Tactical Analysis Through Objective Data in Football

Akira Yamanaka; Hiroshi Otsuka; Tatsuya Deguchi; Ken Okihara; Dota Otsuka; Shinya Uchida; Jorge Diaz-Cidoncha Garcia; Selina Khoo; David Stroud; Masahiro Sugiyama

doi:10.18282/iss.v2i1.257

Akira Yamanaka Ehime University
Hiroshi Otsuka Ehime University
Tatsuya Deguchi Hiroshima University
Ken Okihara Hiroshima University
Dota Otsuka Nagoya University of Economics
Shinya Uchida Gifu University
Jorge Diaz-Cidoncha Garcia Polytechnic University of Madrid Fédération Internationale de Football Association (FIFA)
Selina Khoo University of Malaya
David Stroud Lake Erie College
Masahiro Sugiyama University of Malaya

Article ID: 257

2041 Views, 133 PDF Downloads

DOI: https://doi.org/10.18282/iss.v2i1.257

Keywords: Football Tactics, Numerical Data, Mathematical Model, Team Sports

Abstract

Tactical analysis in football has rarely been conducted using a mathematical model with numerical data (although tactical analysis through objective data has been used more often). Therefore, this study establishes principles for tactical analysis in team sports using numerical data, through a mathematical model based on the location of the players and the ball. A competitive match between Sanfrecce Hiroshima (home) and Ehime FC (away) in the third round of the Japanese Emperor’s Cup 2011 was filmed and used for the match analysis. Observations were made by a team analyst as well as extracted from official match records. The main procedure in the research flow was to establish a mathematical offence/defence model based on tactical concepts in football, which was applied for the location of players, which, in turn, was quantified from video images in order to categorise a team’s tactical performance (in relation to attacking or defending). Furthermore, the authors focused on attacking categories and identified different types of passes during a specific period, as well as comparing these findings with an actual match video. The results obtained from the numerical data derived from applying the offence/defence model led to the same overview as the tactical analysis produced by a team analyst. In addition, the results when categorising types of passes (as extracted through the mathematical model) again mirrored those retrieved from an actual match video. This leads to the conclusion that the offence/defence model could provide relevant insight into types of attacks. The data revealed that football tactical analysis can be successfully performed using a numerical model, which might possibly enable automatic tactical analysis of football games without a match analyst.

Author Biography

Jorge Diaz-Cidoncha Garcia, Polytechnic University of Madrid Fédération Internationale de Football Association (FIFA)

Jorge Diaz-Cidoncha has played and coached for diverse teams in Spain, Australia and Switzerland. He holds a Bachelor's degree in Sport Sciences, 2 Master's degrees in Sport Sciences/Sport Management and a PhD in Sport Sciences, as well as a UEFA PRO license and a RFEF Technical Director license. He supports diverse international organizations such as IOC and UN, currently works as FIFA Youth Football and Grassroots Manager and also support Competition Management of the FIFA World Cup on a regular basis. The focus of his work is mainly soccer development, small sided games and technical and tactical youth training.

References

Stiehler G, Konzag I, Döbler H. Sportspiele: Theorie und Methodik der Sportspiele Basketball, Fußball, Handball, Volleyball. Berlin: Sportverlag; 1988.

Kern J. Taktik im Sport. Schorndorf: Hofmann; 1989.

Soma R. Information utilisation in sports: From Olympics to health management. Science & Technology Trends 2015; 148(1-2): 24-6.

Takai Y. The scientific research on tactical and performance analysis in football and its application. NSCA Japan 2018; 25(9): 4-12.

Fujiiwa H. Analysis of goal trends in football games. Journal of Economics, Management & Information Science 2012; 13(1): 177-86.

Naritsuka T. Mathematics of match-type team sports in football games. Communications of the Operations Re-search Society of Japan 2018; 63(10): 615-20.

Mizukami H, Izumi H, Shirahata K, et al. The research of factors using tracking data to determine victory or defeat of a professional football team, Vegalta Sendai. Sendai University Research Bulletins 2016; 47(2): 49-56.

Sasaki H. Data utilisation and next-generation technology in sports. Mukogawa Journal of Health and Exercise Science 2016; 6(1): 39-46.

Koutake N. System design for improvement of sports value and data application. Journal of the Operations Re-search Society of Japan 2018; 63(10): 603-7.

Kakemizu T, Ohashi J, Akagi S. Football: Interesting Science – Rational Practice Based on Scientific Analysis, Tokyo: Tokyo Denki University Press; 1996.

Kato K. Data analysis and improving a team in football. Communication Society Magazine 2016; 10(1): 29-34.

Tamura Y and Sakaori F. About ‘‘special edition: a new challenge in the science of sports statistics’’. Proceedings of the Institute of Statistical Mathematics 2017; 65(2): 183-4.

Yamanaka A and Otsuka H. Evaluation of the offense/defence model in football using the dominant area diagram with time limitation. Proceedings of the 77th Japan Annual Convention; 2015 Mar 17-19; Kyoto, Japan; 2015. p. 407-8.

Otsuka H and Yamanaka A. Application of the dominant area diagram with time limitation to the extraction of game situations around the ball in football. Proceedings of the 77th National Journal of the Information Pro-cessing Society of Japan; 2014 Mar 11-13; Tokyo, Japan; 2014. p. 281-2.

Takii T. Tactics of World Football. Tokyo: Baseball Magazine Sha Co., Ltd.; 1995.

Tawa K. Coaching in Football (Modern Sports Coaching Complete Works). Tokyo: Taishukan Publishing Co., Ltd.; 1974.

Wade A and Asami T. England – Football Curriculum. Tokyo: Baseball Magazine Sha Co., Ltd.; 1973.

Worthington E. Teaching Soccer Skill. London: A & C Black Publishers Ltd.; 1980.

Ohasi J. The speed level, frequency and interval of a player’s transition in a football game. Proceedings of the 43rd Congress of the Japanese Society of Physical Education; 1992 Dec 22-23; Tokyo, Japan; 1992. p. 733.

J.League data site. (2019). Player data. Retrieved from https://data.j-league.or.jp/SFIX03/

Fédération Internationale de Football Association. (2018). Technical Report for the 2018 FIFA World Cup Russia. Retrieved from https://img.fifa.com/image/upload/xgwsmrcals5qku0nmrge.pdf

Japan Football Association official record. (2011). The 91st Emperor’s Cup third round. Retrieved from http://www.jfa.or.jp/match/matches/2012/0101tennouhai/schedule_result/pdf/m67.pdf

Sanfrecce Hiroshima FC. (2011). Latest match record. Retrieved from https://www.sanfrecce.co.jp/info/result/?n=330

J.League data site. (2011). Rankings: aggregate results – J1 division teams. Retrieved from https://data.j-league.or.jp/SFRT08/search?competitionYearEx=2011&competitionIdEx=1&selectedCompetitionName=%EF%BC%AA%E3%83%AA%E3%83%BC%E3%82%B0%E3%80%80%E3%83%87%E3%82%A3%E3%83%93%E3%82%B8%E3%83%A7%E3%83%B3%EF%BC%91&selectedCompetitionYear=2011%E5%B9%B4&competitionYear=2011&competitionId=1

J.League Data Site. (2011). Rankings: aggregate results – J2 division teams. Retrieved from https://data.j-league.or.jp/SFRT08/search?competitionYearEx=2011&competitionIdEx=2&selectedCompetitionName=%EF%BC%AA%E3%83%AA%E3%83%BC%E3%82%B0%E3%80%80%E3%83%87%E3%82%A3%E3%83%93%E3%82%B8%E3%83%A7%E3%83%B3%EF%BC%92&selectedCompetitionYear=2011%E5%B9%B4&competitionYear=2011&competitionId=2

Sato Y, Yamanaka A, Otsuka H. Pass extraction from an offense/defence model in football. Forum on Information Technology 2015; 14(1): 145-8.

Otsuka H and Yamanaka A. Evaluation of the pass extraction from an offense/defence model in football. The Na-tional Journal of the Information Processing Society of Japan 2016; 78(1): 281-2.