Statistical analysis for the influencing factors on average score of players in football matches

Abstract

In recent years, by using of data science to explore patterns and knowledge in football games has become a hot research topic. However, most studies still use black-box machine learning methods to classify and predict the data generally, and the analysis of its specific influencing factors is not comprehensive. Even if the influence of each variable on the game results is considered, it is mainly analyzed from the perspective of the strength of their respective influences, and the discussion of the interaction between them is still insufficient. Therefore, this paper uses 126,947 football match data to explore which factors have a significant impact on football scores and how they interact by combining multivariate analysis of variance and descriptive statistics. The experimental results show that height and player position are the main factors affecting the average score of the game. The main effect and interaction effect between them are tested and displayed for better decisions.