Sports Economics with Steve Bickley - ONLINE ONLY
Date
From: Thursday September 10, 2026, 12:00 pm
To: Thursday September 10, 2026, 1:00 pm
From AI-generated forecasts to elite football matches, new data-driven approaches are transforming how we study human judgement and behaviour.
This seminar presents preliminary findings from two current research projects using sport as a rich empirical setting for studying decision-making, creativity and adaptation in complex environments.
The first project examines whether large language model (LLM)-based synthetic expert panels can complement traditional corporate foresight. Replicating two Delphi studies of the future of top-tier sports media consumption and production, the study compares human experts with AI agents across assessments of probability, desirability and impact, exploring where AI-generated forecasts align with human judgement, where they diverge, and whether greater consistency represents useful noise reduction or potentially problematic over-convergence.
The second project uses more than 3.7 million passes from over 4,000 professional football matches across ten European leagues to develop data-driven measures of pass novelty and creativity. Using detailed Impect GmBH event and pressure data, the study explores how creative behaviour changes under pressure, across different stages of a match and depending on the competitive situation. Together, the projects illustrate how AI and increasingly granular behavioural data can provide new ways to study judgement, uncertainty, creativity and adaptation in complex systems.
Dr Steve Bickley is a behavioural economist, computational social scientist and engineer working at the intersection of artificial intelligence, complexity science and public policy. He is currently a Research Fellow at the ARC Industrial Transformation Training Centre for Behavioural Insights for Technology Adoption (ARC BITA) in the School of Economics and Finance at Queensland University of Technology (QUT). His research examines how interactions between people, organisations and intelligent systems shape decision-making, learning, creativity, coordination and adaptation. Drawing on behavioural and experimental economics, artificial intelligence, agent-based simulation and large-scale real-world data, his work develops computational and empirical approaches for understanding complex social, economic and technological systems. He also works across research translation, developing AI-enabled research infrastructure and collaborating with academic, industry and government partners to translate research into practical tools and applications.
Click here to Book Online