Machine learning modeling of hit-into-play probability and quantification of pitch sequence effects

Excerpt

arXiv:2606.17345v2 Announce Type: replace-cross Abstract: Although pitch sequencing is a central topic in baseball analytics, previous studies have primarily focused on improving predictive performance for the final pitch or its outcome, leaving the role of preceding pitches insufficiently examined. To address this issue, this study conducted a machine learning-based analysis to quantify the importance of preceding pitches and deepen the tactical understanding of baseball. A Transformer-based mo