Athlete Rankings: An Analysis of Elite Women's Cyclists

Abstract

Women’s professional sports are on the rise, and with that comes an increased interest in athlete statistics and predictive analytics. Many mainstream approaches used to rank athletes today involve an analysis of naturally paired data in head-to-head match-ups between two individuals or teams. This paper aims to progress the field of women’s sports analytics, proposing a novel approach to establishing rankings for elite women’s cyclists using linear algebra and statistical-based methods with data based on race type. In particular, Massey’s and Colley’s methods as well as the Elo and Glicko ratings systems are considered. The exploration of data from the 2022 UCI Women’s World Tour season suggests that statistical-based approaches are more in line with the UCI’s own descriptive points system.