MyTwin predicts sports injuries: first deployment in professional tennis

MyTwin's R&D team unveils a new application of its digital twin: an injury prediction algorithm designed for elite athletes. The first use case is deployed in professional tennis.

The Technology

The algorithm developed by the MyTwin team analyzes a set of athlete-related data: injury history, training load, physiological data, competition conditions and fatigue signals. By cross-referencing these parameters, the AI can predict up to 80% of potential injuries before they occur.

This prediction capability allows athletes and their medical teams to take preventive measures: adjusting training, strengthening a vulnerable area or simply scheduling rest at the right time.

Why Tennis?

Tennis is a particularly demanding sport for the body. Competitions follow one another across varied surfaces (clay, grass, hard court), with very different physical demands. Injuries are frequent and can compromise an entire season, or even a career.

This context makes it an ideal testing ground for an injury prediction tool. The first data collected in real-world conditions validates the approach's relevance.

Prospects for Other Sports

Tennis is just the beginning. The algorithm was designed to be adaptable to many sports disciplines: football, basketball, track and field, combat sports... Each sport has its own injury patterns, and the AI can learn to recognize and anticipate them.

This new application illustrates the versatility of the MyTwin digital twin: after health risk information, mental health monitoring and skin risk assessment, it is the world of elite sports that benefits from this technology.