Project tasks

Football Player Analysis:

• Top 100 players with the highest rating.
• Top 100 players with the highest salaries. Compare with task 1.
• Top 30 goalkeepers with the highest rating.
• Top 30 teams with players having the highest rating.
• Top 30 teams with players having the highest average speed.
• Top leagues with the best dribblers.
• Top 30 teams with players of the highest rating, including 1 goalkeeper, 4 defenders, 4 midfielders, and 2 forwards.

Data Visualization:

• Diagram of player distribution by age and position.
• Diagram of player distribution by rating and position.
• Diagram of nationality distribution by player rating.

Metrics and Rankings:

• Devise a metric to evaluate penalty kick quality.
• Devise a metric to evaluate the quality of goalkeepers saving penalties.
• Identify clubs where penalty takers are significantly better (define "significantly") than penalty-saving goalkeepers, and vice versa.
• Top 10 clubs with the best penalty takers.
• Top 10 clubs with the best goalkeepers.

Business Perspective:

• Describe a dataframe from a business standpoint. What useful information does it contain? What can be explored?

Data Science Tasks:

• Conduct exploratory data analysis (EDA) from a Data Scientist's perspective. Identify dataset problems.
• Perform feature engineering and prepare necessary variables for modeling.
• Conduct feature selection, choose variables essential for model building.
• Select a classification algorithm. Make predictions for player positions based on parameters. Try multiple models and aim for the highest accuracy.