Using Artificial Intelligence Technologies to Analyze Technical and Tactical Actions in Boxing

Анотація

The article discusses the potential of technologies for analyzing technical and tactical actions in boxing, with an emphasis on the theoretical aspects of their implementation and use. The purpose of the study is to explore the capabilities of modern machine learning algorithms, computer vision, and big data analytics to improve the accuracy of boxing technique assessments and reduce the subjectivity of traditional analysis methods. Research methods include theoretical approaches such as analysis, synthesis, abstraction, induction, and deduction, as well as empirical methods involving the use of real data on the technical and tactical actions of boxers. The results of the study indicate the significant potential of artificial intelligence technologies in the development of individual training programs that take into account the specific needs of boxers. The article analyzes modern AI-based training applications that offer a variety of features to improve athletes' physical performance and technical skills. The use of video analysis, motion tracking, and biometric monitoring systems allows coaches to obtain detailed information about the execution of technical elements. Key data for collection, such as the speed and accuracy of punches, as well as physiological indicators, are identified, enabling the creation of structured analytical reports for coaches, which may include graphical representations of data and recommendations for optimizing the training process. The study's findings emphasize that the introduction of artificial intelligence technologies can significantly improve the effectiveness of boxer training, but there are challenges related to the high cost of equipment, the need to train coaches and athletes, and ethical issues regarding data collection and use. Further research should focus on developing strategies to overcome these challenges and optimize the use of artificial intelligence in boxing.