Hoop Convos: Kirk Goldsberry

August 20, 2012 in Cover Story, Hoop Convos

There are few things better than getting philosophical about the game of basketball. In ‘Hoop Convos,’BallinMichigan will do just that, engaging in (hopefully) meaningful, free-flowing conversations with compelling writers and thinkers who love the game as much as we do. This week, we’ll have three special conversations, all related to the advanced stats movement in basketball and its ties to the state of Michigan.

By Patrick Hayes

Pretty much every basketball fan would agree that the game is fun. People who like statistics would probably agree that those are fun too. But when you try and bring advanced stats into a basketball discussion … well, results can be mixed.

The stats-vs.-anti-stats debates are not really worth rehashing, but in a nutshell, it amounts to anti-stat people feeling like a concept that can be dry (data, math and numbers) nerds up a pastime that people enjoy precisely because they aren’t required to put a lot of time and energy into learning new, complex concepts. That’s certainly understandable, but with NBA and even college teams increasingly using advanced statistical analysis, it takes more work to be an informed fan these days.

That’s why Kirk Goldsberry‘s work is so exciting. Goldsberry (follow him on Twitter), a visiting scholar at the Harvard Center for Geographic Analysis and an assistant professor in the Department of Geography at Michigan State University, started Court Vision Analytics, a project that combines Goldsberry’s academic and professional background in mapping and imaging with his love of basketball to create easy to understand infographics that tell complex statistical stories. Goldsberry presented his work at the MIT Sloan Sports Analytics Conference, he’s contributed to the New York Times NBA coverage and his work has been featured on many different NBA sites.

Below, Goldsberry, one of several of the state of Michigan’s connections to advanced statistical work in basketball who I will feature this week, discusses his work, what he loves about basketball and more.

Talk about your interest in basketball and what attracted you to this type of research and work?

I’ve loved basketball my whole life, played basketball a little bit, not in college or anything, but I still play pickup here at Harvard and at Michigan State. Like a lot of people, I try to make work enjoyable, and one of the ways to do that I’ve found is to study or write about things that you like. My favorite things are statistics, graphics and sports, and basketball is my favorite sport, so the project was kind of a natural confluence of my main interests.

I started doing the project last year and it really picked up in November/December of 2011. I presented at Sloan (MIT Sloan Sports Analytics Conference) in March and at that point, I was really surprised at how popular the project was getting. Then I started devoting a little more time to it and started the blog.

More than anything, as a basketball fan and as a statistics guy, I saw an opportunity to uncover these invisible truths about how basketball players play and reveal invisible spacial structures we all kind of have in our head about players like LeBron James or Carmelo Anthony. We all have these mental images or maps of different teams strengths and weaknesses as they relate to the court. The project is simple — the idea is to get those out of our minds and onto a computer screen to really help us understand what makes individual players different and expose these spatial tendencies or patterns in different parts of the court.

I think it’s become popular because it’s unique, but also because it corresponds to how we think about the game as players — for example, we all have our own sweet spots, where jumpshots are better or worse from different angles. I think it’s an interesting way to expose how people think about the game in a way that text simply can’t do. I obviously love text, I’ve written a dissertation, I have a blog, but at the end of the day, sometimes you need a picture to tell the story, and I found an opportunity to use scientific pictures to tell basketball stories. My expertise is in visualization and map-making. At Michigan State, I teach students how to make good graphics, how to make maps and how to communicate visually, so the project is a confluence of both what I teach and what I’m interested in personally, so for me, it’s really a perfect project.

There is really a lot of in-depth statistical work going on with complex and continuously evolving stats and measures in basketball, but there has always been a kind of push-back on that from people who may not understand or want to be bothered with the complex math or science behind it or who don’t think it’s a necessary element in the game. Do you think that work you’re doing, putting complex stats work into easy to understand graphics, can maybe help bridge that gap some?

I know it can. We’ve seen it in other domains. For instance in chemistry, the Periodic Table has made a huge set of chemical elements understandable in new ways. The power of graphics to simplify or translate statistical information into knowledge is one of the huge pillars of the project. My project is not unique in that sense, but it is unique in the context of basketball. I think that’s what it has the potential to do. Every one of those charts you look at is thousands of numbers encoded visually as opposed to encoded in a spreadsheet.

These spacial structures are immediately understandable to the human eye. You can take advantage of the most powerful sense we have as human beings, which is vision. I can show that chart to a basketball coach in four seconds and circle key areas with a Sharpie and walk away, and that coach has just understood the product of a really sophisticated statistical analysis in a few seconds without ever seeing brief notation, without ever seeing a decimal, without ever seeing some obtuse numerical jargon that, let’s face it, most basketball people and most human beings don’t communicate in that statistical language.

So yes, this helps people who are not domain experts in statistics understand statistics or at least understand the findings of statistical analysis. When you hear coaches or general managers or people in the media who are skeptical of statistical work or don’t see a use for it, to me, that’s on the analytics community, not the people pushing back. It’s part of our job to make our findings digestable by people. It’s the part of of the scientific process I like to describe as landing the plane. Great, you’ve done great analysis, you’ve found something out, now you know that. But I think that’s where a lot of people stop. One of the strengths of good visualization is it helps you land the plane in the sense that not only do you know that, now you’re sharing that with other people who also just learned that. The more effective you can be in that sharing, the better you are as a scientist, the better you are as a communicator.

Growing up a Pistons fan, two of my favorite players were Dennis Rodman and Ben Wallace, so obviously, your ‘Where do rebounds go?,’ research was really interesting to me and helped me appreciate even more the unique skillset those two had as dominant rebounders. Are there players who have come up in your research who you’ve discovered things about or maybe found some new appreciation for based on your work?

Oh certainly. One of the cool things for me about the project is when I’m toiling away at the computer working on analysis, I don’t know what’s going to come out of it, so I’m learning too.

When I was doing the New York Times piece during the Finals, I remember looking at James Harden. I’ve watched a fair amount of Thunder games this year, but I didn’t realize (before the analysis) that he doesn’t really have any mid-range game. I’m sure Thunder fans, the team and his opponents know that, but I didn’t know that. I’m not picking on James Harden, these things are just really interesting because they reveal truths about a player’s game, about the spatial nature of rebounding, the strengths and weaknesses of teams. I learned that the Sixers shoot a ton of mid-range shots and I never knew that. It makes you think about players in new ways and watch the game differently.

I made a graphic that shows Carmelo (Anthony) is extremely asymmetric – he shoots far more from the right side than the left — and it makes it more interesting when you actually see that play out in the game.

The rebounding graphic, one of the reasons I like it, is analytics have an opportunity not only for the Miami Heat to understand why Chris Bosh shooting mid-range shots isn’t a good thing, but they can help Miami fans understand that as well. That’s one of the reasons I started the blog — we can all learn from getting this information out there, analytics don’t have to just be in these silos for NBA teams to use, we can all use them.

The NBA has this really unique, vibrant community of writers online and there has always been kind of a graphic or infographic element in some of that unique coverage, particularly with Free Darko. Your work has really become popular in that audience. Did you have any idea it would when you started out?

No, I really didn’t. The project really blew up at the Sloan conference. I was just floored by the reception it got there from people like Zach Lowe, reporters from the New York Times, a lot of the TrueHoop guys were so nice to me and so supportive in helping me understand how to get this off the ground.

The NBA blogosphere is unique and I really love it. There are not only a lot of really smart and creative people in it, but they’re also really nice and supportive and doing all of these wonderful things. I’ve been really floored by not only how popular the project has done, but also by the number of people who have really helped me make it more popular. People like Zach Lowe, Kevin Arnovitz, Henry Abbott and Beckley Mason have each helped me multiple times in different ways and they didn’t have to do that. I’m really a huge fan of the NBA blogosphere and there’s a lot of creative and under-appreciated work going on out there.

One of my favorite things to do is just ready my Twitter feed during NBA games. It’s such a wild interaction, it’s like watching sports with 200 of the coolest basketball fans on the planet. Before March, I was kind of isolated in this world, but since, I’ve just really enjoyed getting to know these people and meet them.

Looking at your work on the corner three for example, you see concepts like that being talked about by teams and coaches more and more — one of the big reasons the Heat signed Ray Allen was for his ability to hit the corner three, Lawrence Frank talked about it with the Pistons last year — with more teams realizing the importance of this type of statistical work, do you have aspirations of working in a front office or scouting department at some point?

Yeah, I’m certainly open to it. I’ve talked to a few teams. Who wouldn’t want a chance to get your competitive juices flowing and try and help one NBA team beat another team? I still don’t know if I’ll ever get the chance to do that, but the possibility is a lot more realistic now than it was for me last year. The idea that I could work for a NBA team and help them understand how to get one or two competitive advantages in a game is really excited to me. I don’t think many of us would turn that opportunity down.

As a fan, who are the teams or players you enjoy watching the most?

I like to watch the Celtics, being here in Boston, but in general, I like to watch the quote-unquote smart teams — Boston, Oklahoma City, Dallas, San Antonio, Miami. Some of the people here in Boston don’t like that I like the Heat, but I just like watching the teams that play well together.

I also like to watch players or teams I’ve recently studied or uncovered something about. I did the Kevin Durant chart, so when you see his shooting chart and watch it happen, it’s a lot of fun. I put out the chart in April, which showed how extremely effective Durant is from the top of the arc. It’s his favorite shot, he shoots a ton there, he owns that spot. The fast forward to the playoffs when the Lakers are playing the Thunder, then last possession of the game, Durant is approaching the top of the arc and Ron Artest is for some reason sitting back six feet and we all know what happened — Durant nails that shot. What struck me was why didn’t the Lakers know that was his best shot?

I like to watch that because you can sometimes see the awareness or lack of awareness of a player’s strengths. Similarly, I like to watch transactions now. Ray Allen is my favorite shooter and one of my favorite basketball players of all-time. When he left for Miami, he took the best corner three shot in the league with him. The second best guy in the league at the corner three is Courtney Lee and three weeks later, the Celtics have Courtney Lee, to me, that’s just showing that they’re doing the same thing that I’m doing. It’s not really out there that much who the best corner three shooters in the league, but some NBA teams have it. You lose an older Ray Allen and you put a younger Courtney Lee in his place and you don’t lose that much. I think that’s fascinating now. So it has not only changed the way I watch games, but also the offseason, free agency and the draft as well.