ACADEMIA Letters
Tennis Player Clustering with anthropometric and
technical player data from the top 100 ranked Association
of Tennis Professional (ATP) and Women’s Tennis
Association (WTA) players
Shane Liyanage
The aim of research is to use anthropometric and technical player data from the
top 100 ranked Association of Tennis Professional (ATP) and Women’s Tennis
Association (WTA) players to derive player type groupings using the unsuper-
vised learning technique of clustering.
Methods
Data Collection
The following broad types of data will be collected for the clustering
• Player Anthropometric
• Technical player grips
Anthropometric Data
Data related to anthropometric characteristics of tennis players was scraped from player tour
websites including the WTA, ATP, and ITF websites.
Academia Letters, December 2021
Corresponding Author: Shane Liyanage
Citation: Liyanage, S. (2021). Tennis Player Clustering with anthropometric and technical player data from the
top 100 ranked Association of Tennis Professional (ATP) and Women’s Tennis Association (WTA) players.
Academia Letters, Article 4228. https://doi.org/10.20935/AL4228.
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©2021 by the author — Open Access — Distributed under CC BY 4.0