Infosys grand slam: Partnering ATP to redefine data consumption

In 2009, Abdul Razack, head of big data and analytics at Infosys, was watching the men's singles French Open tennis final when something happened that he said has stuck with him ever since.

Sweden's Robin Söderling had beaten four-time defending champion Rafael Nadal in the fourth round, and went on to cement his position in the final, where he faced Roger Federer.

"Federer was down two sets -- down 0-30 -- and at that point he turned the entire match around," Razack said.

"As a fan, that's the story that has stuck in my mind -- for someone to be able to go back and relive that match with the data that was captured in the umpire's chair, it's a powerful thing to do and improves the experience of the consumer, the media, opponents, and it's all around better for the game."

As Razack's eyes were glued to the screen, Federer won his first ever French Open.

Razack said as an analyst, that defining moment when Federer turned the match around was very intriguing, and he was curious as to how exactly he changed the direction of the match and wanted to find out if it was a trend that could be monitored and isolated to pinpoint the particular moment the game was Federer's.

At the 2014 Association of Tennis Professionals (ATP) event in London, Razack had a conversation with the president of the ATP who was talking about creating an experience around a tennis match. What resulted was a statistics platform that compiles in-depth player match information ranging from the match-winning point to where a ball lands from a particular serve.

The user interface on the ATP World Tour website even allows you to pin two players head-to-head to run through various scenarios from previous match data to see who would come off victorious.

"This year's finalists were even asking questions to the user interface," Razack said. "That's the best validation you can get -- they look at it as valuable insight."

Razack said that in compiling the statistics for ATP, Infosys had over 12 million data points as well as five years of Hawk-Eye data to work with.

"It was just a matter of applying data, applying techniques, and machine learning techniques to start to figure out the probability and correlating data points to events that -- in the case of Federer -- turned the match around," he said.

"The analysis of what happened when and why, that's why we were a little bit passionate about this. It was about improving the fan experience and the story experience of a particular match and using data to amplify that."

Having the ability to perform high data processing of millions of data points, Razack said he can go back and relive that moment that stuck with him as a fan.

According to Razack, driving the notion of platforms, mostly focused around data processing, automation, and artificial intelligence (AI)-based technology, gives the services company a point of differentiation. With automation as an example, he said AI or machine learning gives Infosys the ability to do things better.

Using essentially the same technology as used with the ATP platform, Razack said that Infosys customers range from those in retail, finance, mining, insurance, and telco, to manufacturing.

"It's the same technology -- obviously the data is different and the algorithms are different -- but the foundational technology is the same," he said.

Looking down the barrel of an Internet of Things (IoT) explosion, Razack said that in the sport sector, there is only going to be more data to leverage. He said as shirts, racquets, and shoes are embedded with sensors, the available data will be greater than ever before.

"Everything with a sensor will always give out data -- so what will you do with the data?" he said. "How to make sense out of the data and how do you apply it to something meaningful that is value-driven and that can give either an improved experience or an improved business value."

Razack said that data collection needs to be value-driven, not just data for data's sake.

"Just look at any enterprise, I'm sure they're all sitting on data up to their nose -- how do you make sense out of it, that's the big question," he said.