Data Mining Algorithm in Volleyball Match Technical and Tactical Analysis

Yongfen Yang

Application of Big Data, Blockchain, and Internet of Things for Education Informatization. First EAI International Conference, BigIoT-EDU 2021, Virtual Event, August 1–3, 2021, Proceedings, Part II

Research Article

Data Mining Algorithm in Volleyball Match Technical and Tactical Analysis

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-030-87903-7_27,
    author={Yongfen Yang},
    title={Data Mining Algorithm in Volleyball Match Technical and Tactical Analysis},
    proceedings={Application of Big Data, Blockchain, and Internet of Things for Education Informatization. First EAI International Conference, BigIoT-EDU 2021, Virtual Event, August 1--3, 2021, Proceedings, Part II},
    proceedings_a={BIGIOT-EDU PT2},
    year={2021},
    month={10},
    keywords={Data mining Markov process Data preprocessing Technical and tactical analysis},
    doi={10.1007/978-3-030-87903-7_27}
}

Yongfen Yang
Year: 2021
Data Mining Algorithm in Volleyball Match Technical and Tactical Analysis
BIGIOT-EDU PT2
Springer
DOI: 10.1007/978-3-030-87903-7_27

Yongfen Yang¹

1: Kunming University

Abstract

This paper analyzes the difficulties in the application of data mining algorithm in the technical and tactical analysis of sports competition, and puts forward a scheme for mining the key factors of winning volleyball matches. By applying the data mining algorithm based on Markov process and calculating the system reliability difference, the problem of finding the key action conversion process in volleyball competition is solved. In order to solve the problem of data acquisition speed, this paper proposes a method to solve the problem of data acquisition in real-time by setting the threshold of data acquisition. The design experiment shows the correctness and feasibility of the scheme.

Keywords: Data mining Markov process Data preprocessing Technical and tactical analysis

Published: 2021-10-18
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-030-87903-7_27