EUROPEAN SOCCCER DATABASE

In this exercise we will analyze a database on European football matches to know the data in our possession and extrapolate interesting information

The tools used

Data Analysis: SQL on Google Bigquery

Supporting graphs: Python on Google Colaboratory

Presentation: Google Slides

The composition of database

match;

leagues;

team;

player.

First, the size of the `match` dataset was analyzed to verify how many matches and how many leagues were present.

Subsequently the time range and how many games were played per season.

By analyzing the number of matches per league, an anomalous case was discovered regarding the Belgium Jupiler League.

The total number of matches played for each month was then subsequently analysed.

An in-depth analysis was also done regarding the statistics and goals scored in each season and for each league.

The players were then analysed. The weight was converted into kg. A jointplot shows the strong correlation between weight and height. This indicates that our athletes are all quite fit. Only 7.8% of them do not have an optimal BMI.

Finally, the highest score of the last season was analyzed, the team that was the best for the most seasons and a table was created with the 10 teams that scored the most goals.

You can find in this repository all the material to repeat the exercise yourself.

Thanks for your attention