2021_Developing Soccer Performance Model Based on Anthropometriy, Fitness, and Skill Components Using Machine Learning Approach
| Format: | General Document |
|---|
| _version_ | 1860798076265955328 |
|---|---|
| building | INTELEK Repository |
| collection | Online Access |
| collectionurl | https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 |
| copyright | Copyright©PWB2025 |
| country | Malaysia |
| date | 2022-01-24 |
| format | General Document |
| id | 15782 |
| institution | UniSZA |
| internalnotes | Sila masukkan subject wajib Dissertations, Academic. Terima kasih... |
| originalfilename | DEVELOPING SOCCER PERFORMANCE MODEL BASED ON ANTHROPOMETRIY, FITNESS, AND SKILL COMPONENTS USING MACHINE LEARNING APPROACH (MASTER_2021).pdf |
| person | Safa’a Ahmad Al Masri |
| recordtype | oai_dc |
| resourceurl | https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15782 |
| sourcemedia | Server storage Scanned document |
| spelling | 15782 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15782 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 General Document Malaysia Library Staff (Top Management) Library Staff (Management) Library Staff (Support) Terengganu Faculty of Health Sciences English application/pdf 1.5 17 SAMBox 2.3.4 Server storage Scanned document Universiti Sultan Zainal Abidin UniSZA Private Access UNIVERSITI SULTAN ZAINAL ABIDIN Copyright©PWB2025 2022-01-24 DEVELOPING SOCCER PERFORMANCE MODEL BASED ON ANTHROPOMETRIY, FITNESS, AND SKILL COMPONENTS USING MACHINE LEARNING APPROACH (MASTER_2021).pdf 2021_Developing Soccer Performance Model Based on Anthropometriy, Fitness, and Skill Components Using Machine Learning Approach Safa’a Ahmad Al Masri Soccer—Performance analysis In this study, 89 soccer’s players whose age around 13 years from Terengganu area involved in performing 10 parameters aiming at determining the performance of those players based on assessing the contribution of each activity and its corresponding significant level. The 10 parameters were involved anthropometry (BMI), fitness test (agility, coordination, muscular endurance (push and sit up), power, YoYo level), and football skill test (dribbling with ball, dribbling without ball and juggling). All the parameters are carried out based on international standard and performed by well trained staff. The Pearson correlation analysis was used to achieve the objective in this study. Result shows a positive correlation between the two types of muscular parameters; the power is influenced by BMI and coordination; the specific football tests are highly impacted by the power and agility. The coefficient of determination R2 and the significance level p-values show that the parameters that can be significantly considered are the anthropometric BMI (0.020), agility (0.025), muscular endurance (0.039 and 0.043), power (0.039), special football test without the ball (0.041), and juggling (0.046). The coordination, YoYo, football special test with the ball were not found significantly accounted for preparing the young players to achieve the required performance. Based on the results of the coefficient of determination and the significance p-values of the parameters, a model was proposed to determine the highest and lowest parameters that play important roles in the performance needed for the young players. Dissertations, Academic Sila masukkan subject wajib Dissertations, Academic. Terima kasih... Soccer Performance Modeling With AI Anthropometry And Fitness in Soccer Players Skill Assessment in Soccer Using Machine Learning Thesis |
| spellingShingle | 2021_Developing Soccer Performance Model Based on Anthropometriy, Fitness, and Skill Components Using Machine Learning Approach |
| state | Terengganu |
| subject | Soccer—Performance analysis Dissertations, Academic |
| summary | In this study, 89 soccer’s players whose age around 13 years from Terengganu area involved in performing 10 parameters aiming at determining the performance of those players based on assessing the contribution of each activity and its corresponding significant level. The 10 parameters were involved anthropometry (BMI), fitness test (agility, coordination, muscular endurance (push and sit up), power, YoYo level), and football skill test (dribbling with ball, dribbling without ball and juggling). All the parameters are carried out based on international standard and performed by well trained staff. The Pearson correlation analysis was used to achieve the objective in this study. Result shows a positive correlation between the two types of muscular parameters; the power is influenced by BMI and coordination; the specific football tests are highly impacted by the power and agility. The coefficient of determination R2 and the significance level p-values show that the parameters that can be significantly considered are the anthropometric BMI (0.020), agility (0.025), muscular endurance (0.039 and 0.043), power (0.039), special football test without the ball (0.041), and juggling (0.046). The coordination, YoYo, football special test with the ball were not found significantly accounted for preparing the young players to achieve the required performance. Based on the results of the coefficient of determination and the significance p-values of the parameters, a model was proposed to determine the highest and lowest parameters that play important roles in the performance needed for the young players. |
| title | 2021_Developing Soccer Performance Model Based on Anthropometriy, Fitness, and Skill Components Using Machine Learning Approach |
| title_full | 2021_Developing Soccer Performance Model Based on Anthropometriy, Fitness, and Skill Components Using Machine Learning Approach |
| title_fullStr | 2021_Developing Soccer Performance Model Based on Anthropometriy, Fitness, and Skill Components Using Machine Learning Approach |
| title_full_unstemmed | 2021_Developing Soccer Performance Model Based on Anthropometriy, Fitness, and Skill Components Using Machine Learning Approach |
| title_short | 2021_Developing Soccer Performance Model Based on Anthropometriy, Fitness, and Skill Components Using Machine Learning Approach |
| title_sort | 2021_developing soccer performance model based on anthropometriy, fitness, and skill components using machine learning approach |