Google will use machine learning to predict Final Four winner

  • Google will use machine learning to predict the winners of the NCAA Final Four.
  • Once it has its prediction ready, it will post an ad during halftime announcing who it thinks will win.
  • Google will use real-time data from the game as well as historical sports data to generate its predictions.

If you’ve placed any bets on the upcoming NCAA Final Four college basketball games, you might want to talk to Google before placing any more. That’s because Google will be using machine learning to determine which teams will win the Final Four games, processing both past data and data that’s happening in real time as the games progress.

We can all agree that no matter how lucky you think you are when it comes to predicting basketball games, Google’s machine learning systems are probably better.

Google teamed up with NCAA late last year to load almost a hundred years of sports data into Google Cloud Platform. Using that data combined with real-time information rolling in as the games are happening, Google will determine the winner of the current game. The Google NCAA predictions will air in an ad during halftime for each game.

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According to the blog post on the matter, Google will be taking into account “everything from who blocks more shots per minute (for the record: juniors) to whether teams with a certain type of animal mascot cause more March Madness upsets (hint: meow).” But will the Google NCAA predictions be correct? We’ll have to wait and see.

While the notion of using machine learning to predict sports games is undoubtedly novel, Google hopes that the experience will help it apply Google Cloud Platform learning more broadly. One could imagine using machine learning to predict natural disasters, or even help respond to areas hit by natural disasters, for example.

But for now, it’s all about basketball. You can read Google’s blog post on the topic here, and read in-depth on the Big Data blog to see how Google will actually formulate its predictions.

NEXT: A closer look at Arm’s machine learning hardware



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