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

Abstract

This paper first analyzes the basic law of the formation process of volleyball skills, puts forward the four-stage theory based on this, and then gives the elements of modern volleyball players’ competitive ability. Then, the evaluation system of volleyball players’ competitive level is constructed, the weight of the index is calculated, and the data is analyzed by grey correlation analysis, entropy method and other algorithms. Finally, data mining algorithms such as least square support vector regression and long and short memory neural networks are used to mine different kinds of data to achieve the purpose of risk prediction and timely release of early warning information. Finally, the women’s volleyball team of B City is taken as an example to evaluate and test. The results show that the top four weights of the secondary indexes are running height, field of vision, serving skill score and height, and their weights are 0.5157, 0.4862, 0.4431 and 0.4248, respectively. It shows that volleyball players can improve their muscle reaction speed by actively developing the explosive power of their lower limbs so as to improve the mastery of volleyball skills and enhance the level of volleyball competition.