AI in Sports: Deep Learning Models for Player Performance Analysis and Injury Prediction
Keywords:
AI in Sports, Deep Learning, Player Performance Analysis, Injury Prediction, Sports Analytics.Abstract
AI and deep learning are now omnipresent in sports by offering predictions of performance and injuries among the players. This paper aims at examining the usefulness of employing deep learning to predict athlete’s performance and identify the kind of training they require as well as to study the possibilities of preventing injuries among athletes. The collected real-time data from wearing and video, biomechanical analysis, and other datasets can be fed into CNNs, RNNs, and other programmed algorithms to analyze these copious datasets to learn the trend of performance, to understand fatigue level, and to predict and identify the possible elements that indicate an injury risk. Analytical models derived from artificial intelligence help coaches to get insights regarding the workload on certain players, their movements during the game, and their overall contribution to the game, thereby allowing coaches to develop training plans that can optimize the usage of the athlete while minimizing the risk of injuries. Moreover, it is evident that complex levels of biomechanical analysis are possible, and such analysis shows evidence of injury, and the subsequent treatment plan needs to be initiated as soon as possible. AI is used in this game in a more advanced level through a computer vision system that assists in tracking players, their position and other factors and strategies which can be so useful in enhancing the games and gaining an edge. This paper also provides convincing evidence of effectiveness of the proposed approach compared to the conventional ways of predicting injuries based on the results found out that the proposed approach improve the accuracy of injury prediction and the overall efficiency of players. With the help of deep learning IT departments in sport organizations can solve the problems of effective personnel management, longevity of athletes, as well as decrease metrology expenses on the treatment of injuries. This paper discusses how modern projects and analyses in sports can be given a boost and protect athletes from injuries through the help of AI. The advancement of AI in the sports science is set to transform the age of training strategies, athlete’s well-being, and game tactics in the future sports.
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