approved
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.

Tags
Data and Resources
To access the resources you must log in
Additional Info
Field Value
Accessibility Both
AccessibilityMode Download
AccessibilityMode OnLine Access
Availability On-Line
Basic rights Download
CreationDate 2019-09-30 09:00
Creator Pappalardo, Luca, lucapappalardo1094@gmail.com, orcid.org/0000-0002-1547-6007
Field/Scope of use Non-commercial only
Group Health Studies
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
Sublicense rights Yes
Territory of use World Wide
Thematic Cluster Human Mobility Analytics [HMA]
UsageMode Download
link to repository https://github.com/mesosbrodleto/playerank
system:type Method
Management Info
Field Value
Author Pappalardo Luca
Maintainer Pappalardo Luca
Version 1
Last Updated 14 September 2023, 22:27 (CEST)
Created 29 April 2021, 11:12 (CEST)