The Artificial Intelligence (AI) Impact of Momentum Factors on the Success of Professional Athlete

The rapid development of artificial intelligence (AI) technology is profoundly transforming the training, competition strategies, and overall athletic performance of professional athletes. With the widespread application of AI technology, the path to success for professional athletes is undergoing unprecedented changes. AI provides athletes with more precise and personalized training programs through data analysis and prediction. Utilizing advanced sensors and wearable devices, AI can monitor athletes' physiological indicators, movement patterns, and athletic performance in real-time, thereby tailoring training plans for them. This personalized training approach not only improves training efficiency but also helps avoid overtraining and injury risks, laying a solid foundation for athletes' long-term success. In terms of competition strategies, AI analyzes historical data and opponent intelligence to provide scientific decision support for coaching teams. This aids athletes in better coping with various situations in competitions, enhancing their athletic performance. Additionally, AI can simulate competition scenarios, helping athletes engage in targeted training to improve their actual combat abilities. Furthermore, AI plays a significant role in athletes' physical recovery and psychological adjustment. By monitoring athletes' sleep quality, muscle fatigue levels, and other factors through intelligent devices, AI can provide scientific recovery suggestions to accelerate their physical and mental recovery. In summary, artificial intelligence has a profound impact on the success of professional athletes. It not only enhances training efficiency and the scientific nature of competition strategies but also provides strong support for athletes' physical recovery and psychological adjustment. In the future, with the continuous advancement of AI technology, we have reason to believe that professional athletes' athletic performance will reach unprecedented heights. We take Tennis as an example, established a GBP-radar judgment AI model, which combined with radar chart and GBP score model which is accumulated with base score, hold score, break score and score in a raw. The higher the GBP score, the better the performance. And the GBP score results of both players are calculated on a per set basis. Bringing the data of the 2023-wimbledon-1701 match, we found out that Carlos Alcaraz had a higher GBP score in the second set, the third set and the fifth set, and performed better, which is closely matched with the actual win/loss results, as well as plotted a radar chart to analyze the degree of good performance of the players who performed well.