The Regional Breakdown of the Online Poker Market€¦ · Gambling Research. Data Set • Online poker is a goldmine for data mining • Data collection in corporation with PokerScout

University of HamburgInstitute of Law & EconomicsGambling Research

The Regional Breakdown of the Online Poker Market

Ingo Fiedler & Ann-Christin Wilcke

Funded by the city of Hamburg

8th European Conference on Gambling Studies and Policy Issues

16th September 2010


Deutscher Suchtkongress 2010Prof. Dr. Michael Adams

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?

3The Regional Breakdown of the Online Poker MarketVienna 2010


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

The Regional Breakdown of the Online Poker MarketVienna 2010

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)



The Online Poker Market

Poker site

2009a 2010b

Data

collection?Players

(Ø

7 days)Market

sharePlayers

(Ø

7 days)Market

share

Pokerstars 22,000 35.07% 29,200 40.20% Yes

Full Tilt Poker 12,000 19.13% 14,600 20.10% Yes

iPoker Network 5,900 9.41% 5,900 5.99% No

Party Poker 5,300 8.45% 4,400 6.06% No

Cereus Network 2,300 3.67% 1,960 3.67% No

Everest Poker 2,050 3.27% 2,100 2.89% Yes

Microgaming 1,980 3.16% 2,000 2.75% No

IPN (Boss Media) 1,920 3.06% 2,250 3.10% Yes

Cake Poker Network 1,580 2.52% 1,300 1.79% Yes

Ongame (bwin) 1,260 2.01% 2,650 3.65% No

Others 6,450 10.25% 7,250 9.80% No

Total 62,720 100% 73,610 100%

6

a: 18th June 2009, www.pokerscout.com.b: 11th May 2010, www.pokerscout.com.



Players per Country

Rank Country Observed player

identitiesExtrapolated identities

whole market

Extrapolated

active poker

players

Market

share

1 USA 1,315,953 1,489,659 1,266,210 21.09%2 Germany 347,903 535,235 454,950 7.58%3 France 266,820 410,492 348,918 5.81%4 Russia 240,394 369,837 314,361 5.24%5 Canada 207,043 318,528 270,749 4.51%6 UK 161,128 247,889 210,706 3.51%7 Spain 151,431 232,971 198,025 3.30%8 Netherlands 143,446 220,686 187,583 3.12%9 Brazil 92,093 141,682 120,429 2.01%10 Australia 77,626 119,425 101,511 1.69%11 Hungary 73,298 112,766 95,851 1.60%

Others 991,676 1,525,655 1,296,807 21.60%

Non identified 522,531 803,894 683,310 11.38%

Total 4,591,342 6,528,719 5,549,411 100%


On average every player loses 432 USD per year.


Player Fraction in a PopulationRank Country Active poker players Population Players/population

1 Denmark 70,848 5,515,575 1.285%2 Iceland 3,910 308,910 1.266%3 Estonia 15,035 1,291,170 1.164%4 Netherlands 187,583 16,783,092 1.118%5 Norway 50,503 4,676,305 1.080%6 Finland 55,988 5,255,695 1.065%7 Sweden 80,083 9,074,055 0.883%8 Canada 270,749 33,759,742 0.802%9 Luxembourg 3,720 497,538 0.748%10 Slovenia 14,790 2,003,136 0.738%14 Germany 454,950 82,282,988 0.553%15 Austria 45.234 8.214.160 0,551%19 Australia 101,511 21,262,641 0.477%25 USA 1,266,210 310,232,863 0.408%27 UK 210,706 62,348,447 0.338%

Total 5,549,411 6,842,454,978 0.081%



Players per Internet User

9

Rank Country Active poker players Internet user Players/internet users

1 Hungary 95,851 6,176,400 1.552%

2 Estonia 15,035 969,700 1.550%

3 Portugal 78,316 5,168,800 1.515%

4 Denmark 70,848 4,750,500 1.491%

5 Iceland 3,910 301,600 1.296%

6 Cyprus 5,044 433,800 1.163%

7 Netherlands 187,583 14,872,200 1.261%

8 Finland 55,988 4,480,900 1.249%

9 Norway 50,503 4,431,100 1.140%

10 Slovenia 14,790 1,298,500 1.139%

12 Canada 270,749 26,224,900 1.032%

21 Austria 45,234 6,143,600 0.736%

22 Germany 454,950 64,123,800 0.709%

28 Australia 101,511 17,033,826 0.596%

29 USA 1,266,210 239,893,600 0.528%Total 5,549,411 1,965,162,316 0.282%



Player Fraction in the Federal States of the USA



Situation in Germany

11

Federal State PopulationObserved

player

identities

Extrapolated

players

Player

fraction

federal state

Players/popu

lation

Proportion

region to

country

Germany total 82,002,356 216,520 454,950 100% 0.55% 1.00%

Hamburg 1,772,100 8,737 18,358 4.04% 1.04% 1.87

Bremen 661,866 2,862 6,014 1.32% 0.91% 1.64

Berlin 3,431,675 13,768 28,929 6.36% 0.84% 1.52

Nordrhein‐Westfalen 17,933,064 58,212 122,315 26.89% 0.68% 1.23

Schleswig‐Holstein 2,834,260 8,627 18,127 3.98% 0.64% 1.15

Saarland 1,030,324 2,933 6,163 1.35% 0.60% 1.08

Niedersachsen 7,947,244 21,155 44,451 9.77% 0.56% 1.01

Mecklenburg‐Vorpommern 1,664,356 4,140 8,699 1.91% 0.52% 0.94

Hessen 6,064,953 14,786 31,068 6.83% 0.51% 0.92

Rheinland‐Pfalz 4,028,351 9,364 19,676 4.32% 0.49% 0.88

Bayern 12,519,728 28,107 59,058 12.98% 0.47% 0.85

Baden‐Württemberg 10,749,506 23,186 48,718 10.71% 0.45% 0.82

Sachsen 4,192,801 7,982 16,772 3.69% 0.40% 0.72

Brandenburg 2,522,493 4,795 10,075 2.21% 0.40% 0.72

Thüringen 2,267,763 3,947 8,293 1.82% 0.37% 0.66

Sachsen‐Anhalt 2,381,872 3,919 8,235 1.81% 0.35% 0.62



Factors Influencing the Player Fraction in a Population: GDP per capita

•

Only countries with more than 100,000 internet users

•

Player fraction per internet users +0.009 percentage points if GDP per capita +1,000 USD.


Sample (n=158)

VariableRegressions‐coefficient t‐value Significance

Constant 0,150 4,116 0,000GDP 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)


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 14.229 (p<0.001), F-Value GPD per capita 12.987 (p<0.001)

•

Direction of effect confirmed by Turkey-Test (compares mean values)

13

N Mean

Western 47 0.638 0.452Orthodox 13 0.450 0.326Islamic 41 0.076 0.108African 23 0.079 0.059Latin American 20 0.185 0.100Sinic 6 0.019 0.018Hindu 5 0.112 0.196Buddhist 6 0.128 0.157

Total 161 0.289 0.369

Standard deviationCulture

Sample (n=161)



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


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 18-35 year

olds?

15The

Regional Breakdown

of the

Online Poker MarketVienna 2010


Market Share of Poker Sites in Countries (of the

whole

market

not

the

sample)

16The

Regional Breakdown

of the

Online Poker MarketVienna 2010

Rank CountryMarket share

IPN

(Boss Media)Market share

Everest Poker Market share

Full Tilt

Poker

Market

share

Cake

Poker

Market share

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)


Add on: Playing habits


Playing habits: Overall

18

IPN Boss

MediaEverest

PokerFull Tilt Poker Cake Poker Pokerstars

Player Identities 264,394 275,494 1,388,483 233,580 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 ?

Average time played in

hours per player19,53 23,72 ? 17,27 ?

Number of Sessions 5,030,129 6,110,816 ? 4,063,332 ?

Average number of

sessions per player19.03 22.18 ? 17.40 ?



Playing habits: Session Length

19

IPN Boss Media Everest Poker Cake Poker

Average session length in

minutes61.57 64.17 59.57

Median session length in

minutes40 42 40

Standard deviation session

length in min.*67.88 69.18 66.66

Top 5% session lengths in min. 189 191 181

Maximum session length in

hours31,98 41,98 36,31

Interquartil range session length

in min.60 63 59

*: Session time is not normally distributed (Kurtosis > 300,000).



Playing habits: Multitabling

20

IPN Boss

MediaEverest

PokerFull Tilt Poker Cake Poker Pokerstars

Average number of

tables played2,08 2,43 2,66 2,14 3,12

Median number of

tables played? ? ? ? ?

Standard deviation of

tables played*2,08 2,331 2,764 2,479 4,243

Maximum number of

tables played44 25 27 98 74

Top 5% number of

tables played? ? ? ? ?

•

Multitabling:= Playing more than one table at the same time

•

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)

*: Number of tables is not normally distributed (Kurtosis > 100,000).



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



Thank you for your kind attention!

Do you want to know how many active players are from your country or region?

Contact us:[email protected]

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Documents

The Regional Breakdown of the Online Poker Market€¦ · Gambling Research. Data Set • Online poker is a goldmine for data mining • Data collection in corporation with PokerScout