Jesse Davis

Jesse Davis is a professor of computer science at KU Leuven, where he heads the Sports Analytics Lab and applies machine learning to soccer and other sports. He studied at Williams College and the University of Wisconsin–Madison, earning a PhD under David Page in 2007; his 2006 ICML paper with Mark Goadrich linked precision-recall and ROC curves. As a postdoc with Pedro Domingos at the University of Washington, he worked on Markov logic networks. After joining KU Leuven in October 2010, he set up the Sports Analytics Lab in 2014, and a 2019 paper on valuing player actions in soccer won the Best Paper Award in the applied data science track at KDD. He served on the International Olympic Committee's AI working group behind the Olympic AI Agenda, launched in April 2024, and EurAI elected him a Fellow in 2026 for his contributions to machine learning and their application to sports analytics.

Now at: KU Leuven and Runeasi
Badges: Founder
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Timeline

2002–2007

Williams and a Wisconsin PhD

He grows up going to basketball and football games at the University of Wisconsin–Madison and discovers soccer during the 2002 World Cup. After a BA in computer science at Williams College in 2002, he earns an MS in 2005 and a PhD in 2007 at Wisconsin under David Page, working with radiologists to analyze mammography reports.
2006

Precision-recall and ROC curves

In 2006, he and Mark Goadrich publish "The Relationship Between Precision-Recall and ROC Curves" at ICML. The paper shows that a curve dominates in ROC space if and only if it dominates in precision-recall space, and the pair write a Java package that draws both curves and computes the area under them.
2009

Markov logic with Pedro Domingos

As a postdoc with Pedro Domingos at the University of Washington, he works on Markov logic networks, released as the Alchemy system. In 2009, the pair present "Deep Transfer via Second-Order Markov Logic" at ICML, an approach that transfers learned knowledge between molecular biology, social network and Web domains.
2010–2014

KU Leuven and a sports lab

He joins KU Leuven in October 2010 as a member of the Machine Learning group in the Declarative Languages and Artificial Intelligence Lab (DTAI), working on AI and health care with a focus on monitoring athletic performance. In 2014, he founds the Sports Analytics Lab, which applies machine learning to soccer, basketball, volleyball and field hockey.
2019

A KDD best paper on soccer

With Tom Decroos, Lotte Bransen and Jan Van Haaren, he coauthors "Actions Speak Louder Than Goals: Valuing Player Actions in Soccer", which values any player action by its impact on the game outcome. The paper wins the Best Paper Award in the applied data science track at KDD 2019.
April 2024

The Olympic AI Agenda

He serves on the International Olympic Committee's AI working group, which produces the Olympic AI Agenda launched in April 2024. At the launch event, he and Masomah Ali Zada discuss a bike design study and the impact of AI on sports equipment.
2026

A EurAI Fellowship

EurAI elects him a Fellow in 2026 for his contributions to machine learning and their application to sports analytics. The award also recognizes his contributions to the international and European machine learning and AI communities.
As of October 2026

Lab head and Runeasi co-founder

He is a professor of computer science at KU Leuven and head of its Sports Analytics Lab, whose open-source tools include VAEP, a model that assesses the effects of all actions on the ball. He co-founds the spinoff Runeasi, which launches in December 2020, and serves as its scientific advisor and board member.