nazihkalo / fifa19-scouting-analysis

For this project, I am positioning myself as a scouting agency that uses analytics to, among other things, enhance the discovery of talents and help soccer clubs better understand the dynamics (features) that come into play when determining the value, overall and future potential of a player. I will be utilizing the FIFA Player dataset available on Kaggle and apply various Data Mining techniques to achieve this objective.

FIFA19-Scouting-Analysis

For this project, I am positioning myself as a scouting agency that uses analytics to, among other things, enhance the discovery of talents and help soccer clubs better understand the dynamics (features) that come into play when determining the value, overall and future potential of a player. I will be utilizing the FIFA Player dataset available on Kaggle and apply various Data Mining techniques to achieve this objective.

Project Objectives

1. Cluster players based various features to identify different player types for our similarity database.
2. Identify under-valued and over-valued players based on ability measures relative to their value, salary, and/or release clause.
3. Building predictive models for future value and potential of players.

Dataset

• Source: Kaggle
• Description: Detailed attributes for every player registered in the latest edition of FIFA 2019 database.
• Size: 9.1MB (18.2k observations x 89 features)