Transforming Approaches to the Analysis of Sports Results through Artificial Intelligence and Machine Learning in Sports Research

Abstract

The article discusses the transformation of approaches to the analysis of sports results in the context of the use of artificial intelligence in sports analytics. It has been proved that the introduction of artificial intelligence and machine learning technologies improves the accuracy of sports performance assessment, optimises training loads, and reduces the risk of injury to athletes. The relevance of the study is due to the need to improve methods of analysing sports performance by integrating modern technologies into the training process. The purpose of the study is to analyse the transformation of approaches to analysing sports performance through the use of artificial intelligence and machine learning algorithms. The methods of comparative analysis, systematisation and generalisation were used to determine the role of artificial intelligence and machine learning technologies in modern sports science. Traditional and modern approaches to the analysis of sports results are analysed, the peculiarities of adapting artificial intelligence models to different sports are identified, and the limitations of their application are determined.

It has been found that the main challenges of using artificial intelligence technologies are dependence on the quality and completeness of input data, the complexity of explaining algorithm solutions, and the risks of over-automation of strategic decision-making in sports. It is proved that the use of artificial intelligence technologies can create an imbalance in access to technology among different teams and athletes, which affects competitiveness. It is established that the lack of interpretability of deep neural network solutions limits their practical application in the training process.

It is recommended that the methods of analysing sports data be improved by developing explainable artificial intelligence models that allow coaches and analysts to control the logic of decisions made. It is proposed that artificial intelligence technologies be integrated with sensor technologies to improve the accuracy of monitoring the physical condition of athletes and personalise training programmes.

Prospects for further research include the development of adaptive artificial intelligence models that take into account both physiological and psychological parameters of athletes, as well as the study of the impact of automated analytics on strategic management in professional sports.