SC2EGSet: StarCraft II Esport Replay and Game-state Dataset

TL;DR

This paper introduces SC2EGSet, a comprehensive and large-scale dataset of StarCraft II esports replays and game states, along with open-source tools, to facilitate scientific research in AI, ML, psychology, and HCI.

Contribution

The authors provide the largest publicly available StarCraft II esports dataset with raw and processed data, plus open-source tools for data extraction and modeling, enabling broader scientific analysis.

Findings

Largest publicly available StarCraft II esports dataset

Processed 55 tournament replay packs with 17,930 files

Tools for data loading and modeling are open-sourced

Abstract

As a relatively new form of sport, esports offers unparalleled data availability. Despite the vast amounts of data that are generated by game engines, it can be challenging to extract them and verify their integrity for the purposes of practical and scientific use. 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 related to various laboratory-based measurements (e.g., behavioral tests, brain imaging). We have gathered publicly available game-engine generated "replays" of tournament matches and performed data extraction and cleanup using a low-level application programming interface (API) parser library. 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. To prepare the dataset, we processed 55 tournament "replaypacks" that contained 17930 files with game-state information. Based on initial investigation of available StarCraft II datasets, we observed that our dataset is the largest publicly available source of StarCraft II esports 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.