Available at: https://digitalcommons.calpoly.edu/theses/2809
Date of Award
6-2024
Degree Name
MS in Statistics
Department/Program
Statistics
College
College of Science and Mathematics
Advisor
Beth Chance
Advisor Department
Statistics
Advisor College
College of Science and Mathematics
Abstract
Sports analytics arrived in the mainstream media through the novel and film Moneyball. However, its origins date back to operations researchers following World War II. Often considered a subdiscipline of statistics, sports analytics draws from statistics but also includes concepts from data science, communication, and marketing. As a passionate fan of sports, I have pursued statistics in my undergraduate and graduate education with the dream of working in sports for my career. However, educational opportunities in sports analytics are limited nationwide, and more specifically, there is no educational opportunity at my university, California Polytechnic State University in San Luis Obispo. This thesis investigates the sports analytics discipline, aiming to explain what sports analytics is, how it differs from statistics, how sports analytics is used in various organizations, what sports analysts do, and how sports analytics should be taught at the undergraduate level here at Cal Poly. To accomplish this, I have taken three online sports analytics courses, conducted interviews with professors of sports analytics and sports analysts of professional and college teams, done extensive online research and literature review, and gauged interest campus-wide in a potential sports analytics course. Ultimately, this thesis led me to conclude that sports analytics differs from statistics, and there should be a course in sports analytics at Cal Poly offered by the Statistics Department. Skills including SQL and Tableau, communication to various sports constituents, data collection and data management, machine learning methods such as classification trees and clustering, advanced statistical methods such as General Additive Models and spatial analysis, and visualization techniques are all prominent in sports analytics. Statistics students at Cal Poly do not gain a firm foundation in all of these ideas and could benefit from a course which teaches these skills. The significance of this work is that I have created a course proposal for a sports analytics course. If this course were to be adopted by the Statistics Department, students would learn essential skills to prepare them for a career in sports or any data related career. This work can advance sports analytics education and lead to the creation of other courses in the discipline down the line.