Examinando por Autor "Antequera, Daniel R."

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Consistency and identifiability of football teams: a network science perspective
(Nature, 2020-11-12) Garrido, David; Antequera, Daniel R.; Busquets, Javier; López del Campo, Roberto; Resta Serra, Ricardo; Jos Vielcazat, Silvestre
We investigated the ability of football teams to develop a particular playing style by looking at their passing patterns. Using the information contained in the pass sequences during matches, we constructed the pitch passing networks of teams, whose nodes are the divisions of the pitch for a given spatial scale and links account for the number of passes from region to region. We translated football passings networks into their corresponding adjacency matrices. We calculated the correlations between matrices of the same team to quantify how consistent the passing patterns of a given team are. Next, we quantified the differences with other teams’ matrices and obtained an identifiability parameter that indicates how unique are the passing patterns of a given team. Consistency and identifiability rankings were calculated during a whole season, allowing to detect those teams of a league whose passing patterns are different from the rest. Furthermore, we found differences between teams playing at home or away. Finally, we used the identifiability parameter to investigate what teams imposed their passing patterns over the rivals during a given match.
The resumption of sports competitions after COVID-19 lockdown: The case of the Spanish football league
(Elsevier, 2020-09) Buldú, Javier M.; Antequera, Daniel R.; Aguirre, Jacobo
In this work, we present a stochastic discrete-time SEIR Susceptible- Exposed-Infectious-Recovered model adapted to describe the propagation of COVID-19 during a football tournament. Specifically, we are concerned about the re-start of the Spanish national football league, La Liga, which is currently –May 2020– stopped with 11 fixtures remaining. Our model includes two additional states of an individual, confined and quarantined, which are reached when an individual presents COVID-19 symptoms or has undergone a virus test with a positive result. The model also accounts for the interaction dynamics of players, considering three different sources of infection: the player social circle, the contact with his/her team colleagues during training sessions, and the interaction with rivals during a match. Our results highlight the dramatic influence of the days between matches, the fre- quency of virus tests and their sensitivity on the number of players infected at the end of the season. Following our findings, we finally present a variety of strategies to minimize the probability that COVID-19 propagates in case the season of La Liga was re-started after the current lockdown.