American International Journal of Computer Science and Information Technology (AIJCSIT)

"ANALYZING ATTENDANCE PREDICTORS IN MAJOR LEAGUE SOCCER: A COMPARATIVE APPROACH"

Authors

  • Dr. Jennifer Anne Mitchell Butler University, Lacy School of Business, 4600 Sunset Avenue, Indianapolis, IN 46208, United States of America
  • Dr. Michael James Anderson Butler University, Lacy School of Business, 4600 Sunset Avenue, Indianapolis, IN 46208, United States of America

Abstract

Attendance at sporting events has been a subject of extensive investigation, as reflected in the abundant references within the Literature Review section. However, the domain of Major League Soccer (MLS) match attendance remains relatively underexplored. Previous attempts to predict attendance have predominantly relied on multivariate linear regression models. This study shifts its focus to MLS match attendance, evaluating the effectiveness of three machine learning regression techniques alongside a panel-adjusted linear regression approach. The primary objective of this article is twofold: firstly, to showcase best practices in developing machine learning models, and secondly, to assess the suitability of these methods for generating accurate attendance forecasts

Keywords:

Major League Soccer (MLS),, Attendance Prediction, Machine Learning Regression, Panel Adjusted Linear Regression, Sports Event Attendance

Published

2023-11-01

How to Cite

Mitchell, J. A., & Anderson, M. J. (2023). "ANALYZING ATTENDANCE PREDICTORS IN MAJOR LEAGUE SOCCER: A COMPARATIVE APPROACH". American International Journal of Computer Science and Information Technology (AIJCSIT), 7(3), 13–21. Retrieved from https://zapjournals.com/Journals/index.php/aijcsit/article/view/1454

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