This study presents the development of a software prototype designed to collect, integrate, and analyze biometric, physical, and technical performance data from players on the college football team at the Instituto Politécnico Nacional, a prominent university in Mexico City. The prototype employs advanced data mining and analysis techniques to help coaches make data-driven decisions. By transforming and processing diverse datasets, the system offers comprehensive insights into player performance, enhancing decision-making capabilities. The findings indicate significant improvements in team performance and the ability to meet technical and athletic challenges. This integration of multifaceted data demonstrates the potential for data-driven methodologies in sports analytics.