	48	145	2233	15.4	46.5	67	229	3058	13.35	45.6
202	Milt Morin	1966--1975	cle	TE	56	165	2599	15.75	46.4	46	117	1710	14.62	37.2
203	Reggie Langhorne	1985--1993	cle-clt	WR	63	205	2923	14.26	46.4	59	229	2874	12.55	48.7
204	Pat Tilley	1976--1986	crd	WR	61	189	2830	14.97	46.4	74	280	4186	14.95	56.6
205	John Mackey	1963--1972	clt-sdg	TE	89	253	4128	16.32	46.4	33	77	1133	14.71	34.3
206	Michael Timpson	1989--1997	nwe-chi-phi	WR	41	137	1900	13.87	46.3	61	164	2154	13.13	35.3
207	Bill Schroeder	1997--2004	gnb-det-tam	WR	50	150	2311	15.41	46.2	47	159	2342	14.73	49.8
208	Chris Cooley	2004--2011	was	TE	48	187	2211	11.82	46.1	60	252	2635	10.46	43.9
209	Brett Perriman	1988--1997	nor-det-kan-mia	WR	74	258	3390	13.14	45.8	72	294	3522	11.98	48.9
210	Dave Casper	1974--1984	rai-oti-min	TE	70	230	3202	13.92	45.7	44	175	2377	13.58	54
211	Dave Logan	1976--1984	cle-den	WR	47	133	2147	16.14	45.7	47	133	2166	16.29	46.1
212	Bobby Joe Conrad	1960--1969	crd-dal	WR-HB	62	191	2830	14.82	45.6	55	192	2563	13.35	46.6
213	Koren Robinson	2001--2008	sea-min-gnb	WR	51	159	2325	14.62	45.6	46	150	2063	13.75	44.8
214	Bobby Engram	1996--2009	chi-sea-kan	WR	80	301	3641	12.1	45.5	101	384	4586	11.94	45.4
215	Gary Ballman	1962--1973	pit-phi-nyg-min	WR-TE	35	89	1565	17.58	44.7	68	212	3451	16.28	50.8
216	Nat Moore	1974--1986	mia	WR-RB	119	363	5315	14.64	44.7	55	163	2312	14.18	42
217	Duriel Harris	1976--1985	mia-cle-dal	WR	68	185	3037	16.42	44.7	44	133	2284	17.17	51.9
218	Jack Snow	1965--1975	ram	WR-SE	85	214	3773	17.63	44.4	42	115	1978	17.2	47.1
219	Freddie Scott	1974--1983	clt-det	WR	36	95	1592	16.76	44.2	58	173	2766	15.99	47.7
220	Ray Butler	1980--1988	clt-sea	WR	34	90	1503	16.7	44.2	64	152	2543	16.73	39.7
221	Devery Henderson	2005--2011	nor	WR	64	150	2828	18.85	44.2	47	104	1697	16.32	36.1
222	J.J. Stokes	1995--2003	sfo-jax-nwe	WR	66	238	2913	12.24	44.1	49	141	1812	12.85	37
223	Charlie Sanders	1968--1977	det	TE	60	174	2643	15.19	44.1	50	151	1995	13.21	39.9
224	Kevin Johnson	1999--2005	cle-jax-rav-det	WR	38	133	1672	12.57	44	63	255	3063	12.01	48.6
225	Donte Stallworth	2002--2011	nor-phi-nwe-cle-rav-was	WR	61	164	2656	16.2	43.5	55	170	2372	13.95	43.1
226	Freddie Solomon	1975--1985	mia-sfo	WR	83	214	3595	16.8	43.3	63	191	2788	14.6	44.3
227	Ben Coates	1991--2000	nwe-rav	TE	70	276	3019	10.94	43.1	70	249	2794	11.22	39.9
228	Vernon Davis	2006--2011	sfo	TE	42	150	1811	12.07	43.1	45	164	2284	13.93	50.8
229	Rocket Ismail	1993--2001	rai-car-dal	WR	61	168	2617	15.58	42.9	65	204	2865	14.04	44.1
230	Qadry Ismail	1993--2002	min-mia-nor-rav-clt	WR	83	228	3544	15.54	42.7	58	143	1880	13.15	32.4
231	O.J. McDuffie	1993--2000	mia	WR	71	248	3005	12.12	42.3	52	217	2672	12.31	51.4
232	Mark Bavaro	1985--1994	nyg-cle-phi	TE	77	239	3254	13.62	42.3	40	142	1845	12.99	46.1
233	James Jett	1993--2001	rai	WR	55	127	2322	18.28	42.2	53	142	2269	15.98	42.8
234	Brent Jones	1987--1997	sfo	TE	113	366	4769	13.03	42.2	33	111	1166	10.5	35.3
235	Jeremy Shockey	2002--2011	nyg-nor-car	TE	82	309	3450	11.17	42.1	61	260	2918	11.22	47.8
236	Chris Calloway	1990--2000	pit-nyg-atl-nwe	WR	64	170	2691	15.83	42	72	223	2891	12.96	40.2
237	David Patten	1997--2008	nyg-cle-nwe-was-nor	WR	77	200	3236	16.18	42	63	144	1739	12.08	27.6
238	J.T. Smith	1978--1990	was-kan-crd	WR	64	211	2671	12.66	41.7	91	323	4172	12.92	45.8
239	Brandon Stokley	1999--2011	rav-clt-den-sea-nyg	WR	80	226	3295	14.58	41.2	49	156	2005	12.85	40.9
240	Calvin Williams	1990--1996	phi-rav	WR	58	184	2381	12.94	41.1	41	141	1744	12.37	42.5
241	Nate Burleson	2003--2011	min-sea-det	WR	64	210	2626	12.5	41	60	204	2576	12.63	42.9
242	Ron Jessie	1971--1981	det-ram-buf	WR	74	181	3031	16.75	41	43	96	1431	14.91	33.3
243	Keith Jackson	1988--1996	phi-mia-gnb	TE	87	288	3560	12.36	40.9	47	204	2557	12.53	54.4
244	Jeff Chadwick	1983--1992	det-sea-ram	WR	44	103	1799	17.47	40.9	62	191	2750	14.4	44.4
245	Curtis Duncan	1987--1993	oti	WR	58	210	2368	11.28	40.8	42	146	1841	12.61	43.8
246	Mike Sherrard	1986--1996	dal-sfo-nyg-den	WR	62	162	2528	15.6	40.8	32	104	1476	14.19	46.1
247	Shawn Jefferson	1991--2003	sdg-nwe-atl-det	WR	96	253	3914	15.47	40.8	88	244	3390	13.89	38.5
248	Marshall Faulk	1994--2005	clt-ram	RB	99	422	4022	9.53	40.6	89	397	3372	8.49	37.9
249	Jabar Gaffney	2002--2011	htx-nwe-den-was	WR	66	199	2681	13.47	40.6	82	269	3223	11.98	39.3
250	Willie Green	1991--1998	det-tam-car-den	WR	55	147	2233	15.19	40.6	35	117	1844	15.76	52.7
251	Todd Heap	2001--2011	rav-crd	TE	83	273	3369	12.34	40.6	63	250	2791	11.16	44.3
252	Mike Ditka	1961--1972	chi-phi-dal	TE	80	239	3240	13.56	40.5	54	184	2416	13.13	44.7
253	Torrance Small	1992--2001	nor-ram-clt-phi-nwe	WR	51	141	2053	14.56	40.3	71	213	2624	12.32	37
254	Peerless Price	1999--2007	buf-atl-dal	WR	54	159	2158	13.57	40	67	254	3244	12.77	48.4
255	Mike Renfro	1978--1987	oti-dal	WR	53	140	2117	15.12	39.9	60	190	2759	14.52	46
256	Quinn Early	1988--1999	sdg-nor-buf-nyj	WR	73	203	2914	14.35	39.9	76	278	3790	13.63	49.9
257	Chris Burkett	1985--1993	buf-nyj	WR	41	110	1635	14.86	39.9	66	185	2772	14.98	42
258	Ike Hilliard	1997--2008	nyg-tam	WR	79	258	3148	12.2	39.8	85	312	3534	11.33	41.6
259	Drew Bennett	2001--2008	oti-ram	WR	44	116	1752	15.1	39.8	53	205	2868	13.99	54.1
260	Jerricho Cotchery	2004--2011	nyj-pit	WR	62	206	2461	11.95	39.7	58	199	2761	13.87	47.6
261	Mike Pritchard	1991--1999	atl-den-sea	WR	58	172	2297	13.35	39.6	67	263	3043	11.57	45.4
262	Nate Washington	2005--2011	pit-oti	WR	55	139	2175	15.65	39.5	45	137	1892	13.81	42
263	Riley Odoms	1972--1983	den	TE	83	220	3279	14.9	39.5	61	176	2379	13.52	39
264	Sam McCullum	1974--1983	min-sea	WR	51	131	2003	15.29	39.3	63	150	2128	14.19	33.8
265	Jay Novacek	1985--1995	crd-dal	TE	84	298	3281	11.01	39.1	52	186	1994	10.72	38.3
266	Ozzie Newsome	1978--1990	cle	TE	102	324	3977	12.27	39	98	365	4376	11.99	44.7
267	Bob Trumpy	1968--1977	cin	TE-WR	60	147	2331	15.86	38.9	58	147	2103	14.31	36.3
268	Raymond Chester	1970--1981	rai-clt	TE	80	199	3099	15.57	38.7	63	172	2146	12.48	34.1
269	Travis Taylor	2000--2007	rav-min-rai-ram	WR	52	153	2013	13.16	38.7	50	172	2162	12.57	43.2
270	Joe Jurevicius	1998--2007	nyg-tam-sea-cle	WR	68	195	2629	13.48	38.7	51	145	1832	12.63	35.9
271	Wesley Walls	1989--2003	sfo-nor-car-gnb	TE	68	206	2604	12.64	38.3	81	253	2766	10.93	34.1
272	Ricky Proehl	1990--2006	crd-sea-chi-ram-car-clt	WR	112	299	4279	14.31	38.2	117	393	4962	12.63	42.4
273	Bob Tucker	1970--1980	nyg-min	TE	56	161	2129	13.22	38	82	255	3187	12.5	38.9
274	Steve Jordan	1982--1994	min	TE	86	255	3269	12.82	38	81	269	3381	12.57	41.7
275	Leonard Thompson	1975--1986	det	WR-HB	52	116	1976	17.03	38	80	169	2868	16.97	35.9
276	Charles Johnson	1994--2002	pit-phi-nwe-buf	WR	69	204	2616	12.82	37.9	49	173	2283	13.2	46.6
277	Jerry Smith	1965--1977	was	TE-WR	75	206	2841	13.79	37.9	60	190	2344	12.34	39.1
278	Rich Caster	1970--1981	nyj-oti-nor-was	TE-WR	58	123	2197	17.86	37.9	76	207	3385	16.35	44.5
279	Michael Jenkins	2004--2011	atl-min	WR	52	144	1954	13.57	37.6	54	184	2168	11.78	40.1
280	Alge Crumpler	2001--2010	atl-oti-nwe	TE	73	196	2740	13.98	37.5	68	191	2168	11.35	31.9
281	Paul Coffman	1979--1987	gnb-kan	TE	49	145	1838	12.68	37.5	62	196	2489	12.7	40.1
282	Courtney Hawkins	1992--2000	tam-pit	WR	55	170	2059	12.11	37.4	70	204	2572	12.61	36.7
283	Russ Francis	1975--1988	nwe-sfo	TE	96	277	3587	12.95	37.4	55	151	2149	14.23	39.1
284	Billy Cannon	1960--1970	oti-rai-kan	TE-RB	80	174	2986	17.16	37.3	31	81	945	11.67	30.5
285	Jimmie Giles	1977--1989	oti-tam-det-phi	TE	50	122	1861	15.25	37.2	88	232	3306	14.25	37.6
286	Brian Brennan	1984--1992	cle-cin-sdg	WR	61	172	2267	13.18	37.2	62	184	2378	12.92	38.4
287	Eric Green	1990--1999	pit-mia-rav-nyj	TE	55	167	2017	12.08	36.7	57	200	2488	12.44	43.6
288	Troy Brown	1993--2007	nwe	WR	120	392	4392	11.2	36.6	81	223	2668	11.96	32.9
289	Gino Cappelletti	1960--1970	nwe	FL-SE	63	132	2305	17.46	36.6	70	139	2037	14.65	29.1
290	Justin McCareins	2001--2008	oti-nyj	WR	61	145	2230	15.38	36.6	53	118	1806	15.31	34.1
291	Rick Upchurch	1975--1983	den	WR	67	151	2439	16.15	36.4	53	117	1939	16.57	36.6
292	Frank Wycheck	1993--2003	was-oti	TE	86	299	3129	10.46	36.4	67	243	2310	9.51	34.5
293	Heath Miller	2005--2011	pit	TE	80	239	2863	11.98	35.8	39	138	1498	10.86	38.4
294	Floyd Turner	1989--1998	nor-clt-rav	WR	46	129	1638	12.7	35.6	54	167	2382	14.26	44.1
295	Mark Ingram	1987--1996	nyg-mia-gnb-phi	WR	65	153	2301	15.04	35.4	47	128	1815	14.18	38.6
296	Ken Dilger	1995--2004	clt-tam	TE	69	192	2439	12.7	35.3	75	180	1819	10.11	24.3
297	Rodney Holman	1982--1995	cin-det	TE	81	210	2816	13.41	34.8	79	173	2200	12.72	27.8
298	Dennis Northcutt	2000--2009	cle-jax-det	WR	49	132	1702	12.89	34.7	97	278	3390	12.19	34.9
299	Pete Holohan	1981--1992	sdg-ram-kan-cle	TE	62	190	2149	11.31	34.7	63	189	1995	10.56	31.7
300	Mickey Shuler	1978--1991	nyj-phi	TE	68	222	2352	10.59	34.6	71	248	2845	11.47	40.1
301	Jerome Barkum	1972--1983	nyj	TE-WR	54	129	1855	14.38	34.4	72	201	2990	14.88	41.5
302	Az-Zahir Hakim	1998--2006	ram-det-nor	WR	57	145	1917	13.22	33.6	55	192	2558	13.32	46.5
303	Brian Westbrook	2002--2010	phi-sfo	RB	80	269	2658	9.88	33.2	49	203	1605	7.91	32.8
304	Larry Centers	1990--2003	crd-was-buf-nwe	FB	84	341	2782	8.16	33.1	119	507	4177	8.24	35.1
305	John L. Williams	1986--1995	sea-pit	FB	81	290	2677	9.23	33	75	287	2222	7.74	29.6
306	Brandon Lloyd	2003--2011	sfo-was-chi-den-ram	WR	32	81	1049	12.95	32.8	73	230	3735	16.24	51.2
307	Billy Johnson	1974--1988	oti-atl-was	WR	65	159	2110	13.27	32.5	71	176	2077	11.8	29.3
308	Randy McMichael	2002--2011	mia-ram-sdg	TE	53	160	1686	10.54	31.8	88	257	2802	10.9	31.8
309	Roger Craig	1983--1993	sfo-rai-min	RB	127	431	4005	9.29	31.5	53	195	1500	7.69	28.3
310	Ricky Watters	1992--2001	sfo-phi-sea	RB	91	289	2851	9.87	31.3	63	215	1815	8.44	28.8
311	Ronnie Harmon	1986--1997	buf-sdg-oti-chi	RB-WR	94	283	2934	10.37	31.2	89	350	3612	10.32	40.6
312	Tiki Barber	1997--2006	nyg	RB	80	267	2497	9.35	31.2	80	338	2817	8.33	35.2
313	Eric Metcalf	1989--2002	cle-atl-sdg-crd-car-was-gnb	RB-WR	83	238	2564	10.77	30.9	102	317	3185	10.05	31.2
314	Jim R. Mitchell	1969--1979	atl	TE	57	139	1759	12.65	30.9	66	160	2375	14.84	36
315	Keith Byars	1986--1998	phi-mia-nwe-nyj	FB-TE	119	390	3665	9.4	30.8	79	272	2439	8.97	30.9
316	Freddie Jones	1997--2004	sdg-crd	TE	37	109	1131	10.38	30.6	79	295	3101	10.51	39.3
317	Tony Nathan	1979--1987	mia	RB	89	290	2705	9.33	30.4	45	158	1536	9.72	34.1
318	Tony McGee	1993--2002	cin-dal	TE	39	92	1178	12.8	30.2	89	230	2911	12.66	32.7
319	Jackie Harris	1990--2001	gnb-tam-oti-dal	TE	63	157	1881	11.98	29.9	79	251	2650	10.56	33.5
320	Joe Morrison	1960--1972	nyg	RB-WR	66	147	1958	13.32	29.7	79	224	2747	12.26	34.8
321	Charle Young	1973--1985	phi-ram-sfo-sea	TE	76	190	2253	11.86	29.6	71	241	3002	12.46	42.3
322	David Hill	1976--1987	det-ram	TE	71	182	2091	11.49	29.5	76	187	2211	11.82	29.1
323	Billy Joe DuPree	1973--1983	dal	TE	101	213	2933	13.77	29	42	93	1079	11.6	25.7
324	Antwaan Randle El	2002--2010	pit-was	WR	88	184	2473	13.44	28.1	66	220	2402	10.92	36.4
325	Kelvin Martin	1987--1996	dal-sea-phi	WR	68	138	1839	13.33	27	74	238	3023	12.7	40.9
326	Thurman Thomas	1988--2000	buf-mia	RB	130	346	3411	9.86	26.2	71	202	1719	8.51	24.2
327	Marcus Pollard	1996--2008	clt-det-sea-atl	TE	81	183	2113	11.55	26.1	81	185	2402	12.98	29.7
328	LaDainian Tomlinson	2001--2011	sdg-nyj	RB	104	341	2683	7.87	25.8	76	308	2265	7.35	29.8
329	Walter Payton	1975--1987	chi	RB	113	278	2645	9.51	23.4	86	236	2071	8.78	24.1
330	Herschel Walker	1986--1997	dal-min-phi-nyg	RB	84	211	1957	9.27	23.3	106	311	2962	9.52	27.9
331	Kevin Faulk	1999--2011	nwe	RB	125	328	2885	8.8	23.1	54	154	1228	7.97	22.7
332	Marcus Allen	1982--1997	rai-kan	RB	145	341	3186	9.34	22	91	299	2755	9.21	30.3
333	Warrick Dunn	1997--2008	tam-atl	RB	98	244	2141	8.77	21.8	92	301	2454	8.15	26.7
334	Earnest Byner	1984--1997	cle-was-rav	RB	111	271	2399	8.85	21.6	102	278	2584	9.29	25.3
335	Tony Galbreath	1976--1987	nor-min-nyg	RB	79	175	1470	8.4	18.6	90	326	2667	8.18	29.6

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Three weeks ago, I set forth the argument that perhaps Calvin Johnson was not even the most productive receiver in his own division. While Megatron racked up the numbers, I argued that you have to account for the situation. The relevant situation here is that the Lions ran an incredible 1,160 plays compared to just 999 for the Bears, and Detroit attempted 740 passes while Chicago threw only 485 times.

When one team throws 255 more passes than the other, I don’t think it’s appropriate to compare the receivers based on their raw receiving yards. One thing we could look at is yards per team attempt. The table below lists the number of team attempts for each wide receiver, his raw receiving statistics, and also his yards per attempt. The table is sorted by yards per team passing attempt. And while it is not relevant when discussing Marshall and Megatron, I have also included a Pro-rated Yards per Attempt column, which pro-rates the number of team attempts for the number of games played by the receiver (this helps Percy Harvin, of course).

As it turns out, Calvin Johnson was neither the best Johnson nor the best receiver in his division, at least as measured by this metric. I’m not convinced or even arguing that yards/attempt is the best way to rank receivers, but I do think the statistic represents an improvement on just receiving yards. Since receiving yards are so highly correlated with attempts, some adjustment needs to be made, and I plan on providing more analysis on how to grade wide receivers this off-season.
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