Data about sports have long been the subject of research and analysis by sports scientists. The article takes deep dive into the positive impact of ML integration on sports analytics. This paper focuses on deploying the ML into the field of predicting sports injury. ML not only increases the knowledge of sports injury but also assist in proactively taking steps to avoid sports injury by predicting ahead of time. To this end, technological advancements have enabled the collection of multiple points of data for use in analysis and injury prediction. The full breadth of available data has, however, only recently begun to be explored using suitable statistical methods & processing of these large data through ML algorithms.
Paper focuses on sports injuries on Synthetic players surfaces (artificial grass) compared that of Natural surfaces. It takes deep look at the prior work in this domain and opens some of the unanswered questions and shares importance of ML in analysing the large sports data collected over a case study too.
Paper utilizes the advances in automatic and interactive data analysis with the help of machine learning algorithms & establishes the intricacies of the playing surface & injury relationship. Real time data shared by NFL for injured 250 players & 150 non-injured players, over two regular season is taken for case study. Data includes complex real time player data with player movement, injury type, type of playing surface (synthetic Vs Natural), weather, player position, speed, /acceleration of player, and so on. Data sports analytic competition is analysed for the relationship between playing surface, NFL player's movements, and their damage, leading to potentially improved performance and minimizing the risk of injury. With this huge amount of data, the use of complex models for data analysis is mandatory and, for this reason, machine learning models are increasingly used in sports science. Article also briefly underlines the importance of critical sports parameters accurate data collection & direct impact on ML accuracy in prediction too.