Skip to content

annus3/Goal-Score-Forecasting

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

61 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Data Analysis of Premier League and La Liga Goal Score Forecasting

Project Overview

The project centers on analyzing player statistics in two of Europe's top football leagues, the Premier League and La Liga. By leveraging machine learning techniques, this endeavor aims to uncover key performance indicators influencing goal-scoring patterns from various player positions. Through the examination of datasets, 'Premier League Player Statistics' and 'La Liga Player Stats,' encompassing player attributes like goals scored, assists, passes completed, shots on target, player positions, and match details, the goal is to develop predictive models. These models will assist in understanding the determinants of successful goal scoring in different positions across both leagues. Ultimately, this analysis seeks to provide insights for optimizing team strategies and player performance, fostering a deeper understanding of impactful metrics in the world of football.

Datasets

Datasource1: Premier League Player Statistics

Datasource2: La Liga Player Stats

This combined dataset compiles player statistics from both the Premier League and La Liga. It includes detailed information like player age, goals scored, assists, passes completed, shots on target, player positions,and performance metrics across various seasons. It serves as a valuable resource for in-depth analysis, providing insights into player capabilities, team strategies, and positional performance assessment

Methodology

In this project we employed Machine learning algorithms and statistical analysis to analyze the datasets and draw insights into the elements that influences goal scoring forcasting in both the leagues.

Project report

Following link provide you with a detailed report about entire analysis and modeling process: Project Report

Issues

If you encounter any issues or have any suggestions for improvement, please create a new issue on Github. I appreciate your feedback and and contributions!

About

Template repository for the Methods of Advanced Data Engineering course at FAU

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 99.4%
  • Other 0.6%