Application of Data Analysis Methods in Sports Research
Abstract
At present, digital technologies are widely used both in the development of mass sports and high-performance sports. Achievements in many sports disciplines are unthinkable without the use of various technical control schemes and computer processing. This article discusses the application of data mining methods in sports. The main focus is on finding patterns that reflect the relationship between physiological, genetic and sports indicators. The specificity of the tasks being solved is that each person is considered as a complex system, the state of which depends on many different factors. Manifestations of some factors are traced by the results of tests and competitions. Other factors have a hidden, latent character, individual for each person, and are at the genetic level. As one of the means of solving the tasks, it is possible to use methods of data mining (DM). To use these methods, initial information is required, presented in the form of a table of experimental data, consisting of objects of study - athletes (table rows) and features (properties) describing these objects. This article examines the issues of creating, storing and processing data of such a table. The structure of the database has been developed for inclusion in the information model. Work is currently underway to enter the athletes' initial data into the database for further processing using DM methods.