Latest News: Final Standings, Revised Tuesday, August 13, 2024 at 10:40 AET
Welcome to my Alternative Olympic Games Medal Tally for the 2024 Paris Olympic Games.
Final rankings 1, 2, 3 - Dominica, Grenada, Jamaica (GDP), Dominica, Grenada, NZ (Per capita), and China, North Korea, Kenya (GDP per capita).
Note my treatment of the AIN athletes and the Refugee Olympic Team which is explained below.
We will revisit this in four years time and I may compile some new indicators depending on data availability.
You can see the tallies for the past 5 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 $GDP. But it is a measure of how efficient the medalperformance is for the scale of the economy. Column (10) can be expressed in words as the amount in millions of GDP (USD) per weighted medal. So the smaller this number the 'better' is the performance given the capacity of the economy (as measured by GDP).
- Column (1) shows rank according to weighted per capita total.
- Column (2) shows the actual rank according to official medal tally.
- Column (3) is nation.
- Column (4) is GDP in Billions of International dollars (purchasing-power parity) averaged over 2018-23.
- Columns (5) to (8) is Actual Official Gold, Silver, Bronze and Total medals, respectively.
- Columns (9) is the weighted total medals (as described above).
- Column (10) is the measure of how much GDP ($ billion) per weighted total medals.
The data is ranked according to Column (10).
The LOWEST number is best.
Last computed: Revised Tuesday, August 13, 2024 at 10:40 AET.
1 62 Dominica 1 1 0 0 1 1.0 0.9
2 80 Grenada 2 0 0 2 2 0.7 3.0
3 44 Jamaica 31 1 3 2 6 3.6 8.5
4 24 Georgia 67 3 3 1 7 5.3 12.6
5 84 Cape Verde 5 0 0 1 1 0.3 13.9
6 68 Kyrgyzstan 37 0 2 4 6 2.6 14.2
7 11 New Zealand 238 10 7 3 20 15.6 15.2
8 74 Fiji 13 0 1 0 1 0.7 19.0
9 66 Armenia 46 0 3 1 4 2.3 19.9
10 72 Moldova 37 0 1 3 4 1.7 22.5
11 73 Kosovo 23 0 1 1 2 1.0 23.3
12 55 Botswana 43 1 1 0 2 1.7 25.6
13 33 Bahrain 82 2 1 1 4 3.0 27.5
14 14 Hungary 361 6 7 6 19 12.6 28.6
15 13 Uzbekistan 296 8 2 3 13 10.3 28.7
16 30 Croatia 136 2 2 3 7 4.3 31.6
17 32 Cuba 157 2 1 6 9 4.6 33.9
18 34 Slovenia 92 2 1 0 3 2.7 34.7
19 27 Serbia 146 3 1 1 5 4.0 36.7
20 30 Azerbaijan 162 2 2 3 7 4.3 37.6
21 17 Kenya 275 4 2 5 11 7.0 39.4
22 26 Bulgaria 184 3 1 3 7 4.7 39.5
23 4 Australia 1464 18 19 16 53 35.8 40.9
24 79 Tajikistan 41 0 0 3 3 1.0 41.8
25 6 Netherlands 1112 15 7 12 34 23.6 47.1
26 70 Lithuania 119 0 2 2 4 2.0 60.1
27 -- Belarus 200 1 3 1 5 3.3 60.3
28 74 Cyprus 42 0 1 0 1 0.7 64.3
29 74 Mongolia 44 0 1 0 1 0.7 67.3
30 18 Norway 385 4 1 3 8 5.7 68.2
31 22 Ukraine 528 3 5 4 12 7.6 69.3
32 80 Albania 46 0 0 2 2 0.7 69.8
33 55 Uganda 117 1 1 0 2 1.7 70.8
34 52 Tunisia 143 1 1 1 3 2.0 72.1
35 49 Ecuador 220 1 2 2 5 3.0 74.0
36 29 Denmark 377 2 2 5 9 5.0 75.8
37 16 Sweden 623 4 4 3 11 7.6 81.6
38 5 France 3386 16 26 22 64 40.4 83.8
39 7 Great Britain 3413 14 22 29 65 38.1 89.6
40 41 Israel 435 1 5 1 7 4.6 93.9
41 51 Greece 350 1 1 6 8 3.6 96.1
42 47 Ethiopia 308 1 3 0 4 3.0 103.5
43 23 Romania 657 3 4 2 9 6.3 104.3
44 9 Italy 2813 12 13 15 40 25.5 110.2
45 19 Ireland 550 4 0 3 7 5.0 110.3
46 8 South Korea 2511 13 9 10 32 22.2 112.9
47 25 Belgium 667 3 1 6 10 5.6 118.3
48 12 Canada 2063 9 7 11 27 17.3 119.6
49 60 Guatemala 166 1 0 1 2 1.3 125.0
50 28 Czechia 476 3 0 2 5 3.7 130.1
51 59 Dominican Republic 225 1 0 2 3 1.7 135.4
52 43 Kazakhstan 548 1 3 3 7 4.0 138.1
53 68 North Korea 375 0 2 4 6 2.6 142.0
54 50 Portugal 395 1 2 1 4 2.7 149.1
55 48 Switzerland 681 1 2 5 8 4.0 171.5
56 74 Jordan 115 0 1 0 1 0.7 174.5
57 3 Japan 5759 20 12 13 45 32.2 178.8
58 36 Austria 544 2 0 3 5 3.0 181.8
59 80 Puerto Rico 120 0 0 2 2 0.7 182.2
60 37 Hong Kong 485 2 0 2 4 2.7 182.3
61 21 Iran 1451 3 6 3 12 8.0 182.5
62 55 St Lucia 311 1 1 0 2 1.7 187.5
63 15 Spain 2070 5 4 9 18 10.6 195.1
64 10 Germany 4940 12 13 8 33 23.2 212.7
65 84 Zambia 71 0 0 1 1 0.3 215.4
66 74 Panama 152 0 1 0 1 0.7 230.7
67 44 South Africa 879 1 3 2 6 3.6 241.5
68 60 Morocco 333 1 0 1 2 1.3 250.2
69 39 Algeria 615 2 0 1 3 2.3 264.0
70 42 Poland 1444 1 4 5 10 5.3 272.9
71 1 United States 23366 40 44 42 126 82.9 281.9
72 55 Chile 514 1 1 0 2 1.7 309.8
73 20 Brazil 3489 3 7 10 20 10.9 319.5
74 66 Colombia 840 0 3 1 4 2.3 363.6
75 44 Thailand 1381 1 3 2 6 3.6 379.3
76 35 Taiwan 1428 2 0 5 7 3.7 391.1
77 37 Philippines 1053 2 0 2 4 2.7 395.8
78 2 China 26600 40 27 24 91 65.7 404.6
79 84 Côte d'Ivoire 159 0 0 1 1 0.3 482.3
80 52 Argentina 1096 1 1 1 3 2.0 550.6
81 84 Slovakia 199 0 0 1 1 0.3 604.4
82 52 Egypt 1466 1 1 1 3 2.0 736.9
83 64 Türkiye 2893 0 3 5 8 3.6 797.0
84 84 Qatar 281 0 0 1 1 0.3 852.6
85 65 Mexico 2819 0 3 2 5 2.6 1067.9
86 62 Pakistan 1332 1 0 0 1 1.0 1331.9
87 84 Peru 469 0 0 1 1 0.3 1420.7
88 80 Malaysia 1012 0 0 2 2 0.7 1533.5
89 39 Indonesia 3623 2 0 1 3 2.3 1555.1
90 84 Singapore 643 0 0 1 1 0.3 1947.3
91 71 India 10554 0 1 5 6 2.3 4569.0
92 -- Russia 4479 0 1 0 1 0.7 6786.0
-- -- Refugee Olympic Team ----- 0 0 1 1 0.3 ------
Notes
- The - Refugee Olympic Team - "represents more than 100 million forcibly displaced people worldwide" and comprises "37 athletes, hosted by 15 National Olympic Committees and competing across 12 sports". I have no way of dealing with the complexity involved in integrating this group into the rankings. So I applaud the solidarity efforts to allow them to be in the sports, they are at the bottom of my tallies but at the top of my hopes and wishes.
- The Official Medal Tally publishes results for the so-called category - Individual Neutral Athlete - AIN (Athlètes Individuels Neutres) - which covers Russian and Belarussian athletes who have been allowed to compete as individuals but barred by the Western-dominated Olympic Committee from competing under their national flag because of the 'war in Ukraine'. It is always claimed that politics is separate from the sport but in isolating these individuals in this way, out of their normal team environment, the IOC is offering a particular and contested construction of the conflict that mirrors the NATO bias. I have decided to ignore that way of treating the achievements of these athletes and have instead used their national data in the rankings. So Belarus and Russia are in the Olympics whether the IOC like it or not. The Official Medal Tally, however, does not even list their medals and so I have decomposed them by athlete and nation but the official ranking is a - in my tables.
- I have also used Taiwan instead of the IOC's insistence in using Chinese Tapei.
- Data for North Korea is difficult to verify - I used the information in https://en.wikipedia.org/wiki/Economy_of_North_Korea. Probably underestimates GDP.
- Ireland's PPP GDP is also ridiculous given the way they treat private capital formation with the head offices of multinational corporations.
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 2023 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: Revised Tuesday, August 13, 2024 at 10:40 AET.
1 62 Dominica 0.1 1 0 0 1 1.0 13.6911 2 80 Grenada 0.1 0 0 2 2 0.7 5.2828 3 11 New Zealand 5.2 10 7 3 20 15.7 2.9986 4 33 Bahrain 1.4 2 1 1 4 3.0 2.0190 5 24 Georgia 3.8 3 3 1 7 5.3 1.4178 6 4 Australia 26.6 18 19 16 53 36.0 1.3509 7 6 Netherlands 17.9 15 7 12 34 23.7 1.3234 8 14 Hungary 9.6 6 7 6 19 12.7 1.3203 9 44 Jamaica 2.8 1 3 2 6 3.7 1.2970 10 34 Slovenia 2.1 2 1 0 3 2.7 1.2570 11 30 Croatia 3.9 2 2 3 7 4.3 1.1242 12 18 Norway 5.5 4 1 3 8 5.7 1.0265 13 19 Ireland 5.3 4 0 3 7 5.0 0.9501 14 29 Denmark 5.9 2 2 5 9 5.0 0.8405 15 66 Armenia 2.8 0 3 1 4 2.3 0.8392 16 16 Sweden 10.5 4 4 3 11 7.7 0.7274 17 26 Bulgaria 6.4 3 1 3 7 4.7 0.7256 18 74 Fiji 0.9 0 1 0 1 0.7 0.7113 19 70 Lithuania 2.9 0 2 2 4 2.0 0.6959 20 72 Moldova 2.5 0 1 3 4 1.7 0.6699 21 55 Botswana 2.7 1 1 0 2 1.7 0.6227 22 27 Serbia 6.6 3 1 1 5 4.0 0.6043 23 5 France 68.2 16 26 22 64 40.6 0.5963 24 73 Kosovo 1.8 0 1 1 2 1.0 0.5690 25 7 Great Britain 68.4 14 22 29 65 38.3 0.5606 26 84 Cape Verde 0.6 0 0 1 1 0.3 0.5567 27 74 Cyprus 1.3 0 1 0 1 0.7 0.5285 28 25 Belgium 11.8 3 1 6 10 5.7 0.4792 29 41 Israel 9.8 1 5 1 7 4.7 0.4780 30 48 Switzerland 8.8 1 2 5 8 4.0 0.4518 31 9 Italy 58.8 12 13 15 40 25.7 0.4366 32 12 Canada 40.1 9 7 11 27 17.3 0.4322 33 8 South Korea 51.7 13 9 10 32 22.3 0.4318 34 30 Azerbaijan 10.1 2 2 3 7 4.3 0.4284 35 32 Cuba 11.2 2 1 6 9 4.7 0.4168 36 68 Kyrgyzstan 7.1 0 2 4 6 2.7 0.3753 37 -- Belarus 9.2 1 3 1 5 3.3 0.3630 38 37 Hong Kong 7.5 2 0 2 4 2.7 0.3538 39 51 Greece 10.4 1 1 6 8 3.7 0.3538 40 28 Czechia 10.9 3 0 2 5 3.7 0.3372 41 23 Romania 19.1 3 4 2 9 6.3 0.3322 42 36 Austria 9.1 2 0 3 5 3.0 0.3285 43 13 Uzbekistan 36.4 8 2 3 13 10.3 0.2837 44 10 Germany 84.5 12 13 8 33 23.3 0.2761 45 3 Japan 124.5 20 12 13 45 32.3 0.2596 46 50 Portugal 10.5 1 2 1 4 2.7 0.2532 47 1 United States 334.9 40 44 42 126 83.3 0.2487 48 80 Albania 2.7 0 0 2 2 0.7 0.2428 49 15 Spain 48.4 5 4 9 18 10.7 0.2204 50 80 Puerto Rico 3.2 0 0 2 2 0.7 0.2079 51 22 Ukraine 37.0 3 5 4 12 7.7 0.2071 52 43 Kazakhstan 19.9 1 3 3 7 4.0 0.2009 53 74 Mongolia 3.4 0 1 0 1 0.7 0.1932 54 49 Ecuador 18.2 1 2 2 5 3.0 0.1648 55 52 Tunisia 12.5 1 1 1 3 2.0 0.1605 56 35 Taiwan 24.0 2 0 5 7 3.7 0.1531 57 74 Panama 4.5 0 1 0 1 0.7 0.1491 58 59 Dominican Republic 11.3 1 0 2 3 1.7 0.1471 59 42 Poland 36.7 1 4 5 10 5.3 0.1453 60 17 Kenya 55.1 4 2 5 11 7.0 0.1270 61 84 Qatar 2.7 0 0 1 1 0.3 0.1227 62 68 North Korea 26.2 0 2 4 6 2.7 0.1017 63 79 Tajikistan 10.1 0 0 3 3 1.0 0.0986 64 21 Iran 89.2 3 6 3 12 8.0 0.0897 65 55 Chile 19.6 1 1 0 2 1.7 0.0849 66 60 Guatemala 17.6 1 0 1 2 1.3 0.0757 67 55 St Lucia 22.0 1 1 0 2 1.7 0.0756 68 84 Slovakia 5.4 0 0 1 1 0.3 0.0614 69 44 South Africa 60.4 1 3 2 6 3.7 0.0607 70 74 Jordan 11.3 0 1 0 1 0.7 0.0587 71 84 Singapore 5.9 0 0 1 1 0.3 0.0563 72 39 Algeria 45.6 2 0 1 3 2.3 0.0512 73 44 Thailand 71.8 1 3 2 6 3.7 0.0510 74 20 Brazil 216.4 3 7 10 20 11.0 0.0508 75 2 China 1410.7 40 27 24 91 66.0 0.0468 76 66 Colombia 52.1 0 3 1 4 2.3 0.0448 77 64 Türkiye 85.3 0 3 5 8 3.7 0.0429 78 52 Argentina 46.7 1 1 1 3 2.0 0.0429 79 60 Morocco 37.8 1 0 1 2 1.3 0.0352 80 55 Uganda 48.6 1 1 0 2 1.7 0.0343 81 47 Ethiopia 126.5 1 3 0 4 3.0 0.0237 82 37 Philippines 117.3 2 0 2 4 2.7 0.0227 83 65 Mexico 128.5 0 3 2 5 2.7 0.0207 84 80 Malaysia 34.3 0 0 2 2 0.7 0.0194 85 52 Egypt 112.7 1 1 1 3 2.0 0.0177 86 84 Zambia 20.6 0 0 1 1 0.3 0.0162 87 84 Côte d'Ivoire 28.9 0 0 1 1 0.3 0.0115 88 84 Peru 34.4 0 0 1 1 0.3 0.0097 89 39 Indonesia 277.5 2 0 1 3 2.3 0.0084 90 -- Russia 143.8 0 1 0 1 0.7 0.0046 91 62 Pakistan 240.5 1 0 0 1 1.0 0.0042 92 71 India 1428.6 0 1 5 6 2.3 0.0016 -- -- Refugee Olympic Team ----- 0 0 1 1 0.3 ------
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 2018-23.
- 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: Revised Tuesday, August 13, 2024 at 10:40 AET.
1 2 China 18855 40 27 24 91 65.7 3.4866 2 68 North Korea 1500 0 2 4 6 2.6 1.7600 3 17 Kenya 5569 4 2 5 11 7.0 1.2516 4 13 Uzbekistan 8612 8 2 3 13 10.3 1.1972 5 1 United States 70476 40 44 42 126 82.9 1.1763 6 47 Ethiopia 3045 1 3 0 4 3.0 0.9787 7 5 France 51766 16 26 22 64 40.4 0.7808 8 7 Great Britain 50723 14 22 29 65 38.1 0.7509 9 3 Japan 45856 20 12 13 45 32.2 0.7024 10 4 Australia 56571 18 19 16 53 35.8 0.6332 11 20 Brazil 17298 3 7 10 20 10.9 0.6313 12 55 Uganda 2787 1 1 0 2 1.7 0.5957 13 22 Ukraine 13540 3 5 4 12 7.6 0.5628 14 9 Italy 47365 12 13 15 40 25.5 0.5390 15 68 Kyrgyzstan 5663 0 2 4 6 2.6 0.4661 16 21 Iran 17163 3 6 3 12 8.0 0.4632 17 8 South Korea 48564 13 9 10 32 22.2 0.4580 18 10 Germany 59167 12 13 8 33 23.2 0.3924 19 6 Netherlands 63614 15 7 12 34 23.6 0.3707 20 14 Hungary 37140 6 7 6 19 12.6 0.3393 21 11 New Zealand 46822 10 7 3 20 15.6 0.3334 22 44 Jamaica 11314 1 3 2 6 3.6 0.3217 23 12 Canada 53824 9 7 11 27 17.3 0.3205 24 71 India 7524 0 1 5 6 2.3 0.3070 25 24 Georgia 18036 3 3 1 7 5.3 0.2944 26 37 Philippines 9604 2 0 2 4 2.7 0.2770 27 30 Azerbaijan 16165 2 2 3 7 4.3 0.2666 28 44 South Africa 14691 1 3 2 6 3.6 0.2478 29 15 Spain 43718 5 4 9 18 10.6 0.2427 30 49 Ecuador 12472 1 2 2 5 3.0 0.2389 31 79 Tajikistan 4306 0 0 3 3 1.0 0.2299 32 32 Cuba 21437 2 1 6 9 4.6 0.2164 33 27 Serbia 21506 3 1 1 5 4.0 0.1855 34 23 Romania 34173 3 4 2 9 6.3 0.1844 35 44 Thailand 19764 1 3 2 6 3.6 0.1842 36 39 Indonesia 13350 2 0 1 3 2.3 0.1745 37 26 Bulgaria 27350 3 1 3 7 4.7 0.1700 38 39 Algeria 13870 2 0 1 3 2.3 0.1680 39 62 Pakistan 6023 1 0 0 1 1.0 0.1660 40 52 Tunisia 11988 1 1 1 3 2.0 0.1660 41 -- Belarus 21422 1 3 1 5 3.3 0.1545 42 66 Armenia 15505 0 3 1 4 2.3 0.1490 43 60 Guatemala 9152 1 0 1 2 1.3 0.1453 44 60 Morocco 9201 1 0 1 2 1.3 0.1446 45 66 Colombia 16605 0 3 1 4 2.3 0.1391 46 42 Poland 38351 1 4 5 10 5.3 0.1379 47 43 Kazakhstan 28782 1 3 3 7 4.0 0.1379 48 52 Egypt 14445 1 1 1 3 2.0 0.1378 49 16 Sweden 59785 4 4 3 11 7.6 0.1276 50 30 Croatia 34480 2 2 3 7 4.3 0.1250 51 65 Mexico 21906 0 3 2 5 2.6 0.1205 52 55 St Lucia 14150 1 1 0 2 1.7 0.1173 53 72 Moldova 14269 0 1 3 4 1.7 0.1156 54 51 Greece 32970 1 1 6 8 3.6 0.1104 55 64 Türkiye 34294 0 3 5 8 3.6 0.1058 56 55 Botswana 16550 1 1 0 2 1.7 0.1003 57 41 Israel 46587 1 5 1 7 4.6 0.0994 58 25 Belgium 57714 3 1 6 10 5.6 0.0977 59 84 Zambia 3690 0 0 1 1 0.3 0.0894 60 52 Argentina 24008 1 1 1 3 2.0 0.0829 61 28 Czechia 44465 3 0 2 5 3.7 0.0823 62 62 Dominica 12518 1 0 0 1 1.0 0.0799 63 18 Norway 71060 4 1 3 8 5.7 0.0795 64 59 Dominican Republic 21386 1 0 2 3 1.7 0.0776 65 29 Denmark 64420 2 2 5 9 5.0 0.0771 66 73 Kosovo 12971 0 1 1 2 1.0 0.0763 67 50 Portugal 38387 1 2 1 4 2.7 0.0690 68 74 Jordan 10473 0 1 0 1 0.7 0.0630 69 55 Chile 26382 1 1 0 2 1.7 0.0629 70 34 Slovenia 43955 2 1 0 3 2.7 0.0605 71 84 Côte d'Ivoire 5458 0 0 1 1 0.3 0.0605 72 35 Taiwan 60887 2 0 5 7 3.7 0.0599 73 33 Bahrain 54110 2 1 1 4 3.0 0.0553 74 48 Switzerland 78702 1 2 5 8 4.0 0.0504 75 74 Mongolia 13127 0 1 0 1 0.7 0.0503 76 36 Austria 60741 2 0 3 5 3.0 0.0492 77 74 Fiji 13858 0 1 0 1 0.7 0.0476 78 70 Lithuania 42192 0 2 2 4 2.0 0.0469 79 19 Ireland 108687 4 0 3 7 5.0 0.0459 80 80 Albania 16035 0 0 2 2 0.7 0.0412 81 37 Hong Kong 64857 2 0 2 4 2.7 0.0410 82 84 Cape Verde 8182 0 0 1 1 0.3 0.0403 83 80 Grenada 17697 0 0 2 2 0.7 0.0373 84 84 Peru 14296 0 0 1 1 0.3 0.0231 85 -- Russia 30576 0 1 0 1 0.7 0.0216 86 80 Malaysia 31019 0 0 2 2 0.7 0.0213 87 74 Panama 35269 0 1 0 1 0.7 0.0187 88 80 Puerto Rico 37689 0 0 2 2 0.7 0.0175 89 74 Cyprus 47458 0 1 0 1 0.7 0.0139 90 84 Slovakia 36632 0 0 1 1 0.3 0.0090 91 84 Qatar 98874 0 0 1 1 0.3 0.0033 92 84 Singapore 113234 0 0 1 1 0.3 0.0029 -- -- Refugee Olympic Team ----- 0 0 1 1 0.3 ------
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
- Compare the Final 2024 Olympics table - Paris
Data Sources Appendix
Population Data
The population data is sourced from the World Bank Indicators Database.The population counts (in millions) are at 2023.
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 2024. The data used is the average 2018-23 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 2024).
The data used is the average 2018-23 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.