Publication Date

4-14-2023

Document Type

Poster

Department

Mathematics

Faculty Mentor

Robert Krueger

Abstract

The goal of this project was to predict home game attendance for all 30 Major League Baseball (MLB) teams in their 2023 season. Researching and understanding that data as well as identifying influential factors of attendance were key factors before building a predictive model. Both the given material and data sets from MinneMUDAC, the competition organizer, was used as well as some outside sources. Finally, a predictive model was coded in Python which gave attendance predictions for every MLB game scheduled in 2023. From these results, insights could be offered to Major League Baseball or each team individually, to help them plan staffing numbers, needed resources, and an increase in revenue in many different areas.

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.