I chose to do this project on the World Cup as we were in the midst of the defining matches of the 2018 World Cup. The constant viewing of matches at work, at home, on Bart had me curious about the players and general quality of the teams. I mainly used Plotly and Seaborn in Python to generate visualizations related to the players and countries that participated.
While I didn't know much about the sport I did learn that the players are diverse in their physical attributes, allowing greater participation. I also learned that Europe tends to have the best clubs and have players from all over the world gravitating to them. The best and worst clubs ended up having players mostly from their own countries (the worst might be due to lack of other opportunities).
As I mentioned, there is some diversity in the physical attributes of the players, for example in their height. Goalies and Defenders being the tallest make senese as this physical trait can help them be effective at their role - stopping the ball from going in the goal and winning the ball in the air.Forwards and Midfielders can be shorter as agility and accuracy are more important to their role than being tall.In general, heights are very diverse, can explain what makes soccer so accessible to the world, compared to the average height in the NBA (6ft 7in).
Generally, players tend to gravitate to the major clubs in Europe highlighted by the boxes(England, France, Germany, Italy, Spain). The listed European leagues have the most competative teams and money availible for premier players or they play in their home country. The top 3 loyal countries are England (100% loyalty rate), Russia and Saudi Arabia.
I'd like to compare the number of fans and the demographics of the fans to the performance of teams. Especially looking at how diverse the fan base is and whether most of the fans are from the team's country or from other countries.
https://www.kaggle.com/djamshed/fifa-world-cup-2018-players
https://www.kaggle.com/abecklas/fifa-world-cup#WorldCups.csv