SPBA - Sport Busi Analytics

SPBA 601 The Business of Sports

Credits 3. 3 Lecture Hours. The Business of Sports provides a comprehensive overview of the sports industry, focusing on the unique business functions that drive its economic and operational dynamics. Students will explore the structure, management, and financial aspects of professional sports, collegiate athletics, and global events like the Olympics. Topics include revenue generation, franchise valuation, media rights, sponsorship, labor issues, and emerging trends such as esports. Through case studies and guest speakers, students will develop a foundational understanding of sports business operations. Prerequisites: Graduate classification or approval of instructor.

SPBA 602 Application of Sports Analytics

Credits 3. 3 Lecture Hours. Focuses on the practical application of data analytics in the sport business industry, emphasizing data-driven decision-making across general business operations, including marketing, finance, operations, strategy, and performance management. The course is designed to provide students with an introduction to sport data analytics utilizing linear regression-based modeling approaches to analyze real-world sport datasets, applying a variety of statistical techniques to predict and optimize performance, financial outcomes, and operational efficiency. The course prioritizes hands-on data applications to produce actionable insights for sport organizations, and students will learn the iterative process of model building through trial and error and by working with other students on hands-on problems and an additional team-based project. At the conclusion of this course, students will be able to collect and analyze sport-related data using data analytics, whether the dependent variable is continuous (i.e., attendance or revenue), binary (i.e., a win or a loss) in nature, or whether group membership is being predicted. Several processes that students will gain experience in include the decision of which type of model is appropriate given the data to be analyzed or research question to be answered, the selection of appropriate independent variables based on knowledge of the sport business industry, the proper interpretation of coefficients and measures of model fit, and the ability to communicate advanced statistical information to a lay audience. Prerequisites: Graduate classification or approval of instructor.

SPBA 610 Athletic Performance Analytics

Credits 3. 3 Lecture Hours. A rigorous and data-driven course, equipping students with advanced analytical skills to optimize athlete performance, prevent injuries, and inform team strategies. Students will analyze athlete performance metrics (e.g., biomechanical, physiological, statistical data) using Python, R, and Tableau, applying sophisticated statistical modeling, machine learning, and visualization techniques. Emphasis on practical applications, with projects involving datasets from professional and collegiate sports (e.g., NFL, NBA, NCAA, EPL). Prerequisites: Graduate classification or approval of instructor.

SPBA 615 Artificial Intelligence and Fan Engagement

Credits 3. 3 Lecture Hours. This course provides students with the analytical, technical and strategic tools to understand and shape the future of fan engagement in the sports industry. Through applications of artificial intelligence (AI), including machine learning, natural language processing (NLP) and predictive modeling, students will learn how to analyze fan behavior and design data-driven engagement strategies across digital and physical platforms. Emphasis is placed on both the technical implementation of AI tools and their ethical, cultural and strategic implications in sport business decision-making. Prerequisites: Graduate classification or approval of instructor.

SPBA 683 Sport Business Consulting

Credits 3. 3 Lecture Hours. Intensive, project-based course where student teams serve as consultants for professional sports teams, college athletic programs or sports-related businesses (e.g., sports tech startups, agencies). Using Python, R, and Tableau, students will deliver data-driven solutions to client challenges, such as revenue optimization, fan engagement, operational efficiency or sponsorship valuation. Course is entirely project-based, with all work focused on scoping, analyzing and presenting actionable recommendations to real clients. Prerequisites: Graduate classification or approval of instructor.

SPBA 684 Professional Internship

Credits 1 to 6. 1 to 6 Other Hours. A directed internship in an organization to provide students with on-the-job training with professionals in organizational settings appropriate to the student's professional objectives. Prerequisites: Graduate classification or approval of instructor.