ATHLETE SELECTION MODEL USING SPORTS STATISTICS DATA FABRIC TECHNIQUES FOR NATIONAL SPORTS EXCELLENCE.

Title:ATHLETE SELECTION MODEL USING SPORTS STATISTICS DATA FABRIC TECHNIQUES FOR NATIONAL SPORTS EXCELLENCE
Author:CHANITA SATTABURUTH, PALLOP PIRIYASURAWONG, PRACHYANUN NILSOOK
Abstract:Physical fitness factors that significantly impact athletes’ performance. This research objective is to analyze and develop a model for the successful selection of athletes based on physical fitness factors. The sample comprises data from high-potential athletes who attend sports schools affiliated with the Thailand National Sports University. The research methodology combines Multi-Layer Perceptron and Multiple Linear Regression as data analysis techniques to identify suitable models for successful competitive athletes. The results of the model evaluation indicate that the accuracy is 72.73% and the R-squared value is 0.665. The experiment shows that analyzing the athlete selection model could reveal the factors that influence the selection of athletes. These factors will be described in this article.
Keywords:Data Mining, Neural Network, Data Fabric Technique, Aquatic Athletes, Physical Fitness
Source:Journal of Theoretical and Applied Information Technology
29th February 2024 — Vol. 101.  No. 4– 2024

Sattaburuth, C. Piriyasurawong, P. Nilsook, P. (2024)
ATHLETE SELECTION MODEL USING SPORTS STATISTICS DATA FABRIC TECHNIQUES FOR NATIONAL SPORTS EXCELLENCE.
Journal of Theoretical and Applied Information Technology, (2024), 1565-1573, 102(4)
https://www.jatit.org/volumes/Vol102No4/22Vol102No4.pdf