Luca Pappalardo and Paolo Cintia’s step-by-step guide to exploring the Wyscout Event data – Video 1 and Video 2. See their paper A public data set of Spatio-temporal match events in soccer competitions. To learn more about the different types of data available, such as Event and Tracking data, please see the “Where can I get data?” section of Devin Pleuler’s soccer_analytics_handbook.
“Some of the owners have different purposes when they buy clubs but for us we want to invest in the club, grow it and make money. Finding the right talent through data helps us to do that.” Experts say one of the challenges is time, as the data needs to be analyzed quickly with matches taking place every few days. “However, most clubs prefer to remain secretive about what they do in terms of data.”
While it is important to know about ‘on-the-ball’ data, the future of non-gamstop football sportsbooks may well lie elsewhere. I caught up with Raúl Peláez Blanco, Head of Sports Technology Innovation Analysis at FC Barcelona, and asked him about the data the team currently uses. Analytics FC is a football analytics specialist with proven experience in delivering data-driven solutions.
We use the data to improve the decision-making of football professionals after processing the more than 2,000 events generated by each match. In our four years of industry experience in football analytics, we have worked with around 25 clubs in 8 different countries. Oscar Ugaz – When it comes to game tactics, player performance, injury prevention, etc., there is indeed a more relevant level of innovation in regard to data-centric solutions. Companies like OPTA and others are creating very interesting and groundbreaking solutions in those areas. But my perception is that football clubs, at least in Europe, are not making extensive use of data in the business field.
Predicting goal probabilities for possessions in football by Nils Mackay. Understand – a Python web scraper by Amos Bastian to scrape Understat shooting and player metadata. Scrape-FBref-data by Parth Athale, ich in turn was written using code from Christopher Martin’s repository, however, this code hasn’t worked since around February 2021. The following open-source Python libraries listed below are some of the most commonly used in Data Science that features in the notebooks in this repository.