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Distinguishing Between Roles of Football Players in Play-by-Play Match Event Data

  • Bart AalbersEmail author
  • Jan Van HaarenEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11330)

Abstract

Over the last few decades, the player recruitment process in professional football has evolved into a multi-billion industry and has thus become of vital importance. To gain insights into the general level of their candidate reinforcements, many professional football clubs have access to extensive video footage and advanced statistics. However, the question whether a given player would fit the team’s playing style often still remains unanswered. In this paper, we aim to bridge that gap by proposing a set of 21 player roles and introducing a method for automatically identifying the most applicable roles for each player from play-by-play event data collected during matches.

Keywords

Football analytics Player recruitment Player roles 

References

  1. 1.
    Arsenal.com: Jack and Xhaka: Strengths and Styles (2018). https://www.arsenal.com/news/news-archive/20161125/jack-and-xhaka-strengths-and-styles. Accessed 3 Aug 2018
  2. 2.
    Barnard, M., Dwyer, M., Wilson, J., Winn, C.: Annual Review of Football Finance 2018 (2018). https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/sports-business-group/deloitte-uk-sbg-annual-review-of-football-finance-2018.PDF. Accessed 3 Aug 2018
  3. 3.
    Bialkowski, A., Lucey, P., Carr, P., Yue, Y., Matthews, I.: Win at home and draw away: automatic formation analysis highlighting the differences in home and away team behaviors. In: Proceedings of 8th Annual MIT Sloan Sports Analytics Conference. Citeseer (2014)Google Scholar
  4. 4.
    Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. JAIR (J. Artif. Intell. Res.) 16, 321–357 (2002)CrossRefGoogle Scholar
  5. 5.
    Cox, M.: World Cup Favourites Choosing Defensive-Minded Midfielders over Deep-Lying Playmakers (2018). http://www.espn.co.uk/football/fifa-world-cup/4/blog/post/3520743. Accessed 3 Aug 2018
  6. 6.
    Goal.com: How Lionel Messi and Andres Iniesta Could Have Ended up in Glasgow (2012). http://www.goal.com/en-gb/news/3277/la-liga/2012/10/23/3471081/how-lionel-messi-and-andres-iniesta-could-have-ended-up-in
  7. 7.
    Mazurek, J.: Which football player bears most resemblance to Messi? A statistical analysis. arXiv preprint arXiv:1802.00967 (2018)
  8. 8.
    Pappalardo, L., Cintia, P., Ferragina, P., Pedreschi, D., Giannotti, F.: PlayeRank: multi-dimensional and role-aware rating of soccer player performance. arXiv preprint arXiv:1802.04987 (2018)
  9. 9.
    Peña, J.L., Navarro, R.S.: Who can replace Xavi? A passing motif analysis of football players. arXiv preprint arXiv:1506.07768 (2015)
  10. 10.
    Poli, R., Besson, R., Ravenel, L.: The CIES Football Observatory 2017/18 season (2018). http://www.football-observatory.com/IMG/pdf/cies_football_analytics_2018.pdf. Accessed 3 Aug 2018
  11. 11.
    Sullivan, J.: Beautiful and Mathematical: Football as a Numbers Game (2016). https://www.bbc.com/news/science-environment-37327939
  12. 12.
    Thompson, M.: Four Types of Forward in the Champions League Final (2018). https://www.footballwhispers.com/blog/four-types-of-forward-in-the-champions-league-final. Accessed 3 Aug 2018

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.SciSportsEnschedeNetherlands

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