The collection and analysis of large databases have become a task increasingly explored by the community from different areas. As interest has grown, tools for data collection have become more accessible and less complex. On the other hand, this leads to the generation of an increasing volume of data, creating challenges for identifying interest information. Sports analytics has shown significant growth in recent years among the activities that fall into this scenario. Through data that evaluate the performance and characteristics of athletes during training or match, it is possible to perform detailed analyzes to support technical decisions for better individual and collective use. This project seeks to create models in machine learning to classify actions performed by athletes from team sports on the court. For this, several steps will be carried out, starting from data collection until the creation of these models.
News published in Agência FAPESP Newsletter about the scholarship: