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In this week’s Radar Podcast episode, O’Reilly’s Mac Slocum chats with Rajiv Maheswaran, CEO of Second Spectrum. Maheswaran talks about machine learning applications in sports, the importance of context in measuring stats, and the future of real-time, in-game analytics.
Here are some highlights from their chat:
There’s a lot of parts of the game of basketball — pick and rolls, dribble hand-offs — that coaches really care about, about analyzing how it works on offense, how to guard them. Before big data and machine learning, people basically watched the games and marked them. It turns out that people are pretty bad at marking them accurately, and they also miss a ton of stuff. Right now, machine learning tells coaches, ‘This is how many pick and rolls these two players have had over the course of the season, how often they do all the different variations, what they’re good at, what they’re bad at.’ Coaches can really find tendencies that can help them play offense, play defense, far more efficiently, based off of machine learning.
What we’re doing is having the machine match human intuition. If I’m watching a game, I know that the shot is harder if I’m farther away, if I have multiple defenders, if they’re close, if they’re closing in on me, if I’m dribbling, the type of shot I’m taking. As a human, I watch this and I have an intuition about it. Now, by giving all that data to the machine, it can make a predictor that actually matches our intuition, and goes beyond it because it can put a number onto what our intuition tells us.
There’s a big emergence of movement data. What we found was that there was no science of moving dots, and if there was, it would transform everything — cities, homes, how we interact with each other, how we operate our businesses. We just found that sports happened to have really great data, and that was a great place to build this science. I think that what comes out of sports — the methodologies, the techniques — are going to affect all aspects of our lives. Because we’re moving everywhere, and we’re tracking that movement now for the first time at scale. We’ll be able to understand lots of aspects of our lives that we were never able to understand before. It’s going to be transformational.
Also in this podcast episode…
In the second segment, Slocum chats with Dstillery’s chief scientist Claudia Perlich about how and why data is undermining established metrics in advertising and how data will shape metrics in the future. Perlich also talks about why advertisers might have brought the ad blocker explosion upon themselves.
Cropped image on article and category pages by Blender Foundation / Netherlands Media Art Institute on Wikimedia Commons.