Batting for the Long Run: How MLB Service Time Influences the Predictive Accuracy of Expected Statistics

In 2015, a new way to track baseball games was introduced to MLB, marking the beginning of the Statcast Revolution. This new way to track the game brought about a number of new statistics, including the use of expected statistics. Expected statistics provide an estimate of what a player’s statistics should be on average with their same actions. This will be explored more in the upcoming paper. While expected statistics are not intended to predict the future performance of players, I theorized that there may be some relation, particularly on younger players. There is not any research on this topic yet, and if there does exist a correlation between expected statistics and future performance, it would allow teams to have a new way to predict data on their players. Research to find a correlation between the two was carried out by taking predictive accuracies of expected batting average and slugging of 12 MLB players throughout their rookie to 8th year seasons and combining them together to find an interval in which I could be confident the correlation lay. Overall, I found that I could not be certain that there was a correlation between the predictive accuracy of expected statistics and the length of time a player has played in MLB. While this conclusion does not offer any insights of how to better predict a player’s future performance, the methodology and findings still present opportunities to gain a better understanding of the predictive measures of expected statistics.