Machine Learning can Now Create the Best Baseball Team in the World!
Baseball and ML: Machine learning could measure better baseball team performance
Baseball has fundamentally changed over the past 40 years, largely thanks to data and machine learning. Machine learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. New research at the Penn State College of Information Sciences and Technology researchers have developed an ML model that could better measure baseball players’ and teams’ short- and long-term performance.
ML model could measure better baseball team performance
Drawing on recent advances in natural language processing and computer vision, their approach would completely change and could enhance the way the state of a game and a player’s impact on the game is measured. Additionally, when combined with traditional saber-metrics, the form embedding can predict the winner of a game with over 59% accuracy. Baseball teams used data to perfect the “product,” and the game changed in fundamental ways.
Earlier, machine learning ruined baseball. Now, it has an opportunity to save it. Firstly, if data is such a big opportunity for coaches, the coach decides to keep the pitcher in, and he gives up a home run. Second, baseball should use data to make better games and schedules. With the help of machine learning and data, coaches can differentiate good players from bad players, but also provides much more nuance into the exact way in which the good players impact the game. Data can better inform not just how teams play, but which teams should play.
Heaton’s research focuses on natural language processing with his interest in the historical statistical analysis of baseball. The researchers hope that their work will serve as a strong starting point toward a new way of describing how athletes in baseball and other sports impact the course of play as they mentioned in their research in ‘Using Machine Learning to Describe How Players Impact the Game in the MLB’ paper.