Data-Driven Athlete Performance Analysis and Talent Identification Using Sports Analytics
Lavanya Ramchandra Patil
This paper presents a data-driven approach for analyzing athlete performance and identifying high-potential talent using sports analytics. A dataset of 1,200 athletes was analyzed using statistical and exploratory techniques. Key performance indicators such as Skill Assessment Score, Cognitive Score, and Olympic Potential Score were examined along with physiological factors like sleep duration, fatigue level, and heart rate. The results highlight strong relationships between recovery and performance. The study demonstrates how data analytics can support decision-making in sports organizations by improving training efficiency and talent identification.