460-2073/02 – Esport, Basic Principles and Methods (ESPORT)

Gurantor departmentDepartment of Computer ScienceCredits4
Subject guarantorprof. Ing. Ivan Zelinka, Ph.D.Subject version guarantorprof. Ing. Ivan Zelinka, Ph.D.
Study levelundergraduate or graduateRequirementOptional
Study languageEnglish
Year of introduction2020/2021Year of cancellation
Intended for the facultiesFEIIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
CUB021 Ing. Jakub Čubík, Ph.D.
PLU042 Ing. Jan Plucar, Ph.D.
REZ106 Ing. Filip Řezáč, Ph.D.
ROZ132 Ing. Jan Rozhon, Ph.D.
SKA206 Ing. Lenka Skanderová, Ph.D.
ZEL01 prof. Ing. Ivan Zelinka, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2

Subject aims expressed by acquired skills and competences

The aim of the course is to acquaint its listeners with a new branch of sport - Esport. Esport is a sports competition in a virtual computer environment in the form of a computer game. Learning outcomes of the course unit, the aim of the course are to give the student a basic overview of the issue in three points of view: 1. Esport issues and PC environment, 2. computer security in Esport and 3. the role of artificial intelligence in Esport. Upon successful completion of this course, the graduate will understand the problems of Esport in the basic concept, including closely related areas. He will also be able to continue in other Esport courses, which will be a deeper and more detailed specialization of this modern and popular area of sports activities.

Teaching methods



The course deals with the issue of Esport, the possibilities of using AI in the field of computer games and computer security in the field of Esport. Students will learn the basic principles of Esport, tournaments, the type of games used, the possibilities to participate in existing tournaments, the legal background of Esport and its national and supranational organization, then it will be acquainted with the AI and its application in computer science. games, mathematical tools to describe player behaviour, and ways to identify suspicious behaviour in online games. The course will also include an insight into the issue of computer security Esport and its abuse and protection.

Compulsory literature:

Reitman, Jason & Anderson-Coto, Maria & Wu, Minerva & Lee, Je Seok & Steinkuehler, Constance. (2019). Esports Research: A Literature Review. Games and Culture. 155541201984089. 10.1177/1555412019840892. Rosell Llorens, M., 2017. eSport gaming: the rise of a new sports practice. Sport, Ethics and Philosophy, 11(4), pp.464-476. Li, R., 2017. Good luck have fun: The rise of eSports. Simon and Schuster. BULLOCK, Jessey a Jeff T. PARKER. Wireshark for security professionals: using Wireshark and the Metasploit framework. Indianapolis, Indiana: Wiley, [2017]. ISBN 978-1-118-91821-0. Kap. 1-4. MÖLLER, Sebastian a Alexander RAAKE. Quality of experience: advanced concepts, applications and methods. Cham: Springer, [2014]. ISBN 978-3319026800. Reitman, Jason & Anderson-Coto, Maria & Wu, Minerva & Lee, Je Seok & Steinkuehler, Constance. (2019). Esports Research: A Literature Review. Games and Culture. 155541201984089. 10.1177/1555412019840892. Funk, D., Pizzo, A.D., Baker, B.J. (2018). eSport management: Embracing eSport education and research opportunities. Sport Management Review, 21(1), 7-13. https://doi.org/10.1016/j.smr.2017.07.008 Freeman, Guo & Wohn, Donghee. (2017). Understanding eSports Team Formation and Coordination. Computer Supported Cooperative Work (CSCW). 10.1007/s10606-017-9299-4. Yan, J., 2018, March. How Does Match-Fixing Inform Computer Game Security?. In Cambridge International Workshop on Security Protocols (pp. 166-170). Springer, Cham. McDonald, B.D. and Maymin, P.Z., 2019. System and Method for Using Artificial Intelligence to Create Live, Mobile, Betting System Offering Time-Sensitive, Curated and Player-Restricted Bets on Sub-Outcomes of Sports and Esport Events. U.S. Patent Application 16/440,382. Jenny, S.E., Manning, R.D., Keiper, M.C. and Olrich, T.W., 2017. Virtual (ly) athletes: where eSports fit within the definition of “Sport”. Quest, 69(1), pp.1-18. Raessens, J. and Goldstein, J., 2011. Handbook of computer game studies. The MIT Press. Hingston, P., 2009. A Turing test for computer game bots. IEEE Transactions on Computational Intelligence and AI in Games, 1(3), pp.169-186. Soboleva, E.V. and Shalaginova, N.V., 2019, December. Simulation of artificial intelligence in a computer game. In Journal of Physics: Conference Series (Vol. 1399, No. 3, p. 033050). IOP Publishing.

Recommended literature:

Skubida, D., 2016. Can some computer games be a sport?: Issues with legitimization of eSport as a sporting activity. International Journal of Gaming and Computer-Mediated Simulations (IJGCMS), 8(4), pp.38-52. Denning, T., Lerner, A., Shostack, A. and Kohno, T., 2013, November. Control-Alt-Hack: the design and evaluation of a card game for computer security awareness and education. In Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security (pp. 915-928). Westera, W., Prada, R., Mascarenhas, S., Santos, P.A., Dias, J., Guimarães, M., Georgiadis, K., Nyamsuren, E., Bahreini, K., Yumak, Z. and Christyowidiasmoro, C., 2020. Artificial intelligence moving serious gaming: Presenting reusable game AI components. Education and Information Technologies, 25(1), pp.351-380.

Way of continuous check of knowledge in the course of semester

The examination is based on the elaboration of the protocols of the subject, by which the student demonstrates not only the understanding of the lecture information but also the ability to implement them in the given programming environment. To obtain a credit, you must hand over all the required protocols and have at least 80% of physical attendance at the laboratories. Credit is a vital condition for admission to the exam. The exam is oral.


Other requirements

It is required the ability to create simple programs in arbitrary programming language and apply lecture knowledge into algorithms. Additional requirements are not defined.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

Lectures: 1. History of Esport (beginnings, introduction to Esport as such) 2. Esport today (current status of Esport, game studios, tournaments) 3. Economy of things (teams, money movement, advertising) 4. Esport and everything around it (stream, doping, VR, future) 5. Network technologies used in Esport (protocols, quality) 6. Network requirements for Esport (stream, multiplayer, STADIA) 7. Computer security in Esport and major incidents associated with Esport 8. Internet user identity, personal data protection, password and keylogger issues, electronic licenses, their administration and payments in the Internet environment 9. Denial of service attacks (DOS, DDOS) 10. Detection of cheats and programs enhancing athletes performance, Pay for play services, booster services, farming and sale of funds 11. The role of AI in Esport, basic algorithms and principles. 12. AI algorithms 13. AI Bot, structure, functionality and creation 14. AI possibilities in games, examples and demonstrations Exercise on computer classroom: 1. Game titles, single / multi player, RPG, MMO, strategy, simulators, Esport, etc.), division into group title selection, team creation strategy, role setting, team platforms. 2. Team play, tournament platform, admin part. 3. Stream, content, technology for stream, software, broadcasting. 4. Integral team training, streaming, media analysis, reach. 5. Simulation of line speed and effect on stream 6. Analysis of data communication in Esport 7. Infection vectors and possible prevention. Sample on prepared examples 8. User identity and password issues. Keylogger creation and testing 9. Spy malware and collecting sensitive data through a scripting framework 10. Denial of service (DOS) attacks, disruption of training for athletes 11. Basic evolutionary principles and algorithms, machine learning methods 12. Neural networks - use in gaming issues 13. Using AI in games, playing a prepared game, collecting data 14. Collection and analysis of game data

Conditions for subject completion

Full-time form (validity from: 2020/2021 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 45  25
        Examination Examination 55  26
Mandatory attendence parzicipation: Completed tasks from exercises and laboratories, 80% participation in laboratories

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Occurrence in special blocks

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