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A survey of competitive sports data visualization and visual analysis

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Abstract

Competitive sports data visualization is an increasingly important research direction in the field of information visualization. It is also an important basis for studying human behavioral pattern and activity habits. In this paper, we provide a taxonomy of sports data visualization and summarize the state-of-the-art research from four aspects of data types, main tasks and visualization techniques and visual analysis. Specifically, we first put sports data into two categories: spatiotemporal information and statistical information. Then, we propose three main tasks for competitive sports data visualization: feature presentation, feature comparison and feature prediction. Furthermore, we classify competitive sports data visualization techniques based on data characteristics into five categories: high-dimensional data visualization, time-series visualization, graph (network) visualization, glyph visualization and other visualization, and we analyze the relationship between major tasks and visualization techniques. We also introduce visual analysis research work of competitive sports, propose the features and limitations of competitive sports data, summarize multimedia visualization in competitive sports and finally discuss visual analysis evaluation. In this survey, we attempt to help readers to find appropriate techniques for different data types and different tasks. Our paper also intends to provide guidelines and references for future researchers when they study human behavior and moving patterns.

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Acknowledgements

This work is supported by the National Key Research and Development Program of China (2016QY02D0304). We appreciate all the authors who gave us permission to reuse their images in this research. We would also like to thank all researchers for their contributions in competitive sports visualization field and the editors of this journal and the anonymous reviewers for their valuable suggestions and comments.

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  1. Meng Du

    Present address: School of New Media, Beijing Institution of Graphic Communication, Beijing, China

Authors and Affiliations

  1. International New Media Institution of Industry-Education-Research Cooperation, Beijing, China

    Meng Du

  2. Key Laboratory of Machine Perception (Ministry of Education), School of EECS, and Center for Computational Science and Engineering, Peking University, Beijing, China

    Meng Du & Xiaoru Yuan

  3. National Engineering Laboratory for Big Data Analysis and Application and Beijing Engineering Technology Research Center of Virtual Simulation and Visualization, Peking University, Beijing, China

    Xiaoru Yuan

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  1. Meng Du
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Correspondence to Xiaoru Yuan.

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M. Du: The presented work was done while Meng Du was a postdoctoral researcher at Peking University.

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Du, M., Yuan, X. A survey of competitive sports data visualization and visual analysis. J Vis 24, 47–67 (2021). https://doi.org/10.1007/s12650-020-00687-2

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