A groundbreaking research initiative, funded by Lero (the Science Foundation Ireland Research Centre for Software) and the IRFU, is harnessing artificial intelligence (AI) to analyse rugby tackles. This cutting-edge project aims to enhance player welfare, optimise performance, and improve coaching strategies.
Led by Professor Anthony Ventresque, Director of the Complex Software Lab at the School of Computer Science and Statistics, Trinity College Dublin, the project seeks to provide players, coaches, and referees with unparalleled insights into tackle techniques. These insights will help identify areas for improvement and ultimately reduce the risk of injury.
"Our research is focused on developing AI that can understand the complexities of rugby tackles," said Professor Ventresque. "By analysing vast amounts of video footage, we can uncover patterns and trends that may be imperceptible to the human eye. This information can be used to create targeted training programs, improving both tackle techniques and player safety."
PhD researchers Will Connors and Caoilfhionn Ní Dheoráin are collaborating with Dr. Kathryn Dane to apply AI in rugby analysis. The project aims to develop advanced AI models capable of automatically detecting and evaluating tackle events, with the potential to revolutionise training techniques.
Key Contributors to the Research
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Professor Anthony Ventresque (Lero & Trinity College Dublin)
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Dr. Kathryn Dane (Lero & Trinity College Dublin)
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Dr. Caithríona Yeomans (Medical Manager, Developmental Game, IRFU)
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Will Connors (Lero, Trinity College Dublin & Leinster Rugby)
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Caoilfhionn Ní Dheoráin (Lero & Trinity College Dublin)
Will Connors, who has represented Ireland at senior, U20, and sevens levels, expressed his enthusiasm for the project. "As a rugby player with a background in computer science, I’m fascinated by AI’s potential to analyse and optimise tackle technique. This research can help players at all levels refine their tackling skills and contribute to a more exciting and dynamic game."
Dr. Kathryn Dane, an international rugby player, emphasised the crucial link between tackle technique and player safety. "By using AI to analyse thousands of tackles, we can pinpoint specific areas where technique improvements can enhance both performance and welfare."
Caoilfhionn Ní Dheoráin, a computer scientist, highlighted the challenge of applying machine learning at scale to domestic club and school-level rugby. "This project presents an exciting opportunity to push the boundaries of AI and deepen our understanding of this complex, fast-paced sport."
Dr. Caithríona Yeomans, the IRFU’s Medical Manager, emphasised the research’s impact on player welfare. "By understanding the mechanics of tackles and identifying areas for improvement, we can help players develop safer, more effective techniques. Collaborating with Lero and the Complex Software Lab at Trinity College Dublin is invaluable in making rugby safer for all."
Kathryn Dane (Research Ireland Lero Centre & Trinity College Dublin), Dr Caithríona Yeomans (Medical Manager Developmental Game, IRFU), Will Connors (Lero, Trinity College Dublin & Leinster Rugby), Prof Anthony Ventresque (Lero & Trinity College Dublin), Caoilfhionn Ní Dheoráin (Lero & Trinity College Dublin)
This initiative aligns with the IRFU’s decision to lower the tackle height in the domestic game. The insights from AI-driven video analysis will help assess the impact of this change on player safety and overall gameplay.
Colm Finnegan, the IRFU’s National Rugby Development Manager and Tackle Trial project lead, affirmed the importance of this collaboration. "We are excited to work with Lero on this pioneering research. Our goal is to make rugby as safe and enjoyable as possible, and AI-driven analysis is a key step toward achieving that."
One of the team’s recent studies, ‘Frisbees and Dogs: Domain Adaptation for Object Detection with Limited Labels in Rugby Data’, explores how AI can detect critical elements in rugby footage, even with limited training data. This breakthrough significantly enhances AI’s ability to analyze rugby gameplay.
Another study, ‘Are We Tackle Ready? Cross-Sectional Video Analysis of Match Tackle Characteristics in Elite Women's Rugby Union’, examines tackle techniques in women’s rugby. The findings indicate that many tackles do not fully align with World Rugby’s ‘Tackle Ready’ guidelines, highlighting the need for targeted interventions to improve performance and reduce injury risks.
The project’s findings are being presented at prestigious international conferences and published in leading academic journals. As the research team continues refining their AI models, they plan to share their insights with coaches and players at all levels, driving forward innovation in rugby training and safety.