Low Latency Telemetry Pipeline

Tempus Ex Mathematics, 2021–22

Liaison(s): Connor Hanlon, Steve Xing
Advisor(s): Jasper Weinburd
Students(s): Sofia Devin, Ryan Edmonds, Robert Gallardo, Callie Morken (PM), Bennett Mountain

Tempus Ex Machina aims to leverage real-time tracking data for predictions and inferences, but currently has no generalized low-latency framework to clean, process, and analyze the incoming telemetry data. The goal of our Clinic project is to develop a robust, flexible, and sport-agnostic pipeline that can standardize and process various sources of telemetry data to generate real-time inferences.