New Players In The NBA: Big Data, User-Controlled Jumbotrons
The NBA ushered in the new season this past week, and fans at the Staples Center for the Los Angeles Clippers' opening game had access to some new toys.
The Clippers were the first NBA team to roll out new features for the huge monitors that hover just above the playing floor. For instance, sometimes the video replay was enhanced to show overlays of intricate new statistics, displaying the game as if viewed from the point of view of the Terminator.
"We have this product called DataFX that combines storytelling, video, advanced stats and special effects, all together to tell sort of the hidden side of what is going on in the game that you might not see," says Rajiv Maheswaran, CEO of Second Spectrum, the company behind this new sports tech.
Another application, called Clippertron, allows fans to "take control of the Jumbotron in real time," Maheswaran tells NPR'S Aruth Rath. Fans use their smartphones to ask for whatever video clip they want — like a shot by Blake Griffin or a DeAndre Jordan dunk — to immediately go up on the big screen. The name of the person requesting it shows up on the Jumbotron, too.
Ballmer: "Do It Now"
When former Microsoft CEO Steve Ballmer bought the Clippers for a cool $2 billion back in August, one of his first stops was Second Spectrum's modest two-room offices in downtown L.A.
"We had a bunch of projects that we had been working on ... we thought would be really good for fans down the road," Maheswaran says. "We demonstrated that to him, and he said, 'This is great. Let's do it now.' "
Maheswaran says the company pulled a working version together in six weeks, but that the version out there today will continue to evolve and improve.
In a video demonstration using a massive 82-inch touchscreen, Maheswaran demonstrates one of the models that he'd originally shown to Ballmer. He pulls up a video that explains one of the most famous plays from last season's championship series: the Miami Heat's Ray Allen hitting a game-tying 3-point shot with five seconds left in regulation.
At key moments in the video, the play pauses and the players each have little bubbles above their heads — like you'd see in a comic strip — but these bubbles have ever-changing numbers in them. They're percentages that indicate how likely they are to score from wherever they happen to be on the court.
Ray Allen's teammate, Chris Bosh, jostles for position after a missed shot by LeBron James. Spatial relationships between player, ball and basket are graphed and overlaid on the video; Bosh instinctively does what the numbers say he should do.
"[Bosh] gets the rebound, pops it out to Ray Allen, and then we can tell you really what likelihood he had of making that shot — which he did," Maheswaran says. "But there was just all this underlying stuff that was going on before that shot that we can now sort of unearth with that moment."
A League-Wide Focus On Statistics
The bread and butter of what Second Spectrum does is crunch a massive amount of data and help sports teams analyze it.
Of course, the sports world has been using stats for years. But what can be done these days makes Moneyball look as simple as counting on your fingers. Compared to the old says of box scores in newspapers, Maheswaran says with player-tracking data in almost every major sport, the amount of data is sort of three orders of magnitude more.
"I know where almost every single player and often the ball is 24 times a second, which is a lot of information," he says. "What are you supposed to do with that? Coaches don't want that; front offices don't want that. They want meaning. They want insight. 'Turn these numbers into things that I care about' — and that's what we do."
Maheswaran says that starting last year, the NBA began tracking every single game, in every arena, using cameras and image processing.
"About three to four hours after the game, they give you these files that tell you ... where every player was in every single second," he says.
But interpreting all of that data is a big challenge, Maheswaran says. It's hard to teach a computer to understand the game of basketball and its complex, often subtle, movements.
"If you don't know figure skating or ballroom dancing, as a human being, you could probably pick up on things very quickly," he says. "It's just very hard for a computer to come in with the knowledge that you have as a person to be able to recognize and separate patterns. And figuring out ways to train a computer to do that is the really hard part."
Maheswaran says that what they've shown at the Staples Center is just an example of what the future might look like.
"There's a lot of ways to slice and dice and interact with data that we haven't started to explore yet," he says.
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Transcript
KEVIN HARLAN: Well, good evening, everyone - opening night here in Los Angeles for the Clippers.
ARUN RATH, HOST:
That's TNT's call Kevin Harlan ushering in a new NBA season this past week. And for fans at that game at the Staples Center, they got some new toys. The Clippers were the first NBA team to roll out new features for the huge monitors that hovered just above the playing floor. Here's one. Sometimes the video replay was enhanced to display all these intricate new statistics. Imagine what the game would look like from the Terminator's point of view.
RAJIV MAHESWARAN: So we have this product called DataFX that combines storytelling, video, advanced stats and special effects, all together to tell sort of the hidden side of what is going on in the game that you might not see.
RATH: That's Rajiv Maheswaran. I'll give you a proper introduction in a moment. There's also another app called the Clippertron.
MAHESWARAN: Which allows fans to take control of the Jumbotron in real time and ask for whatever video clip they want - a shot by Blake Griffin or a DeAndre Jordan dunk. And it would immediately go up there with your name on it.
RATH: Fans control the arena's highlight reel with their smart phones.
(SOUNDBITE OF BASKETBALL GAME)
UNIDENTIFIED ANNOUNCER: When you got a ladder you've got to climb it. And he did - DeAndre Jordan with an emphatic jump.
(MUSIC)
RATH: So now back to Rajiv Maheswaran. He's the CEO of a tech company called Second Spectrum. And they're dealing with the big data of sports.
When former Microsoft CEO Steve Ballmer bought the Clippers for a cool $2 billion back in August, one of his first stops was Second Spectrum's modest two-room offices in downtown L.A.
MAHESWARAN: And we had a bunch of projects that we had been working on that we thought would be really good for fans down the road. And we demonstrated that to him. And he said this is great. Let's do it now.
RATH: So Rajiv, how much time did you guys have to pull this together?
MAHESWARAN: Six weeks.
(LAUGHTER)
MAHESWARAN: We were able to get a, you know, working version one out there today. But we're going to keep improving and it's just going to get better and better with every game.
RATH: Maheswaran shows me one of the models he'd originally shown to Steve Ballmer. This is the biggest touchscreen I think I've ever seen.
MAHESWARAN: Yes. It's an 82-inch. We use it a lot.
RATH: Oh, my kids would love this.
(ELECTRONIC BEEPING)
RATH: He pulls up a video that explains one of the most famous plays from last season's championship series - the Miami Heat's Ray Allen hitting a game-tying 3-point shot with five seconds left in regulation.
At key moments in the video, the play pauses and the players each have little bubbles above their heads like you'd see in a comic strip. But these bubbles have ever-changing numbers in them - percentages that indicate how likely they are to score from wherever they happen to be on the court.
Ray Allen's teammate, Chris Bosh, jostles for position after a missed shot by LeBron James. Spatial relationships between player, ball and basket are graphed and overlaid on the video. Bosh instinctively does what the numbers say he should do.
MAHESWARAN: We know that Chris Bosh is not in position to get the rebound but he moves himself into a better position. And we can talk about how that - quantitatively he gets the rebound, pops it out to Ray Allen. And then we can tell you really what likelihood he had of making that shot, which he did.
(SOUNDBITE OF BASKETBALL GAME)
UNIDENTIFIED ANNOUNCER: History (unintelligible) tied game with five seconds remaining.
(CHEERING)
MAHESWARAN: But there was just all this underlying stuff that was going on before that shot that we can now sort of unearth with that moment.
RATH: The bread and butter of what Second Spectrum does is crunch a massive amount of data and help sports teams analyze it.
Of course, the sports world has been using stats for years. But what can be done these days makes "Moneyball" look as simple as counting on your fingers
MAHESWARAN: In the newspapers, there were these things called box scores that have a certain amount of information - you know, who took a shot, who took a rebound, who got a hit, who struck out.
Now with player tracking data in almost every major sport, the amount of data is sort of three orders of magnitude more. I know where every single player and often the ball is 24 times a second, which is a lot of information. What are you supposed to do with that? You know, coaches don't want that. Front offices don't want that. They want meaning. They want insight. Turn these numbers into things that I care about - and that's what we do.
RATH: So how deep is the data? You have how many games all coded for the data? It seems...
MAHESWARAN: So the National Basketball...
RATH: My head's spinning.
MAHESWARAN: Yeah, so the NBA is also very forward thinking. They have got tracking in every single stadium in the NBA starting last year. So starting last year, every single game in the NBA has been tracked.
RATH: So does that mean that they have motion sensors set up into addition to the video cameras? Or...
MAHESWARAN: So there's a company that installs six cameras in the rooms of all the stadiums and does some image processing. And about three to four hours after the game, they give you these files that tell you here's where every player was in every single second.
RATH: What's hard about teaching a computer to understand basketball?
MAHESWARAN: So this is really the big challenge in understanding movement is that subtle variations can either mean nothing or a lot, right? Like if you don't know figure skating or ballroom dancing, as a human being, you know, you could probably pick up on things very quickly.
It's just very hard for a computer to come in with the knowledge that you have as a person to be able to recognize and separate patterns. And figuring out ways to train the computer to do that is the really hard part. There's a lot of ways to slice and dice and interact with data that we haven't started to explore yet. And this is just an example of what the future might look like.
RATH: That's Rajiv Maheswaran. He's the CEO of Second Spectrum. They're bringing new technology to the NBA and beyond. Transcript provided by NPR, Copyright NPR.
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