Predictive Modeling, Performance Analysis, and Other Emerging Applications of Statistics in Sports

Abstract

This study explores the evolution of data analysis in various areas of sports. The bulk of this research involves attempting to expand on the idea of a multiple linear regression model that is found in the baseball statistic Wins Above Replacement, also known as WAR. This project will use data from NHL teams and PGA Tour players to create models for the respective sports about what areas of either a team or player’s game is most important in determining success or areas of importance. The outcomes of these models will be compared to results from these sports to determine if they are effective in modeling the outcomes based on performance statistics. The secondary area of study is about the applications of statistics in other areas of sports that do not involve in-play performance. This includes examining how trainers use athlete data to create performance and recovery plans for their athletes, as well as how sports broadcasts and betting sites use data to increase fan engagement for profit