April 16, 11:00am EST
Zoom link: https://williams.zoom.us/j/92779537290?pwd=ejNmeEN3Q1VHa2lVQ0dhZThxYTA4dz09
AI-Based Approaches for Analyzing the Performance of Professional Soccer Players
Currently, it is possible to collect massive amounts of data about sports matches and athletes. Consequently, there has been an explosion of interest in using AI techniques to analyze this data. In the context of professional soccer, most existing approaches employ AI to assess a player’s technical and physical performances independent of the game context. This talk will discuss how to quantify a player’s performance during a match and how a player’s performance may be affected during high-mental pressure game situations. To do so, we use AI in two different ways. First, our framework values actions by training a model to assess their expected impact on a match’s scoreline. Second, our mental pressure model uses AI techniques to assign a pressure level to each minute of match by considering both the match context as well as the current game situation. Throughout the talk, I will show provide illustrative use cases about how the insights our models provide could be used by soccer clubs.
Jesse Davis ’02 is a professor (hoogleraar) at the Department of Computer Science of KU Leuven, and a member of the Declarative Languages and Artificial Intelligence division. Prior to joining the KU Leuven faculty in October 2010, Jesse received a bachelor’s degree from Williams College (2002), a PhD from the University of Wisconsin (2007), and completed a post-doc at the University of Washington (2007-2010). His research focuses on developing novel artificial intelligence, data science, machine learning, and data mining techniques, with a particular emphasis on analyzing structured data. Jesse’s passions lie in using these techniques to make sense of lifestyle data, address problems in (elite) athlete monitoring and detecting anomalies. Jesse’s work is regularly featured in the international news media. His work received the Best Paper Award in the Applied Data Science track at KDD 2019.
Jesse is very active in entrepreneurship. He has co-founder and serves on the board of directors for two companies: Activ84Health and runeasi. Activ84Health is an awarding winning start-up that develops innovative technology to motivate nursing home residents to be physically active and improve their quality of life. The company offers an interactive app for nursing home residents that brings the joy and health benefits associated with cycling outdoors to a safe, indoor environment. runeasi is a wearable that interacts with an AI-based app to provide real-time biomechanical feedback to runners, which can be used in rehabilitation or to aid training. Our product has been used by past and prospective Olympic runners as well as professional football players.
For more information, see: https://dtai.cs.kuleuven.be/sports/
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