Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
35th (2021)
Session ID : 1J2-GS-10d-02
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Classification of Basketball Players Based on Mapper Network
*Shunsuke WATANABEGenki ICHINOSE
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

Basketball players generally have fallen into one of five positions. Recently, however, the roles of those positions have become ambiguous and there exist players with different playing styles even in the same position. In this study, we aim to classify the playing styles of 6,600 players who have played in the past 20 seasons from 2000-01 to 2019-20 by visualizing their playing data with Mapper networks. In addition, we compare the differences of playing styles in the the past 20 seasons by quantifying the results of the visualizations which are represented by networks. As a result of the analysis, we classified NBA players into 11 playing styles. Moreover, we found that the differences in playing styles among players have increased over time.

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© 2021 The Japanese Society for Artificial Intelligence
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