See how AI on AWS gives fans new insight into stolen base probability
A foundation for deep learning
MLB has been using AWS to collect and distribute game-day stats to enhance the fan experience since 2015, including data from the pitcher, catcher, and runner on stolen base attempts.
Stealing bases with AI
MLB and the Amazon ML Solutions Lab trained a deep neural network to predict stolen base success by using numerous data including runner’s speed and burst, catcher’s pop time, pitcher’s velocity and handedness, lead-off distance, and the game situation.
Scaling with Amazon SageMaker
The model was quickly deployed using Amazon SageMaker, providing sub-second response times required for integrating predictions into in-game graphics in real time, and on ML instances that auto-scale across multiple availability zones.
Evolving the game
Major League Baseball (MLB) uses machine learning services on AWS to power Statcast AI — the tracking technology used by MLB to analyze player performance for every game on MLB.com and the MLB Network. In addition, Amazon ML Solutions Lab works with the MLB to continue to enhance viewer experiences with more personalized content for each market and geographic region.
Products powering MLB Statcast AI
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Learn more about Statcast AI
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