This machine learning project is designed to predict the potential of football players based on data from the sofifa.com database. Implemented in R for statistical computing and data analysis, the model takes into account various player attributes and performance statistics to predict a player’s future potential.
The project has several potential use cases in the world of football, including scouting and player development. By analyzing player data, the model can identify young players with high potential who may be valuable additions to a team’s squad. This can help teams make more informed decisions when recruiting new players and building their squads.
In addition, the project can be used to evaluate a team’s existing players and identify areas for improvement. By analyzing player data and predicting their future potential, the model can help teams identify which players may need further development and which players are likely to have a significant impact in the future. This can be especially useful for teams that are looking to build a successful long-term strategy.