Category: Free Content

Comparing Quarterback Results With the Jimmy Johnson Chart

In an earlier post I wrote that the Jimmy Johnson Chart is not consistent with a reasonable expectation of the range of human abilities.  The Jimmy Johnson Chart presupposes a group of super-human football players at the top of the draft each year, when those football players don’t exist in reality.  I used the example of wide receiver performance, and the fact that experts often disagree as to the best prospect in a draft, to illustrate this point.

But because people often associate the very top of the draft with quarterbacks, I figured it would be useful to look at quarterback results as well.  We’ll be looking at each quarterback taken at each pick in the draft, and how that quarterback performs relative to the other QBs in career yards thrown.  To put it in terms that can be compared with the Jimmy Johnson Chart, we’ll convert those performances to Standard Deviations Above Average.

Here is a graph which shows how each pick in the draft has fared in terms of standard deviations above average.  The comparison group is each other quarterback in the draft.  For instance, Peyton Manning is 2 standard deviations above the average for his draft class.  I do that and then average out every pick in the draft and create a trend line.image

The first thing to note is that the points are scattershot.  That’s consistent with my argument that experts often disagree as to who is good and who isn’t good.  Talent evaluation is hard.  The scattershot nature of the graph above reflects how difficult talent evaluation is.  The second thing to note is that the trend is fairly flat.  It is not steep like the JJ Chart.

We can compare that trend against the Jimmy Johnson Chart to see if the real world of quarterback abilities is actually consistent with the theoretical world of abilities presupposed by the JJ Chart.  On the graph below I show the trend for QBs and WRs, along with the Jimmy Johnson values.  The JJ Chart starts at 6 SDs above average.  Real world results suggest a more reasonable expectation is 2 SDs above average.


I’ve never met a point I didn’t beat into the ground and this one is no different, so I am going to say it again.  The Jimmy Johnson Chart offers a view of football talent that doesn’t exist in reality.  The super-human football players that the JJ Chart assumes are available, aren’t actually available.

All of my analysis has been based on averages because that’s really the way you have to look at it.  You have to throw Peyton Manning, Sam Bradford, David Carr, Jamarcus Russell, Eli Manning, and Matt Stafford in an imaginary bag and pretend that you’re going to reach into the bag and pull out a name.  But even if you didn’t look at it that way, even if you assumed that you could pick with total clairvoyance, your picks would not be as unique as the JJ Chart says they would be.  No quarterback in the last 20 years is 6 standard deviations above the rest of the quarterbacks in his draft class.

More Problems with the Jimmy Johnson Draft Chart

Last night I suggested on Twitter that the Jimmy Johnson Chart has another problem that people seem to overlook.  Everyone knows that NFL talent evaluators often disagree on the rankings of prospects.  That’s actually to be expected.  Reasonable people can often disagree.  But it does present a problem for the Jimmy Johnson Chart.  The Jimmy Johnson Chart says that the universe of NFL abilities is one made up of a very few elite performers.  The falloff from the top picks is steep.


But if reasonable experts often disagree as to the rankings of prospects, then the talent curve is not shaped like the Jimmy Johnson Chart says it is.  The Jimmy Johnson Chart says that the talent curve is steep.  But disagreement among experts implies that the talent curve is flatter (flatter like the kind of flat I proposed the other day).

Let’s take this year’s wide receiver class as an example.

Below I’ve listed the top three wide receiver rankings of three NFL talent evaluators (media, not team employed).  None of them share the same ordering of prospects.  That strikes me as reasonable.  Josh Norris has Kendall Wright as the top WR, Mike Mayock has Blackmon, and Bleacher Report’s Matt Miller has Alshon Jeffery on top.

Josh Norris

Rank Name
1 Kendall Wright
2 Michael Floyd
3 Justin Blackmon


Mike Mayock

Rank Name
1 Justin Blackmon
2 Michael Floyd
3 Kendall Wright


Matt Miller

Rank Name
1 Alshon Jeffery
2 Michael Floyd
3 Kendall Wright


I can anticipate an objection where someone might say “Yes, but this year’s wide receiver class is an outlier and usually talent isn’t that flat.  Usually it follows a steeper falloff as shown in the JJ Chart.”

But the problem with the JJ Chart is how steep the falloff is.  The JJ Chart isn’t believable based on what we can observe of the range of human abilities.  The first overall pick value is 6 standard deviations above the average pick value.  That implies the existence of individuals with other-worldly football ability.  If individuals like that actually existed, they would be so obvious in talent that there would be no debate as to their ability or where they might rank among their peers.  Six standard deviations implies almost super human ability.  I can’t think of a single individual that has entered the draft without debate as to their abilities.  Peyton Manning wasn’t even the clear cut #1 selection.  He turned out to be better than Ryan Leaf, but there was no consensus pre-draft.  Even Calvin Johnson, who is a physical freak and was an accomplished wide receiver in college, is only about 3.2 standard deviations above the other receivers in his class in terms of receiving yards.  That’s actually really good.  It’s ridiculous actually.  But it’s nowhere near 6 standard deviations and he’s the the closest thing I can think of to an other-worldly individual in terms of football ability.

Here’s a graph which shows how many standard deviations above average each pick in the draft has averaged in the past 20 years (wide receivers only).  There are no receivers who are 6 SDs above average, and when you then average it for each pick, the numbers come down to earth even more (Keyshawn Johnson and Carlos Rogers pull the numbers down while Larry Fitzgerald, Andre Johnson, and Calvin Johnson push the numbers up).


Now let’s look at that same trendline when shown along with what the JJ Chart says we should expect from each pick relative to the average.  Again, the JJ Chart starts at 6 SDs above average.  But the expectation for actual wide receiver performance says that the very top is closer to 2 SDs over average.


The problem with the JJ Chart is that it asks us to subscribe to a view of human abilities that doesn’t actually exist.  When it does that, it misprices the value of the assets that it purports to be a price sheet for.

Teams that use the Jimmy Johnson Chart to buy picks are operating under a view of football abilities that isn’t supported by reality.  Teams that use the Jimmy Johnson Chart to sell picks are taking advantage of the teams willing to buy on those terms.

How Old is Too Old for a Fantasy Running Back?

I’ve posted before on the effects that age might have wide receivers and coaches.  I’ve even posted on running backs, although I looked at running back yards/carry rather than any fantasy football measure.  Based on a request from @vote4parag on Twitter I took a look at running backs from a fantasy standpoint. 

The graph below is the result of that analysis.  I looked at each running back relative to their career peak.  That’s an important point.  I’m not measuring each running back against every other running back.  I’m only comparing each guy with his career peak in terms of fantasy points/game.

Running backs basically peak when they’re 23-25.  The age of 24 seems to be the absolute peak.


Once again, these are just averages.  Not every back is going to conform to the average.

For purposes of actionable fantasy intelligence, how should we think about these results?  I don’t think you should be looking to get out of every 25+ year old back on your roster.  First, if you have a running back that catches passes, I think those are the backs you shouldn’t be pushing the eject button on.  Those guys will stay relevant longer.  I would be worried about any 26-ish back who gets most of his points from the running game and is also nearing the dreaded 4 yards per carry mark.  The other thing to think about is the fact that 80% of a stud running back (that’s the expectation at 29 years old) is often better than 100% of a 24 year old running back who might be unproven.

Because people always respond to examples better than they do to generalizations, here are the career graphs of a few running backs.  I show the trend for all backs so that you can see how each guy’s career arc differs a little from the average.








Offered for Consideration: Yet Another Theory of Draft Pick Value

Here’s my general outlook on conventional wisdom: It might be right… or it might not be.  But I don’t have a lot of reverence for conventional wisdom.  I just think there are too many examples of truths that we took for granted at one point, only to find out later that those truths weren’t actually… wait for it… true.  Probably my favorite example of the idiocy of conventional wisdom is the fact that Galileo was sentenced to house arrest for supporting the heliocentric view of the solar system and questioning the earth-centric view.

It strikes me that the current debate surrounding the value of NFL draft picks is a classic debate over the value of conventional wisdom.  The Harvard Sports Analysis Collective (HSAC) has advanced a theory of draft pick value (Harvard Chart) based on some analysis that disagrees with conventional wisdom.  The Harvard Chart is often the subject of criticism from adherents of the traditional system for valuing draft picks (which I will call the Jimmy Johnson Chart).

If you want to read a compelling criticism of the Harvard Chart, check out @SigmundBloom on Bleacher Report.  I posted a short response on Bloom’s article if you want to check that out.  But this post is going to go in another direction, so it wasn’t really appropriate as a comment.

I actually don’t think you can have just one theory of valuation for draft picks.  I think it depends on the team and what the team needs.  Good teams and bad teams aren’t going to have the same types of needs in the draft.  I’m always more interested in the shitty teams (the Patriots and the Packers don’t need any help) so let’s start there.  Here’s my general theory of how shitty football teams should think about their rosters:

  1. Football teams start 22 men (not counting special teams)
  2. Football is a violent sport which often results in losing players for games or even full seasons.
  3. Shitty teams are almost never just one player away.  If they were just one player away, they would be 8-8, not 2-14.
  4. Because of numbers 1 through 3, shitty teams should be looking to stockpile players.  They don’t just need one or two players.  They are often starting a number of players that couldn’t start on any other team.

Given those assumptions that I have about shitty teams and their draft needs, here is a chart that is based not on player value, but on how many “Games Started” you can expect to get from each pick in the draft.  image

But here’s something important.  When you’re talking about “expect”, it becomes pretty important how you define “expect”.  Should you define the expectation as being the average of games played for each draft spot?  That might not work. 

Consider for example 10 hypothetical picks from the 6th round.  Let’s say that 9 of the 10 players never start an NFL game.  But let’s say the other guy starts 120 games.  The average games started for the group is 12.  But 9 out of the 10 guys were well below the average.  This is what you could call skewness.  One outlier in the group is having an outsized impact on the average.

For that reason I used median games started as the measurement in the graph below.  That creates a more accurate picture of what you can “expect” to get out of each pick.  Half of the players picked in that slot will be better than the median and half will be worse.

If we’re talking about improving shitty teams, then what we really want is to pick a number of guys who can come in and contribute right away.  We want NFL starters.  That’s what the theory of draft value that I am proposing would give you.

Let’s compare this theory of draft value to the Jimmy Johnson Chart and the Harvard Chart.


My theory disagrees with the JJ Chart on the equivalent value of early picks and agrees with the JJ Chart on the worthlessness of the late picks.


My theory disagrees with the Harvard Chart on the value of late picks (HC says they’re worth something, I say they aren’t), but agrees more with the Harvard Chart on the value of the early picks.

I think my theory of value addresses a shortcoming in the Harvard Chart that @RumfordJohnny and I were discussing.  NFL teams have a limited ability to even evaluate all of the talent they have in camp.  Bringing in 20 guys from the 6th round isn’t that helpful when you have just a few weeks to get a look at them.  My theory of value would place very little value in those guys. 

There’s also another problem with the late round picks.  They aren’t much better than undrafted free agents, which have no draft value.  It just doesn’t make sense that you would assign value to a pick that might only be slightly better than a guy you could bring in off the street.

As to the Jimmy Johnson Chart, here’s a problem with it that its defenders would have a hard time explaining.  According to the JJ Chart, the 7th and 8th picks added together don’t equal the value of the number one overall pick.  If you’re a shitty team and you have a million holes to plug, wouldn’t you rather have two top 10 picks than just the one guy at the top of the draft?  I would.

To get back to a point I made in the beginning of this post, this doesn’t have to be a one size fits all theory of drafting.  After a team compiles enough starter-level players to dig themselves out of the cellar, then they can think about whether they might be one player away.  But until then, they should keep in mind that they are playing a violent sport that starts 22 players.

One more thing to add about being “one player away”.  Two of the greatest quarterbacks to ever put on a uniform, Peyton Manning and Dan Marino, have a combined one Super Bowl win.  Football is a team sport.  The Jimmy Johnson Chart ignores that reality.

At What Age Do Wide Receivers Peak in Fantasy Value?


(Marvin Harrison pictured because the Fantasy Douche once stayed on the Marvin Harrison bus a little too long)

In the past I’ve written on the effect that age has on coaches and running backs.  Because I’ve sort of railed against a team giving up a first round pick for Mike Wallace and then giving him a big contract, I thought I would look at the effect that age has on wide receivers.

One of my key arguments against paying Mike Wallace has been that he will be 26 next year, which will make him 28 in the third year of his deal.  I’ve also made the argument that a small receiver like Wallace requires 4.3 speed to get open/produce and that might leave him by the time he’s 28 (although I will get to that part of the argument tomorrow and the graph below isn’t enough to establish whether that point is true or not).

The following graph shows receiver (all non-RB ball catchers) production (fantasy points per game) as a percent of peak season production.  Basically a WR will peak between the time that they are between 24 and 26.  The important thing to remember is that this is comparing each receiver against themselves.  This is not comparing each receiver with every other receiver.


Because people always respond to examples better than statistics, I figured I would offer a few.

  • Andre Johnson had his best per game fantasy numbers in 2007 when he caught 8 touchdowns in just 9 games.  He was 26 that year.
  • Larry Fitzgerald was 25 during his 2008 season when he caught 12 touchdowns.
  • Dwayne Bowe was 26 during the 2010 season when he set a personal best for touchdowns.
  • Brandon Marshall was 25 during the 2009 season when he caught 1100 yards and 10 touchdowns.


Obviously there are going to be exceptions, and the graph above is only based on averages.  Randy Moss was obviously ridiculous in 2007.  He was 30 that year.  Steve Smith had a very good season last year.  Marvin Harrison obviously had his better years in his late 20s and early 30s.

But on average, receivers have their best season in their mid-20s.

For fantasy purposes I’ll be using the graph above to make sure that I am targeting guys who are entering, or still in their prime.  To me it’s a simple value thing.  If you can still get a guy who is on his way up, you’re not paying for production that is more likely to increase vs. decrease.  It’s also important to note that this is a probability thing, not a certainty thing.  When you double down in blackjack, the dealer is going to throw some 4′s out there.

What does this mean for my point about Mike Wallace and whether age should be a consideration for a team that might sign him?

  1. Receivers do tend to decline in production after 26.  Whether or not it’s dramatic enough to price in to free agent contracts is difficult to say I guess.  I actually think this really comes down to a judgment call.
  2. Maybe receivers have four career phases:
    1. 21-22 – Getting Good
    2. 23-27 – Being Good
    3. 28-30 – Trying to stay good
    4. 30+ – The Steady Decline
  3. To me the value tradeoff for free agents basically comes down to this:  You’re paying for peak production and you’re probably going to get 90-95% of that peak production.  So to me it mostly comes down to salary, not really declining production.  Although teams should keep age in mind when doing free agent deals.

Excerpt from Game Plan: That’s Genius

Cover-Price“Game Plan: A Radical Approach to Decision Making in the NFL” is now on sale for $0.99 at  The below excerpt is from Game Plan’s opening chapter.

That’s Genius

Implicit in the coverage of the National Football League’s coaches is notion that football coaches are geniuses. The idea that lifelong football men are elite in some cognitive sense is prominent when the NFL is discussed.

There are the obvious geniuses like Bill Walsh. Walsh was the legendary architect of the West Coast offense who also helped the San Francisco 49ers build a dynasty. New England Patriots head coach Bill Belichick is probably in Walsh’s company. Belichick’s defenses have appeared in no fewer than eight Super Bowls. Former Seahawks and Packers head coach Mike Holmgren has also been called a “mad genius,” based on his body of work coaching offenses to the Super Bowl and even winning a few as a head coach and a coordinator. Walsh, Belichick and Holmgren have unassailable records. The genius label might be appropriate in their cases.

But then there are the lesser geniuses. In an article in the New York Times, former Giants head coach Jim Fassel is described as an “offensive genius”. But Fassel has had only one top five scoring offense during any of his 13 years as an offensive coordinator or head coach.

Former Browns and Jets head coach Eric Mangini had, for a while, the nickname “Man-genius”, even though the label may have been prematurely applied to a coach who didn’t last very long at either of his coaching stops.

During an episode of Monday Night Football in 2000, comedian co-host of the show Dennis Miller called then Denver head coach Mike Shanahan a genius not once, but four times. Miller isn’t anyone’s favorite football analyst, but he was only voicing a commonly held belief among football’s chattering class. Shanahan was regarded as a genius at that time. But he hasn’t been much of a genius since. Shanahan’s offenses haven’t been in the top five in the league since that year, and he hasn’t cracked the top 10 since 2006.

Former Redskins coach Steve Spurrier was regarded as a genius on his way into the league and a short two seasons later he left the league as something of a joke.

Former Ravens coach Brian Billick was hired for his only head coaching job based on his reputation as an offensive genius. But while head coach of the Ravens, they had just one top ten offense in nine years.

The architect of the St. Louis Rams’ “Greatest Show on Turf”, Mike Martz, was regarded as an offensive genius. The label even managed to stick after his offenses stopped cracking the top half of the league in points scored.

The NFL it seems is a league made up of genius coaches, coaching against other genius coaches…even though some of them aren’t even above average.

An interesting question is whether football’s geniuses resemble real geniuses in any meaningful way? On at least one important point, they do not. Geniuses often have displayed their gift by a young age. Football coaches are not young people. Over the past 30 years, the average age of an NFL coach is about 51 years old.

Contrast the middle agedness of football coaches with Albert Einstein who was 26 when he published the paper that contained his thoughts on relativity.

Isaac Newton was just 24 when he published his first discussion of what would later become calculus.

Thomas Edison developed the light bulb at the age of 32.

Gary Kasparov became the undisputed World Chess Champion at the age of 22. He wasn’t even especially young for a great chess player. The average age of a first time Grand Master is now about 23 years old.

Mick Jagger and Keith Richards were 22 when they wrote “Satisfaction”.

Steve Wozniak started designing the hardware and operating system for the Apple I at the age of 21. By 26 he and Steve Jobs had founded Apple.

Bob Dylan wrote arguably his greatest song, “Like a Rolling Stone”, when he was 24.

F. Scott Fitzgerald was 29 when “The Great Gatsby” was published.

J.D. Salinger was 32 when “The Catcher in the Rye” was published.

The Wright Brothers took the world’s first flight when Orville was 32 and Wilbur was 37.

Mark Zuckerberg launched Facebook when he was 20 years old.

Sergey Brin and Larry Page were just 23 when they invented the PageRank algorithm that tells Google what pages on the web are more important than other pages.

Why is it that a genius can invent Facebook, or Google, or write one of the greatest American novels, or write two of the greatest rock songs, or discover the theory of relativity, all in their 20s, but our football coaches are more demographically similar to a high school vice principal? Why is it that great chess players become grandmasters at 23 and for some reason you have to be 50 years old to understand the 4-3 defense?

This is the point in the conversation where football people attempt to make it seem as if their sport is beyond understanding, or as if the scope of a football coach’s knowledge might be wider than chess master Gary Kasparov’s knowledge. But this is an easy claim to embarrass. It’s easy to embarrass because 25 year old football players are responsible for understanding the game. A 25 year old linebacker has to be able to understand the 4-3 defense, although for some reason it takes another 25 years to be able to coach it. That seems like a long time. In that amount of time you could go to medical school and become a brain surgeon… twice.

There is another gaping hole in the idea that coaches somehow need an additional 25 years of age on top of the ages of the athletes that play the game. In 2011, the Denver Broncos made a midseason quarterback change when they benched Kyle Orton in favor of former Heisman Trophy winning quarterback Tim Tebow. When the Broncos did that, they drastically changed their offensive scheme in favor of a spread offense, similar to the one that Tebow had run at Florida. But according to accounts at that time, Tebow was responsible for helping the coaches understand the offense. The coaches were used to a pro-style offense and didn’t know the spread offense.

The way that the Broncos changed quarterbacks at midseason, changed the offense to one the coaches weren’t familiar with, and then succeeded to make the playoffs, is a black mark on the idea that somehow offensive coordinators need 20 years of experience in the West Coast offense in order to be successful.

Maybe the reason football coaches are older is that being a football coach is a management position and it takes most of a lifetime to learn the people skills related to coaching. But Facebook is more valuable than all of the NFL’s teams (combined) and Facebook has a 27 year old sitting in the CEO’s chair. Mark Zuckerberg is just one example.

Any number of technology company CEOs are under 30 years old. They include the CEOs of Foursquare,, LivingSocial, Spotify, and Dropbox. Several of these businesses are on par, or more valuable, than a number of NFL teams.

For instance, Dropbox is a company that is moving file storage online. It has a $4 billion valuation, which would be roughly like adding the value of the Washington Redskins and the Dallas Cowboys together. Dropbox’s 28 year old CEO both conceived of the idea of Dropbox and also runs the company. Dropbox is expanding to 400 employees. Why is it then that a 20-something can conceive of and run a company like Facebook or Dropbox, but again, NFL coaches are roughly the ages of elected politicians?

At this point someone might point to the macho culture of the NFL and say that while a 28 year old might be respected to lead a $4 billion tech business, that same person might not be respected in the NFL. But if it’s leadership and respect that we’re talking about, then the U.S. military might have something to say. The military trains 20-somethings to lead about the same number of people that might be on a football team. The book “Outlaw Platoon” is a true story written by Captain Sean Parnell. Parnell led the legendary 10th Mountain Division in Afghanistan where they were tasked with hunting down insurgents near the Pakistani border. Parnell was named commander of the 10th Mountain Division when he was 24. He was responsible for the lives of 40 other men when he was half the age of the typical NFL coach. Unless those men trust and respect him, it’s unlikely any of them go home alive. He wasn’t ordering around 53 guys on a football field. His job was to return his entire division safe to their families. He performed a job that required mental ability and leadership. He also retired from the military by the time he was 30.

There’s a Good Chance You’re Following These People… But Just in Case (Under 20k Followers)

One more football related list of twitter accounts here.  You’re probably already following all of these people.  But just in case, check out the list below.  Also, I didn’t confine to just fantasy writers because at this level the writers are often covering fantasy and/or real football.


Name Followers Link Details
Mike Clay 6019 PFF_MikeClay NFL Writer/Stathead. Founder/Managing Editor at Pro Football Focus: Fantasy. Writer at NBC Rotoworld. Creator of aDOT. Also an Accountant.
Chris Wesseling 9294 ChrisWesseling Senior NFL football editor at, writer for, creator of Sons of the Tundra Dynasty Rankings blog, part-time roisterer.
Evan Silva 16875 evansilva Senior NFL Editor for Rotoworld, writer for NBC Sports &
Matt Williamson 19712 WilliamsonNFL NFL Scout for and Scouts, Inc. Also host of Football Today Podcast.
Sigmund Bloom 9613 SigmundBloom NFL Draft lead writer for Bleacher Report, Audible co-host, projector, writer for, Stay-at-Home Dad, Pontificater
Wes Bunting 15484 WesBunting Blogger @NFPost
Stephanie Stradley 5346 StephStradley Write about Houston Texans @ Houston Chronicle Online & sports formerly @ AOL Sports FanHouse. Lawyer too. Try to be nice, helpful one.
Russell Lande 5349 RUSSLANDE NFL DRAFT EXPERT for GM Jr. Scouting ( & The Sporting News (
Dave Richard 17941 daverichard Sports news and analysis for Fantasy Football by writer Dave Richard, an NFL talent evaluator & member of Pro Football Writers of America.
Cecil Lammey 5836 cecillammey NFL Insider for 102.3 ESPN Denver and senior writer for
Aaron Nagler 8050 Aaron_Nagler National lead NFL blogger for @BleacherReport, Co-Founder, @CheeseheadTV, husband and father.
Walter Cherepinsky 11297 walterfootball
SC_DougFarrar 14206 SC_DougFarrar Football dork for Yahoo Sports; Editor of Shutdown Corner. Team player w/rebellious tendencies. Yes, I am pissed off for greatness.
Greg A. Bedard 18976 GregABedard Wet Blanket of Reason. And, oh yeah, Boston Globe NFL writer, father and husband.
Jay Clemons 5382 ATL_JayClemons Former award-winning writer with who’s now killing it with Bleacher Report. Future Oscar and Razzie nominee for Best/Worst Original Screenplay, as well.
Brad Evans 15663 YahooNoise Award-winning Yahoo! Sports Fantasy columnist, Fantasy Football Live contributor, Freak Show host on YSR, bracketologist and owner/operator of TEAM HUEVOS.
Smart Football 18360 smartfootball Chris Brown, editor of Smart Football.
Dave Razzano 5268 DaveRazzano NFL scout for more than 22 yrs,49ers, Rams, Cardinals. Have wrked with 5 Super Bwl teams. NFL Analyst on 95.7 TheGame in S.F.
Adam Levitan 5595 adamlevitan Rotoworld NFL/NBA writer, Metro Philly Sixers/fantasy writer, wannabe NBA general manager.
Joe Fortenbaugh 6221 JoeFortenbaugh Writer @ The National Football Post.  Travel, golf, wine=good.  Not covering the spread=bad.
KC Joyner 6697 KCJoynerTFS NFL, Fantasy Football & College Football Insider

Want to Know Why NFL Decision Making is Bad? Start in the Owner’s Box

Cover-PriceIn Game Plan (which is available for less than $1 I might add) I argue that decision making in the NFL isn’t actually any good, and that there are a number of things that teams could do to improve that decision making.

The obvious objection to this thesis is as follows:

NFL teams are owned by businessmen who have been successful enough to acquire enough capital to buy a team.  They must be pretty smart.

But my sense is that this argument isn’t based in reality.  To illustrate this point, let’s look at the sale of baseball’s Los Angeles Dodgers, which is currently underway.  From the New York Times Dealbook blog:

Using insurance money — which is typically supposed to be invested in simple, safe assets — to buy a baseball team, the ultimate toy for the ultrarich, seems like a lawsuit waiting to happen. Mr. Walters has been somewhat open in acknowledging that Guggenheim’s companies will be tapped, but the investor group has not disclosed how much of the purchase price is coming from individuals.

The transaction seems even more questionable when considering Mr. Walter’s own words to The New York Times two weeks ago: “I don’t want to realize a return on investment on buying the Dodgers. I want to have a multigenerational relationship that changes my life, Magic’s life, Magic’s grandchildren’s lives and all of our lives.”

Buying a sports teams isn’t a business decision.  The decision doesn’t have anything to do with making money.  As Malcolm Gladwell has argued, it’s like buying a piece of art.  Sometimes that art appreciates in value, but that is just a happy accident when it happens.  The owner is going to enjoy it regardless of whether it appreciates in value.

The total universe of sports team owners is not going to be biased towards the best and the brightest business owners.  Instead it will be biased towards people who see value in conspicuous consumption.  It doesn’t end there.  Any winning bidder in a competitive bidding process is going to be impacted by what is known as Winner’s Curse.  They paid more for the team than anybody else was willing to. 

Now we really have a problem.  We have conspicuous consumers who paid more for a team than anybody else would.  What would that tell us about the quality of football decisions that are likely to emanate from the owner’s box after this happens?

There are no doubt good team owners.  But the problem is that our perception of them as being good team owners is because they are competing against 25 guys who make decisions like the “Real Housewives” choose implant doctors.  We really don’t know how good the “good” team owners are.


Announcing the Mock Draft Free Roll (You Could Be the Proud Owner of $50)


Just some more semi-gambling fun here.  I figured it would be fun to have a mock draft contest in the spirit of the NCAA tournament contests.  The winner will get $50.  Also, @RumfordJohnny has been nice enough to throw in a custom twitter avatar ($20 value – example ) for the 2nd place finisher.

Here are the rules:

  1. Your entry fee is that you have to have re-tweeted the tweet that announced the contest.  I don’t care if you have 8 followers and they’re all spam bots.  Go re-tweet that message.  I’m keeping track because I’m a dick like that.
  2. For each draft pick just choose the player you think will go in that spot.  The pull down list contains the names of about the top 50 prospects.
  3. Even if the team currently in that slot trades out, you still have to match up each player with the draft spot that they go in.
  4. If a player gets picked in the first round and that player isn’t in your first round, I’m just going to mark you down for slotting that player in the 33rd spot.
  5. After the draft I will tally up the absolute error for each entry and award the winner to the entry that had the lowest total absolute errors.  Absolute error means that if you say Trent Richardson is going 4th and he goes 6th, that’s 2 spots of absolute error.  If he goes 2nd, that’s still 2 spots of absolute error.  If Richardson fell to the 40th pick then your absolute error is 36 picks.
  6. Because I could see things getting tight, I have a tie breaker that should be pretty difficult.  You have to guess Marvin McNutt’s draft spot.
  7. You can enter as many times as you want.  However, I’m using the last entry you submit.  So basically if you change your mind, you can come back and re-enter.
  8. I’ll lock the entries on Thursday 4/26 at noon PST.  Then I’ll post all of the entries on a Google doc so that you can check your progress as the draft happens.


Why the Film Study Crowd and the Stats Crowd are Both Half-Right


As Ryan Forbes and I discussed last night on the 2Mugs Podcast, there is a brewing battle between the people who think the film doesn’t lie and people who think numbers don’t lie (see: Pete Prisco v. Pro Football Focus).  I’m in the numbers group just because I don’t know enough about football to actually “grind tape”.  When I watch basketball games I actually do look for things like whether a shooter gets set, whether he shoots with balance, and whether he keeps his elbow in. 

But I don’t know enough about football to do those things, so I use the only tool I have.  I use numbers.

The funny thing though is that numbers actually work pretty well.  If you had a contest between stats and scouts to see who could better predict NFL wide receiver production, the stats would win.  NFL draft position isn’t as indicative of WR production as a simple algorithm based on college touchdowns per game and college share of passing yards.  Draft position is the scouting baseline and it can’t beat a simple algorithm.

But to use only film study OR stats is only getting the answer half right.  If you combine the two, you can explain more of WR production than either can on its own.  That’s why both crowds are half right.

I actually think the ideal scouting system is one similar to the way that Pandora classifies music.  They use expert musicians who are responsible for assigning scores to each song based on set parameters like major key tonality, percussion, etc.  A scouting system that worked like this would involve knowledgeable football people scoring prospects based on a set criteria.

The important thing is to agree to the criteria and how they would be weighted ahead of time.  The other important thing about doing evaluation this way is that it can get better over time.  Let’s say that you weighted offensive linemen evaluations heavily towards footwork.  You could then go back and see if the offensive linemen who scored well on footwork were actually the best linemen.  Maybe you would adjust your scoring to weigh more heavily towards upper body strength.

If you enjoy ideas like this, be sure to check out my book Game Plan: A Radical Approach to Decision Making in the NFL


Not Following These 25 Fantasy Football Twitter Accounts is Like Admitting That You Drink Zima (Under 5k Followers)

zimaFirst of all, I have no idea if they even make Zima anymore.  If they don’t then I really burned myself there by trying to come up with an ironic reference that only dates me and makes me seem less cool.

Second, I’m using the same methodology I’ve used before.  As @RyFo18 says, this is Pandora for Twitter accounts.  Each of these twitter accounts is followed by a group of fantasy foobtall mavens in greater numbers than can be accounted for by their total followers.

Only accounts under 5,000 followers are listed.

Name Followers Link Details
Chet 4977 Chet_G I write about fake sports in an ironic way as to remain pseudo-hipster. Check me out at Razzball Football and other such places. #fantasyNFL
Bryan Fontaine 2622 Bryan_Fontaine Dynasty Editor/Senior Writer and Quick Snap podcast host for @PFF_Fantasy  – member of the @FSWA – Fantasy Football Stat Geek. Fan of @NFL
Jim Day 3916 Fantasytaz Anything and everything Fantasy Football at and….
Andy Miley 2432 AndrewMiley 20 year FF vet, co-founder of, staff writer for &, FSWA member
Josh Norris 3380 JoshNorris Rotoworld NFL Draft Contributor. One NFL Team’s Scouting Department Intern during ’10 Training Camp & ’11 NFL Draft. Elon Graduate.
John Paulsen 4314 4for4_John FantasyPros Most Accurate Fantasy Football Expert of 2010. (#2 in 2011.) Winner of 2011 FFLibrarian/FSTA Accuracy Challenge. Senior Editor, @4for4football
Matt Waldman 4495 MattWaldman Magazine journalist. Rookie Scouting Portfolio author and blogger. and Football columnist. Acolyte of Trane, Newk, and Brecker.
Sablich Brothers 2612 5thDownFantasy Jason and Justin Sablich provide fantasy football and baseball advice for @nytimes. Top 5 in @FantasyPros_NFL 2011 accuracy challenge. Also see @JSablichNYT.
Ryan Burns 2844 FtblSickness Editor-in-Chief of FOOTBALLSICKNESS.COM, THE Online Community For Pigskin Addicts.  Get Your Helmet On!
Jene Bramel 2906 JeneBramel Dad, Doc, Defensive Diehard, staff writer for, contributor to Matt Waldman’s RSP blog and the NY Times Fifth Down blog.
Melissa Jacobs 3884 thefootballgirl Managing Editor, espnW contributor.  Current likes: My husband, my infant son, Jim Harbaugh, karaoke.  Order changes daily.
Nathan Jahnke 2129 PFF_NateJahnke I’m an analyst and writer for @profootbalfocus as well as the Fantasy side of PFF.
Aaron Aloysius 2395 AaronAloysius Draft prospect video guy ( who writes for & Avatar by the great @RumfordJohnny
Shane P. Hallam 3835 ShanePHallam Fantasy Football/NFL Draft Expert.  Draft Analyst  Member of the Football Writer’s Association of America
David Dodds 2136 fbg_dodds Trying my best to ruin job productivity everywhere. Co-owner of
Liz Loza 2407 TheFFGirl A Fantasy Football enthusiast/expert who loves a good tight end and shares a b-day w/ Coach Ditka.  Some things are destined. (Also check out
Josh Moore 2721 4for4_Josh Owner & Editor of Top 5 Most Accurate Expert (FantasyPros). Primarily I predict the future. I also tweet a lot, mostly about sports.
Andrew Garda 2841 Andrew_Garda Footballguys Staff writer, NFC North lead writer for Lucky dad and husband, huge nerd.
Sara Holladay 2843 fflibrarian Fantasy Football Librarian
Michael Schottey 3621 Schottey NFL Associate Editor at Bleacher Report, Member of the Pro Football Writers of America.
Christopher Hansen 4797 RaidersBlog Owner of & #Oakland #Raiders featured columnist for @BleacherReport.
William Del Pilar 2056 wdelpilar Built and led during glory years (97-06). Sold in ’06. Created player news format that’s now industry standard. Former and FSV board member.
Josh Buchanan 2070 JoshBDraft owner, former all-star game scout/SID, Pro Hopefuls writer for, Phil Steele writer, and FWAA/PFWA member.
Ryan Lownes 2127 ryanlownes NFL Draft analyst, enthusiast, and writer for Undergraduate student at Ohio University from the Philadelphia area. Let’s talk some football.

Game Plan: A Radical Approach to Decision Making in the NFL

Cover-PriceToday I’m proud to announce the release of my new book Game Plan: A Radical Approach to Decision Making in the National Football League.  I’m calling it the ultimate book for the thinking football fan.

I could use this post to tell you all of the good things in the book, but I thought a more productive use of our time (I’m here, you’re here, it is our time after all) would be to tell you what’s in it for you.

  1. The book is super cheap.  Priced at just $0.99, you can buy the e-book for basically the cost of a song on iTunes.  But this is a full book.  It’s over 50,000 words of anecdotes, examples, stories and analysis that cover how NFL teams could improve their decision making.  At just $0.99, this book is cheap enough that you could buy it for the Kindle App on your iPhone and then just read it when you’re waiting in line at the DMV (let’s be honest here… we all know I’m talking about reading it in the john).
  2. The book will change the way that you think about the decisions that NFL teams make.  Football teams are essentially a series of decisions.  They make decisions to hire coaches, they make decisions to draft players.  Getting those decisions right is the key to winning football.  Game Plan will show you where some NFL teams are going wrong and what they need to do to right the ship.

You’re still here…  I really thought the pricing would be enough to send you over to Amazon already… ok, here’s the rest of the sell.

The key comparison I make in the book is between football coaches and poker players.  Coaches and poker players are doing the same things.  They make moves, they anticipate their opponent moves, and they try to give themselves the best chance of winning (a game of football, or a poker hand).  But the example of poker also allows us to illustrate all sorts of problems with the NFL’s current decision making structure.

If you want to understand how viewing the NFL’s coaches as poker players… or how viewing NFL scouts as doctors… or any of the other powerful analogies I make in the book… can help you understand what your team would need to do to get better, then all you have to do is spend 99 cents on Amazon.

20 Fantasy Football Twitter Accounts Under 2000 Followers (Even Though They Should Have Eleventy Bazillion Followers)

More “sabremetrics for twitter accounts” here.  The list below is for a group of fantasy relevant twitter accounts that are all below 2,000 followers.  As I’ve said before, I think content discovery on Twitter is really difficult.  I’m just trying to connect the dots for you in figuring out who to follow.

The accounts below are all followed by a group of maven fantasy football accounts, and at higher numbers than you would expect given their total follower numbers.

If you don’t follow them, you’re only hurting yourself.

Name Followers Link Details
Matt Schauf 1648 mschauf63 I love my family, fantasy football and good beer (not the stuff your uncle drinks). The order of that list depends on when you ask me.
Alessandro Miglio 1854 PFF_Alex Redraft Editor for @PFF_Fantasy. Member of @FSWA. #Dolphins featured columnist for @BleacherReport. All opinions here are my own.
zach_law 948 zach_law Find Ask Your Fantasy Football Expert blog posts at I also write for Bleacher Report
Steve Wyremski 1030 SteveWyremski NFL / FF freak, Writer for Dynasty League Football
Eric Dickens 1702 DLFootball #Dynasty Football…the beast never sleeps.
Jeff Ratcliffe 903 JeffRatcliffe Sports enthusiast, anthropologist, college professor, and the IDP Director and Senior Fantasy Writer for PFF Fantasy
Miller 1156 FantasyJedi Commissioner of The Fantasy Premier League (@FPLChampionship) and the Fantasy Champions League (Coming in 2013) Writer of Fiction. Pontificator. Homebrewer.
RumfordJohnny 1548 RumfordJohnny Co-founder of (w/ @RyFo18) a fantasy football site for beer geeks. President & lone member of the Ross Ventrone Fan Club.
Michael Daneshgar 442 MDaneshgar Write for @DraftBreakdown and the Dynasty section with @profootbalfocus. UF Sport Management grad student cursed to be raised as a Cleveland sports fan.
Eye of the Gator 777 EyeoftheGator Now writing for Dynasty League Football (DLF to those in the know). Creator of Race to the Bottom: [Improved Site Coming Soon!]
Dexter’s Library 856 Dexters_Library Dexter Manley’s Library: expert #fantasyfootball advice for the functionally illiterate. Fake it till you make it. #NFL #Comedy #ManleyAxioms
Akshay Anand 930 PFF_Akshay Monster Pats fan. Senior Fantasy Writer for Pro Football Focus Fantasy. Find my content here:
Rick Drummond 1521 PFF_Rick Editor, Pro Football Focus. I remember where I was standing when my dad told me Stabler had been traded.
Eric Yeomans 1935 Eric_Yeomans Featured Contributor/Account Manager at and Senior Writer at Pro Football Focus
Tyson Langland 616 PFF_Tyson UNLV Alumni. Agent/player relations, player participation and writing, all for Pro Football Focus. All thoughts on Twitter are thoughts of my own.
Ryan Forbes 764 RyFo18 Co-Founder of @2MugsFF w/ @RumfordJohnny. Sports nut (Chiefs, Brewers, Red Wings, Jayhawks). My tweets are ramblings about the sports world.
Brian Quinlan 1085 BNQuinlan Part-time fantasyfootball expert. Full time addict. I also like beer.
Andrea Hangst 1087 FBALL_Andrea NFL analyst. Bleacher Report AFC North Lead Blogger. PFF Fantasy contributor, & F*BALL editor/podcaster. Chicago lady/Steelers fan/not a homer or a hater.
Chad Parsons 1102 PFF_ChadParsons Dynasty Podcast Host:, Dynasty Writer:
Ross Miles 1113 PFF_RossMiles FantasyPros’ 2011 IDP Expert Accuracy Winner. IDP Editor for @PFF_Fantasy. St Louis Rams fan. Surprisingly, I’m English & live in London.
Clint Chugg 1382 YHIHF Owner of, and writer for, You Heard It Here First fantasy football, and contributing writer for Razzball fantasy football (
Allie Fontana 1451 AllieFontana NFL & Fantasy Analyst; Managing Editor, Bruno Boys Fantasy Football; Co-host Fantasy Gridiron Live!; Sports lover, fashionista, foodie & pop culture savant.
Erik Frenz 1543 ErikFrenz Cover the AFC East for @BleacherReport. PatsPropaganda & Frenz podcast co-host. Warning: I tweet a lot. RT =/= endorsement.
Ms. Cakes 492 patycake15 Bears|Rams|Steelers. FFball champ|Triathlete|Marathoner. STLRams Reporter for @ThePigskinArch on@AerysSports|@101ESPN Columnist.

One Simple Idea to Help NFL Teams Draft Better


The Dallas Cowboys famously laid the groundwork for a three Super Bowl dynasty using the results of analysis that one of Jerry Jones’ partners did on the value of each pick in the NFL draft.  That analysis was the basis for what is now known simply as “The Chart”.  The Chart has driven valuations on draft pick trades for some time now.  I’m sure there were any number of other factors that led to the three Super Bowls that Dallas won in the 90s, but The Chart was at least part of it.

Because even simple analytics (The Chart was based on some very crude analysis and yet was extremely effective until the market adjusted) can help teams, I’m always amazed at the general skepticism towards analytics in football.

In any case, between now and the draft I’ll be throwing out some ideas on how I think teams could draft better.  Like The Chart, these ideas are the result of crude analysis.  NFL teams can and should hire more sophisticated analysts than just one idiot with a little Excel knowledge (that idiot is me).

Teams should adopt a Supply/Demand Theory of Drafting.

Every NFL team starts 5 offensive linemen and 1 running back.  But teams do not draft these positions in the same ratios that they appear on the field.  Teams only draft linemen about twice as often as they draft running backs.  This is despite the fact that running backs are involved primarily in the running game, while lineman are required for every play.

To further this argument that teams should pay attention to supply and demand when drafting, here are two charts that help make the case.

The first graph shows that O-Line positions play about 75 career games on average if they are drafted (does not count undrafted free agents).  By contrast, running backs play about 10 fewer career games on average.  The second graph shows the rate that these positions were drafted from 1990-2006.  Offensive line is only drafted about twice as often as running back despite outnumbering running backs by 5:1 on the field.  In case you’re worried about the 2006 cutoff, these ratios were even more out of balance in 2010-2011.  The 2006 cutoff was done simply to get a better sample on career games played.

(Source Data: Pro-Football-Reference)



Note that if there wasn’t a general scarcity of linemen, then their career games played wouldn’t be so high.  Oversupply/competition would send that number down.

To illustrate why this graph supports my Supply/Demand theory, think about what might happen if NFL teams started drafting linemen in greater numbers.  Right now teams are very good at selecting linemen.  The linemen they select tend to play a lot of career games.  But as teams begin to select more linemen, they would mix in some “bad” linemen.  Those “bad” linemen would play fewer career games and the position group would go down in “average games played”.  But in addition to adding more bad linemen to the mix, there would be more competition for the line spots, which would also send that “average games played” stat downward.

At the same time that teams are selecting more linemen, they would select fewer running backs.  When they do that, they would be selecting only running backs that they feel really strongly about.  The overall quality of the running backs they select would go up, which would reduce the odds of drafting “busts”.  But at the same time that “bust” odds are reduced, teams would be introducing fewer running backs to the system.  The running backs who are drafted would be of greater quality and would have less competition.  Their “average games played” statistic would likely increase.

It’s not that the goal is to draft more bad linemen, it’s just that teams should draft more linemen, which will increase the odds of drafting bad ones.  Basically, NFL teams should just reverse the attitudes that they have about linemen and running backs.

Let’s say we ran a team and wanted to implement this strategy.  First, why would it help us?  Because:

  • We would let other teams keep throwing darts at their running backs
  • We would be upgrading the relative quality of our offensive line,
  • We would be pulling linemen out of the talent pool, which would mean that…
  • Other teams’ relative offensive line quality would go down even further.
  • Teams who were counting on being able to get a quality undrafted free agent lineman wouldn’t be able to.  We would have already drafted him.


We would be probably be starting an undrafted running back behind an excellent line, while other teams would start their running back (who might be good or might be bad) behind a substandard offensive line.  This strategy would also likely help our passing game as well.

Because I can see someone raising the objection that I haven’t included injuries in my logic, let me address that briefly.  First, I do think it’s already included.  Linemen get injured just like running backs do.  But because linemen are in short supply, they play through injuries and they come back and play on beaten up bodies.  When running backs get injured, they’re thrown on the scrap heap and a new running back is inserted into their position.  This is essentially a supply and demand issue.  Teams overdraft running backs and then treat running back injuries like you would treat a “totalled” car.  Teams underdraft linemen and then just settle for linemen who might be playing injured.

This have been just one simple idea.  More to come before draft day.

The Crowd Likes Michael Floyd

Below is a table which has the results of the quick WR poll I just ran.  The poll questions were basically how many Pro Bowls each wide receiver will play in.  There were a few interesting things to note.

I’ve posted the variance for each player as well as I thought it was really interesting how the voting shook out.  Kendall Wright was by far the most consistent (lowest variance).  He only got one vote for zero Pro Bowls.  Justin Blackmon on the other hand was all over the board.  People seem to be deeply divided as to whether or not he’ll be good.  His fans think he’ll be awesome, while others have a much lower opinion.

Michael Floyd ended up being the winner by a decent margin.

Average Pro Bowls Predicted  Variance
Michael Floyd 2.73 1.80
Justin Blackmon 2.33 2.62
Kendall Wright 1.67 0.89
Stephen Hill 0.87 1.32
Alshon Jeffery 0.53 1.32
Rueben Randle 0.50 1.68