Latest News: August 20, 2016
Welcome to my Alternative Olympic Games Medal Tally for the 2016 Rio Olympic Games.
You can see the tallies for the past 4 Olympic Games using the links below.
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 $GDP. But it is a measure of how efficient the medal performance is for the scale of the economy. Column (10) can be expressed in words as the amount in millions of GDP (USD) per weighted medal. So the smaller this number the 'better' is the performance given the capacity of the economy (as measured by GDP).
- Column (1) shows rank according to weighted per capita total.
- Column (2) shows the actual rank according to official medal tally.
- Column (3) is nation.
- Column (4) is GDP in Billions of International dollars (purchasing-power parity) as at 2011.
- Columns (5) to (8) is Actual Official Gold, Silver, Bronze and Total medals, respectively.
- Columns (9) is the weighted total medals (as described above).
- Column (10) is the measure of how much GDP ($ billion) per weighted total medals.
The data is ranked according to Column (10).
The LOWEST number is best.
Last computed: 9:30 August 22, 2016 (Australian Time) - Final Standings
1 69 Grenada 1.4 0 1 0 1 0.7 2.1
2 16 Jamaica 25 6 3 2 11 8.6 2.9
3 51 Bahamas 9 1 0 1 2 1.3 6.9
4 54 Fiji 8 1 0 0 1 1.0 8.0
5 42 Armenia 25 1 3 0 4 3.0 8.5
6 34 North Korea 40 2 3 2 7 4.6 8.6
7 38 Georgia 36 2 1 4 7 4.0 8.9
8 69 Burundi 8 0 1 0 1 0.7 11.7
9 17 Croatia 91 5 3 2 10 7.6 11.9
10 15 Kenya 142 6 6 1 13 10.3 13.8
11 19 New Zealand 168 4 9 5 18 11.6 14.5
12 18 Cuba 129 5 2 4 11 7.6 16.8
13 54 Kosovo 17 1 0 0 1 1.0 17.4
14 32 Serbia 98 2 4 2 8 5.3 18.4
15 39 Azerbaijan 169 1 7 10 18 8.9 19.0
16 12 Hungary 258 8 3 4 15 11.3 22.9
17 54 Tajikistan 23 1 0 0 1 1.0 23.3
18 45 Slovenia 64 1 2 1 4 2.7 24.1
19 21 Uzbekistan 188 4 2 7 13 7.6 24.6
20 69 Niger 19 0 1 0 1 0.7 28.9
21 28 Denmark 259 2 6 7 15 8.3 31.3
22 40 Belarus 168 1 4 4 9 5.0 33.8
23 67 Mongolia 36 0 1 1 2 1.0 36.4
24 48 Bahrain 65 1 1 0 2 1.7 39.0
25 44 Ethiopia 162 1 2 5 8 4.0 40.7
26 22 Kazakhstan 429 3 5 9 17 9.3 46.3
27 37 Slovakia 161 2 2 0 4 3.3 48.5
28 64 Lithuania 82 0 1 3 4 1.7 49.9
29 31 Ukraine 339 2 5 4 11 6.6 51.3
30 78 Moldova 18 0 0 1 1 0.3 53.9
31 2 Great Britain 2679 27 23 17 67 47.8 56.1
32 51 Cote d'Ivoire 79 1 0 1 2 1.3 59.1
33 11 Netherlands 833 8 7 4 19 13.9 59.7
34 73 Kyrgyzstan 20 0 0 1 1 0.3 60.9
35 10 Australia 1138 8 11 10 29 18.6 61.3
36 26 Greece 286 3 1 2 6 4.3 66.2
37 29 Sweden 473 2 6 3 11 7.0 68.1
38 43 Czech Republic 332 1 2 7 10 4.6 71.8
39 54 Jordan 83 1 0 0 1 1.0 82.7
40 24 Switzerland 482 3 2 2 7 5.0 96.9
41 7 France 2647 10 18 14 42 26.5 99.9
42 4 Russian Federation 3718 19 18 19 56 37.2 100.1
43 65 Bulgaria 137 0 1 2 3 1.3 103.7
44 30 South Africa 724 2 6 2 10 6.6 109.3
45 78 Estonia 38 0 0 1 1 0.3 113.8
46 9 Italy 2171 8 12 8 28 18.6 117.0
47 35 Belgium 494 2 2 2 6 4.0 124.2
48 23 Colombia 667 3 2 3 8 5.3 125.7
49 75 Tunisia 127 0 0 3 3 1.0 128.3
50 54 Puerto Rico 132 1 0 0 1 1.0 131.9
51 8 South Korea 1849 9 3 9 21 14.0 132.5
52 78 Trinidad and Tobago 44 0 0 1 1 0.3 134.3
53 5 Germany 3841 17 10 15 42 28.6 134.5
54 14 Spain 1615 7 4 6 17 11.6 139.0
55 20 Canada 1632 4 3 15 22 10.9 149.3
56 47 Romania 414 1 1 3 5 2.7 156.2
57 33 Poland 1005 2 3 6 11 6.0 168.7
58 62 Ireland 257 0 2 0 2 1.3 195.0
59 6 Japan 4830 12 8 21 41 24.2 199.5
60 1 United States of America 17947 46 37 38 121 83.0 216.3
61 51 Independent Olympic Athlete * 288 1 0 1 2 1.3 216.8
62 13 Brazil 3192 7 6 6 19 12.9 246.7
63 27 Argentina 972 3 1 0 4 3.7 265.6
64 74 Norway 356 0 0 4 4 1.3 269.9
65 60 Malaysia 816 0 4 1 5 3.0 274.6
66 25 Iran 1371 3 1 4 8 5.0 275.3
67 35 Thailand 1108 2 2 2 6 4.0 278.4
68 48 Vietnam 552 1 1 0 2 1.7 332.7
69 41 Turkey 1589 1 3 4 8 4.3 369.5
70 65 Venezuela 516 0 1 2 3 1.3 390.7
71 3 China 19392 26 18 26 70 46.5 417.4
72 77 Israel 282 0 0 2 2 0.7 427.2
73 62 Algeria 579 0 2 0 2 1.3 438.4
74 78 Dominican Republic 150 0 0 1 1 0.3 453.6
75 54 Singapore 472 1 0 0 1 1.0 471.9
76 69 Qatar 320 0 1 0 1 0.7 484.6
77 50 Taiwan 1099 1 0 2 3 1.7 662.1
78 78 Finland 225 0 0 1 1 0.3 681.8
79 78 Morocco 274 0 0 1 1 0.3 828.9
80 61 Mexico 2227 0 3 2 5 2.6 843.6
81 78 Portugal 290 0 0 1 1 0.3 878.2
82 75 Egypt 1048 0 0 3 3 1.0 1058.5
83 69 Philippines 741 0 1 0 1 0.7 1122.8
84 46 Indonesia 2842 1 2 0 3 2.3 1225.1
85 78 Austria 404 0 0 1 1 0.3 1225.1
86 78 United Arab Emirates 648 0 0 1 1 0.3 1963.1
87 78 Nigeria 1092 0 0 1 1 0.3 3308.2
88 67 India 7965 0 1 1 2 1.0 8045.6
* is Fehaid Aldeehani who won the men's double trap gold medal and Abdullah Al-Rashidi who won the men's skeet bronze medal. Both are from Kuwait and they inherit that nation's economic data.
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 2011 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: 9:30 August 22, 2016 (Australian Time) - Final Standings
1 69 Grenada 0.1 0 1 0 1 0.7 6.2345 2 51 Bahamas 0.4 1 0 1 2 1.3 3.4362 3 16 Jamaica 2.7 6 3 2 11 8.7 3.1786 4 19 New Zealand 4.6 4 9 5 18 11.7 2.5373 5 17 Croatia 4.2 5 3 2 10 7.7 1.8144 6 28 Denmark 5.7 2 6 7 15 8.3 1.4674 7 45 Slovenia 2.1 1 2 1 4 2.7 1.2915 8 48 Bahrain 1.4 1 1 0 2 1.7 1.2097 9 12 Hungary 9.8 8 3 4 15 11.3 1.1510 10 54 Fiji 0.9 1 0 0 1 1.0 1.1209 11 38 Georgia 3.7 2 1 4 7 4.0 1.0870 12 42 Armenia 3.0 1 3 0 4 3.0 0.9935 13 39 Azerbaijan 9.7 1 7 10 18 9.0 0.9320 14 11 Netherlands 16.9 8 7 4 19 14.0 0.8263 15 10 Australia 23.8 8 11 10 29 18.7 0.7846 16 32 Serbia 7.1 2 4 2 8 5.3 0.7510 17 2 Great Britain 65.1 27 23 17 67 48.0 0.7367 18 29 Sweden 9.8 2 6 3 11 7.0 0.7139 19 18 Cuba 11.4 5 2 4 11 7.7 0.6730 20 37 Slovakia 5.4 2 2 0 4 3.3 0.6143 21 24 Switzerland 8.3 3 2 2 7 5.0 0.6032 22 64 Lithuania 2.9 0 1 3 4 1.7 0.5724 23 54 Kosovo 1.8 1 0 0 1 1.0 0.5573 24 22 Kazakhstan 17.5 3 5 9 17 9.3 0.5318 25 40 Belarus 9.5 1 4 4 9 5.0 0.5253 26 43 Czech Republic 10.6 1 2 7 10 4.7 0.4421 27 26 Greece 10.8 3 1 2 6 4.3 0.4003 28 7 France 66.8 10 18 14 42 26.7 0.3990 29 35 Belgium 11.3 2 2 2 6 4.0 0.3543 30 5 Germany 81.4 17 10 15 42 28.7 0.3520 31 51 Independent Olympic Athlete * 3.9 1 0 1 2 1.3 0.3419 32 67 Mongolia 3.0 0 1 1 2 1.0 0.3377 33 9 Italy 60.8 8 12 8 28 18.7 0.3069 34 20 Canada 35.9 4 3 15 22 11.0 0.3067 35 69 Qatar 2.2 0 1 0 1 0.7 0.2979 36 54 Puerto Rico 3.5 1 0 0 1 1.0 0.2878 37 62 Ireland 4.6 0 2 0 2 1.3 0.2870 38 8 South Korea 50.6 9 3 9 21 14.0 0.2765 39 1 United States of America 321.4 46 37 38 121 83.3 0.2592 40 4 Russian Federation 144.1 19 18 19 56 37.3 0.2590 41 74 Norway 5.2 0 0 4 4 1.3 0.2566 42 78 Estonia 1.3 0 0 1 1 0.3 0.2540 43 14 Spain 46.4 7 4 6 17 11.7 0.2513 44 78 Trinidad and Tobago 1.4 0 0 1 1 0.3 0.2451 45 21 Uzbekistan 31.3 4 2 7 13 7.7 0.2449 46 15 Kenya 46.1 6 6 1 13 10.3 0.2243 47 6 Japan 127.0 12 8 21 41 24.3 0.1916 48 65 Bulgaria 7.2 0 1 2 3 1.3 0.1857 49 34 North Korea 25.2 2 3 2 7 4.7 0.1854 50 54 Singapore 5.5 1 0 0 1 1.0 0.1807 51 33 Poland 38.0 2 3 6 11 6.0 0.1578 52 31 Ukraine 45.2 2 5 4 11 6.7 0.1474 53 47 Romania 19.8 1 1 3 5 2.7 0.1344 54 54 Jordan 7.6 1 0 0 1 1.0 0.1317 55 30 South Africa 55.0 2 6 2 10 6.7 0.1212 56 54 Tajikistan 8.5 1 0 0 1 1.0 0.1179 57 23 Colombia 48.2 3 2 3 8 5.3 0.1106 58 60 Malaysia 30.3 0 4 1 5 3.0 0.0988 59 78 Moldova 3.6 0 0 1 1 0.3 0.0938 60 75 Tunisia 11.1 0 0 3 3 1.0 0.0900 61 27 Argentina 43.4 3 1 0 4 3.7 0.0844 62 77 Israel 8.4 0 0 2 2 0.7 0.0795 63 50 Taiwan 23.5 1 0 2 3 1.7 0.0709 64 25 Iran 79.1 3 1 4 8 5.0 0.0632 65 13 Brazil 207.8 7 6 6 19 13.0 0.0625 66 78 Finland 5.5 0 0 1 1 0.3 0.0608 67 69 Burundi 11.2 0 1 0 1 0.7 0.0596 68 35 Thailand 68.0 2 2 2 6 4.0 0.0588 69 51 Cote d'Ivoire 22.7 1 0 1 2 1.3 0.0587 70 73 Kyrgyzstan 6.0 0 0 1 1 0.3 0.0560 71 41 Turkey 78.7 1 3 4 8 4.3 0.0551 72 65 Venezuela 31.1 0 1 2 3 1.3 0.0428 73 44 Ethiopia 99.4 1 2 5 8 4.0 0.0402 74 78 Austria 8.6 0 0 1 1 0.3 0.0387 75 78 United Arab Emirates 9.2 0 0 1 1 0.3 0.0364 76 3 China 1371.2 26 18 26 70 46.7 0.0340 77 62 Algeria 39.7 0 2 0 2 1.3 0.0336 78 69 Niger 19.9 0 1 0 1 0.7 0.0335 79 78 Portugal 10.3 0 0 1 1 0.3 0.0322 80 78 Dominican Republic 10.5 0 0 1 1 0.3 0.0317 81 61 Mexico 127.0 0 3 2 5 2.7 0.0210 82 48 Vietnam 91.7 1 1 0 2 1.7 0.0182 83 75 Egypt 91.5 0 0 3 3 1.0 0.0109 84 78 Morocco 34.4 0 0 1 1 0.3 0.0097 85 46 Indonesia 257.6 1 2 0 3 2.3 0.0091 86 69 Philippines 100.7 0 1 0 1 0.7 0.0066 87 78 Nigeria 182.2 0 0 1 1 0.3 0.0018 88 67 India 1311.1 0 1 1 2 1.0 0.0008
* is Fehaid Aldeehani who won the men's double trap gold medal and Abdullah Al-Rashidi who won the men's skeet bronze medal. Both are from Kuwait and they inherit that nation's economic data.
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) as at 2015.
- 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: 9:30 August 22, 2016 (Australian Time) - Final Standings
1 3 China 14107 26 18 26 70 46.5 3.2933 2 15 Kenya 3208 6 6 1 13 10.3 3.2080 3 34 North Korea 1800 2 3 2 7 4.6 2.5778 4 44 Ethiopia 1801 1 2 5 8 4.0 2.2047 5 1 United States of America 55805 46 37 38 121 83.0 1.4866 6 4 Russian Federation 25411 19 18 19 56 37.2 1.4620 7 21 Uzbekistan 6068 4 2 7 13 7.6 1.2573 8 2 Great Britain 41159 27 23 17 67 47.8 1.1611 9 16 Jamaica 8759 6 3 2 11 8.6 0.9865 10 31 Ukraine 7971 2 5 4 11 6.6 0.8305 11 13 Brazil 15615 7 6 6 19 12.9 0.8287 12 69 Burundi 818 0 1 0 1 0.7 0.8064 13 7 France 41181 10 18 14 42 26.5 0.6435 14 18 Cuba 12000 5 2 4 11 7.6 0.6367 15 6 Japan 38054 12 8 21 41 24.2 0.6362 16 69 Niger 1080 0 1 0 1 0.7 0.6113 17 5 Germany 46893 17 10 15 42 28.6 0.6088 18 9 Italy 35708 8 12 8 28 18.6 0.5198 19 30 South Africa 13165 2 6 2 10 6.6 0.5028 20 39 Azerbaijan 17993 1 7 10 18 8.9 0.4957 21 12 Hungary 26222 8 3 4 15 11.3 0.4309 22 38 Georgia 9630 2 1 4 7 4.0 0.4133 23 51 Cote d'Ivoire 3316 1 0 1 2 1.3 0.4011 24 10 Australia 47389 8 11 10 29 18.6 0.3917 25 32 Serbia 13671 2 4 2 8 5.3 0.3877 26 23 Colombia 13847 3 2 3 8 5.3 0.3835 27 8 South Korea 36511 9 3 9 21 14.0 0.3821 28 22 Kazakhstan 24268 3 5 9 17 9.3 0.3820 29 54 Tajikistan 2749 1 0 0 1 1.0 0.3637 30 17 Croatia 21581 5 3 2 10 7.6 0.3540 31 42 Armenia 8468 1 3 0 4 3.0 0.3519 32 14 Spain 34819 7 4 6 17 11.6 0.3337 33 19 New Zealand 36172 4 9 5 18 11.6 0.3204 34 25 Iran 17251 3 1 4 8 5.0 0.2887 35 11 Netherlands 49166 8 7 4 19 13.9 0.2835 36 40 Belarus 17654 1 4 4 9 5.0 0.2810 37 48 Vietnam 6024 1 1 0 2 1.7 0.2755 38 54 Kosovo 3786 1 0 0 1 1.0 0.2642 39 35 Thailand 16097 2 2 2 6 4.0 0.2472 40 20 Canada 45553 4 3 15 22 10.9 0.2399 41 33 Poland 26455 2 3 6 11 6.0 0.2253 42 41 Turkey 20438 1 3 4 8 4.3 0.2104 43 46 Indonesia 11126 1 2 0 3 2.3 0.2085 44 28 Denmark 45709 2 6 7 15 8.3 0.1809 45 26 Greece 26449 3 1 2 6 4.3 0.1633 46 27 Argentina 22554 3 1 0 4 3.7 0.1623 47 67 India 6162 0 1 1 2 1.0 0.1607 48 61 Mexico 17534 0 3 2 5 2.6 0.1506 49 43 Czech Republic 31549 1 2 7 10 4.6 0.1468 50 29 Sweden 47922 2 6 3 11 7.0 0.1450 51 47 Romania 20787 1 1 3 5 2.7 0.1275 52 60 Malaysia 26315 0 4 1 5 3.0 0.1129 53 37 Slovakia 29720 2 2 0 4 3.3 0.1117 54 54 Fiji 9044 1 0 0 1 1.0 0.1106 55 73 Kyrgyzstan 3363 0 0 1 1 0.3 0.0981 56 35 Belgium 43585 2 2 2 6 4.0 0.0913 57 62 Algeria 14504 0 2 0 2 1.3 0.0910 58 69 Philippines 7254 0 1 0 1 0.7 0.0910 59 75 Tunisia 11428 0 0 3 3 1.0 0.0866 60 45 Slovenia 31007 1 2 1 4 2.7 0.0855 61 24 Switzerland 58551 3 2 2 7 5.0 0.0851 62 75 Egypt 11850 0 0 3 3 1.0 0.0835 63 54 Jordan 12123 1 0 0 1 1.0 0.0825 64 67 Mongolia 12147 0 1 1 2 1.0 0.0815 65 65 Venezuela 16673 0 1 2 3 1.3 0.0792 66 65 Bulgaria 19097 0 1 2 3 1.3 0.0691 67 78 Moldova 5006 0 0 1 1 0.3 0.0659 68 64 Lithuania 28359 0 1 3 4 1.7 0.0582 69 78 Nigeria 6108 0 0 1 1 0.3 0.0540 70 51 Bahamas 25167 1 0 1 2 1.3 0.0528 71 69 Grenada 13128 0 1 0 1 0.7 0.0503 72 78 Morocco 8164 0 0 1 1 0.3 0.0404 73 50 Taiwan 46783 1 0 2 3 1.7 0.0355 74 48 Bahrain 50095 1 1 0 2 1.7 0.0331 75 54 Puerto Rico 37952 1 0 0 1 1.0 0.0263 76 62 Ireland 55533 0 2 0 2 1.3 0.0238 77 78 Dominican Republic 14984 0 0 1 1 0.3 0.0220 78 77 Israel 33656 0 0 2 2 0.7 0.0196 79 74 Norway 68430 0 0 4 4 1.3 0.0193 80 51 Independent Olympic Athlete * 70166 1 0 1 2 1.3 0.0190 81 78 Portugal 27835 0 0 1 1 0.3 0.0119 82 54 Singapore 85253 1 0 0 1 1.0 0.0117 83 78 Estonia 28592 0 0 1 1 0.3 0.0115 84 78 Trinidad and Tobago 32635 0 0 1 1 0.3 0.0101 85 78 Finland 41120 0 0 1 1 0.3 0.0080 86 78 Austria 47250 0 0 1 1 0.3 0.0070 87 69 Qatar 132099 0 1 0 1 0.7 0.0050 88 78 United Arab Emirates 67617 0 0 1 1 0.3 0.0049
* is Fehaid Aldeehani who won the men's double trap gold medal and Abdullah Al-Rashidi who won the men's skeet bronze medal. Both are from Kuwait and they inherit that nation's economic data.
Past GDP and Per Capita Rankings
- Compare the Final 2000 Olympics table
- Compare the Final 2004 Olympics table
- Compare the Final 2008 Olympics table
- Compare the Final 2012 Olympics table
Data Sources:
Population Data
The population data is sourced from the World Bank Indicators Database.The population counts (in millions) are at 2015.
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 publication date is April 2016. The data is for 2015 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 is for 2015.
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.