The scene is familiar to anyone who has ever watch a baseball game: A batter is inching his way from first base, slowly, slowly. The pitcher sees him and fakes a throw, sending the batter scuttling back to his safe position. Moments later, the batter begins to inch his way out again, further, further. Then he breaks into a run, steals and slides safely into second base.
Now, though, fans tuning into a stream of a game can hear MLB broadcast partners analyze the probability that a runner will be able to successfully steal. MLB and its partner Amazon Web Services have developed a deep neural network that can predict stolen base success using metrics such as a runner’s speed and burst, a catcher’s pop time, a pitcher’s velocity and handedness, and lead-off distance.