A team of students led by researchers in the Computer Science Department and the coaching staff of the Duke Women’s Soccer (DWS) team developed analytical tools to provide quantitative evaluations of individual players and whole teams. By applying machine learning techniques and other data science methods to deep event-level and individual player tracking data, students generated key insights to aid the DWS coaching staff in performance optimization, match preparation, and tactical analysis. This was an opportunity for students who are interested in gaining experience in sports analytics and wanted their work to have a direct impact on a top Duke athletics team.
Project Lead: Alex Hartemink
Project Manager: Leonardo Biral
View the team’s project poster here: Team 7
View the team’s project video here:
Watch an in- depth interview with the team and leads as they discuss their project:
