The Regional Breakdown of the

Transcription

1 The Regional Breakdown of the Online Poker Market Ingo Fiedler & Ann-Christin Wilcke Funded by the city of Hamburg 8 th European Conference on Gambling Studies and Policy Issues 16th September 2010

2 Introduction Online poker market operates in a gray area Turnover 2009: 2.4 billion $ Where does the money come from? How many active players come from which country? Do inter- and intra-country differences exist? What are the parameters influencing the player fraction in a population? What are the playing habits of poker players? 2

3 Data Set Online poker is a goldmine for data mining Data collection in corporation with PokerScout (independent market investigator) 6 months 5 poker sites (65% market share) 4.6 million player identities Origion (country or city) Limits played Session lenghts Number of tables 3

4 Limitations of the Data Set Only cash games (no tournaments) Not all sites accept US-players Non-identified origin of some player identities Potential false information 92% successful assignement of cities to regions and countries One player identity one player (multiple accounts) 4

5 The Online Poker Market Poker site 2009 a 2010 b Data Players Market Players Market collection? (Ø 7 days) share (Ø 7 days) share Pokerstars 22, % 29, % Yes Full Tilt Poker 12, % 14, % Yes ipoker Network 5, % 5, % No Party Poker 5, % 4, % No Cereus Network 2, % 1, % No Everest Poker 2, % 2, % Yes Microgaming 1, % 2, % No IPN (Boss Media) 1, % 2, % Yes Cake Poker Network 1, % 1, % Yes Ongame (bwin) 1, % 2, % No Others 6, % 7, % No Total 62, % 73, % a : 18th June 2009, b : 11th May 2010, 5

6 Players per Country Rank Country Observed player Extrapolated identities Extrapolated active identities whole market poker players Market share 1 USA 1,315,953 1,489,659 1,266, % 2 Germany 347, , , % 3 France 266, , , % 4 Russia 240, , , % 5 Canada 207, , , % 6 UK 161, , , % 7 Spain 151, , , % 8 Netherlands 143, , , % 9 Brazil 92, , , % 10 Australia 77, , , % 11 Hungary 73, ,766 95, % Others 991,676 1,525,655 1,296, % Non identified 522, , , % Total 4,591,342 6,528,719 5,549, % On average every player loses 432 USD per year. 6

7 Player Fraction in a Population Rank Country Active poker players Population Players/population 1 Denmark 70,848 5,515, % 2 Iceland 3, , % 3 Estonia 15,035 1,291, % 4 Netherlands 187,583 16,783, % 5 Norway 50,503 4,676, % 6 Finland 55,988 5,255, % 7 Sweden 80,083 9,074, % 8 Canada 270,749 33,759, % 9 Luxembourg 3, , % 10 Slovenia 14,790 2,003, % 14 Germany 454,950 82,282, % 15 Austria ,551% 19 Australia 101,511 21,262, % 25 USA 1,266, ,232, % 27 UK 210,706 62,348, % Total 5,549,411 6,842,454, % 7

8 Players per Internet User Rank Country Active poker players Internet user Players/internet users 1 Hungary 95,851 6,176, % 2 Estonia 15, , % 3 Portugal 78,316 5,168, % 4 Denmark 70,848 4,750, % 5 Iceland 3, , % 6 Cyprus 5, , % 7 Netherlands 187,583 14,872, % 8 Finland 55,988 4,480, % 9 Norway 50,503 4,431, % 10 Slovenia 14,790 1,298, % 12 Canada 270,749 26,224, % 21 Austria 45,234 6,143, % 22 Germany 454,950 64,123, % 28 Australia 101,511 17,033, % 29 USA 1,266, ,893, % Total 5,549,411 1,965,162, % 8

9 Player Fraction in the Federal States of the USA 9

10 Situation in Germany Observed Federal State Population player identities Extrapolated players Player fraction federal state Players/popu lation Proportion region to country Germany total 82,002, , , % 0.55% 1.00% Hamburg 1,772,100 8,737 18, % 1.04% 1.87 Bremen 661,866 2,862 6, % 0.91% 1.64 Berlin 3,431,675 13,768 28, % 0.84% 1.52 Nordrhein-Westfalen 17,933,064 58, , % 0.68% 1.23 Schleswig-Holstein 2,834,260 8,627 18, % 0.64% 1.15 Saarland 1,030,324 2,933 6, % 0.60% 1.08 Niedersachsen 7,947,244 21,155 44, % 0.56% 1.01 Mecklenburg-Vorpommern 1,664,356 4,140 8, % 0.52% 0.94 Hessen 6,064,953 14,786 31, % 0.51% 0.92 Rheinland-Pfalz 4,028,351 9,364 19, % 0.49% 0.88 Bayern 12,519,728 28,107 59, % 0.47% 0.85 Baden-Württemberg 10,749,506 23,186 48, % 0.45% 0.82 Sachsen 4,192,801 7,982 16, % 0.40% 0.72 Brandenburg 2,522,493 4,795 10, % 0.40% 0.72 Thüringen 2,267,763 3,947 8, % 0.37% 0.66 Sachsen-Anhalt 2,381,872 3,919 8, % 0.35%

11 Factors Influencing the Player Fraction in a Population: GDP per capita Only countries with more than 100,000 internet users Variable Sample (n=158) Regressionscoefficient t-value Significance Constant 0,150 4,116 0,000 GDP per capita in th. USD 0,009 5,815 0,000 R²=0,178; adjusted R²=0,173; F-value=33,812 (p=0,000) Player fraction per internet users percentage points if GDP per capita +1,000 USD. 11

12 Factors Influencing the Player Fraction in a Population: Culture Only countries with more than 100,000 internet users GDP per capita to control effect of culture R²= 50.06% F-Value Culture (p<0.001), F-Value GPD per capita (p<0.001) Sample (n=161) Culture N Mean Standard deviation Western Orthodox Islamic African Latin American Sinic Hindu Buddhist Total Direction of effect confirmed by Turkey-Test (compares mean values) 12

13 Factors Influencing the Player Fraction in a Population: Law & Order Regression Analysis 1: 15 Countries GDP per capita to control effect of legislation Prohibition of online poker = 0 Online poker unprohibited = 1 No significant effect of legislation Regression Analysis 2: 15 Countries GDP per capita to control effect of legislation Prohibition of online poker + regulation of cash flows= 0 Online Poker unprohibited or not enforced prohibition = 1 No significant effect of legislation Interpretation: Presently, prohibition of online poker is not enforced 13

14 Factors Influencing the Player Fraction in a Population: Age structure? Most players are between 18 and 35 years old From a non-representative survey among pokerstrategy.deusers Used as an indicator? Player fraction in relation to year olds? 14

15 Market Share of Poker Sites in Countries (of the whole market not the sample) Rank Country MarketshareIPN Market share Market share Market share Market share (Boss Media) Everest Poker FullTilt Poker Cake Poker Pokerstars 1 USA 0% 0% 42.01% 8.14% 38.25% 2 Germany 2.28% 3.47% 18.80% 1.06% 39.39% 3 France 12.54% 11.90% 13.94% 0.42% 26.20% 4 Russia 0.80% 0.03% 18.36% 5.74% 40.06% 5 Canada 0.60% 0.40% 29.17% 2.23% 32.60% 6 UK 4.22% 0.22% 23.22% 2.62% 34.73% 7 Spain 9.72% 0.94% 7.61% 0.45% 46.28% 8 Netherlands 0.71% 3.88% 12.51% 1.29% 46.61% 9 Brazil 1.76% 2.12% 16.49% 1.19% 43.44% 10 Australia 0.36% 0.18% 27.49% 1.73% 35.24% Total 3.74% 3.90% 19.66% 3.31% 34.39% Market share in active player identities has to be adjusted by playing habits (frequency, intensity, session length) 15

16 Add on: Playing habits

17 Playing habits: Overall IPN Boss Media Everest Poker Full Tilt Poker Cake Poker Pokerstars Player Identities 264, ,494 1,388, ,580 2,429,347 Player Identities in % 5.76% 6% 30.24% 5.09% 52.91% Total time played in h 5,161,670 6,535,372? 4,034,444? Averagetime playedin hours per player 19,53 23,72? 17,27? Number of Sessions 5,030,129 6,110,816? 4,063,332? Averagenumberof sessions per player ? 17.40? 17

18 Playing habits: Session Length IPN Boss Media Everest Poker Cake Poker Averagesessionlengthin minutes Median sessionlengthin minutes Standard deviation session length in min.* Top 5% sessionlengthsin min Maximum sessionlengthin hours Interquartil range session length in min. 31,98 41,98 36, *: Session time is not normally distributed (Kurtosis > 300,000). 18

19 Playing habits: Multitabling Multitabling:= Playing more than one table at the same time Averagenumberof tables played Median number of tables played Standard deviationof tables played* Maximum numberof tables played Top 5% numberof tables played IPN Boss Media Everest Poker Full Tilt Poker Cake Poker Pokerstars 2,08 2,43 2,66 2,14 3,12????? 2,08 2,331 2,764 2,479 4, ????? *: Number of tables is not normally distributed (Kurtosis > 100,000). Most people do not play much, but some play excessively Estimation: 5%-10% account for more than half of the playing volume (to be tested) 19

20 Summary Huge data set gathered First time the poker market can be broken down to countries and regions Many possibilities for data analysis GDP and culture have a huge impact on the fraction of active online poker players in a population Enforcement of poker prohibition is not strong enough to yield a significant effect Some people play excessively More results on playing habits will be availible soon Limits played Inter- and intra-country differences Factors influencing inter- and intra-country differences 20

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