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A Survey on Applications of Modern Deep Learning Techniques in Team Sports Analytics

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Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020) (SoCPaR 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1383))

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Abstract

The recent advancement of deep learning algorithms has paved the way to many technological applications and research areas. The field of team sport analytics is one of the interesting research areas in which deep neural network techniques are applied. Availability of both tracking and visual data in sports coupled with the recent development in computing process has made sport analytics via deep learning approach possible. However, comprehensive surveys on these deep learning techniques as leveraged in sport analytics are still limited. This paper attempts to provide a survey along with references for further studies on modern state-of-the-art deep learning techniques leveraged to two typical team sport namely soccer and basketball, where multi-agent interactions and coordination are highly observed. We expect this paper to serve as an insightful and handful resource on team sport analytics for both sports practitioners and researchers from machine learning perspective.

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Acknowledgement

This work is supported by the National Natural Science Foundation of China (Grant No.61702073) and the China Postdoctoral Science Foundation (Grant No. 2019M661079)

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Authors and Affiliations

  1. Department of Intelligence Science and Technology, College of Information Science and Technology, Dalian Maritime University, Dalian, 116026, China

    Gervas Batister Mgaya, Hongbo Liu & Bo Zhang

Authors
  1. Gervas Batister Mgaya
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  2. Hongbo Liu
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  3. Bo Zhang
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Corresponding author

Correspondence to Hongbo Liu .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Systems Innovation, School of Engineering, The University of Tokyo, Bunkyo-ku, Tokyo, Japan

    Yukio Ohsawa

  3. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Vardhaman College of Engineering, Hyderabad, Telangana, India

    M.A. Jabbar

  5. Faculty of Sciences and Techniques, Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  6. Queen’s University, Belfast, UK

    Seán McLoone

  7. Northumbria University, Newcastle, UK

    Biju Issac

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Mgaya, G.B., Liu, H., Zhang, B. (2021). A Survey on Applications of Modern Deep Learning Techniques in Team Sports Analytics. In: Abraham, A., et al. Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020). SoCPaR 2020. Advances in Intelligent Systems and Computing, vol 1383. Springer, Cham. https://doi.org/10.1007/978-3-030-73689-7_42

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