نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی‌ارشد مدیریت ورزشی، دانشگاه کردستان

2 استادیار رفتار حرکتی، دانشگاه کردستان

چکیده

هدف این پژوهش شناسایی پست‏های بازیکنان تیم ملی فوتبال در ایجاد حمله و تحلیل شبکه‏ های آن‌ها بود. سه مسابقة رسمی تیم ملی در جام‌جهانی تحلیل و کدگذاری شدند. پاس بین هم‏ تیمی‏ ها به‌عنوان یک معیار ارتباطی تعریف شده است.پس از هر مسابقه، یک ماتریس مجاور کلی ساخته شد. سپس، برای تحلیل به نرم‏ افزار تحلیل شبکه‏ های اجتماعی وارد شد. تحلیل شبکة بازی‏ها با استفاده از دو مقیاس درجة مرکزیت و درجةاعتبار انجام شد.مقادیر درجة مرکزیت نشان داد که مدافعانکناری، 2/12 درصد و هافبک‏ها 03/12 درصد، مشارکت بیشتریدر گردشتوپو ایجاد حملهداشتند. همچنین، مقادیر درجة اعتبار نشان داد که هافبک‏ها، 65/12 درصد و مهاجم، 90/11 درصد هدف‏های هم‏ تیمی‏ ها برای پاس‌دادن توپ طی توالی پاس بودند.این مطالعهنشان داد که چگونهمعیارهایمرکزیت شبکهمی‏توانند اطلاعات مفیدی رابرای مربیان ونیز برای مطالعةمشارکتفردیبازیکنانبرای فرایندحمله فراهم کنند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Identify Positional Players in Building Attack; The Social Network Analysis of Iran Football Team on FIFA World Cup 2014

نویسندگان [English]

  • Farhad Alahvisi 1
  • Mohammad Maleki 2

1 M.Sc. of Sport Management, University of Kurdistan

2 Assistant Professor of Motor Behavior, University of Kurdistan

چکیده [English]

The purpose of present study was identifying positional players Iran football team in building attack and their networks analysis. Three official matches from national team in FIFA World Cup were analyzed and codified. Pass between teammates defined as linkage criteria. After each match an adjacent matrix general was built. Then imported into Social Networks Visualizer for analysis. Network analysis of the games by 2 scale degree centrality and degree prestige was performed. The values degree centrality reveals lateral defenders (12.2) and midfielders (12.03) had a percent greater participation in the ball circulation and building attack. Also, the values degree prestige reveals midfielders (12.65) and striker (11.90) were the targets of the teammates to pass the ball during the passing sequences. This study showed how network centrality metrics can to provide useful information for coaches and also to study the individual contribution of players for the attacking process.

کلیدواژه‌ها [English]

  • Social Network Analysis
  • Software Socnetv
  • Degree Centrality
  • Degree Prestige
1. Balkundi, P., & Harrison, D. (2006). Ties, leaders, and time in teams: Strong inference about network structure’s effects on team viability and performance. Academy of Management Journal, 49(3), 49–68.
2. Bourbousson, J., Poizat, G., Saury, J., & Seve, C. (2010). Team coordination in basketball: Description of the cognitive connections among teammates. Journal of Applied Sport Psychology, 22(2), 150-66.
3. Carling, C., Williams, A. M., & Reilly, T. (2005). Handbook of soccer match analysis: A systematic approach to improving performance. London & New York: Taylor & Francis Group.
4. Clemente, F. M., Couceiro, M. S., Martins, F. M. L., & Mendes, R. S. (2014). Using network metrics to investigate football team players connections: A pilot study. Motriz, 20(3), 262–71.
5. Clemente, F. M., Couceiro, M. S., Martins, F. M. L., & Mendes, R. S. (2015 d). Using network metrics in soccer: A macro-analysis. Journal of Human Kinetics, 45(1), 123-34.
6. Clemente, F. M., Martins, F. M. L., Kalamaras, D., & Mendes, R. S. (2015 b). Network analysis in basketball: Inspecting the prominent players using centrality metrics. Journal of Physical Education and Sport, 15(2), 212-7.
7. Clemente, F. M., Martins, F. M. L., Kalamaras, D., Oliveira, J., Oliveira, P., & Mendes, R. S. (2015 c). The social network analysis of Switzerland football team on FIFA World Cup 2014. Journal of Physical Education and Sport, 15(1), 136 –41.
8. Clemente, F. M., Martins, F. M. L., Kalamaras, D., Wong, D., P, & Mendes, R. S. (2015 e). General network analysis of national soccer teams in FIFA World Cup 2014. International Journal of Performance Analysis in Sport, 15(1), 80-96.
9. Clemente, F. M., Martins, F. M. L., Wong, D., P, Kalamaras, D., & Mendes, R. S. (2015 a). Midfielder as the prominent participant in the building attack: A network analysis of national teams in FIFA World Cup 2014. International Journal of Performance Analysis in Sport, 15(2), 704-22.
10. Clemente, F. M., Martins, F. M. L., & Mendes, R. S. (2016). Social network analysis applied to team sports analysis. Portugal: Springer Briefs in Applied Sciences and Technology.
11. Couceiro, M. S., Clemente, F. M., Martins, F. M. L., & Tenreiro, M. J. A. (2014). Dynamical stability and predictability of football players: The study of one match. Entropy, 16(2), 645-74.
12. Duarte, R., Araújo, D., Correia, V., & Davids, K. (2012). Sports teams as superorganisms: Implications of sociobiological models of behaviour for research and practice in team sports performance analysis. Sports Medicine, 42(8), 633-42.
13. Duch, J., Waitzman, J. S., & Amaral, L. A. (2010). Quantifying the performance of individual players in a team activity. Plos One, 5(6), 109-19.
14. Fewell, J. H., Armbruster, D., Ingraham, J., Petersen, A., & Waters, J. S. (2012). Basketball teams as strategic networks. Plos One, 7(11), 474-85.
15. Gréhaigne, J. F., Bouthier, D., & David, B. (1997). Dynamic-system analysis of opponent relationship in collective actions in football. Journal of Sports Sciences, 15(2), 137-49.
16. Grund, T. U. (2012). Network structure and team performance: The case of English Premier League soccer teams. Social Networks, 34(4), 682-90.
17. Hughes, M., & Franks, I. (2005). Analysis of passing sequences, shots and goals in soccer. Journal of Sports Sciences, 23(5), 509–14.
18. 18. Kalamaras, D. (2016). Social networks visualizer (SocNetV): Social networks analysis and visualization software. Available at: http://socnetv.sourceforge.net (Accessed).
19. Lusher, D., Robins, G., & Kremer, P. (2010). The application of social network analysis to team sports. Measurement in Physical Education and Exercise Science, 14(4), 211-24.
20. Malta, P., & Travassos, B. (2014). Characterization of the defense–attack transition of a soccer team. Motricidade, 10(1), 27-37.
21. Passos, P., Davids, K., Araújo, D., Paz, N., Minguéns, J., & Mendes, J. (2011). Networks as a novel tool for studying team ball sports as complex social systems. Journal of Science and Medicine in Sport, 14(2), 170-6.
22. Peña, J. L., & Touchette, H. (2012). A network theory analysis of football strategies. In Clanet, C. (Ed.), Sports physics: Euromech Physics of Sports Conference (517–28). Palaiseau, France: Editions de l'Ecole Polytechnique.
23. Yamamoto, Y., & Yokoyama, K. (2011). Common and unique network dynamics in football games. Plos One, 6(12), 29-40.