Sport is an integral part of everyday life, and sports data present unique opportunities and challenges for statisticians. This session offers valuable insights for both sports enthusiasts and statistics professionals, highlighting innovative methods at the intersection of theory and practice in this dynamic and rapidly evolving field. Presenters will showcase cutting-edge statistical methodologies applied across a variety of sports, emphasising bespoke models tailored to sports contexts and data-driven solutions to real-world problems.
Jessica Hargreaves, University of York:
The Lioness Effect: investigating the determinants of stadium attendance in elite women's football
Pete Philipson, Newcastle University:
A flexible distribution for count differences
Ben Powell, University of York:
Neural density estimation with application to sports data
Organised by Daniel Henderson
Dr Jessica Hargreaves is a Lecturer in Data Science at the University of York. The main focus of her research is utilising wavelet techniques to model time series whose characteristics evolve through time. Her research is motivated by various applied statistics problems in fields such as biology, chemistry and sport.
Jess works with a number of professional sports organisations, with the goal of making quantitative analysis in sport more accessible. She is the Vice Chair of the RSS Statistics in Sport Section and helps to organise their annual prediction competition.
The Lionesses' victory at the 2022 UEFA Women’s European Championship significantly raised the profile of women’s football in England. Sustaining this momentum requires increasing attendance at domestic fixtures, a key driver of the sport’s commercial development. This study examines the determinants of stadium attendance in the English FA Women’s Super League (WSL). Using time-varying coefficient regression models to analyse matchday data across eight seasons (2017–2024/25), we investigate both contextual and sport-related factors influencing crowd numbers. Our findings reveal a sustained increase in attendance over the study period, with significant positive associations identified for variables such as the away team’s reputation, favourable weather conditions and the scheduling of men’s football fixtures. Additionally, we present an open-source R Shiny application designed to generate interactive visualisations of WSL attendance data.