Motivation

Algorithmic performance tracking tools—such as Catapult, GPS-based wearables, and real-time analytics platforms—are increasingly used in professional and semi-professional sports. These systems shape how coaches monitor athletes, make tactical decisions, and design training programs, creating emerging forms of algorithmic co-supervision. Yet we lack structured insights into how such tools are implemented across clubs and sports. This thesis aims to identify real users (clubs, coaches, athletes), analyze their practices, and classify them using the ACS taxonomy to derive sport-specific insights.

Description

This thesis explores how sports teams and coaches use algorithmic tools (e.g., Catapult, GPS wearables, analytics dashboards) to evaluate and guide athlete performance. Through case identification and interviews.

Tasks

• Identify sports teams, coaches, or athletes using performance-tracking tech.
• Collect data through desk research and, where possible, interviews
• Classify each case along the ACS taxonomy to capture supervisory configurations
• Integrate findings into the broader literature on algorithmic control and sports analytics

Requirements

• Interest in Sport and technology
• Motivation is the most important one

What we offer

• Supervision and methodological guidance
• Feedback on structure and writing process
• Opportunity to contribute to ongoing research projects

Application

If you are interested in writing your thesis, please send me an email (oezdemir@ise.tu-…) including your transcript of records, CV and feel free to tell if you have an active network in this area.