Recent developments show that artificial intelligence and data science are becoming central to athlete development.
- Teams are now using AI models to identify young talent and predict performance.
- Advanced analytics and “digital twin” technology are helping optimize training and scouting.
👉 Insight: The future of sports science is technology-driven, blending biomechanics, data, and performance analysis.
Ineos Grenadiers has partnered with Swansea University to help create new ways of identifying cycling talent, it was announced this week.
The British WorldTour team will work with the Welsh university’s Applied Sport, Technology, Exercise and Medicine (A-STEM) Research Centre to “develop cutting-edge data and AI solutions that could revolutionize how emerging talent is identified in professional cycling,” according to the press release.
A joint project has begun, called Towards the development of digital twins for efficient talent identification in professional cycling. This means there will be a dedicated PhD student working with Ineos to explore how “data-informed systems can help teams identify emerging and currently overlooked talent earlier and more effectively.”
The project aims to combine the team’s internal performance metrics with public race data to monitor junior riders; an automated system will be created which flag performances, and allow the squad to keep track of developing talent.
If it works, Ineos will hope to catch the next generational talent at a younger age and sign them, rather than seem them go to a rival team or not make it to the WorldTour at all.
Ineos Grenadiers’ performance director, Dr Scott Drawer, said: “The emerging fields of data science and AI are the next frontier for the sport. These projects form part of a large portfolio of work with academia and industry to accelerate our understanding and application to our sport.
“My personal experience of working with Swansea has always been positive and delivered direct impact to the way we work.”
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