Proposal of a predictive model for the attack in women's football depending on the part of the match

Abstract

Women’s football is currently a phenomenon in expansion, both in the number of practitioners and federative records. Scientific research must be at the forefront of this growth, proposing solutions with empirical support that help improve performance not only during training but also during competition. The objective of this study was to propose a multivariate model based on the decision tree technique, with the aim of classifying and predicting the criteria that modulated the attack depending on the part of the match (either the first or second part). To do this, 6063 attacks from the two most recent world championships have been collected and analysed. The available results indicate that, although more attacks occur during the first part, it is in the second part when the goals are scored. In addition, the presented model confirms that the most successful attacks (goal, shot or sending to the area) occur with the score winning or losing, and with a duration of less than 20 seconds. The results of this study can help female soccer coaches to improve the training process of offensive actions and attack