Senior Design 2020 – Computer Science and Engineering Team 14
This video contains proprietary information and cannot be shared publicly at this time.
Computer Science and Engineering Team 14
Renzo Corihuaman Rome McColl Matthew Rumbel Renukanandan Tumu Lawrence Wu
Web-Based Athletic Data Visualization
As college athletics has become increasingly competitive, the use of specialized coaching, monitoring staff, and equipment has become necessary to ensure competitiveness. The UCONN Athletics strives to push the performance of its coaching staff and athletes, while ensuring safety. UConn Athletics trainers utilize Polar wearables to monitor the activity of athletes during practice sessions.
UCONN Athletics seeks to visualize highly nuanced performance data for their student athletes. Trainers initially leveraged Microsoft Power BI to create visualizations of performance data obtained manually from Polar Team Pro’s online portal (exported to CSV). However, the export did not expose the full raw data. The current export only includes data taken at 1 Hz frequency. The use of Polar Team Pro’s API will allow access to data taken at 10 Hz frequency, which is needed to accurately calculate nuances in athlete movement and biometrics.