Objective: The aim of the research is to make a bibliometric analysis of articles published using machine learning-sports key concepts. For this purpose, 654 studies published in the sources scanned in the Web of Science Core Collection database between 1999-2021 will be examined bibliometrically and the trend in the last 23 years will be revealed. Material and Methods: The database was searched using the keywords 'machine learning' and 'sports' and the number of studies for years, the average number of citations per year, the journals and authors that published the most on this subject, the citation burst values of the authors, the countries and cooperation status of the responsible authors, the most the cited articles, word cloud and word tree map and conceptual structures were examined under their sub-titles. Results: According to the results obtained, it can be said that the interest in the subject has increased after 2014. The journal in which the articles on this subject were published the most was 'Sensors', and it was determined that Musa RM was the author who wrote the most articles. The most cited work was written by Li and Wu in 2010. Conclusion: In the articles written, it has been determined that Australia and the United Kingdom are the countries most open to cooperation, and the most used concepts in the keyword and title section are 'performance' and 'learning'. It is believed that the results obtained will shed light on researchers who want to conduct research on this subject.