Analysis of Japanese Football Games by the Tracking Data and Sport Live Event Annotations

Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 496)

Abstract

The purpose of this study is to learn what kind of play would lead to opportunities and to pinches, by using data from the tracking system, as well as live coverage of the real-time sport broadcasting from a game played by Shonan Bellmare and Kashima Antlers, Japanese professional football teams. In this study, we present a novel approach for sports event detection based on analysis and alignment of tracking data and real-time sport broadcasting. Based on these results of analyses, we will evaluate tactics and movements of main players from the standpoint of the better team management.

Keywords

Football games Tracking data Real-time sport event annotations 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

This research has made use of Data Stadium Inc. database.

References

  1. 1.
    Cotta, C., Mora, A.M., Merelo, J.J., Merelo-Molina, C.: A network analysis of the 2010 FIFA world cup champion team play. J. Syst. Sci. Complex 26, 21–42 (2013)CrossRefMATHGoogle Scholar
  2. 2.
    Kim, H.-C., Kwon, O., Li, K.-J.: Spatial and spatiotemporal analysis of soccer. In: Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information System, pp. 385–388. (2011)Google Scholar
  3. 3.
    Taki, T., Hasegawa, J., Fukumura, T.: Development of motion analysis system for quantitative evaluation of teamwork in soccer games. In: Proceedings of the International Conference in Image Processing 1996, vol. 3, pp. 815–818. (1996)Google Scholar
  4. 4.
    Vilar, L., Araújo, D., Davids, K., Bar-Yam, Y.: Science of winning soccer: emergent pattern-forming dynamics in association football. J. Syst. Sci. Complex. 26, 73–84 (2013)CrossRefGoogle Scholar
  5. 5.
    Carling, C., Williams, A.M., Reilly, T.: The Handbook of Soccer Match Analysis. Routledge, Abingdon, UK (2005)CrossRefGoogle Scholar
  6. 6.
    Bebie, T., Bieri, H.: Soccer man: reconstructing soccer games from video sequences, Proc. ICPR 898–902 (1998)Google Scholar
  7. 7.
    Intille, S.S., Bobick, A.F.: Closed-world tracking, Proc. ICCV 672–678 (1995)Google Scholar
  8. 8.
    Seo, Y., Choi, S., Kim, H., Hong, K.S.: Where are the ball and players? Soccer game analysis with color based tracking and image mosaic. Proc. ICIAP 196–203 (1997)Google Scholar
  9. 9.
    Xu, M, Orwell J., Jones, G.: Tracking football players with multiple cameras. ICIP 2014, (2014)Google Scholar
  10. 10.
    D’Orazio, T., Leo, M.: A review of vision-based systems for soccer video analysis. Pattern Recogn. 43, 2911–2926 (2010)CrossRefGoogle Scholar
  11. 11.
    Renno, J.R., Orwell, J., Thirde, D.J., Jones, G.A.: Shadow classification and evaluation for soccer player detection. In: British Machine Vision Conference, 7–9 September, pp. 839–848. Kingston University, London (2004)Google Scholar
  12. 12.
    Kim, H., Nam, S., Kim, J.: Player segmentation evaluation for trajectory estimation in soccer games. In: Proceeding of Image and Vision Computing, 26–28 November, pp. 159–162. Palmerston North, New Zealand (2003)Google Scholar
  13. 13.
    Figueroa, P.J., Leite, N.J., Barros, L.R.M.: Background recovering in outdoor image sequences: an example of soccer player segmentation. Image Vis. Comput. 24(4), 363–374 (2006)CrossRefGoogle Scholar
  14. 14.
    Hughes, M.D., Franks, I.M.: Notational Analysis of Sport Second Edition—A Perspective on Improving Coaching. F. N. Spon, London (2004)Google Scholar
  15. 15.
    Kotzbek, G., Kainz, W.: Football games analysis: a new application area for cartographers and GI-Seientists? In: 5th International Conference on Carthography and GIS, pp. 299–306 (2014)Google Scholar
  16. 16.
    Wisbey, B., Montgomery, P.G., Pyne, D.B., Rattray, B.: Quantifying movement demands of AFL football using GPS tracking. J. Sci. Med. Sport. 13(5), 531–536 (2010)Google Scholar
  17. 17.
    Hahm, G-J., Cho. K.: An approach of webcast event clustering for sport video event annotation. In: Proceedings of the International Conference on Information and Communication Technology Convergence (ICTC) 2015, pp. 849–851 (2015)Google Scholar
  18. 18.
    Nakayama, M., Haranaka, M., Sasaki, R., Tabei, R., Kuwabara, T., Hirashima, Y.: Comparative analysis of attack-related game aspects in the Japanese university football league, Japanese J-League, and UEFA champions league, comparative analysis of attack-related game aspects in the Japanese university football league, Japanese J-League. Football Sci. 12, 58–66 (2015)Google Scholar
  19. 19.
    ChyronHego, http://chyronhego.com/. Retrieved 23 Feb. 2016
  20. 20.
    J-League on Demand, http://vod.skyperfectv.co.jp/feature/jleaguelivetop/. Retrieved 23 Feb. 2016
  21. 21.
    Lamantia, J.: Text Clouds: A New Form of Tag Cloud? March 15, (2007). Retrieved 19 Feb. 2016Google Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Department of Management Science and EngineeringAkita Prefectural UniversityYurihonjo, AkitaJapan

Personalised recommendations