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REVIEW article

Front. Sports Act. Living
Sec. Sports Science, Technology and Engineering
Volume 6 - 2024 | doi: 10.3389/fspor.2024.1456998
This article is part of the Research Topic Tennis: Bridging Tradition and Progress - An In-depth Analysis of the Sport’s Evolution and Its Prospect for the Future View all 3 articles

Transforming Tennis with Artificial Intelligence: A Bibliometric Review

Provisionally accepted
Tatiana Sampaio Tatiana Sampaio 1João P Oliveira João P Oliveira 1Daniel A Marinho Daniel A Marinho 1Henrique Pereira Neiva Henrique Pereira Neiva 1Jorge E Morais Jorge E Morais 2*
  • 1 University of Beira Interior, Covilhã, Portugal
  • 2 Instituto Politécnico de Bragança, Bragança, Portugal

The final, formatted version of the article will be published soon.

    The aim of this study was to conduct a scoping and bibliometric review of articles using artificial intelligence (AI) in tennis. The analysis covered various aspects of tennis, including performance, health, match results, physiological data, tennis expenditure, and prize amounts. Articles on AI in tennis published until 2024 were retrieved from the Web of Science database. A total of 389 records were screened, and 108 articles were retained for analysis. The analysis identified intermittent gaps in publication output during certain intervals, notably in the years 2007 – 2008 and 2012 – 2013. From 2012 onward, there was a clear upward trend in publications and citations, peaking in 2022. The theme was led by China, the United States, and Australia. These countries maintain their status as the top contributors in terms of publications. The analysis of author collaborations revealed multiple clusters, with notable contributions from researchers in China, Australia, Japan, and the United States. This bibliometric review has elucidated the evolution of AI research in tennis, highlighting the countries and authors that have significantly contributed to this field over the years. The prediction model suggests that the number of articles and citations on this topic will continue to increase over the next decade (until 2034).

    Keywords: machine learning, deep learning, artificial intelligence, Sport, Tennis

    Received: 29 Jun 2024; Accepted: 27 Nov 2024.

    Copyright: © 2024 Sampaio, Oliveira, Marinho, Neiva and Morais. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jorge E Morais, Instituto Politécnico de Bragança, Bragança, Portugal

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