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- ISSN: 2010-3646 (Online)
- Abbreviated Title: Int. J. Social. Scienc. Humanit.
- Frequency: Bimonthly
- DOI: 10.18178/IJSSH
- Editor-in-Chief: Prof. Paul Sudnik
- Executive Editor: Ms. Yoyo Y. Zhou
- Abstracting/ Indexing: Google Scholar, Index Copernicus, Crossref, Electronic Journals Library
- E-mail: ijssh.editorial.office@gmail.com
Home> Archive> 2017> Volume 7 Number 12 ( Dec. 2017)
IJSSH 2017 Vol.7(12): 747-750 ISSN: 2010-3646
doi: 10.18178/ijssh.2017.V7.919
doi: 10.18178/ijssh.2017.V7.919
Analysis of NBA Team Strength Using Players' Race Data Based on Clustering Method
Mingzhe Xu and Junhui Gao
Abstract—In this paper, we use k-means, a basic type of clustering analysis, to analyze the data downloaded from the official site of NBA. We analyze the relevance between the number of clusters a team has and its winning percentage, the correlation coefficient is not high. However, we find that when the assuming number of clusters is ten, the relevance between the research items is the highest.
Index Terms—NBA, clustering analysis, correlation, statistics, winning percentage.
Mingzhe Xu is with Wuxi Big Bridge Academy, Jiangsu, China.
Junhui Gao is with the American and European International Study Center, Wuxi, China (Corresponding author: Junhui Gao; e-mail: jhgao68@163.com).
Index Terms—NBA, clustering analysis, correlation, statistics, winning percentage.
Mingzhe Xu is with Wuxi Big Bridge Academy, Jiangsu, China.
Junhui Gao is with the American and European International Study Center, Wuxi, China (Corresponding author: Junhui Gao; e-mail: jhgao68@163.com).
Cite: Mingzhe Xu and Junhui Gao, "Analysis of NBA Team Strength Using Players' Race Data Based on Clustering Method," International Journal of Social Science and Humanity vol. 7, no. 12, pp. 747-750, 2017.