ABSTRACT
Machine Learning (ML) is an Artificial Intelligence algorithm which is being used majorly in classification and outcome prediction areas. Due to the large financial stakes associated with wagering and betting, one of the developing sectors that demands great accuracy is sports. To comprehend and create the necessary match-winning strategies, club managers and owners are also working on categorization models. These models are based on several game-related factors, such as opponent information, player performance indicators, and match results from previous games. With a main focus on how Artificial Neural Networks (ANNs) are used to forecast the outcome of sporting events, this work also focuses on the use of ML in this area. As a result, it presents a cutting-edge framework for sports forecasting that uses ML as a learning technique. To address the low prediction accuracy of current models, a deep learning-based model for predicting sports performance is proposed. This study demonstrates that models are superior to conventional methods for predicting athletic performance, with the gap between the two becoming larger.
