Complex network study of Brazilian soccer players
Although being a very popular sport in many countries, soccer has not received much attention from the scientific community. In this paper, we study soccer from a complex network point of view. First, we consider a bipartite network with two kinds of vertices or nodes: the soccer players and the clu...
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description | Although being a very popular sport in many countries, soccer has not received much attention from the scientific community. In this paper, we study soccer from a complex network point of view. First, we consider a bipartite network with two kinds of vertices or nodes: the soccer players and the clubs. Real data were gathered from the 32 editions of the Brazilian soccer championship, in a total of \(13,411\) soccer players and 127 clubs. We find a lot of interesting and perhaps unsuspected results. The probability that a Brazilian soccer player has worked at \(N\) clubs or played \(M\) games shows an exponential decay while the probability that he has scored \(G\) goals is power law. Now, if two soccer players who have worked at the same club at the same time are connected by an edge, then a new type of network arises (composed exclusively by soccer players nodes). Our analysis shows that for this network the degree distribution decays exponentially. We determine the exact values of the clustering coefficient, the assortativity coefficient and the average shortest path length and compare them with those of the Erd\"os-Rényi and configuration model. The time evolution of these quantities are calculated and the corresponding results discussed. |
doi_str_mv | 10.48550/arxiv.0409609 |
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In this paper, we study soccer from a complex network point of view. First, we consider a bipartite network with two kinds of vertices or nodes: the soccer players and the clubs. Real data were gathered from the 32 editions of the Brazilian soccer championship, in a total of \(13,411\) soccer players and 127 clubs. We find a lot of interesting and perhaps unsuspected results. The probability that a Brazilian soccer player has worked at \(N\) clubs or played \(M\) games shows an exponential decay while the probability that he has scored \(G\) goals is power law. Now, if two soccer players who have worked at the same club at the same time are connected by an edge, then a new type of network arises (composed exclusively by soccer players nodes). Our analysis shows that for this network the degree distribution decays exponentially. We determine the exact values of the clustering coefficient, the assortativity coefficient and the average shortest path length and compare them with those of the Erd\"os-Rényi and configuration model. The time evolution of these quantities are calculated and the corresponding results discussed.</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.0409609</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Apexes ; Clustering ; Nodes ; Players ; Shortest-path problems ; Soccer</subject><ispartof>arXiv.org, 2004-10</ispartof><rights>Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the associated terms available at http://arxiv.org/abs/cond-mat/0409609.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780,27902</link.rule.ids></links><search><creatorcontrib>Onody, Roberto N</creatorcontrib><creatorcontrib>de Castro, Paulo A</creatorcontrib><title>Complex network study of Brazilian soccer players</title><title>arXiv.org</title><description>Although being a very popular sport in many countries, soccer has not received much attention from the scientific community. In this paper, we study soccer from a complex network point of view. First, we consider a bipartite network with two kinds of vertices or nodes: the soccer players and the clubs. Real data were gathered from the 32 editions of the Brazilian soccer championship, in a total of \(13,411\) soccer players and 127 clubs. We find a lot of interesting and perhaps unsuspected results. The probability that a Brazilian soccer player has worked at \(N\) clubs or played \(M\) games shows an exponential decay while the probability that he has scored \(G\) goals is power law. Now, if two soccer players who have worked at the same club at the same time are connected by an edge, then a new type of network arises (composed exclusively by soccer players nodes). Our analysis shows that for this network the degree distribution decays exponentially. We determine the exact values of the clustering coefficient, the assortativity coefficient and the average shortest path length and compare them with those of the Erd\"os-Rényi and configuration model. 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In this paper, we study soccer from a complex network point of view. First, we consider a bipartite network with two kinds of vertices or nodes: the soccer players and the clubs. Real data were gathered from the 32 editions of the Brazilian soccer championship, in a total of \(13,411\) soccer players and 127 clubs. We find a lot of interesting and perhaps unsuspected results. The probability that a Brazilian soccer player has worked at \(N\) clubs or played \(M\) games shows an exponential decay while the probability that he has scored \(G\) goals is power law. Now, if two soccer players who have worked at the same club at the same time are connected by an edge, then a new type of network arises (composed exclusively by soccer players nodes). Our analysis shows that for this network the degree distribution decays exponentially. 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subjects | Apexes Clustering Nodes Players Shortest-path problems Soccer |
title | Complex network study of Brazilian soccer players |
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