Latest News: Final Tally August 8, 2021
Welcome to my Alternative Olympic Games Medal Tally for the 2021 Tokyo Olympic Games.
The Final Tallies are now available.
Back again (maybe) for the Paris Games in 2024.
You can see the tallies for the past 4 Olympic Games using the links below.
You may get the impression that I like the Olympic Games. That impression would be wrong. I like the data and the fact that my alternative rankings militate against the bully nations of the world claiming glory.
I also found these Jacobin articles to be worth reading:
- The Olympics Is a Racket (July 19, 2021).
- Abolish the Olympics (July 20, 2021).
Introduction
The following analysis is derived from the Olympic Games Medal Tally and aims to present a different view of the Games. The absolute (official) medal count allows large nations to hear their national anthem a lot but hides facts like how large their economy is (the largest having more resources to devote to sport and nutrition etc), how large their population is (more people to win medals), and how much income per person the nation has (arguably the best measure of the capacity of the nation to mount a sport's campaign in pursuit of medals).
The following alternative medal counts modify the official tally to take into account size of economy, size of population and the income per head that each medal-winning nation enjoys.
The comparisons cannot be used to extrapolate anything. There are clearly not enough medals available at the Olympic Games for a largely populated country like China or the US or India, to name a few of several to win their 'fair share'. But then we also would expect the large countries to exhibit scale economies that smaller countries cannot. Whatever, the tables are not statistical or probabilistic in nature and carry no predictive value. They are just for some fun and should not be taken seriously.
The following Tables are available which modify the raw tally:
GDP per Weighted Medal
This table shows the Gross Domestic Product for the medal winning countries expressed in billions of 2011 International dollars for comparative purposes. The next columns are the actual Gold, Silver, Bronze and Total medals won by the respective nations. The Weighted Medal Total is formulated by treating a Gold medal as a complete medal, Silver as 0.666 of a medal, and Bronze as 0.3333 of a medal. So the formula for column (9) = (5) + 0.66(6) + 0.33(7).
Column (10) is gained by dividing (4) by (9). The division is done in this way to avoid very small numbers should we have presented Medals per $GDP. But it is a measure of how efficient the medal performance is for the scale of the economy. Column (10) can be expressed in words as the amount in millions of GDP (USD) per weighted medal. So the smaller this number the 'better' is the performance given the capacity of the economy (as measured by GDP).
- Column (1) shows rank according to weighted per capita total.
- Column (2) shows the actual rank according to official medal tally.
- Column (3) is nation.
- Column (4) is GDP in Billions of International dollars (purchasing-power parity) averaged over 2017-20.
- Columns (5) to (8) is Actual Official Gold, Silver, Bronze and Total medals, respectively.
- Columns (9) is the weighted total medals (as described above).
- Column (10) is the measure of how much GDP ($ billion) per weighted total medals.
The data is ranked according to Column (10).
The LOWEST number is best.
Last computed: 19:40 August 8, 2021 (Australian Time)
1 72 San Marino 2 0 1 2 3 1.3 1.5
2 21 Jamaica 29 4 1 4 9 6.0 4.8
3 86 Grenada 2 0 0 1 1 0.3 5.6
4 42 Bahamas 14 2 0 0 2 2.0 7.0
5 59 Fiji 12 1 0 1 2 1.3 8.9
6 33 Georgia 55 2 5 1 8 5.6 9.7
7 42 Kosovo 20 2 0 0 2 2.0 10.1
8 14 Cuba 137 7 3 5 15 10.6 12.9
9 13 New Zealand 209 7 6 7 20 13.3 15.8
10 69 Armenia 39 0 2 2 4 2.0 19.6
11 70 Kyrgyzstan 33 0 2 1 3 1.7 20.1
12 31 Slovenia 81 3 1 1 5 4.0 20.2
13 26 Croatia 115 3 3 2 8 5.6 20.4
14 71 Mongolia 39 0 1 3 4 1.7 23.5
15 28 Serbia 127 3 1 5 9 5.3 23.9
16 15 Hungary 316 6 7 7 20 12.9 24.5
17 19 Kenya 225 4 4 2 10 7.3 30.9
18 36 Uganda 100 2 1 1 4 3.0 33.5
19 59 Estonia 48 1 0 1 2 1.3 36.4
20 30 Bulgaria 161 3 1 2 6 4.3 37.4
21 77 Namibia 25 0 1 0 1 0.7 37.4
22 63 Bermuda 38 1 0 0 1 1.0 38.3
23 67 Azerbaijan 145 0 3 4 7 3.3 43.9
24 7 Netherlands 993 10 12 14 36 22.5 44.1
25 59 Latvia 59 1 0 1 2 1.3 44.5
26 6 Australia 1302 17 7 22 46 28.9 45.1
27 45 Belarus 184 1 3 3 7 4.0 46.4
28 25 Denmark 337 3 4 4 11 7.0 48.4
29 77 North Macedonia 34 0 1 0 1 0.7 52.0
30 18 Czech Republic 435 4 4 3 11 7.6 56.9
31 20 Norway 346 4 2 2 8 6.0 57.8
32 44 Ukraine 536 1 6 12 19 8.9 60.1
33 32 Uzbekistan 234 3 0 2 5 3.7 64.0
34 50 Slovakia 178 1 2 1 4 2.7 67.1
35 4 Great Britain 3096 22 21 22 65 43.1 71.8
36 68 Dominican Republic 192 0 3 2 5 2.6 72.9
37 38 Ecuador 199 2 1 0 3 2.7 74.8
38 58 Tunisia 125 1 1 0 2 1.7 75.1
39 23 Sweden 554 3 6 0 9 7.0 79.7
40 24 Switzerland 619 3 4 6 13 7.6 81.2
41 46 Venezuela 258 1 3 0 4 3.0 86.7
42 5 ROC 4028 20 28 23 71 46.1 87.4
43 86 Moldova 34 0 0 1 1 0.3 103.1
44 74 Jordan 103 0 1 1 2 1.0 103.9
45 36 Greece 317 2 1 1 4 3.0 105.9
46 56 Ethiopia 250 1 1 2 4 2.3 107.6
47 10 Italy 2569 10 10 20 40 23.2 110.7
48 41 Qatar 259 2 0 1 3 2.3 111.3
49 63 Puerto Rico 112 1 0 0 1 1.0 112.1
50 77 Bahrain 74 0 1 0 1 0.7 112.3
51 86 Botswana 40 0 0 1 1 0.3 122.0
52 11 Canada 1856 7 6 11 24 14.6 127.2
53 29 Belgium 597 3 1 3 7 4.7 128.3
54 3 Japan 5370 27 14 17 58 41.9 128.3
55 86 Burkina Faso 44 0 0 1 1 0.3 133.5
56 39 Israel 363 2 0 2 4 2.7 136.3
57 49 Hong Kong 455 1 2 3 6 3.3 137.6
58 77 Turkmenistan 91 0 1 0 1 0.7 138.3
59 17 Poland 1248 4 5 5 14 9.0 139.4
60 8 France 3088 10 12 11 33 21.6 143.3
61 53 Austria 499 1 1 5 7 3.3 150.6
62 56 Portugal 356 1 1 2 4 2.3 153.5
63 77 Lithuania 104 0 1 0 1 0.7 156.9
64 39 Ireland 431 2 0 2 4 2.7 162.1
65 83 Kazakhstan 484 0 0 8 8 2.6 183.4
66 22 Spain 1898 3 8 6 17 10.3 185.0
67 34 Taiwan 1231 2 4 6 12 6.6 185.9
68 16 South Korea 2235 6 4 10 20 11.9 187.2
69 46 Romania 576 1 3 0 4 3.0 193.2
70 9 Germany 4534 10 11 16 37 22.5 201.1
71 27 Iran 1118 3 2 2 7 5.0 224.5
72 12 Brazil 3142 7 6 8 21 13.6 231.0
73 66 Colombia 734 0 4 1 5 3.0 247.2
74 1 United States 20630 39 41 33 113 77.0 268.1
75 63 Morocco 277 1 0 0 1 1.0 277.1
76 52 South Africa 738 1 2 0 3 2.3 318.0
77 2 China 22234 38 32 18 88 65.1 341.7
78 50 Philippines 927 1 2 1 4 2.7 349.8
79 35 Turkey 2427 2 2 9 13 6.3 385.8
80 54 Egypt 1182 1 1 4 6 3.0 396.7
81 86 Côte d'Ivoire 133 0 0 1 1 0.3 402.7
82 85 Finland 272 0 0 2 2 0.7 412.8
83 86 Ghana 163 0 0 1 1 0.3 492.9
84 86 Kuwait 210 0 0 1 1 0.3 637.9
85 72 Argentina 1013 0 1 2 3 1.3 767.4
86 74 Malaysia 892 0 1 1 2 1.0 900.5
87 59 Thailand 1276 1 0 1 2 1.3 959.5
88 74 Nigeria 1042 0 1 1 2 1.0 1052.9
89 55 Indonesia 3161 1 1 3 5 2.7 1193.0
90 84 Mexico 2534 0 0 4 4 1.3 1919.9
91 48 India 8944 1 2 4 7 3.6 2457.1
92 77 Saudi Arabia 1628 0 1 0 1 0.7 2467.1
- ROC is the Russian Olympic Committee - the IOC refuse to recognise Russia as a result of systematic doping. Perhaps they should spread their non-recognition net wider given the broad incidence of drug abuse in other nations.
- Syria is excluded from the list. It has won one bronze medal but there is no reliable data from 2010 on the GDP aggregates, given the on-going civil war.
Weighted Per Capita Rankings
This measure shows the medals by million people and also a weighted medal tally per million people. The rankings are sorted on this latter measure. It takes the official medal tally and expresses the Gold, Silver and Bronze in per capita terms. In this case, I have chosen to use Medals per Million People as the per capita measure even if some countries have less than a million citizens. The measure just means that they would achieve this is scaled up proportionately. The weighted per capita total differs from the actual per capita total in that I have weighted a Gold medal as a complete medal, Silver as 0.666 of a medal, and Bronze as 0.3333 of a medal.
Various weightings could be applied but I chose this presumably defensible weighting. After all: "you don't win a silver, you lose gold!".
The Gold column is the actual Gold medals per million people in that country, the Silver column is the actual Silver medals per million people in that country, and the Bronze is the actual Bronze medals per million people in that country. The Unweighted total is the Total medals without the weighting applied. The final column is the Total medals per capita weighted as described above.
- Column (1) shows rank according to weighted per capita total.
- Column (2) shows the actual rank according to actual medals.
- Column (3) is nation.
- Column (4) is 2020 population in millions.
- Columns (5) to (8) is Actual Gold, Silver, Bronze and Total medals, respectively.
- Column (9) is the weighted total medals count.
- Column (10) is the weighted per capita total medals count (Column (9) divided by Column (4).
The nations are ranked according to column (10).
The HIGHEST number is best.
Last computed: 19:40 August 8, 2021 (Australian Time)
1 72 San Marino 0.03 0 1 2 3 1.3 39.2738 2 42 Bahamas 0.4 2 0 0 2 2.0 5.0859 3 86 Grenada 0.1 0 0 1 1 0.3 2.9621 4 13 New Zealand 4.8 7 6 7 20 13.3 2.7641 5 21 Jamaica 3.0 4 1 4 9 6.0 2.0260 6 31 Slovenia 2.1 3 1 1 5 4.0 1.9237 7 59 Fiji 0.9 1 0 1 2 1.3 1.4873 8 33 Georgia 4.0 2 5 1 8 5.7 1.4197 9 26 Croatia 4.1 3 3 2 8 5.7 1.3798 10 15 Hungary 9.7 6 7 7 20 13.0 1.3452 11 7 Netherlands 17.1 10 12 14 36 22.7 1.3223 12 25 Denmark 5.8 3 4 4 11 7.0 1.2080 13 6 Australia 25.5 17 7 22 46 29.0 1.1370 14 42 Kosovo 1.8 2 0 0 2 2.0 1.1111 15 20 Norway 5.4 4 2 2 8 6.0 1.1065 16 59 Estonia 1.3 1 0 1 2 1.3 1.0051 17 14 Cuba 11.3 7 3 5 15 10.7 0.9415 18 24 Switzerland 8.7 3 4 6 13 7.7 0.8855 19 41 Qatar 2.9 2 0 1 3 2.3 0.8099 20 18 Czech Republic 10.7 4 4 3 11 7.7 0.7157 21 59 Latvia 1.9 1 0 1 2 1.3 0.7069 22 23 Sweden 10.1 3 6 0 9 7.0 0.6927 23 69 Armenia 3.0 0 2 2 4 2.0 0.6745 24 4 Great Britain 67.9 22 21 22 65 43.3 0.6381 25 30 Bulgaria 6.9 3 1 2 6 4.3 0.6235 26 28 Serbia 8.7 3 1 5 9 5.3 0.6103 27 39 Ireland 4.9 2 0 2 4 2.7 0.5400 28 71 Mongolia 3.3 0 1 3 4 1.7 0.5082 29 50 Slovakia 5.5 1 2 1 4 2.7 0.4882 30 49 Hong Kong 7.5 1 2 3 6 3.3 0.4444 31 45 Belarus 9.4 1 3 3 7 4.0 0.4231 32 29 Belgium 11.6 3 1 3 7 4.7 0.4026 33 77 Bahrain 1.7 0 1 0 1 0.7 0.3914 34 11 Canada 37.7 7 6 11 24 14.7 0.3885 35 10 Italy 60.5 10 10 20 40 23.3 0.3858 36 53 Austria 9.0 1 1 5 7 3.3 0.3700 37 63 Puerto Rico 2.9 1 0 0 1 1.0 0.3495 38 3 Japan 126.5 27 14 17 58 42.0 0.3320 39 8 France 65.3 10 12 11 33 21.7 0.3318 40 67 Azerbaijan 10.1 0 3 4 7 3.3 0.3285 41 77 North Macedonia 2.1 0 1 0 1 0.7 0.3197 42 5 ROC 145.9 20 28 23 71 46.3 0.3174 43 39 Israel 8.7 2 0 2 4 2.7 0.3081 44 36 Greece 10.4 2 1 1 4 3.0 0.2878 45 34 Taiwan 23.8 2 4 6 12 6.7 0.2798 46 9 Germany 83.8 10 11 16 37 22.7 0.2704 47 77 Namibia 2.5 0 1 0 1 0.7 0.2621 48 70 Kyrgyzstan 6.5 0 2 1 3 1.7 0.2552 49 68 Dominican Republic 10.8 0 3 2 5 2.7 0.2456 50 77 Lithuania 2.7 0 1 0 1 0.7 0.2446 51 17 Poland 37.8 4 5 5 14 9.0 0.2377 52 16 South Korea 51.3 6 4 10 20 12.0 0.2340 53 1 United States 331.0 39 41 33 113 77.3 0.2335 54 56 Portugal 10.2 1 1 2 4 2.3 0.2288 55 22 Spain 46.8 3 8 6 17 10.3 0.2209 56 44 Ukraine 43.7 1 6 12 19 9.0 0.2057 57 46 Romania 19.2 1 3 0 4 3.0 0.1558 58 38 Ecuador 17.6 2 1 0 3 2.7 0.1511 59 83 Kazakhstan 18.8 0 0 8 8 2.7 0.1420 60 86 Botswana 2.4 0 0 1 1 0.3 0.1417 61 58 Tunisia 11.8 1 1 0 2 1.7 0.1410 62 19 Kenya 53.8 4 4 2 10 7.3 0.1363 63 85 Finland 5.5 0 0 2 2 0.7 0.1203 64 77 Turkmenistan 6.0 0 1 0 1 0.7 0.1104 65 32 Uzbekistan 33.5 3 0 2 5 3.7 0.1096 66 46 Venezuela 28.4 1 3 0 4 3.0 0.1054 67 74 Jordan 10.2 0 1 1 2 1.0 0.0979 68 86 Moldova 4.0 0 0 1 1 0.3 0.0826 69 63 Bermuda 12.1 1 0 0 1 1.0 0.0825 70 86 Kuwait 4.3 0 0 1 1 0.3 0.0780 71 35 Turkey 84.3 2 2 9 13 6.3 0.0751 72 36 Uganda 45.7 2 1 1 4 3.0 0.0656 73 12 Brazil 212.6 7 6 8 21 13.7 0.0643 74 27 Iran 84.0 3 2 2 7 5.0 0.0595 75 66 Colombia 50.9 0 4 1 5 3.0 0.0589 76 2 China 1439.3 38 32 18 88 65.3 0.0454 77 52 South Africa 59.3 1 2 0 3 2.3 0.0393 78 74 Malaysia 32.4 0 1 1 2 1.0 0.0309 79 72 Argentina 45.2 0 1 2 3 1.3 0.0295 80 54 Egypt 102.3 1 1 4 6 3.0 0.0293 81 63 Morocco 36.9 1 0 0 1 1.0 0.0271 82 50 Philippines 109.6 1 2 1 4 2.7 0.0243 83 56 Ethiopia 115.0 1 1 2 4 2.3 0.0203 84 77 Saudi Arabia 34.8 0 1 0 1 0.7 0.0191 85 59 Thailand 69.8 1 0 1 2 1.3 0.0191 86 86 Burkina Faso 20.9 0 0 1 1 0.3 0.0159 87 86 Côte d'Ivoire 26.4 0 0 1 1 0.3 0.0126 88 86 Ghana 31.1 0 0 1 1 0.3 0.0107 89 84 Mexico 128.9 0 0 4 4 1.3 0.0103 90 55 Indonesia 273.5 1 1 3 5 2.7 0.0097 91 74 Nigeria 206.1 0 1 1 2 1.0 0.0048 92 48 India 1380.0 1 2 4 7 3.7 0.0027
Weighted Medals per $US1000 per capita income
This table shows the weighted medal count in terms of GDP per persons. So it scales the size of the economy by the size of the population. The Weighted Medal Total is formulated by treating a Gold medal as a complete medal, Silver as 0.666 of a medal, and Bronze as 0.3333 of a medal. So the formula for column (9) = (5) + 0.66(6) + 0.33(7).
Column (10) is gained by dividing (9) by (4) then multiplying by 1000 (to get some numbers before the decimal point). Column (10) can be expressed in words as the number of weighted medals a country would have if every person had $US1000 per year. So the larger this number the 'better' is the performance given the wealth of the economy scaled by its population
- Column (1) shows rank according to weighted per capita total.
- Column (2) shows the actual rank according to actual medals.
- Column (3) is nation.
- Column (4) is GDP per person ($PPP) is the average 2017-20.
- Columns (5) to (8) is Actual Gold, Silver, Bronze and Total medals, respectively.
- Columns (9) is the weighted total medals (described above).
- Column (10) is the Weighted Medals per $PPP1000 GDP per person
The data is ranked according to Column (10).
The HIGHEST number is best. Australia slips relative to the Per Capita Rankings because while it is small in population terms, it is relatively rich. China, by comparison which is large in population is poor in terms of GDP per capita.
Last computed: 19:40 August 8, 2021 (Australian Time)
1 2 China 15906 38 32 18 88 65.1 4.0903 2 5 ROC 27436 20 28 23 71 46.1 1.6792 3 19 Kenya 4786 4 4 2 10 7.3 1.5253 4 1 United States 62958 39 41 33 113 77.0 1.2222 5 36 Uganda 2538 2 1 1 4 3.0 1.1779 6 3 Japan 42523 27 14 17 58 41.9 0.9842 7 4 Great Britain 46494 22 21 22 65 43.1 0.9274 8 12 Brazil 15015 7 6 8 21 13.6 0.9058 9 56 Ethiopia 2626 1 1 2 4 2.3 0.8836 10 14 Cuba 12300 7 3 5 15 10.6 0.8642 11 44 Ukraine 12803 1 6 12 19 8.9 0.6967 12 21 Jamaica 10490 4 1 4 9 6.0 0.5701 13 6 Australia 51426 17 7 22 46 28.9 0.5616 14 48 India 6578 1 2 4 7 3.6 0.5534 15 10 Italy 42514 10 10 20 40 23.2 0.5457 16 32 Uzbekistan 7097 3 0 2 5 3.7 0.5157 17 8 France 47586 10 12 11 33 21.6 0.4529 18 9 Germany 54654 10 11 16 37 22.5 0.4124 19 15 Hungary 32348 6 7 7 20 12.9 0.3997 20 7 Netherlands 57602 10 12 14 36 22.5 0.3913 21 33 Georgia 14677 2 5 1 8 5.6 0.3836 22 27 Iran 13509 3 2 2 7 5.0 0.3687 23 46 Venezuela 8882 1 3 0 4 3.0 0.3355 24 70 Kyrgyzstan 5236 0 2 1 3 1.7 0.3151 25 13 New Zealand 42324 7 6 7 20 13.3 0.3135 26 50 Philippines 8701 1 2 1 4 2.7 0.3046 27 63 Bermuda 3285 1 0 0 1 1.0 0.3044 28 11 Canada 49814 7 6 11 24 14.6 0.2929 29 28 Serbia 18169 3 1 5 9 5.3 0.2923 30 16 South Korea 43299 6 4 10 20 11.9 0.2758 31 17 Poland 32856 4 5 5 14 9.0 0.2724 32 22 Spain 40504 3 8 6 17 10.3 0.2533 33 54 Egypt 12048 1 1 4 6 3.0 0.2473 34 38 Ecuador 11610 2 1 0 3 2.7 0.2291 35 67 Azerbaijan 14576 0 3 4 7 3.3 0.2264 36 55 Indonesia 11894 1 1 3 5 2.7 0.2228 37 35 Turkey 29390 2 2 9 13 6.3 0.2140 38 45 Belarus 19440 1 3 3 7 4.0 0.2042 39 66 Colombia 14657 0 4 1 5 3.0 0.2026 40 26 Croatia 28214 3 3 2 8 5.6 0.1999 41 74 Nigeria 5252 0 1 1 2 1.0 0.1885 42 18 Czech Republic 40861 4 4 3 11 7.6 0.1867 43 30 Bulgaria 23145 3 1 2 6 4.3 0.1866 44 52 South Africa 12644 1 2 0 3 2.3 0.1835 45 42 Kosovo 11210 2 0 0 2 2.0 0.1784 46 58 Tunisia 10638 1 1 0 2 1.7 0.1560 47 69 Armenia 13090 0 2 2 4 2.0 0.1513 48 86 Burkina Faso 2195 0 0 1 1 0.3 0.1503 49 68 Dominican Republic 18646 0 3 2 5 2.6 0.1416 50 71 Mongolia 11853 0 1 3 4 1.7 0.1392 51 23 Sweden 54003 3 6 0 9 7.0 0.1289 52 63 Morocco 7826 1 0 0 1 1.0 0.1278 53 34 Taiwan 52166 2 4 6 12 6.6 0.1269 54 25 Denmark 58227 3 4 4 11 7.0 0.1195 55 24 Switzerland 72655 3 4 6 13 7.6 0.1049 56 31 Slovenia 38888 3 1 1 5 4.0 0.1026 57 36 Greece 29499 2 1 1 4 3.0 0.1014 58 83 Kazakhstan 26136 0 0 8 8 2.6 0.1010 59 46 Romania 29570 1 3 0 4 3.0 0.1008 60 59 Fiji 13287 1 0 1 2 1.3 0.1001 61 74 Jordan 10311 0 1 1 2 1.0 0.0960 62 20 Norway 64771 4 2 2 8 6.0 0.0923 63 29 Belgium 52186 3 1 3 7 4.7 0.0891 64 50 Slovakia 32651 1 2 1 4 2.7 0.0812 65 59 Thailand 18356 1 0 1 2 1.3 0.0725 66 56 Portugal 34608 1 1 2 4 2.3 0.0670 67 39 Israel 40426 2 0 2 4 2.7 0.0658 68 84 Mexico 20126 0 0 4 4 1.3 0.0656 69 77 Namibia 10124 0 1 0 1 0.7 0.0652 70 86 Côte d'Ivoire 5115 0 0 1 1 0.3 0.0645 71 86 Ghana 5442 0 0 1 1 0.3 0.0606 72 53 Austria 56244 1 1 5 7 3.3 0.0589 73 72 Argentina 22663 0 1 2 3 1.3 0.0582 74 49 Hong Kong 60924 1 2 3 6 3.3 0.0543 75 42 Bahamas 37186 2 0 0 2 2.0 0.0538 76 59 Latvia 30698 1 0 1 2 1.3 0.0433 77 77 Turkmenistan 15675 0 1 0 1 0.7 0.0421 78 77 North Macedonia 16528 0 1 0 1 0.7 0.0399 79 59 Estonia 36576 1 0 1 2 1.3 0.0364 80 74 Malaysia 27454 0 1 1 2 1.0 0.0361 81 39 Ireland 87694 2 0 2 4 2.7 0.0303 82 63 Puerto Rico 34856 1 0 0 1 1.0 0.0287 83 86 Moldova 12580 0 0 1 1 0.3 0.0262 84 41 Qatar 93560 2 0 1 3 2.3 0.0249 85 72 San Marino 60943 0 1 2 3 1.3 0.0217 86 86 Grenada 16639 0 0 1 1 0.3 0.0198 87 86 Botswana 17700 0 0 1 1 0.3 0.0186 88 77 Lithuania 36926 0 1 0 1 0.7 0.0179 89 77 Saudi Arabia 48300 0 1 0 1 0.7 0.0137 90 85 Finland 49396 0 0 2 2 0.7 0.0134 91 77 Bahrain 49399 0 1 0 1 0.7 0.0134 92 86 Kuwait 45099 0 0 1 1 0.3 0.0073
Past GDP and Per Capita Rankings
- Compare the Final 2000 Olympics table - Sydney
- Compare the Final 2004 Olympics table - Athens
- Compare the Final 2008 Olympics table - Beijing
- Compare the Final 2012 Olympics table - London
- Compare the Final 2016 Olympics table - Rio
- Compare the Final 2021 Olympics table - Tokyo
Data Sources Appendix
Population Data
The population data is sourced from the World Bank Indicators Database.The population counts (in millions) are at 2020.
Gross Domestic Product
The economic activity measure used for comparative purposes Gross domestic product based on purchasing-power-parity (PPP) valuation of country GDP as published by the International Monetary Fund in their World Economic Outlook (WEO). The latest data is April 2021. The data used is the average 2017-20 and the specific WEO series used is denoted PPPGDP.
The comparative unit is what the IMF refer to as the current international dollar. The IMF say that:
"These data form the basis for the country weights used to generate the World Economic Outlook country group composites for the domestic economy. The IMF is not a primary source for purchasing power parity (PPP) data. WEO weights have been created from primary sources and are used solely for purposes of generating country group composites. For primary source information, please refer to one of the following sources: the Organization for Economic Cooperation and Development, the World Bank, or the Penn World Tables."
Gross Domestic Product per Capita
The economic activity measure used for comparative purposes is GDP in PPP (Purchasing Power Parity (PPP) dollars per person as published by the IMF World Economic Outlook (last publication is April 2016).
The data used is the average 2017-20 and the specific WEO series used is denoted PPPPC.
The IMF note that the data "are derived by dividing GDP in PPP dollars by total population".
See additional notes applicable for GDP in PPP.