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Can Numbers Turn Around The Pacers? Say Hello To Kevin Pelton

Numbers alone won't turn things around for the Indiana Pacers, but they can play a huge role when properly applied. That's why I'm so excited that the Pacers are working with Kevin Pelton, well regarded APBRmetrician and writer from Basketball Prospectus, to sharpen their decision-making process by utilizing Pelton's analysis.

In fact, this move by the Pacers equates to landing a productive top pick in this year's draft. Consider it a deft free agent signing, especially for a team that has no cap room to sign any free agent players this summer. So I thought it might be nice to learn a little bit about Kevin Pelton and he was kind enough to answer some general questions about his background and thoughts on the rise of advanced stats in the NBA. 

Indy Cornrows: How did you get into this field of work? Can I assume you are passionate about both basketball and numbers? If so, can you believe how the field of advanced stats has progressed from the perspective of the NBA organizations, where in the not too distant past it was likely viewed as a nice little hobby to now, where we're at a point that this type of analysis is the life blood of some very successful organizations?

Kevin Pelton:Yes, it's definitely safe to assume I'm passionate about both of those topics. As a kid, numbers in sports always interested me, and I recall calculating stats for the Sonics in Microsoft Works back when I had to type everything in from the paper. By the time I got into college, I started reading first Rob Neyer and then Baseball Prospectus, who opened up a whole new world to me in terms of understanding how statistics could be more useful in baseball. Looking for similar basketball analysis was a natural next step, and eventually I discovered Dean Oliver's pioneering work, as well as what John Hollinger was doing long before he was a fixture on I started writing about basketball using their building blocks, and was lucky enough to catch on with Basketball Prospectus when the site started prior to the 2007-08 season.

As for the growth of the APBRmetrics field in that time, yeah, it's pretty remarkable. I was working for the Sonics' Web site when Oliver was hired by them as a full-time consultant in 2004, which was a pretty huge step forward. One of the great things about Dean is he's always been about the community rather than his own progress, and by setting a good example of how statistical analysis could help teams, he's responsible for a lot of the growth. The other big factor was Moneyball, since a lot of owners read the book and started wondering if they could do the same thing in basketball. So within a span of about six years, we've come from a point where a couple of teams were getting numbers from some outside consultant to the point where the Wall Street Journal recently reported that half the league's teams have someone devoted to analytics and in many cases that person (or people) have a prominent role. I never would have anticipated that had you told me about it in 2004.

Indy Cornrows: How did you end up consulting for the Pacers? Did you have to sell your services (for lack of a better term) to some in the organization?

Kevin Pelton: David Morway and I actually share a close mutual friend, so he was aware of my work in addition to what other people are doing. Working for a team wasn't necessarily something I was actively looking to do, but because the Pacers were willing to allow me to continue to write and they had an interest in making the numbers part of what they look at in the decision-making process, the fit was a good one.

Indy Cornrows: The Pacers currently gather a lot of data and at least seem to apply some sort of +/- analysis to their game prep. It's one thing to gather all kinds of data but another thing to use it effectively. Will you be able to utilize that data and re-purpose it for your own analysis?

Kevin Pelton: One of the places I may be able to help the organization is in terms of understanding and explaining some of the data that is out there. I hope to bring some expertise in that specific area, like other members of the front office do in terms of scouting, while the decision-makers have the much more challenging task of synthesizing all the information they've gathered.

Indy Cornrows:Your SCHOENE projections (a name I love since Russ Schoene was part of some of my favorite teams with the Supes when I was in college and fittingly also had a little run with the Pacers) are a fantasy gold mine. How do you feel about putting some of those methods to the test for a real NBA team? What other methods of analysis are you partial to with regard to individual players and team play?

Kevin Pelton:It's an exciting challenge, but also a responsibility. While we take the analysis we do at Basketball Prospectus very seriously, here there are real-life implications. The aspect that makes working for a team very different than writing about all of them is the importance of fit, something I try to emphasize as much as possible. Often, in writing the idea is to try to come up with the value of a player independent of his teammates, his coach and his situation. That's essentially the goal of many player rating systems, like Hollinger's PER or the WARP system I use. Here, context is everything, since a player has to make sense not in general but for the Pacers specifically. So there is definitely a lot more nuance than simply looking at a list of players and picking out the one with the best rating.

At the team level, per-possession Offensive and Defensive Ratings underlie all the other analysis we do. Beyond them, I'm a big believer in the Four Factors that break down offense and defense another level. As for individuals, I think a big piece of the analysis is understanding the importance of and the tradeoff between True Shooting Percentage (the best measure of scoring efficiency) and usage rate (the percentage of his team's possessions a player uses while on the floor). All of those stats can be found on our player and team pages at Basketball Prospectus. Plus-minus is also a piece of the analysis, though it has to be used with more care because the results can be misleading, especially during a single season.