In Game Plan I point out that while in the realm of football few decision makers are ever under the age of 40, the world’s hottest tech company is run by a guy who started the company when he wasn’t even old enough to drink.  That tech company, Facebook, is now worth more than all of the NFL’s franchises combined.

The primary difference between managing or coaching a football team, and managing/running a tech company, is that software is a domain that allows practitioners to get good on their own, while in football the only way to acquire experience is to ask somebody else’s permission to do so.  In domains where practitioners are allowed to get good on their own (poker, music, software) the age of the masters of those domains tends to be extremely young.  In domains that require that you ask someone’s permission to get good, the age of masters tends to be much older.

I saw something last night that told me that the days of football being a permission based knowledge domain are coming to an end.  I saw this headline:

A new way to make six figures on the Web: teaching

When I say that football is a permission based knowledge domain, I mean that in order to acquire the knowledge to become a master at it, you literally have to ask someone’s permission.  You have to apply to become an unpaid assistant at a high school or college, and then you have to hope that someone in that organization takes a chance on you.  The internet is going to change that.  You’ll still have to ask someone’s permission to get paid to do something football related, but you won’t have to ask anyone’s permission to actually acquire football knowledge.  That difference is going to be a disruptive game changer for the NFL.  Here’s how it’s going to happen.

The article I link to above is for an online education site that allows teachers to actually charge for disseminating their knowledge.  Let’s imagine something that I’ll call “Football University”, but which is essentially just a collection of videos on a site like Udemy, the one mentioned in the article.  The key for Football University is that the teachers can teach the class just once, but can profit from it indefinitely.  They don’t have to fill up a college lecture each semester in order to make it cost feasible.  They teach the class once, then the video stays on Udemy forever and allows the teacher to continue to profit from it.

Now let’s imagine the kind of courses that could be taught at Football University, and the kind of people who might teach those classes.

Maybe former Browns scout Matt Williamson teaches a series of classes on scouting various positions.  Scouting Cornerbacks 101, Scouting Linemen 101, etc.

Maybe former Packers VP Andrew Brandt or former Broncos GM Ted Sunquist could teach a series of classes covering NFL player contracts, the salary cap, and the finance of football.

Maybe Smart Football author Chris Brown teaches a series of Xs and Os based courses.  The 46 Defense 101, etc.

Maybe the emerging group of sports analysts all have a group of courses.  People like Skeptical Sports’ Ben Morris and Advanced NFL Stats’ Brian Burke could teach classes that cover statistics as applied to sports.  Predictive Analytics 101, Sports and Probabilities, etc.

Retired/fired coaches could get into the act as well.  They could teach classes about motivation, or the organizational/managerial side of coaching.

I’ve tried to throw out a lot of examples because the internet supports abundance.  It supports the creation of every type of imaginable content.  The emergence of sites like Udemy now make the economics favorable for the people that I mention above to actually take time out of their lives to do what I suggest (and if the people I mention don’t do it, someone else will).

However, just because the internet can change that way that people teach/learn about a business like football, doesn’t necessarily mean that it will be disruptive to the NFL, which is what I suggested in the title of this post.  Except actually, it does.  As I discuss in Game Plan, the NFL is currently drawing its decision makers from tiny talent pools (ex-players) because the infrastructure to educate outsiders has never been in place.  But with the education of what I call “obsessed amateurs” through online learning, the traditional paradigm for educating people about football is going to change.  Ex-players will no longer have a stranglehold on the acquisition of football knowledge.

The disruption that I am talking about is already under way. 

One of the Fantasy Douche readers has written me a few emails to tell me his story, which as he points out, is pretty much exactly what I talk about in Game Plan.  This reader is a current college student and ex-poker player.  He took a small deposit and turned it into over $10,000 by playing poker online (before the government shut down poker sites in the US).  Now this reader is trying to get into the business of football.  His story is illustrative of why the teaching/learning system that I discuss above is an important change.

This FD reader is what I would call an Obsessed Amateur, so let’s just call him O.A. 

OA isn’t an insider to football, but he wants to become one and he’s willing to burn a lot of calories to become one.  He sends notes to me and other internet/twitter folks and asks questions about how he can break into the business of football.  He spends time going through Brian Burke’s Advanced NFL Stats, paying attention to things like the relative value of running backs compared to receivers. 

OA worked through his college honors advisor to actually get a meeting with some of the coaches of the D1 school he is attending in order to pitch them that he could be their Game Theory/Analytics guy. They were impressed with some of the things he had to say, like a suggestion that their team should rely on one of their more efficient, but underutilized goal line running backs.  But there were some red tape hangups with working with that program, so now OA is transferring to another school where he has already been in contact with the football program and has pitched them on looking at their recruiting practices from an analytics standpoint.  The football program has thus far been receptive to working with OA.

There are a number of important takeaways from OA’s story.  First, he has an analytical/obsessed mind.  He’s like a 1,000 kids who taught themselves to play poker.  He’s basically exactly the kind of person who should be involved in football.  Second, even though OA is obsessed, he still has to ask permission under the current system.  He’s waving a flag saying “Please, please let me in.” which is what any employer should want from a prospective employee.  But because he wants to get into the world of football, he faces long odds to break in.  There are a lot of people who want to work in football, and football organizations are used to turning away people just like OA.

The disruption to football learning that I describe above is the game changer for people like OA.  It’s a game changer because OA could take a number of online courses so that when he tries to break into the world of football, and the organization is trying to decide whether to hire OA, or perhaps their recently graduated safety, who was one of their smarter players, OA is now on close to equal footing with the recent grad in terms of football knowledge.

We’re running a little long here, so let me bring this back full circle.  Mark Zuckerberg learned to program under a system where he could get good on his own.  By the time he launched Facebook he was already an extremely accomplished programmer.  Innovations like Udemy mean that people who might aspire to become experts in the game of football could also benefit from learning and getting good on their own.  When (not if) that happens, the NFL will see a game changing disruption.  The change to the teaching/learning paradigm of football means that the NFL could grow its talent pool by orders of magnitude and select the best minds, not just the best minds conditional upon also being an ex-player.

The following is an excerpt from Game Plan: A Radical Approach to Decision Making in the NFL.

In 2011, Jason Garrett was the 45 year old first time head coach of the Dallas Cowboys. Garrett’s resume prior to becoming Dallas’ head coach was as follows:

• Quarterback at Princeton
• Back-up NFL Quarterback with 9 career starts
• Quarterbacks coach for the Miami Dolphins (2 years)
• Offensive coordinator for the Dallas Cowboys (4 years)

As offensive coordinator, Garrett directed an offense that was generally packed with high profile names (Terrell Owens for instance) although critics would say that the results were uneven. The Cowboys were top five in the league in points scored twice during Garrett’s tenure and were closer to the middle of the pack the other years.

Garrett’s experience prior to becoming head coach can probably be summed up as 64 games coached as an offensive coordinator, 32 games as a quarterbacks coach, and over 100 games as a back-up quarterback. Garrett’s practice as a decision maker is probably about 64 games, while the rest of his games largely fall in the spectator category as back-up quarterbacks are not responsible for making any decisions during the course of the game.

Garrett took significant criticism during the 2011 season for one end of game situation that might have cost the Cowboys a win, in a year in which they missed the playoffs by just one game. In their game against the Arizona Cardinals, the Cowboys had a chance to win the game in regulation by kicking a field goal to break a 13-13 tie. That opportunity was set up by the following events:

Dallas got the ball for a potentially game winning drive at their 32 yard line with 2:54 left on the game clock. They needed only a field goal to win. In most situations that would be so much time that teams would be afraid of scoring too quickly and giving the ball back to their opponent. The result of their first two plays from scrimmage was 12 total yards of field position, but almost a full minute of game clock. Advanced NFL Stats (ANS) estimates the probability of each team winning a game following each play. According to ANS, Dallas started the drive with about a 70% chance of winning the game. After letting the minute of clock run, they had only a 60% chance of winning. Despite gaining field position, they had somehow become less likely to win. One of the plays that the Cowboys had run was a pass to tight end Jason Witten that actually lost a yard and ended with Witten being tackled in bounds and the game clock continuing to run until the two minute warning. Quarterback Tony Romo would have been better off throwing the ball into the ground so that at least the clock would stop. The yard that Witten lost would be damaging later as the Cowboys’ next play was one yard short of a first down. That meant that the yard that Witten lost required the Cowboys to run a quarterback sneak to pick up the first down. The quarterback sneak cost another 30 seconds of game clock.

At this point the Cowboys had moved the ball just 20 yards in roughly two minutes of game time. However, they had the ball with first down at the Arizona 44 yard line and they had two timeouts. There was still 1:06 of game time, so with the two timeouts and about 15 yards to gain to be in field goal range, the game was still very winnable. But the Cowboys then took a false start penalty which meant that first down with 10 yards to go became first down with 15 yards to go. The next play was an incomplete pass. After the incomplete pass, the Cowboys were flagged for delay of game! They weren’t able to run a play in the time allotted under the play clock. They were staring at 2^nd down with 20 yards to gain for a first down. With the ball at their own 45 yard line, they were well outside of field goal range. They had started a drive with almost 3 minutes in game clock and had moved the ball a mere 13 yards of net field position.

The Cowboys next play was a nine yard pass to Dez Bryant, who was tackled in bounds allowing another 30 seconds of game clock to run before the Cowboys next play. Dallas snapped the ball with 31 seconds left on the game clock and completed another pass to Bryant at the Arizona 31 yard line. They were finally in field goal range. What happened next generated a lot of criticism. Tony Romo rushed the offense up to the line and spiked the ball to stop the clock with 0:08 seconds left on the game clock… even though Dallas still had their two timeouts left.

Dallas didn’t at that point use either of their timeouts to run another play in order to attempt to move the ball closer so that field goal kicker Dan Bailey would have an easier kick. They were apparently content with attempting a 49 yard field goal, even though attempts from that distance miss about 1/3 of the time. Bailey would miss this particular kick. Dallas would go on to lose the game in overtime.

It’s probably better that Dallas’ 49 yard field goal ended up in the “miss” category as we have what some might call a teachable moment. Had Bailey made that field goal, the abomination that was the Cowboys’ execution leading up to that point in the game might have gone overlooked. During those three minutes of game time the Cowboys put on a clinic in letting game clock run while not advancing the ball at all. They didn’t optimize their use of timeouts and in fact it’s probably likely that they didn’t even know they had the timeouts. If they had known, they wouldn’t have had Tony Romo rush the offense to the line to spike the ball.

Head coach Jason Garrett took considerable criticism after the game for the poor end of game management. Garrett refused to admit any mistake. Primarily the media focused on Garrett’s non-use of his timeouts and the fact that the Cowboys’ hadn’t tried to move the ball closer for the field goal. Garrett’s response to the criticism was that the Cowboys felt like they were in field goal range and he didn’t see a reason to risk running a play for a loss with just eight seconds on the game clock. Garrett would say of his decision making:

“We very well could have taken a timeout there. We felt like we were in field-goal range. We have yard lines that we use as guidelines before the game. We felt like we were in range at that point. Tony (Romo) had them on the line of scrimmage quickly, so we went ahead and clocked it and used that as a timeout. …You see so many situations where you have negative plays in those situations. We felt like we were in his range to give him a chance to kick the game-winner.”

Garrett is making the equivalent of a probability based argument. He’s saying that the Cowboys chances of winning were greater just kicking the field goal than they would have been if the Cowboys had tried to run another play. Garrett says you see “so many situations where you have negative plays”. The question is: Is Garrett right?

Are negative plays likely to happen in those late game situations? First of all, Advanced NFL Stats’ Brian Burke pointed out that Garrett’s explanation doesn’t even actually make sense. While holding on to timeouts, Garrett had the Dallas offense rush to the line to spike the ball and stop the clock. When they did that, they were snapping the ball and risking a false start or illegal formation penalty. That’s exactly what Garrett said he was trying to avoid.

But even if you ignore that Garrett’s logic fails on its own terms, it’s possible to look at his decision making and see that he missed an opportunity to maximize the Cowboys’ chances of winning.

First, as Burke pointed out in his analysis of the game, if the Cowboys had simply taken a timeout after Dez Bryant caught the ball at the 31 yard line, they would have had plenty of time left to run another play without having to worry about the clock expiring. The time it took Romo to rush the offense up to the line could have been saved.

Second, Garrett’s worry that another play could result in an offensive penalty should be balanced out by the reality that some penalty could also be called on the defense, which would increase the Cowboys’ chance of winning. Actually, the penalties probably cancel out at that point. We have to remove false start and illegal formation penalties from the things Garrett can be worried about because they weren’t avoiding the risk of a false start or illegal formation penalty by spiking the ball. If you remove those penalties from the equation, the probability of an offensive penalty is about the same as the probability of a defensive penalty. Since those things cancel each other out, all that’s left is that the Cowboys could have run another play and would have had a free shot at advancing the ball. They also would have had another timeout to use in the event that their next play didn’t result in the clock being stopped on its own.

Garrett’s performance at the end of the game against Arizona looks like the performance of someone who isn’t processing information as fast as they need to be. He may have been overwhelmed by the combination of his play calling duties and the need to manage the clock at the end of the game. If you think about it, he had an amazing amount of information to process. First, Garrett must come up with the offense’s play calls. He has to reason through which plays will be successful, weigh the odds that the defense might expect those plays, and then finally come up with what he thinks is the optimal play call. He also has to keep an eye on the game clock. He needs to be sure that he doesn’t score too early. But he also needs to be sure that he does score at least a field goal. He has to remember that he has timeouts. He has to listen to the other coaches talking in his headset. Garrett also has to process probabilities. What are the odds that a field goal does make it from a certain distance? What are the odds that a negative play puts them out of field goal range?

Garrett also had the appearance of someone who was learning, and who in the future might remember that 49 yard field goals aren’t automatic and might try to move closer for a game winning try. Even Garrett’s defense of his poor game management has the ring of an excuse from someone who has a suspicion that he screwed up, but doesn’t want to admit that it was because he didn’t know what to do.

The interesting question in this instance is whether Garrett should be expected to be any better at end of game management than he is. Has he been accumulating the deliberate practice that researchers say is necessary to become an expert? Would Garrett have gotten this experience in end of game situations during his career as a back-up quarterback? Would he have gotten this experience as a quarterbacks coach? Would he have gotten this experience as an offensive coordinator?

Read the rest of this chapter in Game Plan: A Radical Approach to Decision Making in the NFL

@HeHaithMe is a veritable force on Twitter.  He’s what would happen if you combined the gambling enthusiasm of Jimmy the Greek with the zen mental state of the Tasmanian Devil.  I’ve engaged in a few prop bets with HHM in the past year or so, losing two and then also having to pay him for winning the Mock Draft Free Roll.  So I’m down a few bucks to HHM.

HHM has pretty much been killing his MLB bets this year and while I don’t really have any interest in baseball, I am sort of mildly interested in the issue of whether individual bettors can outpick the books.  So HHM and I are going to do another prop bet.  I took the under on HHM’s record to date in MLB and he took the over.  He was 58% when we made the bet, so every point over 58%, I owe him $100, and every point under 58%, he owes me $100.  The kicker is that 75% of the winner’s take goes to charity.  So it’s going to be pretty difficult for this to be a positive EV bet for me.

In any case, wouldn’t you know it, HHM went like 5-1 the day we made the bet which got him up to 60% for the year.  Here are HHM’s picks from Saturday:

MLB: 81-58-6 58%. SAT: BAL ML +105, STL O7 -125, COL O8 +115, SF ML +105.

— HeHaithMe (@HeHaithMe) May 12, 2012

MLB: Adding CHC O8 -105

— HeHaithMe (@HeHaithMe) May 12, 2012

Then here is his update from Sunday:

MLB: 86-58-6 60% YTD. (0-0 in @lindetrain challenge) SUN (all lines 5Dimes): KC ML +106, STL U7 +105, NYM U 7.5 -115, CLE first 5 in +121

— HeHaithMe (@HeHaithMe) May 13, 2012

MLB continued: TB U8.5 -120, WAS ML +115 @lindetrain

— HeHaithMe (@HeHaithMe) May 13, 2012

Lucky for me, HHM did a little worse on Sunday and he’s right back around 58%.

MLB: 87-64-6 58%.My best day of the year Sat followed by my worst on Sun.Genuinely think bullpens worse this year than any I can recall

— HeHaithMe (@HeHaithMe) May 14, 2012

Here was my thinking in terms of why I proposed this prop bet:

1. We’re like more than 90 days from Week 1 and I am BORED.
2. I think the most likely outcome is that little money money changes hands.  HHM has already picked 150 games, so there is a decent sample available.
3. The bet is almost assymetric in favor of me.  I said almost.  If HHM were only picking games that were –110 on the betting sheet, then I think the bet would be in favor of me by a margin.  Gamblers have to pick those right at 53% just to do better than break even, so I would essentially be on the book side of the bet by taking the under on 58%.  But HHM sometimes takes games that are –125, so the bet isn’t as much in my favor as it would be if all games were –110.  But actually, you can see from above that HHM often picks games that he thinks will return the most for his money, so I’m not concerned that our small prop bet might influence his picks.  He places actual bets on these games, so his wins from picking good bets will have a larger impact for him than simply picking safe bets in order to win a small prop bet where the money is largely going to charity. 
4. When I say assymetric what I mean is that my losses (if I lost) would likely be small, while my wins could be larger.  I would think that a 60% win rate for HHM would really be something, while a 54% win rate wouldn’t be odd at all on the downside.  So I guess I think that even while it’s likely that not a lot of money changes hands, my upside is probably larger than his.

If you know of a good charity, be sure to post it in the comments.  If I win, I might just have HHM donate to that charity.

Code and Football has been doing a series of posts on trades in the NFL draft.  You should check out the site if you haven’t before.  C&F recently linked to my Games Started draft value chart, and then followed that up with something of a rundown of recent discussions of draft trades that have been taking place on the interwebs.

As I was reading the C&F post, I remembered that I had meant to return to the issue of draft trades one more time.  Post-draft I was reading something on ESPN that sort of caught my ire.  John Clayton wrote a piece that was essentially a winners and losers column on the first round trades.  In that piece he included these lines:

Too often in past years, the Patriots got a little too cute. They’d trade a choice for a future first-rounder. They’d trade back and acquire more draft choices than they had roster spots for rookies.

And then this line:

3. St. Louis Rams: Trading out of the top six is usually a bad idea.

Really?  Why?

Maybe I’m getting too excited over a few lines in this Clayton piece, but here’s why I haven’t forgotten about it since I read it.  Clayton is a thought leader as it relates to the NFL.  Maybe he’s outside of the top five guys in terms of being thought leaders, but he’s on the list.  He gets paid to do this stuff.

Why is trading out of the top six “usually” a bad idea?  Even in the world where everybody believes in the Jimmy Johnson Chart, trades are assumed to be equal on each side based on that chart.  For Clayton to assume that trading out of the top six is a bad idea, is to say that the draft chart that transactions are based on isn’t steep enough.  He’s saying that the talent in a draft is even more weighted towards the early picks than everybody already erroneously believes it is.

Clayton also makes the assumption that the Patriots “got too cute” when in reality, they were simply executing a draft strategy that presupposes that football is a sport that starts 22 players who will incur a lot of injuries.  The Patriots were also excellent at taking advantage of the over-discounting that most teams do related to future year picks.  The Patriots were acting like bankers (or loan sharks), advancing near term picks at extremely high interest rates.

I would say about 85% of the post draft coverage I’ve read contains a “bold move” bias.  At the heart of the Bold Move Bias is the faulty idea that every move is a 50/50 proposition, but that the payoffs aren’t weighted that way.  For instance, the Bold Move Bias would break the RGIII trade down based on it either a) works out or b) doesn’t work out.  It would then assign a 50/50 probability to each potential outcome.  But then the Bold Move Bias says that if the trade does work out, the benefits will be outsized because you’ll have a franchise quarterback.  Under that view, every bold move has a positive return on investment.

The unfortunate thing is that the real world doesn’t work that way.  The Bold Move Bias as applied to a roulette wheel would say that the odds of hitting on any number are 50/50 (it either hits on the number or it doesn’t) but that the payoffs are 35/1.  The Bold Move practitioners would then say “Any time you have the chance to put $20 on a single number and potentially make $700, you have to do that.” 

That type of thinking, the kind that considers only the payoffs of the bet and not the costs or the odds, is why a lot of teams spend years in the cellar.  While the Redskins keep putting their money on a number on the roulette wheel, the Patriots, Eagles, Steelers, and Packers keep putting their money in the bank.  Every once in a while it’s reasonable to expect that the Redskins will hit on their number, but that doesn’t mean their outlook is necessarily right.  It’s just bound to happen some of the time.

In Game Plan, I spend a considerable amount of time comparing decision making in football to decision making in poker.  To me it’s a natural connection. But I could see where it might not be a natural connection to everyone.

It’s a natural connection to me because coaching a football game is a series of decisions from set scenarios in the same way that poker is a series of decisions from set scenarios.  Coaches decide whether to run or pass.  Poker players decide whether to bet, check or fold.  Coaches decide what pass play to call.  Poker players decide how much to raise, or whether to check raise, or whether to slow play.  Poker players and coaches both have to anticipate what the opponent will do.  They both have to disguise what their team wants to do.

I spend a not insignificant time in the book talking about poker phenom Tom Dwan.  Dwan is interesting to me for two reasons.  First, he’s young.  He’s a lot younger than any NFL coordinator or head coach.  He’s a lot younger than even the youngest NFL coordinator or head coach.  That goes against the notion that age is an important consideration in forming expertise.  Dwan is probably one of the top five poker players in the world.  But Dwan is also interesting to me because he learned to play online, in a way that the old school pros didn’t even view as being real poker.

The poker hand that I’ve embedded below actually reminds me in some ways of the Sean Payton decision to inside kick in Super Bowl XLIV.  Dwan bluffs two extremely accomplished players out of made hands.

To me the impressive thing is not that Dwan executes this bluff.  If you bluff enough (he does) then some of them are going to work out.  The impressive thing to me is that after the hand, a number of players around the table engage in discussion in order to try to guess whether any of the players had three twos.  Dwan actually ends up engaging in a prop bet with Doyle Brunson where Dwan bets that Peter Eastgate had a two in his hand.

The only player at the table who is younger than Dwan is Peter Eastgate, and yet Dwan’s mastery of the game shows through on a number of levels.  First, he executes a bluff that, like Sean Payton’s decision to onside kick, is not for the faint of heart.  Then, after the hand he shows that he read the hand better than a much more experienced player and that he knew where he was in the hand the entire time.

I think that the most demanding thing that a football coach does is make strategy.  I don’t think that the management side of football is particularly demanding.  If I had to guess how many people in the world are better at managing employees than the NFL’s coaches, I would say “A lot”.  Managing people isn’t something that requires that you’re in the top group of cognitive performers.  But strategy, and implementing strategy within the confines of the play clock, is something that requires elite cognitive ability.  That’s the area where football coaches are similar to poker players.

When Sean Payton came out in the second half of the Super Bowl and decided to employ the high risk, high reward strategy of onside kicking, he had numbers on his side.  But he was also making a decision that, if it went poorly, would probably stain his coaching resume forever.  But he pretty much didn’t give a shit.  He had ice in his veins in the same way that 20-something Tom Dwan had ice in his veins when he put out a $100k bet and he knew he was dominated by the other players in the hand.

For the rest of my thoughts on this topic, be sure to check out Game Plan, which at just $0.99, is like half the cost of using an ATM not owned by your bank.

Just wanted to mention again that I’m going to try to crank out as many guest posts as I can in the month of May.  I just recently finished up a guest post on Greg Little for FootballSickness.com and last week I wrote a post about taking punters in the third round for Big Cat Country.

I’m also working on a few posts on Value Based Drafting (for fantasy football) for some other sites as well as a post on the relative value of quarterbacks and wide receivers (for real football).

OK, one last post tonight to try to put this punting thing to bed.  I’ve noticed that a lot of the comments at Big Cat Country are focusing on the idea that a good punter’s longest punts are what we should look at.  It’s not that the best case scenario shouldn’t be considered.  In fact I argued that in salary cap terms, teams should think about the potential upside from their 3rd round picks.  But the best case scenario is just one potential outcome.  There are always a range of potential outcomes.  Even the best punter in the league is going to have results sometimes that are below average.

I thought I would actually look at the best punter in the league to illustrate this fact.  Shane Lechler is the highest paid punter in the league.  He has a big leg. 

But if you’re looking at Lechler, should you focus on his longest punts, or the average of his results? 

Below is a graph that shows Lechlers kicks based on the line of scrimmage when he kicked them.  I show Lechler’s net punt, and I also show the expected net punt from each yard line on the field.  As you get closer to the other team’s end zone, the expectation for a punt goes down in terms of net.

Lechler is actually better than average if you take his net punt and then subtract out what the average punter gets from each yard line on the field.  But he’s only 2.5 yards per punt better than the average expectation.  This analysis adjusts for field position in the way that the BCC commenters are saying is important.  Lechler also isn’t significantly better when he’s closer to his own end zone.  He’s still just about 2.5 yards per kick better than average.  So in the places where the BCC commenters are saying Lechler can “flip the field”, Lechler is still just 2.5 yards per punt better in terms of net punt than what we would expect.

The average is the central tendency.  For every punt that Lechler kicks that might go 70 yards, he is balancing that out with a shorter kick so that his average is close to what the average kicker yields (although slightly above).

Psychologist Daniel Kahneman has done a number of experiments looking at whether humans can make good judgments about the most likely outcome.  It turns out that we can’t.  We often focus on the best case scenario.  We’re drawn to the idea that the best punter we can find might be able to outkick the next guy by 10 yards per kick.  But that’s not realistic.  It’s not realistic for the same reason that municipal projects never finish on time or on budget.  The projects are always bid with the best case scenario in mind.  Just like the Jaguars probably do feel like they took a guy who can net them an average 50 yards per game in field position.  But a quick review of historical outcomes shows that those expectations aren’t reasonable.

For my guest post at Big Cat Country I looked at whether it made any sense to take a punter in the third round of the NFL draft.  Go check out that post if you’re interested in punters at all.  In the comments of that post a number of people suggested that I had ignored the value that a punter might have in pinning the other team deep in it’s own territory.

I thought I would look at that issue.  First I had to create a formula to figure out whether a punt should or should not be a touchback.  I used results from 2000-2010 to create this graph that breaks down punts by likelihood of becoming a touchback, depending on field position.

I can then use the formula from that graph to analyze actual punts and see whether punters have repeatable ability to avoid touchbacks (when controlled for field position).  When I do that, I am basically calculating Expected Touchbacks vs. Actual Touchbacks.  Doing that, I get the following graph.

The trend line explains about 60% of the variance in touchback results, which is to say that field position explains about 60% of the variance in touchback results.  But that’s not 100% either.  So is the actual punter responsible for causing or preventing the touchbacks that can’t be explained by field position, or is it randomness at play?

It’s probably randomness.  The graph below shows an X, Y scatter where prior ability to prevent touchbacks is the independent variable.  It doesn’t have any explanatory power over future ability to prevent touchbacks.  Just because a punter may have had less touchbacks than you would expect based on field position in the past, doesn’t mean that will continue.

This is something of a “fooled by randomness” issue.  Sometimes it’s easy to mistake randomness for skill.  Some might remember the performance of San Diego punter Mike Scifres in the 2009 playoffs.  Scifres was lauded for his performance against the Colts.  Below is an account from the game:

Scifres, passed over again this year in Pro Bowl voting, booted the ball six times last night for a 51.7 net average – an NFL playoff record for a punter with five or more punts. All six were downed inside the 20-yard line, also an NFL playoff record. Five times Scifres pinned the Colts inside 11 yards, and Indy had 6 yards in returns. Scifres had one booming drive of 67 yards.

But over his career, Scifres has about as many touchbacks as you would expect, based on field position.  Over the long term he hasn’t shown any increased ability to pin the other team deep and avoid touchbacks.  I have Scifres calculated for 44.05 “Expected Touchbacks” and he has 44 “Actual Touchbacks”.  The skill he showed in the playoff game against the Colts may have just been randomness.

In all of this analysis, I only found one punter whose results looked like they deviated from expectation significantly.  That was Shane Lechler, who causes touchbacks a lot more often than should be expected.  Based on field position you would expect that he would have caused about 75 touchbacks in his career.  He’s actually caused 129.  The interesting thing is that Lechler is really bad at that part of the game and yet he’s the highest paid punter in the league.

If you’re a fan of watching the ways that markets work, then the NFL draft pick trade market can be fun to watch.  I sort of got interested in the topic when it occurred to me that the way that the NFL values picks is not probably very efficient based on a reasonable expectation of the distribution of human abilities.  Basically the NFL works off a trade chart that assumes the existence of super human individuals.  I think it’s unlikely that those superhuman individuals actually exist and I would argue that actual player results back me up.

I thought it might be fun to look at the draft day trades and compare the trades on the basis of the Jimmy Johnson Chart and also my chart that focuses on how many games started you can expect to get out of each pick.  As a refresher, here’s my draft pick value chart shown versus the Jimmy Johnson Chart.

In putting this together I relied on this recounting of the trades. 

Here we go!

Browns move up to No. 3: Wanting to secure their top choice, the Cleveland Browns moved to the No. 3 pick in a deal with the Minnesota Vikings. Minnesota acquired the No. 4 pick, plus three additional draft choices ( a fourth-round pick-No. 118 overall, a fifth-round pick-No. 139 overall and a seventh-round pick-No. 211 overall). The Browns moved up one spot to select Alabama running back Trent Richardson, while the Vikings grabbed Southern California offensive tackle Ryan Kalil with the No. 4 pick.

The table below breaks down the value of the picks exchanged. 

Note that the JJ Chart is denominated in points, while my chart is denominated in “Games Started”.  So you can expect to get about 85 career games started out of the fourth overall pick.  The JJ Chart says that Cleveland won the trade by a pretty wide margin, and the FD Chart says that Minnesota won the trade by a pretty wide margin.  Note that if I were to include position specific data, Minnesota would have blown Cleveland out of the water on this one.  Offensive linemen tend to start a significant number of games more than a running back.  Then if you consider salary cap issues and the fact that Minnesota is saving a lot of money on a left tackle and Cleveland is saving less money on a running back, it gets even worse for Cleveland.

Moving on.  From the trade summary on MassLive.

Jaguars go up to get Blackmon: The Jacksonville Jaguars traded up to the No. 5 overall pick to select Oklahoma State wide receiver Justin Blackmon. Tampa Bay acquired the No. 7 overall pick and pick up a fourth-round pick from Jacksonville (No. 101 overall). With the No. 7 pick, Tampa Bay selected Alabama safety Mark Barron.

Again, the Jimmy Johnson Chart says that the team trading up won, my chart says that the team trading down won.  My chart says that the expectation for the games started difference for the 5th and 7th picks isn’t that great.  However, if you look at the actual picks, I think you could make the case that Jacksonville did alright with this trade.

Moving on.  From the trade summary on MassLive.

Cowboys jump up eight spots to No. 6: The Dallas Cowboys have moved up eight spots to the No. 6 pick in a deal with the St. Louis Rams to select LSU cornerback Morris Claiborne. The Rams acquired the No. 14 pick (which St. Louis used to selected LSU defensive tackle Michael Brockers) as well as a second-round pick (the No. 45 pick) from the Cowboys.

The JJ Chart says this one is about even.  My chart says that the team trading down (STL) won, and by a sizable margin.  The 2nd round pick that the Cowboys gave up is worth quite a bit.  In terms of the actual players, I do think there’s something to be said for getting the best corner in the draft due to positional importance.

Moving on.  From the trade summary on MassLive.

Eagles move up to No. 12 for defensive tackle: The Philadelphia Eagles traded up three spots to acquire the No. 12 pick from the Seattle Seahawks to select Mississippi State defensive tackle Fletcher Cox. Seattle picked up the No. 15 pick (which Seattle used on West Virginia outside linebacker Bruce Irvin) plus two additional picks (a fourth-round pick-No. 114 overall and a sixth-round pick-No. 172 overall)

From a pick value standpoint, my chart says that SEA won.  But from an actual pick standpoint, it doesn’t look like they really capitalized on the opportunity.  PHI got Fletcher Cox, who many considered to be a top 10 quality player.  To figure the pick value on this one, it might actually be appropriate to think about Cox in terms of what his inherent value is, not what other teams assigned to him.

Moving on.  From the trade summary on MassLive.

Bengals deal out of No. 21 pick: After taking Alabama cornerback Dre Kirkpatrick with the No. 17 pick, Cincinnati traded out of the No. 21 pick in a deal with New England. The Patriots gave up the No. 27 pick as well as a third-round pick (No. 93 overall) to move up six spots. New England selected Syracuse defensive end Chandler Jones with the No. 21 pick. Cincinnati took Wisconsin guard Kevin Zeitler with the No. 27 pick.

The only comment I have here is that we were talking last night about CIN and how they seem to be increasingly making smarter decisions.  I’m not even saying that they sharked NE here, but between their draft picks last year, the Carson Palmer trade, and then this trade, they are increasingly operating like the smarter franchises.

Moving on.  From the trade summary on MassLive.

Patriots move up again: The New England Patriots moved up for the second time tonight when they acquired the No. 25 pick from the Denver Broncos. Denver acquired the No. 31 pick and a fourth-round pick (No. 126 overall). Denver later dealt those picks to Tampa Bay. The Patriots went defense once again with their draft selection, selecting Alabama linebacker Dont’a Hightower.

I think there’s actually an important point to be made here.  When NE trades down, they often are just swapping picks with a 5 or 6 pick difference, and they will sometimes get a future year number one pick in the deal.  When they do that, they are taking advantage of teams discounting future year picks too heavily.  But even when they trade up, they do in with terms that no other team gets.  In terms of Games Started (my chart metric), this is the first trade where the team trading up got the better end of the deal.

Moving on.  From the trade summary on MassLive.

Vikings jump back into first round:The Minnesota Vikings picked up a second first-round pick in a deal with the Baltimore Ravens. Minnesota acquired the No. 29 pick and in exchange the Ravens received a second-round pick (No. 35 overall) and a fourth-round pick (No. 98 overall). The Vikings selected Notre Dame safety Harrison Smith with the No. 29 pick.

I really have no comment on this one.

Moving on.  From the trade summary on MassLive.

Broncos move back again: The Denver Broncos, who traded out of the No. 25 pick, also traded out of the No. 31 pick in a deal with the Tampa Bay Buccaneers. Denver acquires a second-round pick (No. 36 overall) and a fourth-round pick (No. 101 overall). Tampa Bay picks up the No. 31 pick, to select Boise State running back Doug Martin and a fourth-round pick (No. 126 overall).

No comment here except that Tampa Bay moved up in order to select a running back.

The graph below shows the average pick for the top 20 prospects from the mock draft contest, as well as a line showing the highest and lowest draft slot they appeared in.  The three guys with the widest range seem to be Mark Barron, Stephon Gilmore, and Michael Brockers.

Average, High and Low Pick from the Mock Draft Contest