A wristband that turns a tennis player's movements into performance data.
Built by Priyansh Agarwal
TennEdge explores how motion data can give tennis players a clearer view of their technique and performance.
A tennis player knows whether a shot landed in or out. What is harder to know is why: how fast the racket moved, how much power was generated, what changed in the swing and where technique began to break down.
Priyansh Agarwal, a Class 12 student at DPS Gurgaon, wanted more objective feedback. His experience with tennis and an internship in sports technology led him to explore whether motion sensing could make performance easier to understand.
TennEdge is an AI-powered motion-sensing system designed to capture aspects of a player's movement and convert them into measurable performance insights. The project is intended to analyse indicators such as swing speed, shot accuracy, power and spin.
Rather than changing the racket and potentially disturbing its weight and balance, Priyansh explored a wearable form. Sensor data can then be transmitted to a companion application for analysis.
Professional players can access sophisticated coaching and performance systems. Young and amateur players often rely primarily on observation and feel. Priyansh's larger ambition is to make meaningful feedback accessible beyond elite training environments.
TennEdge remains a student-built prototype that must be tested and refined. But it captures a valuable shift in Indian sport: athletes are not only using technology created elsewhere—they are beginning to build the tools they wish they had.