Line-up Optimization Model of Basketball Players and the Simulation Evaluation

Wang Yichen, Haruka Yamashita

2022

Abstract

This study aims to maximize the offensive capabilities of the basketball team by optimizing the line-up of players at an arbitrary time. We construct a highly accurate prediction model when the members are changed considering the situation in the game and then propose a model to determine the optimal line-up. The Recursive Neural Network model analyzes time series data, and the Neural Network model incorporates player combinations and game conditions as conditions are combined. The model enables an analysis of the past scores and game conditions and the construction of a predictive model of scores that takes the line-up into account and determines the optimal line-up by calculating the prediction of the offense capabilities with changing the line-up. Furthermore, to demonstrate the validity of the proposed model, this study evaluates the accuracy of the prediction of the score using data accumulated from the actual baseball game. Moreover, because it is difficult to use this method in actual games, we applied the proposed model to the play data of a basketball simulation game. We conducted a simulation experiment where members were successively optimized and showed that the score was better than the experiment without the optimization.

Paper Citation

in Harvard Style

Yichen W. and Yamashita H. (2022). Line-up Optimization Model of Basketball Players and the Simulation Evaluation. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-583-8, pages 492-499. DOI: 10.5220/0011307900003269

in Bibtex Style

@conference{data22,
author={Wang Yichen and Haruka Yamashita},
title={Line-up Optimization Model of Basketball Players and the Simulation Evaluation},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2022},
pages={492-499},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011307900003269},
isbn={978-989-758-583-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Line-up Optimization Model of Basketball Players and the Simulation Evaluation
SN - 978-989-758-583-8
AU - Yichen W.
AU - Yamashita H.
PY - 2022
SP - 492
EP - 499
DO - 10.5220/0011307900003269