Ministry of Innovation / Business of Technology

Geeks get in the game at Sports Analytics Conference

Ars checks in from the annual MIT Sloan Sports Analytics Conference, where the …

Back around the time of the NBA All-Star Game, the subject of "basketball analytics" hit the headlines. On February 9, Mark Cuban, owner of the Dallas Mavericks, blogged about his team's stats-driven system for evaluating players and player lineups. Without giving away the guts of the system, Cuban explained that it values a player's performance more during close games and also looks at overall consistency. "Scoring when up by 30 is worth nothing," Cuban wrote. "The lower the variance, the more consistent the player on offense or defense."

One week after Cuban's blog post, the New York Times Magazine wrote about Shane Battier and the Houston Rockets' statistical approach to managing a basketball game.

Both articles suggested that pure trust-your-gut coaching was being heavily supplemented by data from high-tech stats packages like the open source program "R". The tools, in turn, were fed with better data—not just a player's shot percentage, but data about where the shots were taken, for instance.

Stats have been part of the game since its inception, but the sophistication of new approaches means that NBA teams now have to rely on the geeks in addition to the coaches.

A conference to call its own

Sports analytics is now hot enough to spark its own conferences into life; one of the best is the MIT Sloan Sports Analytics conference, which took place in Boston this last weekend.

"The trick of it is to make a case that's not 'I've got this magic black box over here. I can't explain it to you, but it's telling me that you're doing things wrong,'" said Mike Zarren, a Boston Celtics analyst, at the event. "Coaches are pretty competitive people and they want an edge. If you can give them an edge and convince them it really is an edge, they'll be pretty receptive. And the same thing goes for the players."

Zarren and other panelists—like Houston Rockets General Manager Daryl Morey, Dallas Mavericks owner Mark Cuban, Denver Nuggets analyst Dean Oliver, and ESPN basketball writer John Hollinger—spent lots of energy dodging specifics about the "edge" that analytics actually provide. NBA teams view their analytics as trade secrets, and rightly so.

Dean Oliver pointed out that 12 or 13 NBA teams sent representatives to the conference, and those teams were mostly having better seasons than the teams that weren't in attendance. Having that sort of edge means that participants tended to traffic in generalities.

Mark Cuban was the most direct. He described something that stands to become common practice as basketball analysis becomes universal. "We'll track [our players'] best shooting spot on the court and we'll tell them, 'You shoot that 3-pointer over there and you're an idiot because you're 1 for 99,'" he said. "'Move over ten feet and you're shooting 43 percent.' We want you to take that shot as often as possible."

He also pointed to work that the Mavericks do in assessing the performance of entire lineups, work that goes beyond assessing any one player's performance. "Players don't win games. Teams win games," Cuban said. "Over the eight years we've been collecting data you see repetitive elements that we can use to impact our decision-making, whether it's lineup combinations, lineups vs. lineups, coaching influence, whether coaches put together the best lineups, and how often they do it."

"This whole industry will get smarter over time," said Cuban, but probably not as smart as it could get if it actually shared its data. Basketball analytics was also on the agenda when the first Sloan Sports meeting was held three years ago. Then, maybe one hundred pioneers of the discipline met in a medium-sized cinderblock classroom. As a group, they were chastised by famed sabermetrician Bill James for not being more open in terms of sharing their methods and results. Today's basketball analytics practitioners gather online, but it remains as true in online chat rooms as it did at that early conference: withholding the secret sauce is standard industry practice.

Quantifying the game

Despite the increased attention from pro basketball and from the media, sports analytics remains a discipline with big unsolved problems. ESPN's Hollinger brought up how poorly defense is accounted for in game result data. Steals, blocks, and sometimes deflections are counted, but they hardly give a comprehensive picture of defensive success or failure. Better ways of capturing and recording data may help, but there's still an art to the whole process unlikely to ever go away, so long as coaches attempt to capture something as complex as a game in numerical form.

But high-tech gadgetry can certainly help. Cuban presented an open invitation to developers of video annotation and automated gesture recognition technologies, suggesting that these sorts of tools could improve his stats collection. "There are so many ways we can benefit from people who understand video," he said, "and can do things like event recognition of things in video and apply to not just basketball but all sports."

Even as Cuban spoke, the machine vision experts he needed were probably toiling away upstairs, as the conference was held in the same building as the MIT's Laboratory for Computer Science.

But the split between the lab geeks and the basketball court has grown narrower, and the demand for sophisticated computer vision systems to analyze player performance will no doubt shrink it further. Open source tools, such as the OpenCV computer vision library, promise to feed programs like R with massive amounts of data. If a couple of guys with pencils can amass a set of impressive stats out of a single game, just imagine the sort of numbers that automated computer vision systems could produce.

Stats geeks have always been attracted to sports, with its myriad statistics and box scores and hundred-year data sets, but there's generally been a sharp divide between the statheads and the players generating all those numbers. With the advent of sports analytics, though, players and coaches are willing like never before to take guidance from the number geeks.

Expand full story

You must to comment.