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SC2EGSet: StarCraft II Esport Replay and Game-state Dataset

As a relatively new form of sport, esports offers unparalleled data availability. Our work aims to open esports to a broader scientific community by supplying raw and pre-processed files from StarCraft II esports tournaments. These files can be used in statistical and machine learning modeling tasks...

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Detalles Bibliográficos
Autores principales: Białecki, Andrzej, Jakubowska, Natalia, Dobrowolski, Paweł, Białecki, Piotr, Krupiński, Leszek, Szczap, Andrzej, Białecki, Robert, Gajewski, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491788/
https://www.ncbi.nlm.nih.gov/pubmed/37684293
http://dx.doi.org/10.1038/s41597-023-02510-7
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author Białecki, Andrzej
Jakubowska, Natalia
Dobrowolski, Paweł
Białecki, Piotr
Krupiński, Leszek
Szczap, Andrzej
Białecki, Robert
Gajewski, Jan
author_facet Białecki, Andrzej
Jakubowska, Natalia
Dobrowolski, Paweł
Białecki, Piotr
Krupiński, Leszek
Szczap, Andrzej
Białecki, Robert
Gajewski, Jan
author_sort Białecki, Andrzej
collection PubMed
description As a relatively new form of sport, esports offers unparalleled data availability. Our work aims to open esports to a broader scientific community by supplying raw and pre-processed files from StarCraft II esports tournaments. These files can be used in statistical and machine learning modeling tasks and compared to laboratory-based measurements. Additionally, we open-sourced and published all the custom tools that were developed in the process of creating our dataset. These tools include PyTorch and PyTorch Lightning API abstractions to load and model the data. Our dataset contains replays from major and premiere StarCraft II tournaments since 2016. We processed 55 “replaypacks” that contained 17930 files with game-state information. Our dataset is one of the few large publicly available sources of StarCraft II data upon its publication. Analysis of the extracted data holds promise for further Artificial Intelligence (AI), Machine Learning (ML), psychological, Human-Computer Interaction (HCI), and sports-related studies in a variety of supervised and self-supervised tasks.
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spelling pubmed-104917882023-09-10 SC2EGSet: StarCraft II Esport Replay and Game-state Dataset Białecki, Andrzej Jakubowska, Natalia Dobrowolski, Paweł Białecki, Piotr Krupiński, Leszek Szczap, Andrzej Białecki, Robert Gajewski, Jan Sci Data Data Descriptor As a relatively new form of sport, esports offers unparalleled data availability. Our work aims to open esports to a broader scientific community by supplying raw and pre-processed files from StarCraft II esports tournaments. These files can be used in statistical and machine learning modeling tasks and compared to laboratory-based measurements. Additionally, we open-sourced and published all the custom tools that were developed in the process of creating our dataset. These tools include PyTorch and PyTorch Lightning API abstractions to load and model the data. Our dataset contains replays from major and premiere StarCraft II tournaments since 2016. We processed 55 “replaypacks” that contained 17930 files with game-state information. Our dataset is one of the few large publicly available sources of StarCraft II data upon its publication. Analysis of the extracted data holds promise for further Artificial Intelligence (AI), Machine Learning (ML), psychological, Human-Computer Interaction (HCI), and sports-related studies in a variety of supervised and self-supervised tasks. Nature Publishing Group UK 2023-09-08 /pmc/articles/PMC10491788/ /pubmed/37684293 http://dx.doi.org/10.1038/s41597-023-02510-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Białecki, Andrzej
Jakubowska, Natalia
Dobrowolski, Paweł
Białecki, Piotr
Krupiński, Leszek
Szczap, Andrzej
Białecki, Robert
Gajewski, Jan
SC2EGSet: StarCraft II Esport Replay and Game-state Dataset
title SC2EGSet: StarCraft II Esport Replay and Game-state Dataset
title_full SC2EGSet: StarCraft II Esport Replay and Game-state Dataset
title_fullStr SC2EGSet: StarCraft II Esport Replay and Game-state Dataset
title_full_unstemmed SC2EGSet: StarCraft II Esport Replay and Game-state Dataset
title_short SC2EGSet: StarCraft II Esport Replay and Game-state Dataset
title_sort sc2egset: starcraft ii esport replay and game-state dataset
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491788/
https://www.ncbi.nlm.nih.gov/pubmed/37684293
http://dx.doi.org/10.1038/s41597-023-02510-7
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