Democratizing Performance: Impact of The Data Revolution on Recreational Running

In recent years, recreational running has experienced significant growth, with millions of individuals participating in the sport worldwide. This growth has highlighted the need for accessible and effective training tools and methodologies tailored specifically to recreational runners. While elite athletes benefit from high-end performance labs, personalized coaching, and advanced training camps, these resources are often too costly and specialized to be scalable for the average runner. This thesis investigates how recent innovations in wearable devices and data science can democratize access to such elite-level resources. Employing a critical analysis, this study examines the evolution, accuracy, and real-world application of such technologies through case studies and a comprehensive review of existing literature. Additionally, the thesis discusses future technological directions, exploring potential advancements and their implications for the recreational running community. We highlight the urgent need for rigorous and independent research to validate the efficacy of these innovations. It is crucial to quantify their impact on running performance and injury prevention, challenging the often overstated claims found in marketing materials. This research could enable runners to make more informed decisions about their training methods. By making high-quality training more accessible, we aim to improve both the performance and experience of runners at all levels.

Name thesis:degree_name

Master

Department dc:contributor.department

Sloan School of Management

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Allouch, Maxime

Advisor dc:contributor.advisor

• Ruane, Jonathan

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/155998

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/155998