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Social Networks and the Economics of Sports pp 149–156Cite as

Soccer Analytics Using Touch-by-Touch Match Data

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Abstract

This paper discusses several soccer analytics directions exploiting detailed ball touch data from a soccer game. The topics discussed include visualizing team formations and quantifying territorial advantage; determining the network-based structural properties of team play, and computing the importance of individual players for the team interactions. The proposed ideas are illustrated using the data from a real-life Barclays Premier League game, which was made available by StatDNA.

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References

  1. StatDNA. http://www.statdna.com/

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Acknowledgments

We would like to thank Jaeson Rosenfeld, CEO of StatDNA for providing the data used in this study.

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Authors and Affiliations

  1. Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, 77843-3131, USA

    Sergiy Butenko & Justin Yates

Authors
  1. Sergiy Butenko
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  2. Justin Yates
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Corresponding author

Correspondence to Sergiy Butenko .

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Editors and Affiliations

  1. Dept. of Industrial & Systems Engin., University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  2. Laboratory of Algorithms & Technologies, Higher School of Economics, N.Novgorod, Russia

    Victor Zamaraev

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Butenko, S., Yates, J. (2014). Soccer Analytics Using Touch-by-Touch Match Data. In: Pardalos, P., Zamaraev, V. (eds) Social Networks and the Economics of Sports. Springer, Cham. https://doi.org/10.1007/978-3-319-08440-4_9

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