A systematic decision making for functional training in competitive sports training

Abstract

Decision-making is a vital aspect of any sport and competitive success, in particular open, strong, competitive team sports like soccer, volleyball, basketball, and rugby. However, in the notational analysis, it has largely ignored. To successfully win in any game and compete in every sport for individuals and teams at the national and international level, all success factors must be reconsidered to ensure a better winning decision. Hence, in this paper, Exploratory Hybridized Structural Equation Modeling Framework (HSEMF) has been proposed for decision making on functional training competitive sports training. The training environment will allow competitors to weigh up their options, determine, and mistake. However, the main feature of the environment is that athletes must be informed if they make mistakes to ensure that they do not take part in the future. The feedback should be provided to improve the performance of the athlete. The decision accuracy and performance indicators have been evaluated. Overall, the results did not show a causal relationship between changes in decision making after implementing the learning modules. However, it has provided moderate evidence of improved reaction time due to the learning modules for decision-making.

Volleyball players’ mastery of sports skills and improvement of competitive level based on big data analysis

“…The degree of development of competitive sports has become an important symbol of the development level of material and spiritual civilization of countries and regions [1][2]. With the continuous promotion of China's education reform, volleyball teaching in China is gradually developing deeply and entering the golden era with the strong support of national policies [3][4].…”

Relationship between Physical Training and Tactical Training in Sports Training Relying on Boosting and Bagging Algorithms

“…e training environment will allow competitors to weigh their choices, decisions, and mistakes. It provides modest evidence of improved reaction times due to the decision learning module [2]. Kumyaito proposes an individualized athletic training program that specifies an individualized performance training schedule to optimize athlete performance.…”