Football matches present many of the properties of complex systems, notably the emergent features that result from multiple interactions within the system. The dyadic interactions in ball passing or stealing have been successfully represented and explored via social network analysis. Albeit its success, many of these tools fall short to capture match processes that involve n-ary interactions (with n > 2). This has been exposed by recent automated processes for the accurate acquisition of match spatiotemporal data. In this talk we will summarise the constructs provided by hypernetwork formalisms and how they enable the representation of both interactions sets of arbitrary composition, i.e. simplex sets, and their relations. The incorporation of spatiotemporal data into hypernetwork formalisms and tools has enabled valuable insights on teams’ structure and dynamics during a football match. Analysis on the composition of the simplex sets formed in a series of matches revealed 1 vs. 1 to the most frequent elementary structure. Using a multilayer approach, spatiotemporal characteristics of simplices reveal not only their prevalence in both dimensions, space and time, but also during chief moments of the match (e.g., goal scoring opportunities). Changes in the number of simplices and their composition during the match can be quantified via information variation measures and used as a proxy to gauge its dynamic properties. Extending the multilayer hypernetwork concepts and tools to other dimensions and processes in football matches and the effective usage of its results by practitioners is still a challenge and a vast research field to be explored.

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