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How Google used predictive alytics during NCAA's Fil Four

How Google used predictive alytics during NCAAs Fil Four

Sentinel Digital DeskBy : Sentinel Digital Desk

  |  2 April 2018 12:00 AM GMT

San Francisco, April 1: Taking predictive alysis a step further, Google late on Saturday used the technology to predict in real-time the factors that decided the result of the matches during the Fil Four games of the NCAA basketball tourment. Using Google Cloud capabilities and by alysing NCAA data through workflow, Google was able to uncover interesting facts — everything from who blocked more shots per minute to whether teams with a certain type of animal mascot cause more March Madness upsets. The company would do the same during the fil match between Villanova and Michigan on Monday and “report back once the tourment is over”.

On Saturday, Courtney Blacker, Head of Brand Marketing of Google Cloud, in a blog post, said that Google Cloud has been working on an experiment to apply the company’s technologies like predictive alystics to look into factors that influence a team’s performance. “We came to embark on a months-long experiment to apply our own technologies to the NCAA’s treasure trove of data,” Blacker wrote. “We assembled a team of technicians, data scientists and basketball enthusiasts. Our goal wasn’t to predict winners or losers, but to build models that look at influential factors on team performance-after all, it’s not whether you win or lose but how you play the game,” she said.

Google Cloud has been helping teams in NCAA basketball tourment alyse more than 80 years’ worth of statistical game and competition data. In Fil Four games later in the day, the Wildcats had an easy time in a 95-79 victory versus Kansas while the Wolverines had to rally to defeat Loyola-Chicago 69-57. During the Fil Four games, the Google Cloud team was on site in San Antonio and closely followed the games. It used workflow to alyse observations from the first half of each game against NCAA historical data to hone in on a stat-based prediction for the second half that it thought was highly probable. Google shared the predictions in real-time TV ads during halftime using a rendering system. (IANS)

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