Publication Date
4-2020
School
School of Engineering and Computational Sciences
Major
Engineering: Industrial and Systems
Keywords
sport management, ISE, forecasting, scheduling, machine learning, efficiency improvement
Recommended Citation
McGrady, Caleb, "Integration of Forecasting, Scheduling, Machine Learning, and Efficiency Improvement Methods into the Sport Management Industry" (2020). Senior Honors Theses. 936.
https://digitalcommons.liberty.edu/honors/936
Abstract
Sport management is a complicated and economically impactful industry and involves many crucial decisions: such as which players to retain or release, how many concession vendors to add, how many fans to expect, what teams to schedule, and many others are made each offseason and changed frequently. The task of making such decisions effectively is difficult, but the process can be made easier using methods of industrial and systems engineering (ISE). Integrating methods such as forecasting, scheduling, machine learning, and efficiency improvement from ISE can be revolutionary in helping sports organizations and franchises be consistently successful. Research shows areas including player evaluation, analytics, fan attendance, stadium design, accurate scheduling, play prediction, player development, prevention of cheating, and others can be improved when ISE methods are used to target inefficient or wasteful areas.
