Football Blog

Football has always been a huge passion of mine, and in my role as a data scientist, I found the perfect way to combine the two through football data analytics. Inspired by Johann Cruyff's famous quote, “Playing football is very simple, but playing simple football is the hardest thing there is,” my goal is to make the complex world of football analytics simple to understand.

In my football data analytics blog, I dive deep into the fascinating world of football statistics, using data from StatsBomb and other free online sources to unravel the complexities of the game. My first post analyzes the extraordinary 2023/2024 Bundesliga season of Bayer Leverkusen, who went unbeaten throughout the campaign. I focus on understanding the patterns in their attacking play, specifically examining their passing sequences and player movement. To answer how a team can go from average to unbeatable in just a few months, I use tools like interactive passing maps and the centrality index to visualize and analyze their strategies.

In my next blog, I explore the concept of Expected Threat (xT), a newer metric in football analytics that measures the attacking threat of a team based on the positioning of the player in possession. Using data from the 2015/2016 Serie A season, I analyze the average xT per team and identify patterns in the attacking play of both top-tier teams and those lower down the table. I use Python and various packages like matplotlib, mplsoccer, numpy, and pandas to perform the analysis and create compelling visualizations that make the data easier to understand and interpret.

For further details on these blogs please check out this link that will take you to my football data blog that I created with quarto in R.