Machine Learning for Position Detection in Football


In recent years, analytics became increasingly important in sports. Newly developed, wearable tracking devices allow football players to log position and motion data during a game. These data can be exploited for enhancing the performance of individual players and entire teams. We present different machine learning approaches to predict spatial football player positions, which serve for advanced tactical analysis.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL