@inproceedings{6ad867bfaedb43fa84f249d61610dd06,
title = "Anomaly Detection in Player Performances in Multiplayer Online Battle Arena Games",
abstract = "Esports are digital video games that are played professionally. In recent years there has been a growing need to improve the broadcast experience by incorporating real-time data-driven analytics. In these same games, when played by the general public, there is a growing issue of cheating. Using the popular esport and video game DOTA 2 as a case study, we present a novel application of Archetype Analysis that can be used for anomaly detection in player performance. We show how these anomalies can be utilised for both esports broadcasting and cheat detection.",
keywords = "datasets, gaze detection, neural networks, text tagging",
author = "Xin Qian and Rafet Sifa and Xuefei Liu and Shreyashi Ganguly and Borchuluun Yadamsuren and Diego Klabjan and Anders Drachen and Simon Demediuk",
note = "Funding Information: This work is partly funded by the Digital Creativity Labs funded by EPSRC/AHRC/Innovate UK, EP/M023265/1. Publisher Copyright: {\textcopyright} 2022 ACM.; 2022 Australasian Computer Science Week, ACSW 2022 ; Conference date: 14-02-2022 Through 17-02-2022",
year = "2022",
month = feb,
day = "14",
doi = "10.1145/3511616.3513095",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "23--30",
booktitle = "Proceedings of 2022 Australasian Computer Science Week, ACSW 2022",
}