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Visual analysis of soccer players and a team

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Abstract

Soccer is one of the most entertaining and popular sports around the world, and is also very interesting from a scientific point of view. Most of the scientific research on soccer is related to matches and game play analysis. In this paper, we propose a novel system for team performance analysis and visualization in terms of the structure of a team, and concentrate on cause-and-effect relationships between players and their teams based on player transfer data. Our system visualizes the individual player performance, team characteristics, comparisons between teams, and time varying changes of the team characteristics. The analyzed data are presented in two different ways (1) the system creates a pixel-grid visualization that presents the distinct characteristics of each player in a team. (2) A horizon graph is used to display the changes in team characteristics over time due to player transfers. This approach facilitates understanding the influence of player transfers on team characteristics in a very simple and straightforward manner.

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References

  1. Bernard J, Ritter C, Sessler D, Zeppelzauer M, Kohlhammer J, Fellner D (2017) Visual-interactive similarity search for complex objects by example of soccer player analysis. In: proc of the 12th Int joint Conf on computer vision, imaging and computer graphics theory and applications, arXiv preprint arXiv:1703.03385, pp. 75–87

  2. Berthold M, Cebron N, Dill F, Gabriel T, Kotter T, Meinl T, Ohl P, Sieb C, Thiel K, Wiswedel B (2007) KNIME: the Konstanz information miner. Springer, New York

    Google Scholar 

  3. Chapman S, Derse E, Hansen J (2012) Soccer coaching manual. LA84 Foundation, Los Angeles

    Google Scholar 

  4. Chung D, Parry M, Griffiths W, Laramee S, Bown R, Legg A, Chen M (2016) Knowledge-assisted ranking: a visual analytic application for sports event data. IEEE Comput Graph Appl 36(3):72–82

    Article  Google Scholar 

  5. Duarte R, Ara’ujo D, Folgado H, Esteves P, Marques P, Davids K (2013) Capturing complex, non-linear team behaviors during competitive football performance. J Syst Sci Complex 26(1):62–72

    Article  Google Scholar 

  6. FIFA Big Count (2014) from http://www.fifa.com/worldfootball/bigcount/index.html

  7. FIFA TMS from BIG 5: Transfer Window Analysis (Summer 2014), http://www.fifatms.com/en/Reports/reports-2014/

  8. FIFA TMS from BIG 5: Transfer Window Analysis (winter 2015), http://www.fifatms.com/en/Reports/reports-2015/

  9. Financial fair play: UEFA (1 September, 2014) from http://www.uefa.org/protecting-the-game/club-licensing-and-financial-fair-play/

  10. Fonseca S, Milho J, Travassos B, Ara’ujo D, Lopes A (2013) Measuring spatial interaction behavior in team sports using superimposed Voronoi diagrams. Int J Perform Anal Sport 13(1):179–189

    Article  Google Scholar 

  11. FootballDatabase.eu from http://www.footballdatabase.eu/transfertstab.php?competition=1&lieu=Angleterre

  12. Fujimura A, Sugihara K (2005) Geometric analysis and quantitative evaluation of sport teamwork. Syst and Comput 36(6):49–58

    Article  Google Scholar 

  13. Goldsberry K (2012) Courtvision: new visual and spatial analytics for the NBA. In: Proc MIT Sloan Sports Analytics Conf

  14. Gudmundsson J, Wolle T (2012) Football analysis using spatio-temporal tools. In: proc of the 20th Int Conf on advances in geographic information Syst (9):566–569

  15. Jacques B (1983) Semiology of graphics: diagrams, networks, maps. University of Wisconsin Press, Wisconsin

    Google Scholar 

  16. Kang C, Hwang J, Li K (2006) Trajectory analysis for soccer players. In: proc of sixth IEEE Int Conf on ICDM workshops, pp. 377–381

  17. Kim S (2004) Voronoi analysis of a soccer game. Nonlinear Anal Modell Control 9(3):233–240

    MATH  Google Scholar 

  18. Lago-Peñas C, Lago-Ballesteros J, Dellal A, G’omez M (2010) Gamerelated statistics that discriminated winning, drawing and losing teams from the Spanish soccer league. J Sports Sci Med 9(2):288–293

    Google Scholar 

  19. Legg P, Chung D, Parry M, Jones M, Long R, Griffiths I, Chen M (2012) Matchpad: interactive glyph-based visualization for real-time sports performance analysis. Comput Graph Forum 31:1255–1264

    Article  Google Scholar 

  20. Memmert D, Lemmink A, Sampaio J (2017) Current approaches to tactical performance analyses in soccer using position data. Sports Med 47(1):1–10

    Article  Google Scholar 

  21. Nakanishi R, Maeno J, Murakami K, Naruse T (2010) An approximate computation of the dominant region diagram for the real-time analysis of group behaviors. In: RoboCup 2009 robot soccer world cup XIII, (5946):228–239, Springer, Berlin, Heidelberg

  22. Page M, Moere A (2006) Towards classifying visualization in team sports. In: Proc of the Int Conf on IEEE Computer Graphics Imaging and Visualisation, pp. 24–29

  23. Peña J, Touchette H (2012) A network theory analysis of football strategies. In: Proc Euromech Physics of Sports Conf, pp. 517–528

  24. Perin C, Vuillemot R, Fekete JD (2013) SoccerStories: a kick-off for visual soccer analysis. IEEE Trans Vis Comput Graph 19(12):2506–2515

    Article  Google Scholar 

  25. Pileggi H, Stolper C, Boyle J, Stasko J (2012) Snapshot: visualization to propel ice hockey analytics. IEEE Trans Vis Comput Graph 18(12):2819–2828

    Article  Google Scholar 

  26. Robertson PK, Hutchins MA (1994) An approach to intelligent design of color visualizations. In: Proc Scientific Visualization, Overviews, Methodologies, and Techniques, pp. 179–190, IEEE, Washington

  27. Rusu A, Stoica D, Burns E (2011) Analyzing soccer goalkeeper performance using a metaphor-based visualization. In: IEEE 15th Int Conf on information visualisation (IV), pp. 194–199

  28. Sacha D, Stein M, Schreck T, Keim DA, Deussen O (2014) Feature-driven visual analytics of soccer data. In: 2014 I.E. Conf on visual analytics science and technology (VAST), pp. 13–22

  29. Salvo V, Baron R, Tschan H, Calderon M, Bachl N, Pigozzi F (2007) Performance characteristics according to playing position in elite soccer. Sports Med 28(3):222

    Google Scholar 

  30. Spence R (2001) Information visualization. Addison-Wesley, New York, pp 14–16

    Google Scholar 

  31. Sports Interactive. Football Manager from http://www.footballmanager.com/

  32. Stein M, Janetzko H, Seebacher D, Jäger A, Nagel M, Hölsch J, Grossniklaus M (2017) How to make sense of team sport data: from acquisition to data modeling and research aspects. Data 2(1):2

    Article  Google Scholar 

  33. TactFoot: Soccer coaching tactical software (2010), Retrieved from http://www.tactfoot.com

  34. Taki T, Hasegawa J (2000) Visualization of dominant region in team games and its application to teamwork analysis. In: IEEE Proc Computer Graphics Int Conf, pp. 227–235

  35. Ward MO (2010) A taxonomy of glyph placement strategies for multidimensional data visualization. Inf Vis 1(3–4):194–210

    Google Scholar 

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Acknowledgements

This work (NRF-2016R1A2B4016239) was supported by the Mid-Career Researcher Program through an NRF grant funded by the MEST.

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Authors and Affiliations

  1. The Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul, Republic of Korea

    Miohk Ryoo & Namjung Kim

  2. School of Integrative Engineering, Chung-Ang University, Seoul, Republic of Korea

    Kyoungju Park

Authors
  1. Miohk Ryoo
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  2. Namjung Kim
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  3. Kyoungju Park
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Correspondence to Miohk Ryoo.

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Ryoo, M., Kim, N. & Park, K. Visual analysis of soccer players and a team. Multimed Tools Appl 77, 15603–15623 (2018). https://doi.org/10.1007/s11042-017-5137-4

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  • DOI: https://doi.org/10.1007/s11042-017-5137-4

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