Wednesday, June 29, 2011

Future of Sports Analytics

Five questions on the future of sports analytics. What are your thoughts?

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Tuesday, June 28, 2011

Additcted to Math?

My first reaction after reading Jonah Lehrer's piece on Grantland was to try and ignore it. It's the same debate we've been having since Lewis published Moneyball right? But there is something different in this latest railing against sports analytics (and please can we stop referring to statistics applied to any sport as Sabrmetrics? That is a baseball term, nobody in basketball or any other sport refers to their work that way.) The difference here is that instead of being accused of not being relevant, us geeks are being accused of being too relevant. Much as my grandfather accused me of ruining sports, Lehrer is accusing decision makers in sports of ruing the game because they only care about the numbers.

This is a rather bizarre charge, as any of who have worked for teams not named the Houston Rockets can tell you. Decision makers (GM's, coaches, etc) are not exactly waiting breathlessly for the latest pronouncements  from their resident geeks. Do some teams factor good analysis into their decision making? Sure they do. By my count 11 of the 16 NBA playoff teams employed analysts, at least to some degree, but all of those teams also have serious scouting departments that employ a lot more people, and the scouts are not ignored. Personnel and coaching decisions are looked at from every angle imaginable, and it is rather silly to suggest that somehow math has put all of these other sources of information in the back seat.

I do want to address two specifics of the article though. The first is the use of the Mavericks as the counter example and the second is the phrase "The underlying assumption is that a team is just the sum of its players, and that the real world works a lot like a fantasy league." and both points actually tied back to the same idea.

First the Mavericks: The Mavericks are one of the most innovative teams when it comes to analytics, employing the first statistician who actually travels with the coaching staff and works with them on a daily basis. Roland Beech is one of the best statisticians in the world when it comes to basketball, and while I do not know what Roland's numbers looked like for Barea, I can bet that he had  input on the decision. Data may not have made the decision, but, as it should be, was a factor. To continue on the Mavericks example, Lehrer notes that "According to one statistical analysis, the Los Angeles Lakers had four of the top five players in the series. The Miami Heat had three of the top four." (cleverly linking back to Beech's own site 82games.com to make his point). The problem is that not all analysis is created equal. What is published on the internet may not always be the cutting edge of basketball analysis (or football or baseball or soccer ....). Wayne Winston once famously said that, because of his analysis, we would advise a GM not to sign a young Kevin Durant at any price. Just because some one puts a number down does not mean it is a valuable number.

On the second point regarding the assumption that a team is somehow the sum of its parts, I would suggest that most GMs, Coaches, and even statisticians are sophisticated enough to know that  this is simply not the case. I have never heard a serious statistician argue (outside of baseball at least) that you can simply add metrics together and get a result that predicts the outcome of adding a specific player.

What this comes down to, I believe, is a general misunderstanding about how sports analytics is both practiced and utilized. Sports analytics is, at times, a set of sophisticated tools that can help provide insight into the games we love. It can even be applied, as Dean Oliver has, to issues like team fit, but any good statistician will also be the first to explain to a decision maker the limits on the analysis. Are their people that take their analysis too far and draw conclusions that are not supported by their own work? Of course, their are irresponsible people in every profession. That does not mean, however that the tool is being over used or is in any way shifting a decision maker's focus away from the important variables.

Let us not have this debate any longer. Live and let live. Statisticians, scouts, fans, coaches and  general managers can choose how much stock they put into various types of analysis, but lets not dismiss an entire field that is, honestly, still in its infancy.

Monday, June 20, 2011

Sports Analytics: Should Fans Care?

I have not posted for while but the passing of Father's Day yesterday has inspired me. The main reason that Father's Day could have this effect on me is that I am occasionally and forcefully reminded that most of the world does not care one lick about sports analytics, and can even be offended by sports analytics. This reminder was given to me by, of all people, my own grandfather. My grandfather is a rather opinionated man (as any 91 year old has a right to be) and likes to occasionally make proclamations about the world, and how I am personally functioning in it.

His most recent proclamation was that people like me are ruining sports. The normal argument about how advanced statistical analysis is bad for sports rests squarely on the idea that it is not an effective tool. As my grandfather is never one to take the road well traveled, he instead took the opposite tact - sports statistics is too effective a tool. Yes, sports statistics is ruing sports, because the analysis takes all of the uncertainty out of sports. We are too good at what we do.

I thanked him for the complement, but it reminded me of some work I had done with Matt Futterman at the Wall Street Journal. In this analysis, I looked out how predictive baseball standings were on June 1 of whether a team would make the playoffs. Turns out the answer is very predictive (teams below .500 on June 1 has only a 9% chance of making the playoffs). This seems to be in line with my grandfather's argument, fans of teams that are below .500 in MLB now might as well give up. Which leaves me with the question: Did a simple correlation calculation suck all of the fun out of the baseball season for a large chunk of fans?

In my defense, I would like to offer two ideas that, regardless of how well statisticians can predict outcomes, should inspire fans to want more, not less analysis.

The first idea is that all leagues collect and report statistics. These statistics are used all of the time by writers and announcers to tell stories about a player or a team or a season. The problem is that many of these statistics are misleading, incomplete, or just plain wrong. For example, one of the most convoluted statistics in sports is the NFL QB Rating. If a QB completes a 4 yard pass on 3rd and 3, he has made a good play - keeping his team's drive alive, but his QB rating is likely to go down (I say likely as the exact calculation depends upon the QB's performance up to that point in the game), while if a QB completes an 8 yard pass on 3rd and 10, the team has to give up the ball, but the QB's rating probably went up. Having watched the two plays you may know that one QB made a good play, while the other didn't, but if you didn't watch the plays, and just looked at the reported QB ratings, you might get the wrong idea about the performance of the two players. Since we are going to be given numbers to look at and they are going to be used to tell stories, better to have the right numbers.

The second idea has to do with one of the many reasons we love sports: the incredible. Whether it be an incredible play, and incredible game, or an incredible season, the truly spectacular and unexpected moment is a unique aspect of sports. We rarely, if ever, have the truly spectacularly unexpected in any other form of entertainment. What good analysis does, is allows us to recognize again and again, how truly uncommon a moment was. The statistics can give us context for understanding how rare something we just saw, really was. Returning to baseball, the Pittsburgh Pirates are currently 2 games below .500, which means, at best, they have a 9% chance of making the playoffs. But what if they went on a run, maybe picked someone up at the trade deadline, and made the playoffs. The analysis allows us to understand how unlikely and special that would really be, and to appreciate it 4 years from now and remember how special that Pirate's team that beat the odds really was.

I would not try and argue these points with my grandfather, we have plenty of other battles to have, but I would suggest that most fans can appreciate, and in fact desire more and better analysis. When the writers and broadcasters embrace new statistics and analysis, then fans can understand the games they love better, and identity and appreciate the truly spectacular in a deeper and longer lasting manner.