Ongoing

Academic Project

YOLOV8, Roboflow, Python, Computer Vision Algorithms

Date

Project Type

Tools

U-GO

Soccer is not just a sport in Nigeria; it's a cultural phenomenon that offers young players a pathway to change their lives, fueled by both passion and the potential for socioeconomic advancement. Despite the wealth of natural talent, a critical gap exists in the mental and tactical development of young aspirants, primarily due to a lack of specialized mentorship. The stark reality is that only a privileged 2% have access to quality coaching, as most Nigerian schools resort to assigning general teachers as sports instructors and soccer coaches due to financial constraints.

Enter U-GO, a revolutionary coaching assistant designed to bridge this mentoring gap. By leveraging the power of computer vision algorithms and advanced language models, U-GO offers a unique solution. Coaches can upload videos of their players in action, and U-GO analyzes these clips to track performance, evaluate gameplay, and identify each player's skills, strengths, and areas for improvement. This technology-driven approach allows U-GO to provide personalized feedback and tailored training suggestions, catering to the individual needs of each young athlete.

U-GO is more than just a tool; it's a platform that democratizes access to elite soccer training insights, making it possible for aspiring talents across Nigeria to develop their full potential, regardless of their socioeconomic status. This initiative not only nurtures raw talent but also fosters a more inclusive environment where every child has the opportunity to pursue their dreams on the soccer field.

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