hsuanchengsun / performance-prediction-lstm

Performance prediction in major league baseball by long short-term memory networks

The article is published by International Journal of Data Science and Analytics (2022)

Article link: https://doi.org/10.1007/s41060-022-00313-4

Abstract

Player performance prediction is a serious problem in every sport since it brings valuable future information for managers to make important decisions. In baseball industries, there already existed variable prediction systems and many types of researches that attempt to provide accurate predictions and help domain users. However, it is a lack of studies about the predicting method or systems based on deep learning. Deep learning models had proven to be the greatest solutions in different fields nowadays, so we believe they could be tried and applied to the prediction problem in baseball. Hence, the predicting abilities of deep learning models are set to be our research problem in this paper. As a beginning, we select numbers of home runs as the target because it is one of the most critical indexes to understand the power and the talent of baseball hitters. Moreover, we use the sequential model Long Short-Term Memory as our main method to solve the home run prediction problem in Major League Baseball. We compare models’ ability with several machine learning models and a widely used baseball projection system, sZymborski Projection System. Our results show that Long Short-Term Memory has better performance than others and has the ability to make more exact predictions. We conclude that Long Short-Term Memory is a feasible way for performance prediction problems in baseball and could bring valuable information to fit users’ needs.

Keywords— Deep learning, Long short-term memory, Player performance prediction, Baseball projection

Our Contribution

• We started a new research direction on using deep learning to predict baseball players’ future performance.
• We have a systematic analysis of predictions to build new insight into the problem.
• Our result demonstrated that deep learning could be a better solution to solve the performance prediction problem.
• With our study and results, we believe the information would be helpful for the domain users and could create actionable knowledge as the support for them.

Cite the article: Sun, HC., Lin, TY. & Tsai, YL. Performance prediction in major league baseball by long short-term memory networks. International Journal of Data Science and Analytics (2022). https://doi.org/10.1007/s41060-022-00313-4