  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.
