Global Odd Index

The Professional Athlete Index

In this Olympic year, we wanted to understand the statistics behind truly mastering a sport and to celebrate the achievements of the few who do, by calculating the chances of someone being a professional athlete in their country of birth. We then added to the study by calculating where most professionals come from for a range of globally popular sports.

Making it to the top of a sport requires decades of extreme dedication and many thousands of hours of training and practice, which must all be in addition to a complementary set of in-built physical features that mean some people, and not others, have the tools to succeed.

Beyond physical attributes, your country of birth can heavily influence whether the ecosystem is favourable to excelling in a sport. An almost religious love of football across the nation ensures Brazil continues to produce elite footballers by the hundreds, despite limited investment in youth academies in comparison with other countries.

In many places, a sport’s popularity dictates how much financial investment it receives, and these factors combine to facilitate easier progression for budding athletes under the right conditions, or hinder those without.

Make it through these challenges to the upper stratosphere of athletes and you are still at the mercy of injuries or poor form that can limit performance levels and success.

There are obstacles at every turn, meaning only a tiny fraction of amateur sportsmen and women ever turn professional. Here are the probabilities of becoming a professional in a range of globally popular sports around the world.

Football

Number of players per team 11
Current world champions France

It is the world’s most popular sport, the most watched sport, and the sport that connects people across cultures even if they have nothing else in common. Around 250 million people play football globally, attracted by its simplicity and unpredictability. Ahead of the 2015/16 English Premier League season, Leicester City were given odds of 5000/1 to become champions, something they succeeded in doing in one of the greatest sporting shocks of all time. 

Its popularity arguably makes it harder to become a professional, with stiff competition for places restricting opportunities for progression for youngsters with talent. To give an example, there are around 11,000 boys in English football’s youth development system, training regularly at professional clubs. For those entering the system at the age of nine, under 0.5% will ever earn money from football. See below for the odds of becoming a professional footballer in different countries around the world.

Percentage of top tier footballers

This map shows the percentage of current top tier footballers that come from each country.

Country
Percentage of top tier footballers globally
Percentage of top tier footballers globally
Brazil
5.14%
Argentina
4.38%
Nigeria
3.44%
Colombia
3.23%
UK
2.65%
Serbia
2.63%
Saudi Arabia
2.62%
Uruguay
2.60%
Spain
2.47%
Algeria
2.39%
France
2.35%
Peru
1.88%
Czech Republic
1.84%
Netherlands
1.81%
1.79%
Chile
1.75%
India
1.75%
Mexico
1.73%
Ukraine
1.71%
Turkey
1.62%
Ecuador
1.60%
Iran
1.55%
Sweden
1.55%
Bolivia
1.53%
Tunisia
1.51%
Norway
1.50%
Poland
1.47%
Romania
1.47%
South Africa
1.46%
USA
1.42%
Germany
1.42%
Portugal
1.40%
Russia
1.38%
Croatia
1.37%
China
1.36%
Paraguay
1.36%
South Korea
1.35%
Belgium
1.20%
Bulgaria
1.18%
Denmark
1.16%
Iceland
1.13%
Slovakia
1.13%
Austria
1.12%
Italy
1.10%
Costa Rica
1.06%
Australia
1.01%
Hungary
0.99%
Greece
0.98%
Finland
0.90%
Ireland
0.87%
Switzerland
0.81%
Canada
0.69%
Ghana
0.61%
Bosnia
0.50%
Senegal
0.46%
Ivory Coast
0.42%
Cameroon
0.37%
Morocco
0.33%
Montenegro
0.25%
Slovenia
0.23%
Macedonia
0.19%
Albania
0.18%
Georgia
0.16%
New Zealand
0.14%
Israel
0.12%
Panama
0.09%
Jamaica
0.08%
Egypt
0.07%
Moldova
0.07%
Belarus
0.06%
Luxembourg
0.06%
Trinidad & Tobago
0.06%
Estonia
0.05%
Latvia
0.05%
Uzbekistan
0.04%
Haiti
0.04%
Kenya
0.04%
Lithuania
0.04%
Cyprus
0.03%
Kazakhstan
0.03%
Indonesia
0.02%
Malaysia
0.02%
Namibia
0.02%
El Salvador
0.02%
Thailand
0.02%
Cuba
0.01%
Dominican Republic
0.01%
Ethiopia
0.01%
Guatemala
0.01%
Hong Kong
0.01%
Puerto Rico
0.01%
Taiwan
0.01%
Bahamas
0.00%
Barbados
0.00%
Vietnam
0.00%
Philippines
0.00%
Afghanistan
%
Angola
%
Armenia
%
Azerbaijan
%
Bangladesh
%
Belize
%
Benin
%
Bhutan
%
Botswana
%
Brunei Darussalam
%
Burkina Faso
%
BDI
%
Cambodia
%
Central African Republic
%
Chad
%
Democratic Republic of the Congo
%
Djibouti
%
East Timor
%
Equatorial Guinea
%
Eritrea
%
Fiji
%
French Southern and Antarctic Lands
%
Gabon
%
Gambia
%
Greenland
%
Guinea
%
Guinea Bissau
%
Guyana
-%
Honduras
%
Iran
%
Iraq
%
Jordan
%
Kuwait
%
Kosovo
%
Kyrgyzstan
%
Laos
%
Lebanon
%
Lesotho
%
Liberia
%
Libya
%
Madagascar
%
Malawi
%
Mali
%
Mauritania
%
Mongolia
%
Mozambique
%
Myanmar
%
Nepal
%
New Caledonia
%
Nicaragua
%
Niger
%
North Korea
%
Northern Cyprus
%
Oman
%
Pakistan
%
Papua New Guinea
%
Qatar
%
Republic of the Congo
%
Rwanda
%
Sierra Leone
%
Solomon Islands
%
Somalia
%
South Sudan
%
Sri Lanka
%
Somaliland
%
Sudan
%
Suriname
-%
Swaziland
%
Syria
%
Tajikistan
%
Tanzania
%
Togo
%
Turkmenistan
%
Uganda
%
United Arab Emirates
%
Vanuatu
%
West Bank
%
Venezuela
%
Western Sahara
%
Yemen
%
Zambia
%
Zimbabwe
%
Falkland Islands
%
Odds of being a top tier footballer (1:X)

This map reveals the odds of being a top tier footballer in each country, ranked in order of probability. It shows that 1 in every 83 men born in Iceland in the study’s age bracket are top tier footballers, the best odds in the world.

Country
Odds of being a top tier footballer (1:X)
Odds of being a top tier footballer (1:X)
Iceland
82
Montenegro
258
Uruguay
451
Serbia
546
Norway
777
Croatia
802
Slovakia
1,075
Finland
1,166
Czech Republic
1,276
Denmark
1,343
Bosnia
1,421
Costa Rica
1,440
Bulgaria
1,470
Sweden
1,528
Austria
1,770
Peru
1,880
Portugal
1,889
Slovenia
1,924
Luxembourg
1,949
Ireland
2,236
Belgium
2,260
Switzerland
2,298
Paraguay
2,400
Greece
2,445
Hungary
2,504
Netherlands
2,539
Tunisia
2,814
Senegal
3,136
Macedonia
3,207
Namibia
3,236
Chile
3,512
Argentina
3,626
Spain
3,677
Bolivia
3,731
Algeria
3,741
Romania
3,766
Ecuador
4,508
Saudi Arabia
4,866
Albania
5,150
Jamaica
5,348
Australia
5,838
Colombia
6,284
UK
6,357
Ukraine
6,365
Georgia
6,658
Estonia
6,705
Poland
6,753
Cyprus
6,970
France
7,363
Trinidad & Tobago
7,947
New Zealand
9,312
Turkey
10,007
Canada
10,185
Iran
10,605
Italy
11,529
Latvia
11,713
Germany
12,667
Moldova
12,783
15,420
Brazil
15,713
Barbados
15,738
Panama
16,006
South Africa
16,240
South Korea
17,910
Lithuania
22,121
Russia
23,401
Israel
23,842
Ghana
24,528
Mexico
31,220
Nigeria
32,622
Ivory Coast
33,589
Cameroon
37,325
Morocco
38,972
Belarus
40,136
USA
55,393
El Salvador
143,837
Haiti
157,673
Kazakhstan
176,816
Puerto Rico
186,458
Hong Kong
200,741
Cuba
252,405
Uzbekistan
300,588
China
319,615
India
360,494
Guatemala
572,193
Egypt
589,345
Taiwan
639,736
Dominican Republic
686,706
Kenya
701,467
Malaysia
704,705
Thailand
1,050,249
Indonesia
4,981,770
Philippines
6,098,472
Ethiopia
8,842,898
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International Results
Percentage of top tier athletes globally Odds of being a top tier athlete (1:X)
# Country Country Code
13 Guyana GUY - - - - 0.27 - - - 0 0 0 0 130,535 0 0 0
52 Suriname SUR - - - - 0.27 - - - 0 0 0 0 63,939 0 0 0
69 Albania ALB 0.18 0.00 0.01 0.00 0.00 0.00 0.03 0.30 5,150 0 272,912 0 0 0 38,988 45,486
70 Argentina ARG 4.38 0.00 3.77 3.76 0.53 0.90 0.35 0.10 3,626 0 13,198 42,552 2,276,485 267,823 57,634 2,276,485
71 Australia AUS 1.01 1.57 1.26 1.26 1.59 6.27 2.59 2.40 5,838 12,356 14,719 21,983 282,104 14,225 2,894 35,264
72 Austria AUT 1.12 0.72 1.10 1.26 0.53 0.69 0.36 1.15 1,770 9,015 5,624 15,776 283,946 43,685 7,012 24,692
73 Belgium BEL 1.20 0.76 1.43 1.54 0.00 0.26 0.91 7.00 2,260 11,809 5,950 17,713 0 155,862 3,784 5,567
74 Bulgaria BGR 1.18 1.23 0.07 0.88 0.53 0.00 0.27 0.70 1,470 4,670 83,268 19,985 249,802 0 8,191 35,687
75 Bahamas BHS 0.00 0.00 0.08 0.11 0.00 0.00 0.33 0.00 0 0 5,326 12,427 0 0 505 0
76 Bosnia BIH 0.50 0.00 0.75 0.35 0.27 0.00 0.08 0.45 1,421 0 2,964 20,443 204,417 0 10,760 22,714
77 Belarus BLR 0.06 2.31 0.20 0.63 0.27 0.00 0.79 0.85 40,136 3,379 37,907 37,907 682,304 0 3,834 40,136
78 Bolivia BOL 1.53 0.00 0.00 0.42 0.00 0.00 0.08 0.00 3,731 0 0 136,452 0 0 86,181 0
79 Brazil BRA 5.14 0.00 2.77 2.07 13.79 0.16 1.29 0.00 15,713 0 91,301 393,057 445,968 7,730,098 79,420 0
80 Barbados BRB 0.00 0.00 0.01 0.04 0.00 0.00 0.18 0.00 15,738 0 15,738 15,738 0 0 394 0
81 Canada CAN 0.69 11.36 1.39 1.37 1.86 1.21 1.86 0.70 10,185 2,036 15,878 51,703 288,053 87,669 4,802 144,027
82 Switzerland CHE 0.81 2.23 0.14 1.47 0.53 0.53 0.90 2.00 2,298 2,734 40,993 12,689 266,448 53,291 2,626 13,323
83 Chile CHL 1.75 0.00 0.07 0.70 0.00 0.42 0.20 0.00 3,512 0 293,170 87,952 0 219,878 38,240 0
84 China CHN 1.36 0.01 3.92 1.58 0.80 2.16 3.30 0.00 319,615 124,649,428 347,214 2,769,988 41,549,810 3,040,231 167,091 0
85 Ivory Coast CIV 0.42 0.00 0.14 0.04 0.00 0.00 0.04 0.10 33,589 0 312,631 4,064,197 0 0 508,025 2,032,099
86 South Africa ZAF 1.46 0.00 0.01 0.77 0.27 7.80 1.41 1.05 16,240 0 6,820,247 310,012 6,820,247 46,084 21,314 324,775
87 Vietnam VNM 0.00 0.00 0.00 0.11 0.00 0.00 0.10 0.00 0 0 0 1,007,298 0 0 137,360 0
88 Cameroon CMR 0.37 0.00 0.11 0.00 0.27 0.00 0.09 0.20 37,325 0 395,634 0 3,956,335 0 197,818 989,085
89 Colombia COL 3.23 0.00 0.09 0.81 0.00 0.42 0.42 3.85 6,284 0 727,244 252,955 0 727,244 61,894 75,559
90 Costa Rica CRI 1.06 0.00 0.00 0.04 0.00 0.00 0.08 0.10 1,440 0 0 437,383 0 0 23,021 218,692
91 Uzbekistan UZB 0.04 0.00 0.00 0.60 0.27 0.00 0.20 0.15 300,588 0 0 194,499 3,306,461 0 71,881 1,102,154
92 Cuba CUB 0.01 0.00 0.13 0.07 0.00 0.00 0.39 0.05 252,405 0 84,136 504,808 0 0 11,345 1,009,615
93 Cyprus CYP 0.03 0.00 0.13 0.14 0.00 0.00 0.19 0.05 6,970 0 5,228 15,681 0 0 1,494 62,719
94 USA USA 1.42 5.66 26.42 9.59 38.73 23.09 21.99 2.25 55,393 45,526 9,298 82,379 154,037 51,346 4,520 499,762
95 Czech Republic CZE 1.84 5.69 1.96 2.00 0.80 0.32 1.15 1.30 1,276 1,355 3,761 11,810 224,377 112,189 2,590 25,891
96 Germany DEU 1.42 1.09 1.81 4.53 0.53 2.48 2.95 3.25 12,667 54,399 31,133 40,062 2,583,925 109,955 7,737 79,506
97 Denmark DNK 1.16 2.46 0.17 0.21 0.53 2.00 0.44 2.45 1,343 2,073 27,845 74,253 222,756 11,725 4,501 9,093
98 Uruguay URY 2.60 0.00 0.17 0.32 0.00 0.00 0.06 0.55 451 0 20,984 37,304 0 0 25,826 30,522
99 Dominican Republic DOM 0.01 0.00 0.42 0.35 0.00 0.05 0.05 0.00 686,706 0 36,143 137,342 0 1,373,411 57,226 0
100 Algeria DZA 2.39 0.00 0.00 0.11 0.00 0.00 0.24 0.30 3,741 0 0 856,456 0 0 47,582 428,228
101 Ecuador ECU 1.60 0.00 0.01 0.42 0.27 0.00 0.22 0.85 4,508 0 2,073,173 172,765 2,073,173 0 42,311 121,952
102 Egypt EGY 0.07 0.00 0.01 0.67 0.00 0.00 0.19 0.05 589,345 0 11,197,542 589,345 0 0 260,409 11,197,542
103 Spain ESP 2.47 1.32 1.28 4.78 0.53 2.16 2.95 5.20 3,677 22,632 22,245 19,138 1,301,294 63,479 3,897 25,026
104 Estonia EST 0.05 1.05 0.99 0.42 0.00 0.05 0.39 0.90 6,705 1,021 1,032 7,822 0 93,853 1,068 5,215
105 Ethiopia ETH 0.01 0.00 0.00 0.00 0.00 0.00 1.81 0.60 8,842,898 0 0 0 0 0 43,243 1,473,817
106 Finland FIN 0.90 6.93 1.30 0.63 0.00 0.90 1.16 0.70 1,166 498 2,527 16,699 0 17,681 1,144 21,470
107 France FRA 2.35 2.37 2.02 6.53 0.80 3.64 3.38 7.65 7,363 23,936 26,783 26,639 1,651,535 71,807 6,486 32,384
108 UK GBR 2.65 1.01 1.05 3.58 3.18 10.17 3.93 2.60 6,357 54,821 50,253 47,297 402,013 24,997 5,421 92,773
109 Georgia GEO 0.16 0.64 0.64 0.28 1.06 0.00 0.04 0.30 6,658 5,469 2,375 38,278 76,554 0 34,025 51,037
110 Ghana GHA 0.61 0.00 0.01 0.25 0.00 0.00 0.13 0.00 24,528 0 4,292,264 613,181 0 0 143,076 0
111 Greece GRC 0.98 0.00 1.41 0.60 0.00 0.05 0.77 0.70 2,445 0 5,325 40,399 0 686,768 3,925 49,056
112 Guatemala GTM 0.01 0.00 0.00 0.04 0.00 0.05 0.11 0.55 572,193 0 0 1,716,578 0 1,716,578 68,664 156,053
113 Hong Kong HKG 0.01 0.00 0.01 0.28 0.00 0.16 0.06 0.00 200,741 0 401,480 50,186 0 133,827 30,884 0
114 Croatia HRV 1.37 1.48 1.23 1.30 0.00 0.00 0.33 0.70 802 2,442 2,787 8,510 0 0 4,199 22,490
115 Haiti HTI 0.04 0.00 0.03 0.04 0.27 0.00 0.02 0.00 157,673 0 578,130 1,734,389 1,734,389 0 346,879 0
116 Hungary HUN 0.99 2.31 1.69 0.70 0.27 0.00 0.71 0.85 2,504 3,508 4,571 35,421 708,405 0 4,401 41,672
117 Indonesia IDN 0.02 0.00 0.00 0.18 0.00 0.21 0.06 0.00 4,981,770 0 0 5,978,123 0 7,472,654 2,135,045 0
118 India IND 1.75 0.00 0.00 2.28 0.00 2.64 1.07 0.00 360,494 0 0 2,778,570 0 3,612,141 743,240 0
119 Ireland IRL 0.87 0.00 0.00 0.21 0.53 0.79 0.86 0.40 2,236 0 0 93,133 279,396 37,254 2,867 69,850
120 Iran IRN 1.55 0.00 1.40 0.14 0.27 0.00 0.22 0.40 10,605 0 36,782 1,176,999 4,707,991 0 96,082 588,500
121 Iceland ISL 1.13 0.78 0.07 0.00 0.00 0.16 0.12 0.60 82 388 4,381 0 0 8,762 940 2,191
122 Israel ISR 0.12 1.02 1.43 0.95 0.00 0.00 0.30 0.65 23,842 9,377 6,371 30,906 0 0 12,094 64,188
123 Italy ITA 1.10 1.90 1.66 7.13 0.27 1.53 2.59 9.30 11,529 21,877 23,892 17,890 3,631,378 125,221 6,208 19,525
124 Jamaica JAM 0.08 0.00 0.08 0.04 0.53 0.00 1.90 0.00 5,348 0 17,570 122,984 61,492 0 286 0
125 Japan JPN 1.79 0.54 2.57 3.05 1.06 7.96 7.84 0.65 15,420 168,958 33,792 91,277 1,985,246 52,590 4,477 610,846
126 Kazakhstan KAZ 0.03 1.02 0.10 0.56 0.53 0.00 0.28 0.90 176,816 19,868 196,462 110,510 884,076 0 27,628 98,232
127 South Korea KOR 1.35 0.30 1.76 1.23 1.59 6.91 0.51 0.00 17,910 267,261 43,161 198,537 1,158,126 53,045 59,904 0
128 Kenya KEN 0.04 0.00 0.03 0.14 0.00 0.05 4.32 0.05 701,467 0 2,572,044 1,929,033 0 7,716,130 7,899 7,716,130
129 Lithuania LTU 0.04 1.39 2.14 0.46 0.27 0.00 0.00 0.55 22,121 2,195 1,355 20,420 265,446 0 3,124 24,132
130 Luxembourg LUX 0.06 0.00 1.63 0.07 0.00 0.00 0.07 0.80 1,949 0 210 15,589 0 0 1,949 1,949
131 Latvia LVA 0.05 1.15 1.50 0.28 0.27 0.00 0.27 0.55 11,713 1,524 1,112 19,033 152,256 0 2,457 13,842
132 Morocco MAR 0.33 0.00 0.02 0.49 0.00 0.11 0.95 0.15 38,972 0 1,831,653 261,666 0 1,831,653 16,961 1,221,102
133 Moldova MDA 0.07 0.00 0.01 0.18 0.80 0.00 0.08 0.00 12,783 0 268,418 53,684 89,473 0 15,790 0
134 Mexico MEX 1.73 0.80 0.95 0.91 0.27 0.47 0.63 0.75 31,220 220,764 177,626 594,362 15,453,390 1,717,044 108,067 1,030,227
135 Macedonia MKD 0.19 0.00 0.12 0.21 0.00 0.00 0.00 0.45 3,207 0 15,741 28,858 0 0 0 19,239
136 Montenegro MNE 0.25 0.00 2.57 0.00 0.00 0.00 0.03 0.45 258 0 79 0 0 0 2,604 2,026
137 Malaysia MYS 0.02 0.00 0.00 0.11 0.00 0.58 0.14 0.10 704,705 0 0 1,174,508 0 320,321 113,663 1,761,762
138 Namibia NAM 0.02 0.00 0.00 0.04 0.00 0.00 0.08 0.55 3,236 0 0 22,644 0 0 1,259 2,059
139 Nigeria NGA 3.44 3.44 0.39 0.18 0.27 0.00 0.69 0.00 32,622 0 893,462 6,432,923 32,164,612 0 204,871 0
140 Netherlands NLD 1.81 0.85 0.25 2.18 0.80 0.79 1.21 5.65 2,539 17,802 57,275 21,248 439,098 87,820 4,826 11,658
141 Norway NOR 1.50 2.48 0.00 0.25 0.27 0.63 0.71 1.95 777 1,542 0 47,549 332,834 27,737 2,068 8,535
142 New Zealand NZL 0.14 1.47 1.74 0.46 1.06 0.90 0.64 2.80 9,312 2,983 2,402 29,367 95,440 22,457 2,652 6,818
143 Panama PAN 0.09 0.00 0.04 0.00 0.00 0.00 0.05 0.60 16,006 0 104,032 0 0 0 37,830 34,678
144 Peru PER 1.88 1.88 0.01 0.53 0.00 0.00 0.19 0.00 1,880 0 1,011,166 67,412 0 0 23,516 0
145 Philippines PHL 0.00 0.00 1.85 0.21 0.27 0.32 0.08 0.00 6,098,472 0 36,087 1,016,413 6,098,472 1,016,413 338,805 0
146 Poland POL 1.47 0.26 2.34 1.30 3.18 0.11 1.91 1.85 6,753 123,890 13,316 77,013 237,455 1,424,727 6,597 77,013
147 Puerto Rico PRI 0.01 0.00 0.83 0.04 0.00 0.05 0.24 0.50 186,458 0 4,908 372,915 0 372,915 6,781 37,292
149 Portugal PRT 1.40 0.00 0.01 1.16 0.00 0.47 0.87 1.45 1,889 0 760,961 23,060 0 84,552 3,883 26,241
151 Paraguay PRY 1.36 0.00 0.02 0.07 0.27 0.05 0.03 0.00 2,400 0 467,812 467,812 935,623 935,624 133,661 0
153 Romania ROU 1.47 0.72 0.01 1.79 0.00 0.00 0.49 0.05 3,766 25,220 1,588,807 31,154 0 0 14,187 1,588,807
155 Russia RUS 1.38 17.30 1.17 3.65 13.53 0.00 2.01 2.20 23,401 6,153 86,821 89,325 182,152 0 20,463 211,131
157 Saudi Arabia SAU 2.62 0.00 0.00 0.00 0.00 0.00 0.07 0.60 4,866 0 0 0 0 0 228,960 305,280
159 Senegal SEN 0.46 0.00 0.45 0.00 0.00 0.00 0.06 0.00 3,136 0 10,094 0 0 0 31,833 0
161 El Salvador SLV 0.02 0.00 0.01 0.07 0.00 0.00 0.02 0.60 143,837 0 1,006,852 503,427 0 0 251,714 83,905
163 Serbia SRB 2.63 0.76 3.41 1.47 0.27 0.00 0.30 0.65 546 6,233 1,319 9,794 411,314 0 6,050 31,640
165 Slovakia SVK 1.13 4.74 0.16 1.23 0.00 0.05 0.25 0.65 1,075 839 23,135 9,916 0 347,011 6,089 26,694
167 Slovenia SVN 0.23 2.58 2.06 0.46 0.00 0.00 0.35 0.90 1,924 557 662 9,617 0 0 1,583 6,946
169 Sweden SWE 1.55 6.21 0.20 1.40 1.33 4.38 1.16 0.70 1,528 1,252 37,670 16,952 135,609 8,170 2,579 48,433
171 Thailand THA 0.02 0.00 0.00 0.81 0.00 3.37 0.11 0.55 1,050,249 0 0 273,979 0 98,462 242,366 572,864
173 Trinidad & Tobago TTO 0.06 0.00 0.02 0.00 0.00 0.00 0.30 0.00 7,947 0 63,566 0 0 0 1,898 0
174 Tunisia TUN 1.51 0.00 0.13 0.39 0.00 0.00 0.09 0.00 2,814 0 101,725 110,972 0 0 61,035 0
175 Turkey TUR 1.62 0.00 1.81 0.81 0.00 0.00 0.84 0.55 10,007 0 27,970 201,865 0 0 24,309 422,079
177 Taiwan TWN 0.01 0.00 0.00 0.74 0.00 0.79 0.37 0.00 639,736 0 0 91,392 0 127,948 22,849 0
178 Ukraine UKR 1.71 1.51 1.57 1.62 0.80 0.00 1.22 0.80 6,365 23,721 21,745 68,068 1,043,698 0 11,387 195,694

Methodology

The Professional Athlete Index analyses eight globally popular team and individual sports. For each sport, a list of top tier male competitors from the latest completed season or ranking was gathered.

For team sports, player data was taken from every team playing in the top domestic league of the world’s 35 highest ranked nations. For individual sports, the players that feature in each sport’s international association ranking were included.

The athletes were assigned to countries based on their nationality. In cases of multiple nationalities, the athletes were assigned to their country of birth.

To calculate the odds of being a top tier athlete, we compared the number of top tier athletes from each country with that country’s number of births over a 12-year period – representing a typical length of a sporting career at the top level. The odds represent the chances of someone born during that period making it to the elite level of each sport.

  • Percentage of top tier athletes

    This percentage was calculated using the following equation:
    Total number of top tier athletes from each country / Total number of top tier athletes in each sport

  • Odds of being a top tier athlete (1:X)

    The odds were calculated for each country in the study using the following equation:

    1 / (number of top tier athletes from each country / total number of people born in each country over 12-year period) / (number of people born over 12-year period in each country that are not currently top tier athletes / total number of people born in each country over 12-year period)

     

    Source: Male births, years 1991 to 2003, UN Demographic Yearbook.

Sport-Specific Methodology Notes