Data Analyses of European Soccer
Abstract
Using European soccer data sets, which contain data related to common European soccer leagues, players basic information, and teams’ goals, etc., this paper analyzes the characteristics of European soccer and players, explores data visualization regarding European soccer, and makes predictions of results of matches. Based on Python 3 and some of the packages inside, such as numpy, the author improves the data set to make it clear and user-friendly. Visualizations of data and basic statistics, including Poisson Distribution, are then utilized to determine the results. Finally, this paper analyzes the attacking and defending abilities of different leagues and teams in Europe, ascertains distributions of players’ attributes, and predicts match results by using Poisson distribution and Skellam Distribution. Generally, this paper analyzes data from leagues to matches to players. All these analyses are meaningful for the public to understand the characteristics of European soccer and the world behind the numbers.
References
Data Visualization Beginner’s Guide: A Definition, Examples, and Learning Resources [Internet]. Available from: https://www.tableau.com/lean/articles/data-visualization.
Kids Born in These Months Are More Likely to Become Pro Footballers, Mia Kessler [Internet]. Available from: https://the18.com/soccer-entertainment/youth-soccer-relative-age-effect.
Hay R, Musch J. The relative age effect in soccer: Cross-cultural evidence for a systematic discrimination against children born late in the competition year. Sociology of Sport Journal 1999; 16: 54-64.
Konefa M, Chmura P, Andrzejewski M, et al. Analysis of match performance of full-backs from selected European soccer leagues. Central European Journal of Sport Sciences and Medicine 2015; 11(3): 45–53.
Zhang S. Home advantage in soccer. PIT Journal 2015; 6.
Haight FA. Handbook of the Poisson distribution. New York, NY, USA: John Wiley & Sons; 1967.
Katz A, Hayes A, Suresh T. Poisson distribution [Internet]. Available from: https://brilliant.org/wiki/poisson-distribution/.
Rein R, Memmert D. Big data and tactical analysis in elite soccer: Future challenges and opportunities for sports science. Springerplus 2016; 5(1): 1410.
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