Wednesday, December 17, 2014

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Big Data Turns Tennis into Music

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Albany/HV: Big Data Turns Tennis into Music
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Might seem like something a high school math teacher tells his or her students in order to get them more enthusiastic about numbers but really, for the past few years now IBM has been treating what happens at the US Open tennis tournament as big data.

So just like, say, a police department would crunch numbers and crime statistics to figure out where to put more officers, IBM is taking the strengths and weaknesses of pro tennis players, converting them to numbers, and helping you, through the US Open app and website, accurately predict who will win any give match.

“We have a core feature on all digital platforms called Slam Tracker, and within that application there’s a feature called Keys to the Match, and we’ve analyzed the last eight years of Grand Slam tennis data to identify patterns in the data for two players and for a specific match-up. So it’ll identify things like when Federer wins more than 43 percent of his first serves, he tends to win the match. And then we track progress against those keys during the match so fans can see how a player is tracking against those keys," John Kent said.

Again, aside from a being more robust and more visual this time around, it’s something IBM has been offering for the past few years.

So what could IBM possibly do with data this time around that's new and different? Well, how about taking data from matches in order to turn tennis into music.

“Algorithms are built to take tennis data from a specific match and look at an ace and perhaps generate a particular sound based on that, double fault different sound, and then it’s how it’s composed together. The idea is, a match is tighter it’ll have a little bit more of a dramatic kind of feel to it, so there’s an attempt within the algorithms to get a sense of the momentum of the match," Kent said.

Sadly though, to hear that match momentum, you will have to physically be at the US Open.

It is playing, exclusively at IBM’s Big Data wall inside the American Express Fan Experience. ClientIP:, UserAgent: CCBot/2.0 ( Profile: TWCSAMLSP