This study demonstrates the feasibility of obtaining team data immediately following events which can provide valuable information to better study and characterize the workloads of different team members. We sought to assess the feasibility of measuring workload of code team members in real code events, and to analyze the patterns of workload. Many interventions have been proposed to optimize code team performance, yet their addition may result in increasing team member workload during a code event. [Extracted from the article]