A Linear Regression Model for Predicting  Whiff Percentage in Major League Baseball

This paper examines data related to the whiff percentage of five different Major League Baseball (MLB) pitches. A linear regression model is used to predict whiff percentage. Our results show that the models for each pitch, except the curveball, have statistical significance. The results of the cutter model are especially significant and give an indication of which pitchers in the MLB should throw their cutter more. The results found herein not only add a piece to the story but, also, lead to future areas of research in pitch modeling.