“We develop machines that understand sports, and as machines understand content, that changes (the sports) industry,” said Second Spectrum CEO & co-Founder Rajiv Maheswaran during an interview on Day 2 of the ‘17 NeuLion Sports Media & Technology conference. Maheswaran said his L.A.-based company operates in the intersection of sports, data and technology. He said the company is helping build a new infrastructure to help give the industry and fans what they want, when they want it, and how they want it. Second Spectrum tipped off those efforts in the NBA. Maheswaran, a noted basketball fan, on several occasions said the NBA is "one of the more forward-thinking leagues in the world.” He added, “There was a lot of data in basketball that people didn’t know what to do with.” He said the firm started with coaches at four NBA teams and now its technology is “basically league-wide.”
HOOPIN’ IT UP: “Nobody is a tougher customer than an NBA coach,” said Maheswaran. “They’re putting their life on the line. If a coach says, ‘I trust you to change what I’m doing in a game,’ it has to be super accurate.” He added, “The leagues all want to go to the future, but aren’t sure how to navigate it, and different leagues move at different paces. The NBA moves really fast, and it’s great to be with them. We want to partner with people who want to move quickly and have a big audience.” Second Spectrum is also expanding into soccer with partners in MLS and “mostly European soccer leagues.”
NOW YOU’RE MINE: Maheswaran said Second Spectrum is also targeting fans and media more, after signing a deal with ESPN to provide content and analysis for SportsCenter and ESPN.com. “The stuff didn’t get to fans as much as we'd like for it to,” he said. “The real power is to change core content, how it’s sliced and presented to every fan. Machine learning lets everyone get a different experience. There’s no way to give the same broadcast to everyone and make them all happy. The internet allows that. Streaming is turning the internet into cable. It’s about everybody getting what they want, how they want it and when they want it. You can’t have a billion producers for this, you need machine learning to do it.”
