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Does sacking a coach really help? Evidence from a Difference-in-Differences approach

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This project looks to evaluate if football clubs should or should not change their coach in order to improve their performance in the national league. For this analysis I selected, three of the most important European football leagues, La Liga (Spain), Serie A (Italy) and Premier League (England). The data used in this project was taken from the transfermarkt website, a large football platform. The data period is from season 2005-06 to season 2019-20 and has information about individual games results and squad value by player. The steps before the analysis were a data cleaning and consolidation of the information, creation of new features as a performance measure and selection of cases of interest for this analysis based on club and coach profile. Numeric variables were standardized to be on the same scale and make different seasons comparable. A K-means was applied to identify clubs according to their investments which has a proportional correlation with performance. Finally, a difference in differences analysis was applied to evaluate if a club would obtain a performance gain if they decided to sack their coach between game twelve and twenty-six of the season after a poor performance in consideration to squad price. As a general conclusion, it is possible to consider that on average the clubs in the treatment group and comparison group recover their performance after a period of underperforming, but the recovery of the clubs that sack their coach is lower compared with the clubs that keep them.

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Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science

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Difference in Differences Statistics Football Data Scraping Clustering

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