Public data set of spatio-temporal match events in soccer competitions

Soccer analytics is attracting increasing interest in academia and industry, thanks to the availability of sensing technologies that provide high-fidelity data streams for every match. Unfortunately, these detailed data are owned by specialized companies and hence are rarely publicly available for scientific research. To fill this gap, this paper describes the largest open collection of soccer-logs ever released, containing all the spatio-temporal events (passes, shots, fouls, etc.) that occured during each match for an entire season of seven prominent soccer competitions. Each match event contains information about its position, time, outcome, player and characteristics. The nature of team sports like soccer, halfway between the abstraction of a game and the reality of complex social systems, combined with the unique size and composition of this dataset, provide an ideal ground for tackling a wide range of data science problems, including the measurement and evaluation of performance, both at individual and at collective level, and the determinants of success and failure.

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Accessibility Both
AccessibilityMode OnLine Access
AccessibilityMode API Access
AccessibilityMode Download
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Availability On-Line
Basic rights Download
ChildrenData No
Consent obtained also covers the envisaged transfer of the personal data outside the EU N/A (Not appliable)
Consent of the data subject N/A (Not appliable)
CreationDate 2019-10-28 14:00
Creator Pappalardo, Luca, lucapappalardo1984@gmail.com, orcid.org/0000-0002-1547-6007
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External Identifier https://doi.org/10.6084/m9.figshare.c.4415000.v2
Field/Scope of use Non-commercial only
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License term /Not specified
ManifestationType Virtual
Personal data was manifestly made public by the data subject Yes
PersonalData No
PersonalSensitiveData Select PersonalSensitiveData
ProcessingDegree Primary
RelatedPaper Pappalardo, L., Cintia, P., Rossi, A. et al. A public data set of spatio-temporal match events in soccer competitions. Sci Data 6, 236 (2019) doi:10.1038/s41597-019-0247-7, https://www.nature.com/articles/s41597-019-0247-7
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Sublicense rights No
Territory of use World Wide
ThematicCluster Visual Analytics
TimeCoverage 2016-05-01 14:00/2018-12-31 14:00
spatial
system:type SoBigData.eu: Dataset
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Field Value
Author Pappalardo Luca
Maintainer Pappalardo Luca
Version 1
Last Updated 9 December 2019, 14:58 (CET)
Created 9 December 2019, 14:58 (CET)