This paper analyzes the network of passes among the players of the Spanish team during the last FIFA World Cup 2010,where they emerged as the champion,with the objective of explaining the results obtained from the beh...This paper analyzes the network of passes among the players of the Spanish team during the last FIFA World Cup 2010,where they emerged as the champion,with the objective of explaining the results obtained from the behavior at the complex network level.The team is considered a network with players as nodes and passes as(directed) edges.A temporal analysis of the resulting passes network is also done,looking at the number of passes,length of the chain of passes,and to network measures such as player centrality and clustering coefficient.Results of the last three matches(the decisive ones) indicate that the clustering coefficient of the pass network remains high,indicating the elaborate style of the Spanish team.The effectiveness of the opposing team in negating the Spanish game is reflected in the change of several network measures over time,most importantly in drops of the clustering coefficient and passing length/speed,as well as in their being able in removing the most talented players from the central positions of the network.Spain's ability to restore their combinative game and move the focus of the game to offensive positions and talented players is shown to tilt the balance in favor of the Spanish team.展开更多
The FIFA World Cup^(TM) is the most profitable worldwide event.The FIFA publishes global statistics of this competition which provide global data about the players and teams during the competition.This work is focused...The FIFA World Cup^(TM) is the most profitable worldwide event.The FIFA publishes global statistics of this competition which provide global data about the players and teams during the competition.This work is focused on the extraction of behavioural patterns for both,players and teams strategies,through the automated analysis of this dataset.The knowledge and models extracted in this work could be applied to soccer leagues or even it could be oriented to sport betting.However,the main contribution is related to the study on several automatic knowledge extraction techniques,such as clustering methods,and how these techniques can be used to obtain useful behavioural models from a global statistics dataset.The information provided by the clustering algorithms shows similar properties which have been combined to define the models,making the human interpretation of these statistics easier.Finally,the most successful teams strategies have been analysed and compared.展开更多
基金supported in part by the CEI BioTIC GENIL(CEB09-0010)MICINN CEI Program(PYR2010-13)projectthe Andalusian Regional Government P08-TIC-03903,P08-TIC-03928,and TIC-6083 projectsMICINN projects TIN2008-05941 and TIN2011-28627-C04
文摘This paper analyzes the network of passes among the players of the Spanish team during the last FIFA World Cup 2010,where they emerged as the champion,with the objective of explaining the results obtained from the behavior at the complex network level.The team is considered a network with players as nodes and passes as(directed) edges.A temporal analysis of the resulting passes network is also done,looking at the number of passes,length of the chain of passes,and to network measures such as player centrality and clustering coefficient.Results of the last three matches(the decisive ones) indicate that the clustering coefficient of the pass network remains high,indicating the elaborate style of the Spanish team.The effectiveness of the opposing team in negating the Spanish game is reflected in the change of several network measures over time,most importantly in drops of the clustering coefficient and passing length/speed,as well as in their being able in removing the most talented players from the central positions of the network.Spain's ability to restore their combinative game and move the focus of the game to offensive positions and talented players is shown to tilt the balance in favor of the Spanish team.
基金partly supported by:Spanish Ministry of Science and Education under project TIN201019872the grant BES-2011-049875 from the same MinistryJobssy.com company under project FUAM076913
文摘The FIFA World Cup^(TM) is the most profitable worldwide event.The FIFA publishes global statistics of this competition which provide global data about the players and teams during the competition.This work is focused on the extraction of behavioural patterns for both,players and teams strategies,through the automated analysis of this dataset.The knowledge and models extracted in this work could be applied to soccer leagues or even it could be oriented to sport betting.However,the main contribution is related to the study on several automatic knowledge extraction techniques,such as clustering methods,and how these techniques can be used to obtain useful behavioural models from a global statistics dataset.The information provided by the clustering algorithms shows similar properties which have been combined to define the models,making the human interpretation of these statistics easier.Finally,the most successful teams strategies have been analysed and compared.
