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Towards a Community-Based Ranking System of Overwatch Players

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Entertainment Computing – ICEC 2022 (ICEC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13477))

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Abstract

Competitive games usually feature some sort of ranking system to rank players or teams based on their performance. As such these ranking systems allow to draw comparisons across players. In many cases, however, the details of the ranking system are not made transparent to the player community. On the other hand, the community may have a different opinion on which factors should more or less influence a player’s or team’s rank.

In this paper, we report on our first steps towards a community-based ranking system for the professional Overwatch scene built upon results of a survey conducted among the game’s community. Further, we reflect on challenges and discuss possibilities for future work.

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Notes

  1. 1.

    https://overwatchleague.com/en-us/ Accessed: July, 2022.

  2. 2.

    https://www.reddit.com/r/CompetitiveOverwatch/ (Accessed: July, 2022).

  3. 3.

    In Overwatch, players have one extra powerful ability, a so-called ultimate, that they can charge by healing or doing damage.

References

  1. Barrow, D., Drayer, I., Elliott, P., Gaut, G., Osting, B.: Ranking rankings: an empirical comparison of the predictive power of sports ranking methods. J. Quant. Anal. Sports 9(2), 187–202 (2013). https://doi.org/10.1515/jqas-2013-0013

    Article  Google Scholar 

  2. Blizzard Entertainment: Overwatch. Game [PC]. Blizzard Entertainment, Irvine, CA, USA, May 2016

    Google Scholar 

  3. Blizzard Entertainment: The Overwatch League - Stats Lab (beta) (2021). https://overwatchleague.com/en-us/statslab. Accessed July 2022

  4. Blizzard Entertainment: Power Rankings | The Overwatch League (2021). https://overwatchleague.com/en-us/power-rankings?utm_source=owlweb &utm_medium=navigationbar &utm_campaign=generalAccessed: July, 2022

  5. Boscá, J.E., Liern, V., Martínez, A., Sala, R.: Increasing offensive or defensive efficiency? An analysis of Italian and Spanish football. Omega 37(1), 63–78 (2009). https://doi.org/10.1016/j.omega.2006.08.002

    Article  Google Scholar 

  6. Cooper, S., Deterding, C.S., Tsapakos, T.: Player rating systems for balancing human computation games: testing the effect of bipartiteness. In: Proceedings of the First International Joint Conference of DIGRA AND FDG. DIGRA Digital Games and Research Association (2016)

    Google Scholar 

  7. Esports Tales: Overwatch competitive rank distribution: Pc and console - updated monthly (2022). https://www.esportstales.com/overwatch/competitive-rank-distribution-pc-and-console. Accessed: July 2022

  8. Geyser, W.: The incredible growth of esports [+ esports statistics] (2021). https://influencermarketinghub.com/growth-of-esports-stats/. Accessed: July 2022

  9. Gough, C.: Esports market revenue worldwide from 2019 to 2024 (2021). https://www.statista.com/statistics/490522/global-esportsmarket-revenue/. Accessed July 2022

  10. IBM: IBM and the Overwatch League (2021). https://newsroom.ibm.com/Overwatch-League. Accessed: July 2022

  11. Knudsen, C.: How many people play Overwatch? Player count tracker (2022). https://www.dexerto.com/overwatch/how-many-people-play-overwatch-player-count-tracker-2022-1643403/#:~:text=future%20of%20Overwatch-,Overwatch%20Monthly%20Active%20Players,around%20500%2C000%2D600%2C000%20daily%20players. Accessed July 2022

  12. Kou, Y., Gui, X., Kow, Y.M.: Ranking practices and distinction in league of legends. In: CHI PLAY 2016, pp. 4–9. Association for Computing Machinery, New York, NY, USA (2016). https://doi.org/10.1145/2967934.2968078

  13. Lewis, M.: Moneyball: The Art of Winning an Unfair Game. W. W. Norton & Company, London (2004)

    Google Scholar 

  14. McHale, I.G., Scarf, P.A., Folker, D.E.: On the development of a soccer player performance rating system for the English premier league. INFORMS J. Appl. Anal. 42(4), 339–351 (2012). https://doi.org/10.1287/inte.1110.0589

    Article  Google Scholar 

  15. Novak, A.R., Bennett, K.J.M., Pluss, M., Fransen, J.: Performance analysis in esports: Part 2 - modelling performance at the 2018 League of Legends world championship. Int. J. Sports Sci. Coach. 15(2019). https://doi.org/10.31236/osf.io/84fmy

  16. Plat Chat: Plat Chat (2019). https://www.youtube.com/c/PlatChat/featured. Accessed July 2022

  17. Railsback, D., Caporusso, N.: Investigating the human factors in esports performance. In: Ahram, T.Z. (ed.) AHFE 2018. AISC, vol. 795, pp. 325–334. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-94619-1_32

    Chapter  Google Scholar 

  18. Robertson, S., Gupta, R., McIntosh, S.: A method to assess the influence of individual player performance distribution on match outcome in team sports. J. Sports Sci. 34(19), 1893–1900 (2016). https://doi.org/10.1080/02640414.2016.1142106

    Article  Google Scholar 

  19. Sarkar, A., Williams, M., Deterding, S., Cooper, S.: Engagement effects of player rating system-based matchmaking for level ordering in human computation games. In: Proceedings of the 12th International Conference on the Foundations of Digital Games. Association for Computing Machinery, New York, NY, USA (2017). https://doi.org/10.1145/3102071.3102093

  20. Shim, K.J., Ahmad, M.A., Pathak, N., Srivastava, J.: Inferring player rating from performance data in massively multiplayer online role-playing games (MMORPGs). In: International Conference on Computational Science and Engineering, pp. 1199–1204. IEEE (2009). https://doi.org/10.1109/CSE.2009.452

  21. Tiedemann, T., Francksen, T., Latacz-Lohmann, U.: Assessing the performance of German bundesliga football players: a non-parametric metafrontier approach. CEJOR 19, 571–587 (2011). https://doi.org/10.1007/s10100-010-0146-7

    Article  Google Scholar 

  22. Wolf, J.: Overwatch league expansion will face serious stumbling blocks overseas play (2018). https://www.espn.com/esports/story/_/id/22386533/overwatch-leagueexpansion-face-serious-stumbling-blocks-overseas. Accessed July 2022

  23. Zook, A.: Building matchmaking systems. In: Wallner, G. (ed.) Data Analytics Applications in Gaming and Entertainment. Auerbach Publications, Boca Raton, FL, pp. 33–48. Auerbach Publications (2019)

    Google Scholar 

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Correspondence to Günter Wallner .

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Staat, D., Wallner, G., Bernhaupt, R. (2022). Towards a Community-Based Ranking System of Overwatch Players. In: Göbl, B., van der Spek, E., Baalsrud Hauge, J., McCall, R. (eds) Entertainment Computing – ICEC 2022. ICEC 2022. Lecture Notes in Computer Science, vol 13477. Springer, Cham. https://doi.org/10.1007/978-3-031-20212-4_25

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  • DOI: https://doi.org/10.1007/978-3-031-20212-4_25

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