The concept of a digital twin has evolved from an industrial engineering tool into one of the most promising innovations in healthcare and sports science.
A digital twin is a virtual replica of a physical object, system or even a human being. By combining real-world data with advanced modelling and artificial intelligence, digital twins can simulate future scenarios, predict outcomes and identify potential risks before they occur.
The technology is already widely used in industries such as aviation, automotive manufacturing, construction and civil engineering, where it helps predict failures, optimise maintenance and improve operational safety without exposing people or infrastructure to real-world risks.
Now, the same concept is transforming medicine and elite sports.
FC Barcelona’s next innovation frontier
FC Barcelona has long been at the forefront of digital innovation. One of its most notable projects has been the development of a digital twin of Camp Nou, created in collaboration with the Barcelona Supercomputing Center. The virtual stadium allows researchers and managers to simulate crowd movements and test different scenarios on match days.
The technology provides valuable insights for improving safety, designing emergency response plans and optimising fan experiences. It also enables planners to better understand how supporters move through the stadium, helping prevent accidents and improve operational efficiency.
FC Barcelona has taken the concept a step further.
Through a collaboration between Barça Innovation Hub and the health technology company Made of Genes, the club has developed digital twins for individual athletes. These virtual models are built using molecular data, sports performance metrics and artificial intelligence, with the goal of preventing injuries, maximising performance and extending sporting longevity.
Digital twins are not entirely new to medicine.
Researchers and clinicians are increasingly using digital replicas of organs and biological systems to support clinical decision-making. In the United States, digital heart models are helping physicians plan complex procedures with greater precision and effectiveness.
For patients with chronic diseases, digital twins can combine longitudinal data—including medication responses, lifestyle habits and physiological measurements—to predict disease progression and support earlier interventions. Such approaches are being explored for conditions including diabetes and heart failure, where personalised monitoring can improve outcomes and reduce complications.
The same predictive principles are now being adapted for professional athletes.
The objective remains consistent with Barça’s long-standing vision of 360-degree sports medicine: anticipating problems before they become injuries.
By identifying early signs of fatigue, medical teams can intervene through training adjustments, nutrition strategies, sleep optimisation and lifestyle modifications tailored to each athlete. The approach seeks to personalise care and performance management rather than applying the same protocols to every player.
The technological foundation of the initiative is provided by Genomcore, a company owned by Barça Innovation Hub, together with its spin-off Made of Genes.
Genomcore integrates vast quantities of biomedical and performance-related information into a secure, unified platform. Made of Genes then applies artificial intelligence and systems biology to transform that information into actionable insights.
According to Dr Gil Rodas of Barça Innovation Hub, the digital twin functions as an athlete’s avatar — a comprehensive profile capable of integrating thousands of data points.
To build these models, researchers analyse genetics, metabolomics, proteomics, body composition, nutritional habits, sleep patterns and daily physical workload. Every element contributes to a more complete understanding of the athlete’s current condition and future risk profile.
Turning big data into smart data
At the core of the initiative is the challenge of translating enormous quantities of information into meaningful decisions.
Laura Isus, Director of Made of Genes, explains that Barcelona operates a unified biomedical platform capable of integrating multiple layers of information, including genetics, physiological measurements, external and internal training loads and contextual factors affecting athlete health.
Artificial intelligence serves as the intelligence layer that connects these datasets.
The system generates alerts, predictive rules and simulations that can be integrated into daily clinical and performance workflows. While injury prevention remains the primary objective, the same technology can also help optimise nutrition, recovery and long-term performance management.
The ultimate goal is to personalise training loads, detect risks earlier and help athletes maintain peak performance for longer periods.
Made of Genes provides the intelligence that transforms big data into smart data. By combining genetics with other “omics” layers such as metabolomics, as well as training loads, sleep, nutrition and lifestyle factors, the system generates early warning signals and actionable hypotheses that are validated together with the club’s medical and performance teams.
Understanding injury risk
One of the most promising applications of digital twins is injury prediction.
Research conducted by FC Barcelona has already demonstrated that some athletes may have genetic predispositions to specific types of injuries. However, genetics represents only one part of the equation.
Environmental factors, training intensity, accumulated workload and metabolic status also play critical roles.
Modern monitoring systems collect extensive information through GPS devices and wearable technologies, allowing staff to quantify every aspect of physical effort. Biomarkers linked to fatigue can further improve understanding of an athlete’s recovery status.
For female athletes, hormonal fluctuations may also influence injury risk. Depending on the stage of the menstrual cycle, physiological changes may increase susceptibility to certain injuries, creating additional variables that can be incorporated into digital models.
Once genetic information, metabolic indicators, training loads, nutritional status, sleep quality and psychological factors are combined, the volume and complexity of the data exceed what humans can reliably interpret.
AI systems are capable of identifying hidden relationships between variables that would otherwise remain invisible.
Digital twins are increasingly being viewed as one of the most important developments in precision medicine and sports science.
In sports medicine, several research initiatives have already demonstrated the potential of virtual athlete models to predict fatigue and optimise performance. Among the notable examples is the Margaria-Morton model developed through collaboration between French research institutions and the country’s cycling federation.
12.06.2026.
