@article{824173,
      recid = {824173},
      author = {Clemente, Filipe Manuel, and Sequeiros, João Bernardo, and  Correia, Acácio F. P. P., and Silva, Frutuoso G. M., and  Martins, Fernando Manuel Lourenço,},
      title = {Computational metrics for soccer analysis : connecting the  dots /},
      pages = {1 online resource :},
      abstract = {This book provides an account of the use of computational  tactical metrics in improving sports analysis, in  particular the use of Global Positioning System (GPS) data  in soccer. As well as offering a practical perspective on  collective behavioural analysis, it introduces the  computational metrics available in the literature that  allow readers to identify collective behaviour and patterns  of play in team sports. These metrics only require the  bio-dimensional geo-referencing information from GPS or  video-tracking systems to provide qualitative and  quantitative information about the tactical behaviour of  players and the inter-relationships between teammates and  their opponents. Exercises, experimental cases and  algorithms enable readers to fully comprehend how to  compute these metrics, as well as introducing them to the  ultimate performance analysis tool, which is the basis to  run them on. The script to compute the metrics is presented  in Python. The book is a valuable resource for professional  analysts as well students and researchers in the field of  sports analysis wanting to optimise the use of GPS trackers  in soccer.},
      url = {http://library.usi.edu/record/824173},
      doi = {https://doi.org/10.1007/978-3-319-59029-5},
}