PlayeRank evaluation framework

The problem of evaluating the performance of soccer players is attracting the interest of many companies and the scientific community, thanks to the availability of massive data capturing all the events generated during a match (e.g., tackles, passes, shots, etc.). PlayeRank is a data-driven framework that offers a principled multi-dimensional and role-aware evaluation of the performance of soccer players. PlayeRank significantly outperforms known algorithms for performance evaluation in soccer when evaluated on a dataset of players’ evaluations made by professional soccer scouts.

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Accessibility Both
AccessibilityMode Download
AccessibilityMode OnLine Access
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Availability On-Line
Basic rights Download
CreationDate 2019-09-30 09:00
Creator Pappalardo, Luca, lucapappalardo1094@gmail.com, orcid.org/0000-0002-1547-6007
Dependencies on Other SW
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Field/Scope of use Non-commercial only
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License term /Not specified
Owner Pappalardo, Luca, lucapappalardo1094@gmail.com, orcid.org/0000-0002-1547-6007
ProgrammingLanguage Python
RelatedPaper Luca Pappalardo, Paolo Cintia, Paolo Ferragina, Emanuele Massucco, Dino Pedreschi, and Fosca Giannotti. 2019. PlayeRank: Data-driven Performance Evaluation and Player Ranking in Soccer via a Machine Learning Approach. ACM Trans. Intell. Syst. Technol. 10, 5, Article 59 (September 2019), 27 pages. DOI:https://doi.org/10.1145/3343172
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Sublicense rights Yes
Territory of use World Wide
ThematicCluster Human Mobility Analytics
UsageMode Download
input
link to repository https://github.com/mesosbrodleto/playerank
output
system:type SoBigData.eu: Method
Management Info
Field Value
Author Pappalardo Luca
Maintainer Pappalardo Luca
Version 1
Last Updated 4 February 2020, 05:59 (CET)
Created 4 February 2020, 05:59 (CET)