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.
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