Laszlo Gyarmati


Dr. Laszlo Gyarmati is a Senior Software Engineer at Qatar Computing Research Institute (QCRI) where his research focuses on quantitative analysis of football. Prior to QCRI, Laszlo was an Associate Researcher at Telefonica Research in Barcelona, Spain where he was leading a research project on football analytics. Before that, he carried out research in areas such as network economics, game theoretic analysis of communication networks, online price discrimination, and online social networks. He received his PhD and MSc in Computer Science at the Budapest University of Technology and Economics in 2011 and 2008, respectively. His work on football analytics was covered by BBC, The Economist, New Scientist, and MIT Technology Review, among others.



Quantitative Player Scouting: from Datasets to Insights

Big data in football is starting to gain momentum due to the ever-increasing depth and breadth of available datasets. The data-driven decision-making will have a crucial impact on the entire football operation: from player scouting to injury prevention to in-game strategies. This talk focuses on the former one by highlighting the role of quantitative methods in player scouting. Which player would fit into the passing style of a particular team? What kind of pass patterns is the player involved in? Are the movements of the player in line with the strategy of the team? We use diverse datasets to answer these questions and thus reveal actionable insights through examples.