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Data preprocessing of eSport game records: Counter-strike: Global offensive

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10363619" target="_blank" >RIV/00216208:11320/17:10363619 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Data preprocessing of eSport game records: Counter-strike: Global offensive

  • Original language description

    Electronic sports or pro gaming have become very popular in this millenium and the increased value of this new industry is attracting investors with various interests. One of these interest is game betting, which requires player and team rating, game result predictions, and fraud detection techniques. In our work, we focus on preprocessing data of Counter-Strike: Global Offensive game in order to employ subsequent data analysis methods for quantifying player performance. The data preprocessing is difficult since the data format is complex and undocumented, the data quality of available sources is low, and there is no direct way how to match players from the recorded files with players listed on public boards such as HLTV website. We have summarized our experience from the data preprocessing and provide a way how to establish a player matching based on their metadata.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    6th International Conference on Data Science, Technology and Applications, DATA 2017

  • ISBN

    978-989-758-255-4

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    8

  • Pages from-to

    269-276

  • Publisher name

    SciTePress

  • Place of publication

    Setúbal

  • Event location

    Madrid

  • Event date

    Jul 24, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article