Exploring the 2018-2019 English Premier League Season Through Data Analysis

Data Analysis

In this post I dive deep into the exciting world of soccer analytic and explore the 2018-2019 season of the English Premier League, one of the most popular and competitive soccer leagues globally. Using Python and various data analysis techniques, I’ve unearthed some fascinating insights about the teams, players, and matches that defined this thrilling season.

Data Overview

My analysis begins with a dataset that encapsulates every game from the 2018-2019 Premier League season. This rich dataset includes a wide array of statistics, from basic information like team names and match dates to more detailed data such as goals scored, fouls committed, and red and yellow cards issued.

Key Insights and Challenges

  1. Exploration Challenge: I start by addressing an intriguing question: Which team committed the most fouls? This exploration not only reveals insights into the playing style of different teams but also opens discussions on sportsmanship and game strategy.
  2. Visualization Challenge: Next, I visualize the trend of drawn matches throughout the season. This analysis provides a unique perspective on the competitiveness of the league and how teams evolved their strategies as the season progressed.
  3. Analytical Challenge: I delve into a more complex analysis by examining the impact of red cards on a team’s likelihood of winning. This segment offers a blend of statistical analysis and soccer tactics, showcasing the delicate balance between aggression and control in the sport.

Scenario Analysis

In a real-world scenario, we assume the role of a data analyst for a local soccer team. The team wants to maximize the playing time for junior players without compromising game outcomes. Our task is to predict the outcome of a game based on halftime results. This comprehensive analysis involves not only crunching numbers but also presenting findings in a way that’s accessible to a non-technical audience, including the team’s coach and management.


This exploration of the 2018-2019 English Premier League season through data not only highlights the power of analytics in sports but also provides valuable insights for teams, coaches, and fans. By combining statistical analysis with my love for soccer, I can uncover trends and strategies that might otherwise go unnoticed.