Analysis of Factors Influencing Board Game Ownership Based on A Gradient Boosting Model
Research Article
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Analysis of Factors Influencing Board Game Ownership Based on A Gradient Boosting Model

Thomas Xiao 1*
1 Irvine Valley College, Arnold O. Beckman High School, Irvine, CA, US 92620
*Corresponding author: sxiao7@ivc.edu
Published on 6 August 2025
Volume Cover
TNS Vol.132
ISSN (Print): 2753-8826
ISSN (Online): 2753-8818
ISBN (Print): 978-1-80590-305-5
ISBN (Online): 978-1-80590-306-2
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Abstract

This study investigates the factors influencing board game ownership using a comprehensive dataset from BoardGameGeek. By applying statistical techniques such as correlation analysis, Lasso regression, Random Forest, and a Gradient Boosting Model (GBM), the paper explores how variables such as user ratings, complexity, playtime, age rating, and year of publication affect ownership. The analysis reveals that user engagement metrics—particularly the number of users who rated a game—are the strongest predictors of ownership. However, when visibility metrics are excluded, intrinsic attributes like game complexity, playtime, and accessibility (minimum age) emerge as significant drivers. The Gradient Boosting Model, trained with log-scaled ownership values, achieves a high score of 0.975 on the validation set, confirming its strong predictive performance. These findings provide actionable insights for developers, highlighting the importance of both marketing efforts and thoughtful design choices. The study contributes to the understanding of consumer behavior in the board game industry and offers a data-driven framework for optimizing game appeal and commercial success.

Keywords:

Board games, ownership analysis, complexity, predictive modeling, gradient boosting model.

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Xiao,T. (2025). Analysis of Factors Influencing Board Game Ownership Based on A Gradient Boosting Model. Theoretical and Natural Science,132,23-32.

References

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Cite this article

Xiao,T. (2025). Analysis of Factors Influencing Board Game Ownership Based on A Gradient Boosting Model. Theoretical and Natural Science,132,23-32.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-APMM 2025 Symposium: Simulation and Theory of Differential-Integral Equation in Applied Physics

ISBN: 978-1-80590-305-5(Print) / 978-1-80590-306-2(Online)
Editor: Marwan Omar, Shuxia Zhao
Conference date: 27 September 2025
Series: Theoretical and Natural Science
Volume number: Vol.132
ISSN: 2753-8818(Print) / 2753-8826(Online)