This course explores how artificial intelligence and data-driven insights are transforming injury prevention for female and youth footballers. Learners will understand how maturation, growth, neuromuscular development, and hormonal physiology influence injury risk, and how AI-supported monitoring tools help detect high-risk patterns before injuries occur.

The course covers the unique biological profiles of young athletes, the influence of peak height velocity, coordination windows, and exposure management across maturation stages. It also dives into the specific challenges faced by female athletes, including menstrual-cycle fluctuations, hormonal effects on ligament integrity, neuromuscular control, and gender-specific injury patterns. Using evidence-based models, learners will analyze how to tailor training load, recovery strategies, and neuromuscular programs based on developmental stage or hormonal cycle. The course also presents practical monitoring systems, from cycle-tracking apps to wellness dashboards, that help teams individualize prevention strategies. By the end of this course, learners will be able to apply AI-enhanced frameworks to support safer training environments, design individualized prevention programs, and better protect athletes during key phases of growth and hormonal variation.