Player health surveillance outputs have largely been shaped around what matters to researchers, but what is informative to a researcher is not necessarily the most relevant or interpretable information for the people making day-to-day decisions. We are looking for systematic research into the differing needs, preferences, and decision-making contexts of the groups who use surveillance in practice, primarily team medical and performance staff, coaches, and administrators, and how outputs can be tailored to each of these groups. This should clarify the specific information required by each group, how it should be delivered, and how often it should be provided to support decisions.

The goal is to move beyond describing what has happened toward credibly anticipating what is likely to happen. We are therefore looking for predictive modelling of surveillance outcomes using historical data, for example Bayesian methods (or equivalent approaches) that quantify uncertainty and can be updated as new data accrues. 

Football equipment, apparel and playing environments can directly influence performance, safety and inclusivity. This topic invites research that develops and validates evidence-based innovations with measurable outcomes in real-world football contexts. We are particularly interested in interventions that improve player performance or safety, address the needs of different player populations, or develop new methodologies for evaluating equipment, apparel and infrastructure.

Advances in AI, tracking and video technologies create new opportunities to identify and review critical moments in football more effectively. This topic invites research into automated incident detection and real-time decision support, including officiating, medical and performance-related events. Research should aim to improve the speed, accuracy and consistency of decision-making while developing solutions that are scalable and accessible across different levels of football.

Advanced football analysis often relies on specialist expertise, infrastructure and access to high-quality data. This topic invites research exploring how AI can make football intelligence more accessible across different levels of the game. We are particularly interested in scalable approaches that generate actionable insights for performance analysis, coaching, talent identification and tactical understanding, or help quantify and explain player, team and competition behaviours.