Journal of Coaching and Sports Science (Dec 2024)
Smart Sports Recruitment: Leveraging Software for Talent Precision
Abstract
This research highlights the critical role of technology in sports, particularly in identifying and developing talent more effectively. Technology enables better athlete performance analysis; however, talent identification still relies on traditional methods. Coaches and sports teachers often select athletes based solely on competition results without leveraging technology-based analysis. As a result, important biomotor components are frequently overlooked, and the manual processing of talent data is time-consuming and less effective. To develop sports talent identification software based on biomotor and anthropometric databases to accelerate the search for talented athletes and sports recommendations efficiently and accurately. Biomotor and anthropometric test items are adopted from the talent scouting test scoring system of the Ministry of Youth and Sports of the Republic of Indonesia. The development method consists of the following stages: (1) performing needs analysis through surveys and interviews, (2) designing a talent identification model with a flow diagram, (3) developing a talent identification model using the Entity-Relationship Model, (4) testing the validity of the model by material and media experts using the Content Validity Index, and (5) conducting field trials with battery tests and anthropometric measurements. Producing talent identification software called Talent Identification Development (TIDev). Expert validation showed the I-CVI validity index of 0.93 (material) and 0.90 (media), indicating the high effectiveness of TIDev in identifying potential athletes and providing sports recommendations. A trial of 40 junior high school students showed that 34 students felt that the recommendations were based on their interests and talents, covering 12 recommended sports. TIDev can accelerate and simplify athlete recruitment, providing accurate and reliable sports analysis and recommendations.
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