Want to Learn Football Analytics?
Here are some resources and tips to help you dive deeper.
Introduction
Football has developed rapidly. Tech application in that sport is also one of the developing parts. Data science is one of the technologies that they use. It has impacted lots of domains, and football analytics is not an exception. According to BBC, the data scientist is the most successful football signing at the moment [1].
We can see several success stories of applying football analytics, like Liverpool using the physical model to determine optimal space to reduce the opponent’s movement. This model led them to win their 6th UEFA Champions League in 2019 and their first Premier League title after almost 32 years of waiting in 2020 [2].
Brentford also has a successful story on applying data science. They used the Moneyball technique to pick valuable players with a limited budget. This technique helped them reach the highest tier in English football after almost 74 years of playing in lower tier English football league [3].
I believe that you want to deep dive into football analytics but don’t know where to start. This article will show you several resources to help you learn about this domain. Without further ado, let’s get started!
