Starting from data mining technology, this article details its connotation and several common methods. Based on the demand of sports, the sports industry has ushered in new developments and opportunities under the background of the big data era, especially the mining of big data in the sports industry. The application of data mining technology to sports training in the field of decision-making. -creation of a support system, using a large number of experimental data to, In order to effectively improve the effect of sports information mining, a sports safety information mining platform based on sharing multimedia data ยท Summary. Data is everywhere. Examples include sports data. These data are implicit, previously unknown and potentially useful. ~ Among the leading companies in the mining industry, Newmont saw the largest increase in COVID referrals - compared to the previous one, Data Mining in Sports: A Systematic Review. IEEE Latin America, 1 232-239. DOI: 10.1109 TLA.2018.8291478. Authors: Robson Bonidia. University of So, The use of data mining in the development strategy of the sports management information system was therefore considered in connection with the real situation of school sports information. In the age of advanced technology, vast amounts of data are generated and extracted from all aspects of life, such as transportation 1,2,3, social media 4, 5, healthcare 6,7, 8, as well as games and sports. As data resources increase, people want to collect and analyze data for useful insights. Data mining is the process of extracting hidden patterns from data, and it is commonly used in business, bioinformatics, counterterrorism, and, increasingly, in professional sports. First popularized in Michael Lewis's best-selling book Moneyball: The Art of Winning An Unfair Game, it has become an intrinsic part of all professional sports. For example, NBA coaches in the United States use Advanced Scout, a data mining tool provided by IBM, to help decide on on-site replacement of team members. Bonidia et al. data mining technology to study technical calibration and related parameters in sports, and build sports technology and development. We are currently witnessing an unprecedented era of digital transformation in sport, driven by the revolutions in artificial intelligence, virtual reality, augmented reality. AR and DV data visualization. These technologies promise to redefine sports performance analysis, automate data collection, create,