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Wednesday, February 18, 2009

Michael Lewis on basketball statistics

Not directly on topic for this site but it's hard to pass up an opportunity to mention a new Michael Lewis piece. This one is very Moneyball. It's about the Houston Rockets' forward Shane Battier, and the thesis is that, despite his low-scoring output he is one of the best "value" players in the NBA because of the little things he does and defensive prowess, and all that is quantifiable these days. The article is extraordinarily well-written (as always), and contains great summations of an analytical approach to sports, as is usual for a Lewis piece:

Here we have a basketball mystery: a player is widely regarded inside the N.B.A. as, at best, a replaceable cog in a machine driven by superstars. And yet every team he has ever played on has acquired some magical ability to win.

Solving the mystery is somewhere near the heart of Daryl Morey’s job. In 2005, the Houston Rockets’ owner, Leslie Alexander, decided to hire new management for his losing team and went looking specifically for someone willing to rethink the game. “We now have all this data,” Alexander told me. “And we have computers that can analyze that data. And I wanted to use that data in a progressive way. When I hired Daryl, it was because I wanted somebody that was doing more than just looking at players in the normal way. I mean, I’m not even sure we’re playing the game the right way.”

The virus that infected professional baseball in the 1990s, the use of statistics to find new and better ways to value players and strategies, has found its way into every major sport. Not just basketball and football, but also soccer and cricket and rugby and, for all I know, snooker and darts — each one now supports a subculture of smart people who view it not just as a game to be played but as a problem to be solved. Outcomes that seem, after the fact, all but inevitable — of course LeBron James hit that buzzer beater, of course the Pittsburgh Steelers won the Super Bowl — are instead treated as a set of probabilities, even after the fact. The games are games of odds. Like professional card counters, the modern thinkers want to play the odds as efficiently as they can; but of course to play the odds efficiently they must first know the odds. Hence the new statistics, and the quest to acquire new data, and the intense interest in measuring the impact of every little thing a player does on his team’s chances of winning. In its spirit of inquiry, this subculture inside professional basketball is no different from the subculture inside baseball or football or darts.

The key-stat that is used to evaluate Battier's importance is a modified version of the "plus/minus" stat first used in Hockey. The basic gist is one just looks at how good the team does with a player in the game versus out of the game -- i.e. how much do they outscore or get outscored by their opponents. Of course, the raw version of this stat is misleading, because all players from good teams would shoot up the rankings while those on bad teams, even excellent players, would fall far.

Supposedly, the Rockets' manager Daryl Morey has developed this stat further, though is cagey about how. But he is quite confident that Battier has one of the best "plus/minus" values in the league.

Phil Birnbaum of the Sabemetrics Research site is not entirely convinced:

[A]s I said, I'm a bit skeptical, still. I accept that Battier must be exceptionally good at defense, since (a) he plays 33 minutes a game and doesn't have very much in the way of traditional offensive statistics; (b) the Rockets have watched him and studied him and think he's great; and (c) his teams have done well. Still, from a scientific standpoint, the article is mostly anecdote and hearsay.

It shouldn't be all that hard to confirm the article's thesis and measure the size of the effect. If Kobe [Bryant] is good from one place but worse from another, that can be figured out by watching games and counting. If Battier holds him to those low-percentage shots when covering him, that can be counted too. And at the most fundamental level, can't you see what Kobe (and the other players) do when covered by Battier, and compare to what they do against the Rockets when Battier's on the bench? Something is better than nothing.

It's not really that I don't believe the Rockets. It's just that +6 points a game -- when it's acknowledged that Battier isn't all that great on offense – seems pretty high to me, and my instinct is to ask for more evidence.

One answer might be that the evidence is there, but that it is still proprietary. That was Morey's answer in the Lewis piece. Nevertheless, this does indicate to me that people are on the right track in at least trying to really analyze sports, and not get bogged down in trivia.

As a final note, the WSJ Numbers Guy, with a great sense of timing, offers up a post about the plus/minus stat featured in the Lewis article:

Earlier this week, [Mark] Cuban posted to his blog a list of the 30 NBA players who have the biggest positive impact on their teams when they’re in the game. They were ranked by a measure inspired by hockey’s plus/minus statistic, reflecting how well a team does with a player on the court, after accounting for the other players on the court with him. Cuban’s plus/minus adjusts for how good the team is without the player on the court as well as for the opponent and for game situations. (Without such adjustments, players on a top team like the Los Angeles Lakers would all look good, because the Lakers so often dominate.) . . . .

I sent Cuban’s surprising ratings to Roland Beech, proprietor of the NBA stats site, for comment. Beech works on player analysis for the Mavericks and incorporates a version of plus/minus into his own player ratings. But that didn’t keep him from criticizing the numbers Cuban posted. Cuban and Wayne Winston, who developed the system for him, responded. What resulted was a polite yet spirited debate among Cuban and his advisors about how to best analyze players.

Beech told me he considered plus/minus ratings, as adjusted by regression analysis, “one of the most over-hyped player rating systems.” He pointed to the incongruous finding that [Sebastian] Telfair is more valuable than [Dirk] Nowitzki, and blamed other questionable results — San Antonio Spurs point guard Tony Parker as a below-average player — on a paucity of data on top players’ performance without their star teammates. Beech also argued that there is too much noise in the system, because a player’s value is determined by coaching schemes, injuries and their assigned roles. . . .

Winston, the professor of operations and decision technologies at Indiana University who developed the system for Cuban, said that no system is perfect, but that plus/minus beats other player analyses because it can reflect defensive prowess — and Nowitzki’s defense was subpar at the beginning of the season. It’s with defense, Winston said, that plus/minus “really shines,” because defensive stats such as blocked shots, rebounds and steals can’t encapsulate a player’s worth.

We still need more and more of this kind of development with football. At least they're trying.


Newton said...

I think the most obvious way to do this for football would be to have a plus/minus for yards gained/allowed. Of course, you'd need to find a way to allow for differing styles of play. In the NBA, most teams score a similar number of points. That's not true with football.

Anonymous said...

Those that try to calculate or analyze a players value based on statistics are sniffing the wrong scent. I contend that a deep and wide understanding of positional responsibilities and schemes coupled with diligent scouting will always identify talent more efficiently than any mathematical or statistical analysis. This is because sports are inundated with randomness and variety than no equation could predict. Much better to spend one's time investigating a players character and physical tools and to know how he will fit with your scheme, which would obviously imply that a player's worth is variable depending upon his circumstance.

Brian Burke said...

Love the second graph. It's worth a million words--and I promise I'll rip it off sometime ! I think the lesson is that underdogs (if they really just want to win instead of just avoid being blown out) should start playing aggressively from the outset instead of just waiting until the last 5 minutes to start airing it out and going for it on 4th down.

Coaches (at least in the pros) try to minimize the left side of the graph, when they should be maximizing the right side.

Anonymous said...

I think the next article hits on a most important point; you can't just take into account the results of the game when you apply these thoughts.

If a coach makes a "statistically" good decision that works against him, he could be fired.

Doing the statistically correct thing, instead of the "socially" acceptable option, weighs heavily on coaches mind, especially given the atmosphere that coaching on any level has taken on in the last 10-15 years.

According to stats and figures, it may be the right decision. Doesn't make it the best decision for a coach to make.