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The data collected and analyzed in this paper are all publicly accessible on the internet, and we collect the data either with the consent of the website administrators or without violating the terms of service or acceptance usage listed on the hosting website. The data we use do not include any personally identifiable information (PII), and we further anonymize account-related information before storing them into our databases to preserve players’ privacy. In addition, our data collection and analysis procedures are performed solely passively, with absolutely no interaction with any human subject. To avoid abusing the hosting websites (i.e., the gambling websites), the request rates of data-collecting are limited to 1 request per second. Considering the legal concerns and potential negative effects of online gambling 39,40,41,42,43,44,45,46 , our analysis aims only to help better prevent adolescent gambling and problem gambling. Parameter estimation and model selection. In our analysis, the parameters of different distribution models are obtained by applying Maximum Likelihood Estimation (MLE) 47 . To select the best-fit distribution, we compare the models’ Akaike weights 48 derived from Akaike Information Criterion (AIC). Note that analyzing the fitting results, we constantly found that players show a tendency of using simple numbers when allowed to place wagers with arbitrary amounts of virtual currency. As a result, the curves of probability distribution functions appear to peak at simple numbers, and the corresponding cumulative distribution function shows a stepped behavior. This makes the fitting more difficult, especially for the determination of the start of the tail. To address this issue, we choose the start of the tail x min such that we obtain a small Kolmogorov– Smirnov (K– S) distance between the empirical distribution and the fitting distribution, while maintaining a good absolute fit between the complementary cumulative distribution functions (CCDF) of the empirical distribution and the best-fitted distribution. Candidate models for model selection in this paper include exponential distribution, power-law distribution, log-normal distribution, power-law distribution with sharp truncation, power-law distribution with exponential cutoff, and pairwise power-law distribution. More details about parameter fitting and model selection can be found in the article by Clauset et al . article 49 as well as in the previous paper by the authors 8 . Data Availability. The datasets generated and/or analysed during the current study are available from the authors on reasonable request. References. American Gaming Association. State of the states: The AGA survey of the commercial casino industry (2018) (Accessed October 1, 2018). Calado, F. & Griffiths, M. D. Problem gambling worldwide: An update and systematic review of empirical research (2000–2015). J. Behav. Addict. 5 , 592–613 (2016). ArticleGoogle Scholar Calado, F., Alexandre, J. & Griffiths, M. D. Prevalence of adolescent problem gambling: A systematic review of recent research. J. Gambl. Stud. 33 , 397–424, https://doi.org/10.1007/s10899-016-9627-5 (2017). ArticlePubMedGoogle Scholar Kahneman, D. & Tversky, A. Prospect theory: An analysis of decision under risk. Econometrica 47 , 263–291 (1979). ArticleMathSciNetGoogle Scholar Tversky, A. & Kahneman, D. Advances in prospect theory: Cumulative representation of uncertainty. J. Risk Uncertain. 5 , 297–323, https://doi.org/10.1007/BF00122574 (1992). ArticleMATHGoogle Scholar Barberis, N. A model of casino gambling. Manag. Sci. 58 , 35–51, https://doi.org/10.1287/mnsc.1110.1435 (2012). ArticleGoogle Scholar Meng, J. Understanding Gambling Behavior and Risk Attitudes Using Massive Online Casino Data . Bachelor’s thesis, Dartmouth College, Hanover, New Hampshire, USA (2018). Wang, X. & Pleimling, M. Behavior analysis of virtual-item gambling. Phys. Rev. E 98 , 012126, https://doi.org/10.1103/PhysRevE.98.012126 (2018). ArticleADSCASPubMedGoogle Scholar Rhee, I. et al . On the levy-walk nature of human mobility. IEEE/ACM Transactions on Netw. 19 , 630–643, https://doi.org/10.1109/TNET.2011.2120618 (2011). ArticleGoogle Scholar Brockmann, D. Anomalous diffusion and the structure of human transportation networks. Eur. Phys. J. Special Top. 157 , 173–189, https://doi.org/10.1140/epjst/e2008-00640-0 (2008). ArticleADSGoogle Scholar Kim, S., Lee, C.-H. & Eun, D. Y. Superdiffusive behavior of mobile nodes and its impact on routing protocol performance. IEEE Transactions on Mob. Comput. 9 , 288–304, https://doi.org/10.1109/TMC.2009.124 (2010). ArticleGoogle Scholar Wang, X. & Pleimling, M. Foraging patterns in online searches. Phys. Rev. E 95 , 032145, https://doi.org/10.1103/PhysRevE.95.032145 (2017). ArticleADSPubMedGoogle Scholar Toscani, G., Tosin, A. & Zanella, M. Multiple-interaction kinetic modelling of a virtual-item gambling economy. Phys. Rev. E 100 , 012308, https://doi.org/10.1103/PhysRevE.100.012308 (2019). Holden, J. T. Trifling and gambling with virtual money. UCLA Entertain. Law Rev. 25 , 41 (2018). Google Scholar Buhagiar, R., Cortis, D. & Newall, P. W. Why do some soccer bettors lose more money than others? J. Behav. Exp. Finance 18 , 85–93 (2018). ArticleGoogle Scholar Rodríguez, P., Humphreys, B. R. & Simmons, R. The Economics of Sports Betting (Edward Elgar Publishing, 2017). Limpert, E., Stahel, W. A. & Abbt, M. Log-normal distributions across the sciences: Keys and clues. BioScience 51 , 341–352, https://doi.org/10.1641/0006-3568(2001)051[0341:LNDATS]2.0.CO;2 (2001). ArticleGoogle Scholar Gibrat, R. Une loi des réparations Économiques: l’effet proportionnel. Bull. de Stat. Gen. France 19 , 419–513 (1930). Google Scholar Mitzenmacher, M. A brief history of generative models for power law and lognormal distributions. Internet Math. 1 , 226–251 (2003). ArticleMathSciNetGoogle Scholar Kendall, M. & Gibbons, J. D. Rank Correlation Methods (Oxford University Press, 1990). Taylor, J. M. Kendall’s and Spearman’s correlation coefficients in the presence of a blocking variable. Biometrics 43 , 409–416 (1987). ArticleMathSciNetCASGoogle Scholar Dubins, L. E., Savage, L. J., Sudderth, W. & Gilat, D. How to Gamble If You Must: Inequalities for Stochastic Processes . Dover Books on Mathematics (Dover Publications, 2014). Epstein, R. A. The Theory of Gambling and Statistical Logic (Academic Press, 2012). Cherstvy, A. G., Chechkin, A. V. & Metzler, R. Anomalous diffusion and ergodicity breaking in heterogeneous diffusion processes. New J. Phys. 15 , 083039, https://doi.org/10.1088/1367-2630/15/8/083039 (2013). ArticleADSMathSciNetGoogle Scholar Cherstvy, A. G., Chechkin, A. V. & Metzler, R. Particle invasion, survival, and non-ergodicity in 2d diffusion processes with space-dependent diffusivity. Soft Matter 10 , 1591–1601, https://doi.org/10.1039/C3SM52846D (2014). ArticleADSCASPubMedGoogle Scholar Cherstvy, A. G., Thapa, S., Wagner, C. E. & Metzler, R. Non-gaussian, non-ergodic, and non-fickian diffusion of tracers in mucin hydrogels. Soft Matter 15 , 2526–2551, https://doi.org/10.1039/C8SM02096E (2019). ArticleADSCASPubMedGoogle Scholar Inoue, J.-i & Sazuka, N. Crossover between Lévy and Gaussian regimes in first-passage processes. Phys. Rev. E 76 , 021111, https://doi.org/10.1103/PhysRevE.76.021111 (2007). ArticleADSCASGoogle Scholar Rahman, A. Correlations in the motion of atoms in liquid argon. Phys. Rev. 136 , A405–A411, https://doi.org/10.1103/PhysRev.136.A405 (1964). ArticleADSGoogle Scholar Toyota, T., Head, D. A., Schmidt, C. F. & Mizuno, D. Non-gaussian athermal fluctuations in active gels. Soft Matter 7 , 3234–3239, https://doi.org/10.1039/C0SM00925C (2011). ArticleADSCASGoogle Scholar Meiklejohn, S. et al . A fistful of bitcoins: Characterizing payments among men with no names. In Proceedings of the 2013 Conference on Internet Measurement Conference , 127–140, https://doi.org/10.1145/2504730.2504747 (ACM, New York, 2013). CSGOFAST. https://csgofast.com/ (Accessed on April 20, 2018). CSGOSpeed. https://csgospeed.com/home (Accessed on April 20, 2018). ethCrash. https://www.ethcrash.io/play (Accessed on August 1, 2018). SatoshiDICE. https://www.satoshidice.com/ (Accessed on August 1, 2018). Coinroll. https://coinroll.com/home (Accessed on August 1, 2018). Fiedler, I. Online gambling as a game changer to money laundering? (2013). (Accessed on January 8, 2019). Coindesk. Bitcoin (usd) price. https://www.coindesk.com/price/bitcoin/ (Accessed on August 1, 2018). CoinMetrics. Data downloads. https://coinmetrics.io/data-downloads/ (Accessed on August 1, 2018). Martinelli, D. Skin gambling: Have we found the millennial goldmine or imminent trouble? Gaming Law Rev. 21 , 557–565, https://doi.org/10.1089/glr2.2017.21814 (2017). ArticleGoogle Scholar Millar, S. I. Cryptocurrency expands online gambling. Gaming Law Rev. 22 , 174–174, https://doi.org/10.1089/glr2.2018.2232 (2018). ArticleGoogle Scholar Kairouz, S., Paradis, C. & Nadeau, L. Are online gamblers more at risk than offline gamblers? Cyberpsychology. Behav. Soc. Netw. 15 , 175–180, https://doi.org/10.1089/cyber.2011.0260 (2012). ArticleGoogle Scholar González-Roz, A., Fernández-Hermida, J. R., Weidberg, S., Martínez-Loredo, V. & Secades-Villa, R. Prevalence of problem gambling among adolescents: A comparison across modes of access, gambling activities, and levels of severity. J. Gambl. Stud. 33 , 371–382, https://doi.org/10.1007/s10899-016-9652-4 (2017). ArticlePubMedGoogle Scholar Gainsbury, S. M. Online gambling addiction: the relationship between internet gambling and disordered gambling. Curr. Addict. Reports 2 , 185–193, https://doi.org/10.1007/s40429-015-0057-8 (2015). ArticleGoogle Scholar Banks, J. Gambling, Crime and Society . (Palgrave Macmillan, London, 2017). BookGoogle Scholar Redondo, I. Assessing the risks associated with online lottery and casino gambling: A comparative analysis of players’ individual characteristics and types of gambling. Int. J. Mental Heal. Addict. 13 , 584–596, https://doi.org/10.1007/s11469-014-9531-0 (2015). ArticleGoogle Scholar Macey, J. & Hamari, J. eSports, skins and loot boxes: Participants, practices and problematic behaviour associated with emergent forms of gambling. New Media & Soc. 21 , 20–41, https://doi.org/10.1177/1461444818786216 (2019). ArticleGoogle Scholar Bauke, H. Parameter estimation for power-law distributions by maximum likelihood methods. Eur. Phys. J. B 58 , 167 (2007). ArticleADSCASGoogle Scholar Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach . (Springer, New York, 2002). MATHGoogle Scholar Clauset, A., Shalizi, C. & Newman, M. Power-law distributions in empirical data. SIAM Rev. 51 , 661–703, https://doi.org/10.1137/070710111 (2009). ArticleADSMathSciNetMATHGoogle Scholar. Acknowledgements. This work is supported by the US National Science Foundation through grant DMR-1606814, roll the dice कैसीनो के खेल. Author information. In the case of Dr KR Lakshmanan v. State of Tamil Nadu , 3 the Supreme Court of India recognised that horse racing, football, chess, rummy, golf and baseball are games of skill. It further held that betting on horse racing was a game of skill as it involved judging the form of the horse and jockey, and the nature of the race, among other variables. The states and union territories that allow horse-race betting are Andhra Pradesh, Assam, Delhi, Haryana, Karnataka, Maharashtra, Meghalaya, Nagaland (virtual via licence), Punjab, Sikkim (virtual via licence), Tamil Nadu, Telangana, Uttar Pradesh, Uttarakhand and West Bengal. However, active horse racing currently takes place at the turf clubs in Bangalore, Chennai, Delhi, Hyderabad, Kolkata, Mumbai, Mysore, Ooty and Pune. Prize competitions in India are regulated under the Prize Competitions Act 1955. 'Prize competition' has been defined under Section 2(d) of the said Act: 'Prize competition' means any competition (whether called a cross-word prize competition, a missing-word prize competition, a picture prize competition or by any other name) in which prizes are offered for the solution of any puzzle based upon the building up, arrangement, combination or permutation, of letters, words, or figures. The Prize Competition Act's applicability extends to the following states: Andhra, Bombay, Madras, Orissa, Uttar Pradesh, Hyderabad, Madhya Bharat, Patiala and East Punjab States Union, and Saurashtra, all erstwhile Part C States, and Pondicherry, Dadar and Nagar Haveli, Goa, Daman and Diu. The status of sports betting, whether it is a game of skill or a game of chance, has not been clarified by the Supreme Court of India or a high court of a state. The state of Sikkim took the initiative of legalising online sports betting within the state, with the promulgation of the Sikkim Online Gaming (Regulation) Act 2008. Under this Act, a licence for placing bets on sports games such as football, cricket, lawn tennis, chess, golf and horse racing can be issued. In Meghalaya, the sport of teer (a form of archery) has been excluded from within the ambit of the state's Gambling Act, and betting on it is licensed. The state government of Meghalaya promulgated the Meghalaya Regulation of Gaming Act, 2021, followed by the Meghalaya Regulation of Gaming Rules 2021. In the said enactments, inter alia, the process for issuance of licence for placing bets on various sports games as well as horse races has been laid down. In Nagaland, betting on virtual sports and team selection sports can be offered under a licence. Games of skill are identified as a separate category because various states in India (excluding Assam, 4 Odisha (Orissa), 5 Andhra Pradesh, 6 Tamil Nadu 7 and Telangana) 8 have gambling acts that exclude games of skill from the ambit of gambling. In the absence of a legislative definition of a game of skill, the Supreme Court in Dr KR Lakshmanan v. State of Tamil Nadu ; 9 State of Andhra Pradesh v. K Satyanarayana ; 10 and State of Bombay v. RMD Chamarbaugwala 11 has laid down that a game of chance is where the element of chance predominates over the element of skill, whereas a game of skill is where the element of skill predominates over the element of chance. The card games of rummy and bridge, along with other sports like golf and chess, have been classified as games of skill. In R Shankar Creation Association v. State of Karnataka , 12 the Karnataka High Court classified poker, darts, carom and chess, among others, as games of skill. The Punjab and Haryana High Court, the Bombay High Court and the Rajasthan High Court have classified daily fantasy sports, in the format offered by India's leading operator, Dream11, as a game of skill. However, the applicability of the Bombay High Court judgment was stayed by the Supreme Court of India on 6 March 2020. The government of Nagaland under the Nagaland Prohibition of Gambling and Regulation and Promotion of Online Games of Skill Act 2015 (the Nagaland Act) has defined games of skill, roll the dice कैसीनो के खेल. All games enumerated in Schedule A of the Nagaland Act will be classified as games of skill. Schedule A includes games such as chess, sudoku, quiz, bridge, poker, rummy, nap, virtual sports, virtual games (such as monopoly or racing) and virtual fantasy games. A similar definition exists in the Meghalaya Regulation of Gaming Act, 2021.

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