Soccer Analytics Using Machine Learning

Ever got the feeling that 90 mins of an intense game feel less, and you're left wanting more? Well, look no further! This project  provides comprehensive and insightful analysis of soccer data for Europe's top competitions. It is a one-stop-shop for all things related to soccer analytics and statistics. The goal is to give soccer fans, coaches, and analysts access to data-driven insights that can enhance their understanding and appreciation of the sport. Whether it's understanding tactics, evaluating team performance, or comparing leagues, this project covers it all. 

The basic idea is to collect huge chunks of relevant historical data, analyze the same, from a more statistical point of view, in order to gain insights which effectively can provide a competitive edge to a team or individual. Machine learning (ML) and data science are being increasingly used in soccer analytics due to their ability to analyze large and complex data sets, extract meaningful insights, and provide predictive models that can improve decision-making in soccer. By analyzing data from various sources, such as player performance data, match statistics, and social media data, ML and data science can help coaches, scouts, and analysts gain a deeper understanding of player performance, team dynamics, and match strategies.

Click here to view the website created for this project, which elaborately explainsthe methods use, findings and conclusions drawn