80 2025 TSMA In recent years, rapid advancements in technology industries such as computer vision, sensor technology, signal transmission, and data analysis have led to the growing application of AI in sports. According to the 2024 global fitness trends survey by the American College of Sports Medicine, “Wearable Technology” remains the most popular fitness trend, and “Data-Driven Training Technology” has entered the top 20 trends for the first time. This indicates the growing market for sports data analysis, with more teams seeking to quantify athletes’ performance, build databases, provide recommendations, and develop strategies. Performance analysis and injury prevention data applications are gaining attention. As technology continues to advance, the prospects for AI applications in sports will become even broader. Here are a few main directions in which AI can move in sports. AI in sports training The application of AI in sports training is becoming increasingly widespread, providing athletes and coaches with unprecedented tools and technical support. Firstly, AI’s role in data analysis is extremely important. Through wearable devices, AI can instantly collect various data from athletes, such as heart rate, speed, stride, and strength. After AI analyzes this data, it can help coaches develop more scientific training plans and provide personalized training tailored to each athlete’s characteristics. By analyzing a large amount of training data and athletes’ performance, AI can identify the most effective training methods and strategies, dynamically adjusting training plans based on athletes’ progress. For example, AI can analyze an athlete’s running posture, identify bad habits, and suggest improvements to enhance efficiency. AI can also adjust training intensity and content according to an athlete’s fatigue level and recovery status, ensuring they are always in the best condition. Secondly, AI plays a crucial role in training monitoring and feedback. AI sys-
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