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Wednesday, February 27, 2013

Some news is worse than no news: The NFL Scouting Combine and projecting draft picks



In general it is a pretty good assumption that adding information to a decision making process improves the outcome. In specific instances, however, the added information can be extremely disruptive. With respect to the NFL Scouting Combine, does it help? It depends…



The method



While we do not have visibility into teams’ draft boards before and after the combine, we do have access to one consistent record of pre- and post-combine sentiment from a consistent (and remarkably well-coiffed) source: Melvin A. Kiper, Jr.



By pulling several years of draft predictions (2004 to 2008) and evaluating the change in quality of predictions on either side of the combine, we can evaluate whether they improved. For each player, the absolute difference between the value they have delivered and the value of the player picked in that position will be the quality of the prediction: the lower the better. If, before the combine in 2004, Kiper projected Larry Fitzgerald to be the 1st pick, then the quality of that pick would be the value provided by Philip Rivers as the actual most valuable draftee (64% as ranked by Career Salary Cap Value) less the value provided by Fitzgerald (52%). The average of all those individual values is the aggregate quality of the prediction[1]. A prediction with 0 error will have all players ranked in order of their actual career value to date.



Remarkably (or maybe not remarkably, he’s been doing this for a long time), Kiper shows an improvement at the aggregate level from before the combine to after. Across 152 individual players the average improvement in the prediction per player is 0.03% of the salary cap closer to the actual value of the players. Of course this 0.03% means that the average prediction improved by $38,000 of football value at the current cap number. The real action is looking at the distribution of increased (or decreased) accuracy for each position.


Friday, February 22, 2013

How much should LeBron James be paid?



Well look at this, my little blog post has gotten some attention from ESPN. There is also the slight possibility that the brief surge of media interest following NPR’s publication of the story had an impact, but it’s not worth quibbling about the source. The LeBron is underpaid story simply will not go away.



As has been explained at length, LeBron is incapable of being paid what he “deserves” in the NBA. The structure of the collective bargaining agreement between the players association and the owners dictates the maximum that any specific player can earn given their tenure in the league, tenure with their current team and several other factors. As I noted in my earlier post, this has taken the ratio of top salary to average salary from over 20:1 in 1998, when Michael Jordan dominated, to just about 5:1 now with Kobe Bryant leading the way.



But what if it didn’t? What if players could freely sell their services to any team with no limits on the player’s salary or the team’s payroll?



There are a couple different ways to crack this – so I will try them all



Soccer (EPL and La Liga) - $51.5 million



LeBron would probably be quite a soccer player, but would he like to be paid like one? If the NBA’s labor market were like soccer’s (still with the same average salary) he would be in for a big raise.



The average player in the English Premier League in 2011-2012 made an annual salary of 1.16 million pounds (roughly $1.96 million). The highest-salaried player in the world – outside of well-known players slumming it in Russia for massive, oil-fuelled paydays – was Cristiano Ronaldo at Real Madrid with $19 million according to Forbes. Don’t worry about the comparison between EPL and Real Madrid, suffice it to say that there is a roughly 10x multiple above the average player for the best-compensated one.  Taking the NBA’s $5.15 million average, even I can do the math on this one.



NFL - $62 million



With an average salary (as of 2011) at $1.9 million and top salary at $23 million (way to go 2011 Peyton Manning!), the NFL boasts a 12x multiple from average to top.



MLB – $49.8 million


The average MLB player pulls in $3.31 million (again as of 2011) and Alex Rodriguez managed to convince the Yankees to pay him $32 million in the same season.




MLB, but fancier – $120 to $164 million



Buying a win via free agency, in terms of WAR, tends to cost MLB teams roughly $4.5 million. With half the games, however, the wins are worth twice as much in the NBA, so $9 million. Alas, the payrolls are lower overall ($67 million in the NBA vs $92.9 million in MLB) so we will drop it back to $6.5 million to stay in line with the overall spending as it is.



Stepping into our time machine for a second, way back in 2009-10 when LeBron was still shouldering most of the load himself in Cleveland he put up an insane 25.3 WARP according to Kevin Pelton. Basketball-reference.com has him on a slightly less-high 18.5 of their not-quite-comparable Win Shares stat.

Basketball WARP (Kevin Pelton) - $40.5 million

Pelton, who developed WARP for basketball and now writes for ESPN.com, puts $/WARP at $1.5 million and derives $40.5 million from that. 


Three Letters: CBA


All of these numbers, but especially the Baseball to WARP/WS-based metrics, imply that LeBron is seriously underpaid at $17.5 million this season. 

Pelton's $40.5 million is very different from my $120-$164 based on the same WARP (or Win Shares) metrics, but his is based on what teams pay for WARP within the current structure. The MLB number is (relatively) free market compensation for talent and I believe represents a better version of what LeBron would make in a similarly free market.

The NBA’s unique individual player salary caps make it the only league here where the top paid player is neither the best in the league nor had any claim to being the best at the time the contract was signed (calm down Kobe lovers, he used to be really good but he signed that contract in 2010).

Monday, February 18, 2013

Talent Markets in Sports – The value of the Franchise tag



The following is adapted and expanded from my exceptionally and exasperatingly long read on the NFL Draft Value Chart - I'm not sure anyone has made it to the end so I am excerpting key parts when I am too lazy to write a new post.
 

After seeing Andrew Brandt (a must-follow on Twitter @adbrandt) refer to an espn.com article he wrote last summer on the Franchise tag, I thought I would dust off a portion of my NFL Draft behemoth and jump on the bandwagon. 
Each of the three major American sports leagues (with apologies to the Raptors and Blue Jays, and hockey) has a particular way of dealing with their markets for talent. By looking at the comparison we can see some of the sources of value for players and owners - and the massive negotiating advantage that is the Franchise tag.


Baseball – Good for veterans


Baseball allocates the first six years of a player’s Major League career to the team. Arbitration means that the player has some leverage to improve their situation – particularly in later years – but they still receive a salary below their market rate during this period. Once they have completed their first six seasons a player is a free agent in the truest sense. Any team can offer him a contract for any amount or length of seasons. The result of this structure is that the Winner’s Curse tends to play out for in-demand free agents and surplus value to the team is not likely to be found in players outside of their arbitration years.

Thursday, February 14, 2013

In the Super Bowl, bet on the underdog



Editors’ Note: I really did have this started before the Super Bowl, but real work has been a bit crazy lately and this one did not get out in time. Honestly. I promise.

Another year and another upset in the Super Bowl. Here’s a quick primer on how common an occurrence this has been over the past decade or so. I pulled data from armchairanalysis.com, which contains a wonderful database of game data, including spreads, game conditions and play by play data going back to the 2000 season. For the 12 seasons ending in 2011 (2012 data is not available yet), here are the percentages of underdogs covering:



It’s also interesting to see the outperformance of underdogs in terms of points rather than simply covers:



Anyway, just an interesting quick analysis that would have been much more helpful before the game. At least now it’s out there so I can just put it back on the front page next January and end up looking dumb when favorites cover.