Customized prediction of attendance to soccer matches based on symbolic regression and genetic programming
作者：
Highlights：
• Symbolic regression yields the best prediction model for soccer match attendance.
• A panel of experts define candidate independent variables and their interactions.
• We analyze 5 years of attendance to soccer matches played at a large stadium.
• Accurate attendance prediction enables better sport management and marketing plans.
• We contribute to the literature on sports analytics using machine learning methods.
摘要
•Symbolic regression yields the best prediction model for soccer match attendance.•A panel of experts define candidate independent variables and their interactions.•We analyze 5 years of attendance to soccer matches played at a large stadium.•Accurate attendance prediction enables better sport management and marketing plans.•We contribute to the literature on sports analytics using machine learning methods.
论文关键词：Symbolic regression,Genetic programming,Soccer match attendance,Prediction model,Machine learning
论文评审过程：Received 11 November 2020, Revised 5 August 2021, Accepted 12 September 2021, Available online 20 September 2021, Version of Record 22 September 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115912
