Comparison of network processes between successful and unsuccessful offensive sequences in elite soccer

Peixoto, Diogo; Praça, Gibson Moreira; Bredt, Sarah da Glória Teles; Clemente, Filipe Manuel

doi:10.1515/humo-2017-0044

Cited by 11 publications

(11 citation statements)

References 14 publications

(33 reference statements)

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“…On the other hand, the micro interaction analyses according to playing positions within categories showed a higher prominence of midfielders in the U-14 category. These results are in line with the results of previous studies on the formal game 24 and SSG 1 , in which midfielders presented a more active role for constructing offensive actions, taking the ball from the defensive to the offensive field 24 . Midfielders are also important for organizing the defensive actions during the defensive transition because they are usually closer to the game center and, therefore, can properly direct opponents to lower risk areas and create numerical superiority in the game center.…”

Section: Discussionsupporting

confidence: 92%

Defensive interactions in soccer small-sided games: an integrated approach between the fundamental tactical principles and the social network analysis

Praça

Sousa

Bredt

et al. 2018

Rev. Bras. Cineantropom. Desempenho Hum.

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This study aimed to 1) present a new analysis of the interactions between the tactical principles of defensive coverage and delay using the Social Network Analysis (SNA); 2) compare the defensive cooperation patterns presented by players of different categories during a 3vs.3 soccer small-sided games SSG; 3) compare the level of defensive prominence presented by defenders, midfielders, and forwards in 3vs.3 SSG within and between different categories. Twenty-eight soccer athletes from U-13 (n=14) and U-14 (n=14) categories of a sports club performed 3vs.3 SSG for the analysis of the defensive tactical principles. Defensive interactions were considered successful defensive coverage and a delay actions performed within the same time interval. Macro (density and clustering coefficient) and micro (degree centrality, degree prestige and page rank) analyses were used as SNA measures. Results indicated no significant differences between categories for the macro and micro analyses. Only in the U-14 category, midfielders presented higher prominence levels than the other playing positions (p=0.004). We concluded that U-13 and U-14 athletes are not different regarding defensive cooperation patterns. A higher positional tactical knowledge obtained through deliberate practice is essential to induce different defensive interactions between playing positions, as shown by significant differences only in the U-14 category.

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Section: Discussionsupporting

confidence: 92%

Defensive interactions in soccer small-sided games: an integrated approach between the fundamental tactical principles and the social network analysis

Praça

Sousa

Bredt

et al. 2018

Rev. Bras. Cineantropom. Desempenho Hum.

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“…Since no interactions between main effects were observed, two different analysis were conducted for this aim: a comparison between different playing positions within each match status and a comparison between different match statuses within each playing position. In this topic, many studies have discussed the characteristics of each playing position during a football match (López-Peña and Touchette, 2012; Peixoto et al, 2017). For example, CM presented the highest frequencies of successful passes and receptions (Brito et al, 2017), and the highest prominence in official matches (López-Peña and Touchette, 2012; Peixoto et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…In this topic, many studies have discussed the characteristics of each playing position during a football match (López-Peña and Touchette, 2012; Peixoto et al, 2017). For example, CM presented the highest frequencies of successful passes and receptions (Brito et al, 2017), and the highest prominence in official matches (López-Peña and Touchette, 2012; Peixoto et al, 2017). Considering the need to regain the ball possession quickly, losing teams are expected to adopt a more aggressive defensive style, increasing the time constraint to the team in offense, which is in line with the study of Barreira et al (2015), who demonstrated that attacking teams increased their difficult to create a favorable numerical contexts in the game center over the years in modern soccer.…”

Section: Discussionmentioning

confidence: 99%

Influence of Match Status on Players’ Prominence and Teams’ Network Properties During 2018 FIFA World Cup

et al. 2019

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The analyses of players and teams’ behaviors during the FIFA World Cup may provide a better understanding on how football tactics and strategies have developed in the past few years in elite football. The Social Network Analysis (SNA) has been carried out in the investigations about passing distribution, improving the understanding on how players interact and cooperate during a match. In football official matches, studies have used the SNA as a means of coding players’ cooperation and opposition patterns. However, situational variables such as match status were previously investigated and associated with changes on teams’ dynamics within and/or between matches, but were not considered in studies based on Social Network Analysis. This study aimed to analyze the influence of match status on teams’ cooperation patterns and players’ prominence according to playing positions during 2018 FIFA World Cup. Fourteen matches of the knockout stage were analyzed. Macro and micro network measures were obtained from adjacency matrixes collected for each team, in each match status (winning, drawing, and losing). A one-way ANOVA was used to compare teams’ networks (macro-analysis variables) within each match status, while a two-way ANOVA (match status × playing position) was used to compare the micro-analysis variables. Results showed no differences between match status for macro analysis. Winning situations induced higher prominence in central midfielders (0.107; p = 0.001), wide midfielders (0.093; p = 0.001), and center forward (0.085; p = 0.001), while in losing situations lower prominence levels were observed for goalkeepers (0.044; p = 0.001) and center forward (0.074; p = 0.001). Data revealed that teams do not change macrostructures according to match status. On the other hand, the microstructures showed important adaptations regarding game styles, with changes in players’ behaviors according to playing positions. In general, the levels of centrality and prestige in players of different positions indicated a more direct play style in winning situations and a more build-up style in losing situations. These results allow a better understanding about the influence of match status on players’ and teams’ performance during high-level football competitions and may help coaches to improve athletes’ performance in these situations.

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“…Results suggest a negative relationship between the success of offensive plays and network density, which is the only significant predictor variable in the model. This result was supported by Peixoto, Praça, Bredt, and Clemente (2017) who applied social network analysis to study differences across centrality measures in successful and unsuccessful offensive plays.…”

Section: Introductionmentioning

confidence: 75%

“…By only considering offensive sequences that ended with shots in their network analysis, Peixoto et al (2017) had a similar approach to Network 3. In-degree and out-degree centrality measures, which are linked to passes received and passes made, respectively, were calculated and revealed that strikers and midfielders scored highest on the respective measures.…”

Section: Comparison With Existing Literaturementioning

confidence: 99%

Analyzing passing networks in association football based on the difficulty, risk, and potential of passes

Wiig

Håland

Stålhane

et al. 2019

International Journal of Computer Science in Sport

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This paper investigates the use of network analysis to identify key players on teams, and patterns of passing within teams, in association football. Networks are constructed based on passes made between players, and several centrality measures are investigated in combination with three different methods for evaluating individual passes. Four seasons of data from the Norwegian top division are used to identify key players and analyze matches from a selected team. The networks examined in this work have weights based on three different aspects of the passes made: their probability of being completed, the probability that the team keeps possession after the completed pass, and the probability of the pass being part of a sequence leading to a shot. The results show that using different metrics and network weights leads to the identification of key passers in different phases of play and in different positions on the pitch.

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Comparison of network processes between successful and unsuccessful offensive sequences in elite soccer

Cited by 11 publications

References 14 publications

Defensive interactions in soccer small-sided games: an integrated approach between the fundamental tactical principles and the social network analysis

Defensive interactions in soccer small-sided games: an integrated approach between the fundamental tactical principles and the social network analysis

Influence of Match Status on Players’ Prominence and Teams’ Network Properties During 2018 FIFA World Cup

Analyzing passing networks in association football based on the difficulty, risk, and potential of passes

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