Soccer teams ranking simulator

This algorithm simulates the outcomes of an entire season of each team of a football league only relying on technical data (i.e., excluding the goals scored), by exploiting a machine learning model trained on data from past seasons. The simulation produces a team ranking which is close to the actual ranking. This result suggests that a complex systems’ view on soccer has the potential of revealing hidden patterns regarding the relation between performance and success.

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Accessibility Both
AccessibilityMode OnLine Access
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Availability On-Site
Basic rights Temporary download of a single copy only
CreationDate 2018-02-07 11:20
Creator Pappalardo Luca, lucapappalardo1984@gmail.com, orcid.org/0000-0002-1547-6007
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Field/Scope of use Non-commercial only
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License term /Not specified
Owner Pappalardo Luca, lucapappalardo1984@gmail.com, orcid.org/0000-0002-1547-6007
ProgrammingLanguage
RelatedPaper Luca Pappalardo, Paolo Cintia. Quantifying the relation between performance and success in soccer. Advances in Complex Systems, 2017. https://arxiv.org/abs/1705.00885
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Sublicense rights No
Territory of use World Wide
ThematicCluster Human Mobility Analytics
UsageMode as-a-Service by SoBigData Infrastructure
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system:type SoBigData.eu: Method
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Author Cintia Paolo
Maintainer Cintia Paolo
Version 1
Last Updated 29 June 2018, 11:34 (CEST)
Created 29 June 2018, 11:34 (CEST)