We present a set of tools for identifying and studying the offensive and defensive strategies used by football teams in corner kick situations: their corner playbooks. Drawing from methods in topic modelling, our tools classify corners based on the runs made by the attacking players, enabling us to identify the distinct corner routines used by individual teams and search tracking data to find corners that exhibit specific features of interest. We use a supervised machine learning approach to identify whether individual defenders are marking man-to-man or zonally and study the positioning of zonal defenders over many matches. We demonstrate how our methods can be used for opposition analysis by highlighting the offensive and defensive corner strategies used by teams in our data over the course of a season.
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