These days, with the emergence of technologies such as artificial intelligence (AI), virtual reality (VR), augmented reality (AR) and data visualization (DV), we are witnessing unprecedented developments in the field of sports. These technologies help to improve sports performance analysis, collect data automatically, and create effective training environments to improve decision-making processes. Traditional methods of sports performance analysis were usually based on manual data collection, subjective observations, and the use of limited statistical models, but with recent advances in technology, this practice has become objective and up-to-date. For example, AI has revolutionized sports analytics by simplifying data collection, processing large datasets, and automating sports analytics. Virtual reality enables training in highly realistic environments and allows athletes to practice their skills in controlled settings, and augmented reality provides digital information in the real sports environment and facilitates the tactical planning process. Data visualization techniques visualize complex data and improve understanding of performance metrics. This article examines the potential of these emerging technologies to transform sports performance analysis, providing valuable resources to coaches and athletes. The purpose of this article is to increase athletes' performance, optimize training strategies and improve decision-making processes. It also identifies existing challenges and provides solutions for integrating these technologies into current sports analysis methods. Based on the findings, it can be concluded that faster data is turned into actionable insights, training and competition events can be adjusted more quickly to align with specific goals. In this context, different environments, including virtual worlds and mixed reality, can be used to provide educational strategies Also, quality information can lead to valuable insights, and valuable insights can help achieve goals. These goals can primarily be addressed through training and performance improvement, which requires a continuous cycle of measurement and data processing.