Explaining the difference between men's and women's football

TL;DR

This paper uses AI to analyze match data from the last World Cups, identifying key technical differences between men's and women's football, such as accuracy and play dynamics, to better understand their distinctions.

Contribution

It introduces a machine learning approach to distinguish and explain technical differences between men's and women's football based on match performance variables.

Findings

Men's football exhibits higher play accuracy.

Women's football has faster ball recovery times.

Differences are rooted in performance quality and play dynamics.

Abstract

Women's football is gaining supporters and practitioners worldwide, raising questions about what the differences are with men's football. While the two sports are often compared based on the players' physical attributes, we analyze the spatio-temporal events during matches in the last World Cups to compare male and female teams based on their technical performance. We train an artificial intelligence model to recognize if a team is male or female based on variables that describe a match's playing intensity, accuracy, and performance quality. Our model accurately distinguishes between men's and women's football, revealing crucial technical differences, which we investigate through the extraction of explanations from the classifier's decisions. The differences between men's and women's football are rooted in play accuracy, the recovery time of ball possession, and the players' performance quality. Our methodology may help journalists and fans understand what makes women's football a distinct sport and coaches design tactics tailored to female teams.