"Revolutionizing Sports: An In-depth Analysis of Artificial Intelligence in Sports"

Abstract

Background: Artificial Intelligence techniques like neural networks, decision tree classifiers, and support vector machines are utilized in sports to predict sports performance. AI in sports involves gathering data during sports events and extracting valuable insights using algorithms. The application of AI in sports is considered to be in its early stages, prompting a need for increased research investment in the field

Method: Systematic searches through the Sci space, connected Papers and Web of Science online databases were conducted for articles reporting AI techniques or methods applied to sportspersons.

Result: The predictive models built using machine learning techniques showed promising results in the application of AI in sports, particularly in predicting sporting outcomes, has shown high accuracy rates in sportspersons performance prediction. The study highlighted the potential of AI in generating well-formulated training plans, game strategies, and score feedbacks based on past sporting events and predicting within-year and between-year sports injuries in elite sportspersons.

Conclusion: The use of AI approaches in team sports has the potential to expand predictive performance techniques/methods. AI in sports can generate training plans, game strategies, and score feedback based on historical data. Challenges exist in analyzing rich datasets in elite sports due to time constraints and data quantity.