Two years ago, at the fifth annual MIT Sloan Sports Analytics Conference, the backdrop in the main panel room featured a single image, repeated like wallpaper: Kobe Bryant putting up a fadeaway shot as the Houston Rockets' Shane Battier conspicuously sticks his hand in his face. To the roughly 1500 attendees, it was a loaded image—a picture backed by a thousand words. That simple move forms the centerpiece of Michael Lewis's 2009 article casting Battier as "The No-Stats All-Star," a player who exploited analytics favored by Rockets general manager Daryl Morey. Those analytics reveal, among many other things, that Bryant's shooting percentage goes down when you put a hand in his face. The image's message was simple, progressive, ameliorative: Battier played the tendencies, and this gave him an edge.

At this year's conference, held last weekend in front of nearly twice as many attendees, the backdrop to the first panel (moderated by Lewis) presented a much more jumbled impression. There were photos of a number of sports, only some of which featured famous athletes (a shot of LeBron James driving, for instance), and lists of what appeared to be the gambling odds of NFL match-ups. But this backdrop, too, reflected its conference's overriding theme: the manic angst of having more information, which makes finding the optimal ways to use it—and, more to the point, to use it usefully—more elusive than ever.

Each year, as ESPN's Kevin Arnovitz has noted, more and more people are coming to Sloan. That's literally true, but could be said figuratively of sports analytics in general. The days are long gone when seemingly unremarkable players could be signed on the cheap by the few teams smart enough to understand the value of, say, a high on-base percentage. "You used to know how other teams operated," complained stats-friendly Dallas Mavericks owner Mark Cuban at the opening panel. "Now you have to reverse-engineer what they did to see how they do it."

Or, as Nate Silver put it on the same panel, "There's not the low-hanging fruit anymore of having some teams that are totally stupid."

Over the course of the two-day conference, I asked many people which sport—out of the four major U.S. team sports (baseball, basketball, football, hockey) and soccer—is least amenable to an advanced analytical interpretation, where little is to be gained by looking at the game from a new, maverick angle. In short: Which sport can't be Moneyball-ed?