Modularity in Football Passing Networks

Year 2020, Volume: 22 Issue: 2, 296 - 304, 06.09.2020

Necmi Gürsakal Halil Orbay Çobanoğlu Bülent Batmaz Sandy İpeker Fırat Yılmaz

Abstract

In recent decades, within the boundaries of complexity sciences, network science has been used to analyze many kinds of networks. A complex system is formed by smaller subsystems which can be designed independently yet function together as a whole. Modules of a network can be called as groups, clusters or communities and modularity can be defined as a measure of the structure of networks or graphs. If it has dense connections within a network’s modules and sparse connections between nodes in different modules, in this case networks have high modularity. At the end of each football match, successful pass networks can be achieved. These modular structures can be thought as “independent yet function as a whole” football modules. Generally so called modules in the technical directors’ thoughts can be listed as defense, midfielders area and strikers area. If they want to know how modules are generated and how their disconnection leads to functional decay they should analyze the modularity formed as a result of a football match. The aim of this study is to examine to what extent the football teams' managers have implemented their strategies in games. First, 10 matches with the e-analysis football program were analyzed. And then modularity analysis began with transforming the video of a football match into a pass network. Using this pass network, network metrics was to be computed and then these metrics was to be used to make a modularity analysis using Gephi. After modularity analysis using Gephi, modularity classes of these networks were found for all networks. When the results obtained from the modularity analysis were examined, it was observed that the number of modules varied between 2 and 4. Consequently, it was observed that the systems found as a result of the modularity analysis were very different than the planned systems.

Keywords

Network Science, Network metrics, Modularity, Football

References

• Gharajedaghi J. Systems Thinking Managing Chaos and Complexity: A Platform for Designing Business Architecture. 2nd ed. Butterworth-Heinemann, 2005.
• Schlosser G, Wagner GP. Modularity in Development and Evolution. Chicago: Chicago University Press; Chicago, IL, 2004.
• Roh J, Lee SW, Wilger KD. Modular Organization of Exploratory Force Development Under Isometric Conditions in the Human Arm. Journal of Motor Behavior, 2019; 51(1): 83-99.
• Sporns O, Betzel RF. Modular Brain Networks. Annual Review of Psychology, 2016; 67(Jan 4): 613-640.
• Luo F, Yang Y, Chen C, Chang R, Zhou J, Scheuermann RH. Modular Organization of Protein Interaction Networks. Bioinformatics, 2007; 23(2): 207-214.
• Valverde S. Breakdown of Modularity in Complex Networks. Frontiers in Physiology, 2017; 8(497): 1-8.
• Newman MEJ. Communities, Modules and Large-Scale Structure in Networks. Nature Physics, 2012; 8: 25-31.
• Newman MEJ. Modularity and Community Structure in Networks. PNAS, 2006; 103(23): 8577-8582.
• Sol´e RV, Valverde S. Spontaneous Emergence of Modularity in Cellular Networks. Journal of The Royal Society Interface, 2008; 5(18): 129-33.
• Ding J., Sun Y., Tan P., Ning Y. Modularity Maximization for Community Detection in Networks Using Competitive Hopfield Neural Network. International Journal of Innovative Computing, Information and Control, 2019; 15(4): 1455-1467.