ABSTRACT
This study constructs a discrete-time Markov Chain (DTMC) model for a baseball plate appearance (PA) employing Major League Baseball's pitch-by-pitch dataset. Based on the DTMC model, we propose a novel measure for a baseball PA, termed the Importance of Moment (IOM). The IOM quantifies the criticality of each ball-strike count situation, by assessing the probabilistic difference between the pitcher's and hitter's favourable outcomes (out vs reaching base). If the favours significantly vary right after a particular ball-strike count, then the count is deemed critical and is assigned a high IOM value. We empirically verify that IOM explains pitchers' behaviour of fastball speed. We then further investigate whether the behaviour of ace pitchers differs significantly from the majority. Several interesting properties are found from the analysis. Firstly, the path independence assumption generally holds, with the exception of the ball-strike count of 2B1S. Second, pitchers tend to throw the faster fastball at counts with higher IOM values. Lastly, ace pitchers are capable of pitching even faster fastball in two-strike situations in which IOM is high. The DTMC effectively models the probabilistic structure of a baseball PA, and the proposed IOM measure serves as a useful tool for explaining player behaviour.
