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Meet Adjusted Plus/Minus

At 82games.com, Professor Steve Ilardi explains a set of statistics we will be learning more and more about in the years to come: adjusted plus/minus. These statistics are not new. Dan Rosenbaum, for one, has written about them extensively. But Ilardi provides a tidy explanation of what it's all about.

By now, many basketball fans are familiar with the basic plus-minus concept, as it has been showing up for years in game commentary at both the NBA and college levels. You might see it alluded to in a game graphic that looks something like this:

In essence, the plus-minus stat simply keeps track of the net changes in score when a given player is either on or off the court. Logically, of course, the players who make the greatest overall contributions to team success should be the ones with the largest positive plus-minus impact. Unfortunately, however, the plus-minus stat doesn't always fare particularly well in the messy real world of NBA basketball.

For one thing, some players spend most of their time on the court in the company of very good teammates, while others frequently play in tandem with much weaker players. The plus-minus stat doesn't account for these inequities at all. Likewise, some guys always find themselves matched against the opponent's best players, while others more often face the opposing team's second unit. That's another big problem as far as the plus-minus stat is concerned. What's needed, of course, is some way of adjusting the plus-minus stat to account for all such potential confounds.

This is exactly what the adjusted plus-minus stat does: it reflects the impact of each player on his team's bottom line (scoring margin), after controlling statistically for the strength of every teammate and every opponent during each minute he's on the court.

My thought is that this way of assessing players is extremely valuable -- for one thing, unlike almost everything else, it captures defensive effort and skill.

It's also not beholden to box scores, with their inherent biases.

How useful it really turns out to be, however, depends on exactly what's in that adjustment. Presumably that will evolve over time as we understand the game better? I'd love to understand that part of it more.

Ilardi even provides player rankings based on last year's numbers-- with some fascinating results. By this measure, Kevin Garnett nosed out LeBron James as MVP, and Anthony Parker and Rajon Rondo were top 20 NBA players.

(As a Blazer fan, I also noticed this ranking system is brutal on Portland players. The way these statistics tell it, last year was basically Ime Udoka being held back by every other Portland player.)