Identification of Players Ranking in E-Sport
Human activity is moving steadily to virtual reality. More and more, people from all over the world are keen on growing fascination with e-sport. In practice, e-sport is a type of sport in which players compete using computer games. The competitions in games, like FIFA, Dota2, the League of Legends,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/10/19/6768 |
| _version_ | 1797552423416365056 |
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| author | Karol Urbaniak Jarosław Wątróbski Wojciech Sałabun |
| author_facet | Karol Urbaniak Jarosław Wątróbski Wojciech Sałabun |
| author_sort | Karol Urbaniak |
| collection | DOAJ |
| description | Human activity is moving steadily to virtual reality. More and more, people from all over the world are keen on growing fascination with e-sport. In practice, e-sport is a type of sport in which players compete using computer games. The competitions in games, like FIFA, Dota2, the League of Legends, and Counter-Strike, are prestigious tournaments with a global reach and a budget of millions of dollars. On the other hand, reliable player ranking is a critical issue in both classic and e-sport. For example, the “Golden Ball” is the most valuable prize for an individual football player in the whole football history. Moreover, the entire players’ world wants to know who the best player is. The position of each player in the ranking depends on the assessment of his skills and predispositions. In this paper, we studied identification of players evaluation and ranking obtained using the multiple-criteria decision-making based method called Characteristic Objects METhod (COMET) on the example of the popular game Counter-Strike: Global Offensive (CS: GO). We present a range of advantages of the player evaluation model created using the COMET method and, therefore, prove the practicality of using multi-criteria decision analysis (MCDA) methods to build multi-criteria assessment models in emerging areas of eSports. Thus, we provide a methodical and practical background for building a decision support system engine for the evaluation of players in several eSports. |
| first_indexed | 2024-03-10T16:00:50Z |
| format | Article |
| id | doaj.art-743681739a5745b0b13f4a9e2bd1b656 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T16:00:50Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-743681739a5745b0b13f4a9e2bd1b6562023-11-20T15:17:36ZengMDPI AGApplied Sciences2076-34172020-09-011019676810.3390/app10196768Identification of Players Ranking in E-SportKarol Urbaniak0Jarosław Wątróbski1Wojciech Sałabun2Research Team on Intelligent Decision Support Systems, Department of Artificial Intelligence Methods and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, Szczecin ul. Żołnierska 49, 71-210 Szczecin, PolandDepartment of Information Systems Engineering in the Faculty of Economics, Finance and Management of the University of Szczecin, Mickiewicza 64, 71-101 Szczecin, PolandResearch Team on Intelligent Decision Support Systems, Department of Artificial Intelligence Methods and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, Szczecin ul. Żołnierska 49, 71-210 Szczecin, PolandHuman activity is moving steadily to virtual reality. More and more, people from all over the world are keen on growing fascination with e-sport. In practice, e-sport is a type of sport in which players compete using computer games. The competitions in games, like FIFA, Dota2, the League of Legends, and Counter-Strike, are prestigious tournaments with a global reach and a budget of millions of dollars. On the other hand, reliable player ranking is a critical issue in both classic and e-sport. For example, the “Golden Ball” is the most valuable prize for an individual football player in the whole football history. Moreover, the entire players’ world wants to know who the best player is. The position of each player in the ranking depends on the assessment of his skills and predispositions. In this paper, we studied identification of players evaluation and ranking obtained using the multiple-criteria decision-making based method called Characteristic Objects METhod (COMET) on the example of the popular game Counter-Strike: Global Offensive (CS: GO). We present a range of advantages of the player evaluation model created using the COMET method and, therefore, prove the practicality of using multi-criteria decision analysis (MCDA) methods to build multi-criteria assessment models in emerging areas of eSports. Thus, we provide a methodical and practical background for building a decision support system engine for the evaluation of players in several eSports.https://www.mdpi.com/2076-3417/10/19/6768e-sportrankingCOMET method |
| spellingShingle | Karol Urbaniak Jarosław Wątróbski Wojciech Sałabun Identification of Players Ranking in E-Sport Applied Sciences e-sport ranking COMET method |
| title | Identification of Players Ranking in E-Sport |
| title_full | Identification of Players Ranking in E-Sport |
| title_fullStr | Identification of Players Ranking in E-Sport |
| title_full_unstemmed | Identification of Players Ranking in E-Sport |
| title_short | Identification of Players Ranking in E-Sport |
| title_sort | identification of players ranking in e sport |
| topic | e-sport ranking COMET method |
| url | https://www.mdpi.com/2076-3417/10/19/6768 |
| work_keys_str_mv | AT karolurbaniak identificationofplayersrankinginesport AT jarosławwatrobski identificationofplayersrankinginesport AT wojciechsałabun identificationofplayersrankinginesport |