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- Social network measures to match analysis in soccer : a surveyPublication . Manuel Clemente, Filipe; M. L. Martins, Fernando; Mendes, Rui; G. M. Silva, FrutuosoIn this study we will present the most common and adequate network measures to analyse graph properties and to inspect the prominence of each player on a soccer team. Both approaches can provide a range of useful information. This kind of analysis will help to identify the prominence of players and also characterize the collective organization and patterns of the teams. General measures and centrality levels will be described and the applications will be discussed. By using social network analysis will be possible to quantify the structure of play and predict some behaviour. Such methodology will add new options to the field of match analysis.
- Study of network process in children during cooperation gamesPublication . Ferreira, Oriana; Manuel Clemente, Filipe; Amorós, JuanPablo; G. M. Silva, Frutuoso; Mendes, Rui; Campos, Francisco; M. L. Martins, FernandoWhile playing, the child progresses in reasoning ability, develops thinking and other skills, creates social relations, understands the environment, develops knowledge and creativity, and satisfies desires (Dallabona& Mendes, 2004). Thus, playing “increases their independence, stimulates their visual and auditory sensibility, values their popular culture, develops motor skills, exercises their imagination, their creativity, socializes, interacts, rebalances, recycles their emotions, their need to know and reinvent, and thus builds their knowledge” (Dallabona& Mendes, 2004, p.4). However, the interaction with a medium that is still unknown requires the child to explore new spaces, new situations, and new contexts, watching for visible behavioral changes, acquiring patterns of communication and interaction with each other (Martins, Clemente,& Mendes, 2015), all of which is essential for the child’s development.The aim of the present study was to analyze the variance between groups of different sizes in different playful games of cooperation. The groups were randomly formed and consisted of groups of 5 (G5) or 10 (G10) members.In the results obtained, it was possible to verify that there are no significant differences in the groups of 5 and 10 children in the values of proximity prestige, whereas in centroid value statistically significant differences were found in the comparison between groups of 5 and those of 10 children, regarding interaction in the cooperation games.
- Social network analysis applied to children : cooperation games versus cooperation-opposition gamesPublication . Santos, Andreia; Manuel Clemente, Filipe; Sanchez, Juan; Campos, Francisco; G. M. Silva, Frutuoso; Mendes, Rui; M. L. Martins, FernandoIn order to study the effect of cooperative and opposition games in children interactions, 10 preschool children (5 to 6 year olds) were monitored over a 1-month period: the interactions between peers were quantified and analyzed in different games, through Social Network Analysis. Results suggest a significant correlation between a cooperative environment and a more connected and balanced passing network, less dependent on a given player, more focused on the goal at task. This research indicates that a cooperative environment can optimize and enhance the interactions between children, creating a stronger, more functional and more connected network.
- Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014Publication . Manuel Clemente, Filipe; G. M. Silva, Frutuoso; M. L. Martins, Fernando; Kalamaras, Dimitris; Mendes, RuiThe study of teammates’ interaction on team sports has been growing in the last few years. Nevertheless, no specific software has been developed so far to do this in a user-friendly manner. Therefore, the aim of this study was to introduce a software called the Performance Analysis Tool that allows the user to quickly record the teammates’ interaction and automatically generate the outputs in adjacency matrices that can then be imported by social network analysis software such as SocNetV. Moreover, it was also the aim of this study to process the data in a real-life scenario, thus the seven matches of the German national soccer team in the FIFA World Cup 2014 were used to test the software and then compute the network metrics. A dataset of 3032 passes between teammates in seven soccer matches was generated with the Performance Analysis Tool software, which permitted a study of the network structure. The analysis of variance of centrality metrics between different tactical positions was made. The two-way multivariate analysis of variance revealed that the strategic position (γ=1.305 ; F = 24.394; p = 0.001; η2p=0.652 ; large effect size) had significant main effects on the centrality measures. No statistical differences were found in the phase of competition (γ=0.003 ; F = 0.097; p = 0.907; η2p=0.003 ; very small effect size). The network approach revealed that the German national soccer team based their attacking process on positional attacks and not in counter-attack, and the midfielders were the prominent players followed by the central defenders. The Performance Analysis Tool software allowed the user to quickly identify the teammates’ interactions and extract the network data for process and analysis.