Collegiate student-athletes train and compete in a dense data ecology where information about their bodies and performances circulates among coaches, staff, and fans. To understand how student-athletes themselves engage with this data, we conducted interviews with 20 student-athletes, identifying four modes of engagement: 1) performance-directive, executing training and targeting improvement; 2) reflective-monitoring, assessing the body’s reaction to training and daily load; 3) coach-mediated, receiving insights through staff expertise; and 4) selective-disengagement, intentionally stepping back to protect confidence or avoid overload. These findings fill a gap left open by three related areas of research: SportsHCI, collegiate athletics, and personal data engagement. Each mode entails reasons, practices, and trade-offs. Student-athletes draw on different combinations of these modes as they respond to training demands, coaching oversight, and their own well-being. Our findings highlight how an evolving data ecology creates opportunities and pressures, requiring student-athletes to balance performance with protecting their state of mind.
ACM CHI Conference on Human Factors in Computing Systems