Analysis of Factor of Scoring of Japanese Professional Football League

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10904)


In “The Japan Professional Football League (J League)”, the number of customers is increasing every year since 2011. The Japanese football team participates in the Russian World Cup in 2018. Therefore, J league market is expected to become more active. In this research, we analyze the score trend of the league with the aim of proposing tactics and training for the J League team. In each piece of data, position information obtained by dividing a field into an X-axis and a Y-axis are given. Therefore, in the data to use, this research pay attention to the data on the play involved in the score and the position where the play started. In this study, first, cluster analysis is performed to classify the start position of play involved in scores. After that, factor analysis and covariance structure analysis are carried out, and the play highly relevant to the score is discovered. Before analysis, data cleaning is carried out so that similar variables did not exhibit a strong correlation. First, the start position of the play involved in scores is classified by cluster analysis. From the score data, play related to the score was extracted and classified. After this, good results have been obtained with clusters showing mainly attacks from their own field. Therefore, in Japanese professional football, it can be predicted that there is some tendency in score from own field. Next, factor analysis/covariance structure analysis is performed on each cluster, and tactics related to scores are discovered. Factor analysis was conducted and latent variables related to the score were extracted. Define that latent variable as a score-related tactic and analyze the relationship between different tactics using covariance structure analysis. Those with low relevance are considered independent tactics. From the analysis results, in J League found that “side attack” and “pass to empty space” are strongly related to the score. Also, on the left side of the field, the score tendency using “dribbling” was weak. Japanese players, this can be expected to be related to having few players using left foot more than the right. Therefore, it is possible to propose “training of side attacker with excellent physical strength and speed” and “counterattack/strengthen side attack”. Furthermore, we found out that it is a task to put emphasis on cultivating left-handed players. This analysis focused on the attack from the own field. The future task is to analyze the attack pattern from the enemy field and judge whether it is haste from the length of attack time.


Sports marketing Data visualization Cluster analysis Factor analysis Covariance structure analysis 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Information and Telecommunication Engineering, Department of Management System EngineeringTokai UniversityTokyoJapan

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