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Computer Science > Human-Computer Interaction

arXiv:2308.14775 (cs)
[Submitted on 28 Aug 2023]

Title:Online Poker and Rummy -- Games of Skill or Chance?

Authors:Taranjit Kaur, Manas Pati Tripathi, Ashirbad Samantaray, Tapan K. Gandhi
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Abstract:The paper aims to investigate the degree of cognitive skills required for success in online versions of the popular card game rummy and poker. The study focuses on analyzing the impact of experience and learnable skills on success in the online card game. We also propose a framework to analyze online games to conclude on whether they are games of learnable skill or are they games of chance. The hypotheses proposed aim to test whether online and offline card games are comparable in terms of cognitive engagement and skill requirements. To assess these hypotheses, key elements of gameplay such as shuffling of cards, card deck randomness, and seating of players are analyzed. We also adopted statistical approaches to understand the characteristics of card games in terms of random chance or skill. From the analysis, we could see that the normality of the derived variables deviates significantly from the normal distribution showing a non-linear trend. It signifies that the mean of the involved skill variables is not zero as the user plays a greater number of games, thereby strengthening the assumption that the long-term success in online card games is attributed to skill and not chance. There is no difference in online and offline versions of card games (rummy and poker) from the perspective of requirement of skills. Moreover, our finding suggests that there is a preponderance of skills to succeed in online card gaming. Overall, the findings of this research contribute to a better understanding of cognitive skills in online gaming environments.
Subjects: Human-Computer Interaction (cs.HC)
Cite as: arXiv:2308.14775 [cs.HC]
  (or arXiv:2308.14775v1 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2308.14775

Submission history

From: Tapan Gandhi [view email]
[v1] Mon, 28 Aug 2023 11:10:41 UTC (1,384 KB)
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