Box Score Beat

A Statistical Revolution

Posted on 15. Feb, 2009 by Collin Orcutt in Sports Journalism

The NBA is reaching another apex, and in more ways than one. In recent history, the league peaked with the greatness of the Celtics/Lakers rivalry in 80′s, the Bulls’ reign of the early and mid 90′s (with back-to-back Jordanless championships by the Rockets mixed in), and the Lakers’ three-peat through the turn of the millennium. Now, behind the continued maturation of some sensational young talent (James, Wade, Paul, Howard), and with some long-time stars embracing roles as savvy veterans and league ambassadors (Garnett, Bryant, Duncan), the league appears on the cusp of brilliance once more.

The game is not only cresting in level of play, though; it’s also reaching new heights in how it is measured. Over the past few years, there have been big steps taken in both the creation and utilization of some exciting new statistics: things like wins produced per 48 minutes (WP48), a stat created by the triumvirate at Wages of Wins; Player Efficiency Rating (PER), a metric designed by ESPN stat guru John Hollinger; and the field-goal efficiency couplet of True Shooting Percentage (TS%) and Effective Field-Goal Percentage (eFG%), the latter a statistic created by current Clippers’ coach Mike Dunleavy.

However, the creation of stats doesn’t necessarily translate to their implementation by teams. Stat geeks and basketball nerds have been playing with these new metrics for years now, but there have been few reports of teams taking advantage of these methods. Until this weekend.

In the most recent edition of the New York Times Magazine, writer Michael Lewis (he of Money Ball fame) penned an article entitled “Money (Basket) Ball!” In the piece, Lewis simultaneously presented Shane Battier as a player who, by traditional stats, has immeasurable worth, and used him as a lens through which to view the Houston Rockets incorporation of new metrics.

The entire article is full of fascinating stuff (well worth the read if you’re a basketball fan of an type), but there are a few topics that stood out. First was the look at basketball as the most life-like, and therefore most complex, of any sport:

“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 difference in basketball is that it happens to be the sport that is most like life.”

At first, the final comment seems to be unwarranted. Basketball is free-flowing compared to sports like baseball and football, so perhaps it makes sense that Lewis says it’s most life-like. But, then again, soccer is free-flowing. So is hockey. And so is team handball for that matter.

It isn’t until later where his statement becomes clear:

“There is a tension, peculiar to basketball, between the interests of the team and the interests of the individual. The game continually tempts the people who play it to do things that are not in the interest of the group.

…

It is in basketball where the problems are most likely to be in the game — where the player, in his play, faces choices between maximizing his own perceived self-interest and winning. The choices are sufficiently complex that there is a fair chance he doesn’t fully grasp that he is making them.”

What Lewis appears to be saying is that, in basketball, there is an effect for every action, and there are many, many actions throughout the course of a game. Due to the amount of scoring, basketball inherently increases the amount of times where there are decisions to be made, and therefore the amount of ramifications that occur.

More importantly, as much of the article covers, these effects are becoming quantifiable.

In talking about the new era of stats, Lewis also discusses the old ones: points, rebounds, assists — stats that are “easy to measure” and that offer “warped perceptions of the game.”

As Rockets’ General Manager Daryl Morey told Lewis, these stats are the cause for inefficient play by many players in the league:

When I ask Morey if he can think of any basketball statistic that can’t benefit a player at the expense of his team, he has to think hard. “Offensive rebounding,” he says, then reverses himself. “But even that can be counterproductive to the team if your job is to get back on defense.” It turns out there is no statistic that a basketball player accumulates that cannot be amassed selfishly. “We think about this deeply whenever we’re talking about contractual incentives,” he says. “We don’t want to incent a guy to do things that hurt the team” — and the amazing thing about basketball is how easy this is to do. “They all maximize what they think they’re being paid for,” he says. He laughs. “It’s a tough environment for a player now because you have a lot of teams starting to think differently. They’ve got to rethink how they’re getting paid.”

Morey’s point is one that I have heard before. Late last year, I interviewed David Berri, co-author of Wages of Wins and current associate professor of applied economics at Southern Utah University. In the interview, Berri said there is a league wide deficiency in player analysis, with too much emphasis put on scoring:

“If you look at the link between free agent salaries and what players do on the court, the factor that dominates the discussion, dominates the decision, is how many points they score. It’s not how efficiently they score, it’s how many points they score total. So the players have this incentive to take as many shots as they possibly can.”

Berri said that many GM’s make systematic mistakes year after year, something he thinks stems from them basing most of their decisions off of simply watching the games. Because scoring is the most dramatic thing in basketball, Berri surmised, it has historically dominated decision making instead of more useful stats.

And players are smart. They understand this. They know there are far more Ricky Davises and Tim Thomases in the league than there are Ben Wallaces. Said Berri, “The players know that the guy who scores the most is they guy who gets paid the most, so they have every incentive to shoot as much as possible.”

Lewis reported something similar about Battier:

‘…in the final second of any quarter, finding himself with the ball and on the wrong side of the half-court line, Battier refuses to heave it honestly at the basket, in an improbable but not impossible attempt to score. He heaves it disingenuously, and a millisecond after the buzzer sounds.”

If you watch enough NBA games, you’ll see many players doing this. The rationale is simple: it’s a field goal attempt that has very little chance of going in, so it’s almost guaranteed to lower their shooting percentage. Rockets GM Daryl Morey told Battier that they didn’t count “heaves” in their field goal percentage, but Battier didn’t buy it: “… Shane’s smart enough to know that his next team might not be smart enough to take the heaves out.”

Basketball is a business, and there’s no guarantee that Battier will finish out his career as a Rocket. Since not every team has the statistical awareness that Houston does, it’s in Battier’s best interest financially to use every advantage he can when it comes to maximizing his stats.

It may not be too long, though, that the stats Battier’s worrying about aren’t measuring points and field goal percentage as much as efficiency and his effect on wins.

***UPDATE***

Matthew Yglesias at the Think Progress blog writes that, contrary to Lewis’s claim that Batter’s impact can’t be measured, David Berri actually did so, analyzing Battier’s effectiveness through his statistical methods back in 2007. Here is the conclusive point from Berri’s post:

“As we can see in Table One, the story we tell about Battier from the box score depends on how we view the data.  When we rely on scoring — or scoring dominated metrics like NBA Efficiency and PER — we see a below average player.  But when we consider Battier in terms of efficiency, we see a player that is above average and a key player in the success the Grizzlies had from 2003-04 to 2005-06.”

Tags: applied economics, basketball, David Berri, ESPN, John Hollinger, Michael Lewis, Money Ball, NBA, PER, Shane Battier, statistics, Wages of Wins