Bill Mitchell's Alternative Olympic Games Medal Tally - 2008 |
2012 Olympic GamesClick to go to the Alternative Olympic Games Medal Tally Latest News: Wednesday, August 27, 2008, Midday AEST
IntroductionThe data generated by the OGs is interesting and so I once again present my own view of the games:
The comparisons cannot be used to extrapolate anything. There are clearly not enough medals 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. Just a bit of fun.
This table shows the Gross Domestic Product for the medal winning countries expressed in millions of 2007 US 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).
The data is ranked according to Column (10). The lowest number is best Last computed: Sunday, August 24, 2008, 22:30 AEST - THIS IS THE FINAL MEDAL TALLY
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) = (4)/(9)
Rank Actual Country GDP 2007 Gold Silver Bronze Actual Weighted Million
$US millions (actual medals) Total Total GDP per
Medals Weighted Weighted
Medals Medals
1 33 North Korea 2220 2 1 3 6 3.65 608
2 38 Zimbabwe 3418 1 3 0 4 2.98 1147
3 31 Mongolia 3894 2 2 0 4 3.32 1173
4 13 Jamaica 10739 6 3 2 11 8.64 1243
5 27 Georgia 10176 3 0 3 6 3.99 2550
6 15 Kenya 29509 5 5 4 14 9.62 3067
7 28 Cuba 45100 2 11 11 24 12.89 3499
8 65 Kyrgyzstan 3505 0 1 1 2 0.99 3540
9 18 Ethiopia 19395 4 1 2 7 5.32 3646
10 65 Tajikistan 3712 0 1 1 2 0.99 3749
11 16 Belarus 44771 4 5 10 19 10.60 4224
12 79 Armenia 9177 0 0 6 6 1.98 4635
13 65 Bahamas 6586 0 1 1 2 0.99 6653
14 40 Uzbekistan 22308 1 2 3 6 3.31 6740
15 81 Togo 2493 0 0 1 1 0.33 7555
16 39 Azerbaijan 31248 1 2 4 7 3.64 8585
17 11 Ukraine 140484 7 5 15 27 15.25 9212
18 46 Estonia 21279 1 1 0 2 1.66 12819
19 81 Moldova 4396 0 0 1 1 0.33 13321
20 45 Latvia 27154 1 1 1 3 1.99 13645
21 42 Bulgaria 39549 1 1 3 5 2.65 14924
22 29 Kazakhstan 103840 2 4 7 13 6.95 14941
23 60 Trinidad and Tobago 19982 0 2 0 2 1.32 15138
24 41 Slovenia 45451 1 2 2 5 2.98 15252
25 52 Bahrain 16041 1 0 0 1 1.00 16041
26 25 Slovakia 74932 3 2 1 6 4.65 16114
27 57 Lithuania 38328 0 2 3 5 2.31 16592
28 81 Mauritius 6363 0 0 1 1 0.33 19282
29 52 Panama 19740 1 0 0 1 1.00 19740
30 21 Hungary 138182 3 5 2 10 6.96 19854
31 52 Cameroon 20644 1 0 0 1 1.00 20644
32 46 Dominican Republic 36686 1 1 0 2 1.66 22100
33 57 Croatia 51277 0 2 3 5 2.31 22198
34 26 New Zealand 129372 3 1 5 9 5.31 24364
35 81 Afghanistan 8842 0 0 1 1 0.33 26794
36 6 Australia 821716 14 15 17 46 29.51 27845
37 3 Russia 1291011 23 21 28 72 46.10 28005
38 17 Romania 165980 4 1 3 8 5.65 29377
39 71 Iceland 19510 0 1 0 1 0.66 29561
40 62 Serbia 41581 0 1 2 3 1.32 31501
41 24 Czech Republic 168142 3 3 0 6 4.98 33763
42 52 Tunisia 35020 1 0 0 1 1.00 35020
43 7 South Korea 969795 13 10 8 31 22.24 43606
44 1 China 3280053 51 21 28 100 74.10 44265
45 21 Norway 381951 3 5 2 10 6.96 54878
46 20 Poland 420321 3 6 1 10 7.29 57657
47 12 Netherlands 754203 7 5 4 16 11.62 64906
48 71 Ecuador 44184 0 1 0 1 0.66 66945
49 30 Denmark 308093 2 2 3 7 4.31 71483
50 71 Sudan 47632 0 1 0 1 0.66 72170
51 65 Morocco 73275 0 1 1 2 0.99 74015
52 31 Thailand 245818 2 2 0 4 3.32 74042
53 34 Argentina 262331 2 0 4 6 3.32 79015
54 4 Great Britain 2727806 19 13 15 47 32.53 83855
55 61 Nigeria 165690 0 1 3 4 1.65 100418
56 44 Finland 246020 1 1 2 4 2.32 106043
57 71 Vietnam 71216 0 1 0 1 0.66 107903
58 10 France 2562288 7 16 17 40 23.17 110586
59 14 Spain 1429226 5 10 3 18 12.59 113521
60 9 Italy 2107481 8 10 10 28 17.90 117736
61 5 Germany 3297233 16 10 15 41 27.55 119682
62 19 Canada 1326376 3 9 6 18 10.92 121463
63 34 Switzerland 415516 2 0 4 6 3.32 125155
64 46 Portugal 220241 1 1 0 2 1.66 132675
65 65 Algeria 135285 0 1 1 2 0.99 136652
66 37 Turkey 657091 1 4 3 8 4.63 141920
67 56 Sweden 444443 0 4 1 5 2.97 149644
68 23 Brazil 1314170 3 4 8 15 8.28 158716
69 42 Indonesia 432817 1 1 3 5 2.65 163327
70 65 Colombia 171979 0 1 1 2 0.99 173716
71 59 Greece 360031 0 2 2 4 1.98 181834
72 2 United States 13811200 36 38 36 110 72.96 189298
73 62 Ireland 254970 0 1 2 3 1.32 193159
74 51 Iran 270937 1 0 1 2 1.33 203712
75 71 Singapore 161347 0 1 0 1 0.66 244465
76 71 Chile 163915 0 1 0 1 0.66 248356
77 8 Japan 4376705 9 6 10 25 16.26 269170
78 46 Belgium 448560 1 1 0 2 1.66 270217
79 71 Malaysia 180714 0 1 0 1 0.66 273809
80 62 Austria 377028 0 1 2 3 1.32 285627
81 36 Mexico 893364 2 0 1 3 2.33 383418
82 81 Egypt 128095 0 0 1 1 0.33 388167
83 71 South Africa 277581 0 1 0 1 0.66 420577
84 81 Israel 161822 0 0 1 1 0.33 490370
85 80 Chinese Taipei 695388 0 0 4 4 1.32 526809
86 81 Venezuela 228071 0 0 1 1 0.33 691124
87 50 India 1170968 1 0 2 3 1.66 705402
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.
The nations are ranked according to column (10). The highest number is best. Last computed: Sunday, August 24, 2008, 22:30 AEST - THIS IS THE FINAL MEDAL TALLY
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) = (9)/(4)
Rank Actual Country Population Gold Silver Bronze Actual Weighted Weighted
Rank (millions) (actual medals) Medal Actual Total per
Total Total million
Medals persons
1 13 Jamaica 2.7 6 3 2 11 8.66 3.237
2 65 Bahamas 0.3 0 1 1 2 1.00 3.019
3 71 Iceland 0.3 0 1 0 1 0.67 2.141
4 41 Slovenia 2.0 1 2 2 5 3.00 1.486
5 21 Norway 4.7 3 5 2 10 7.00 1.486
6 6 Australia 21.0 14 15 17 46 29.66 1.411
7 52 Bahrain 0.8 1 0 0 1 1.00 1.328
8 31 Mongolia 2.6 2 2 0 4 3.33 1.276
9 26 New Zealand 4.2 3 1 5 9 5.33 1.261
10 46 Estonia 1.3 1 1 0 2 1.67 1.241
11 28 Cuba 11.3 2 11 11 24 12.99 1.154
12 16 Belarus 9.7 4 5 10 19 10.66 1.099
13 60 Trinidad and Tobago 1.3 0 2 0 2 1.33 0.999
14 27 Georgia 4.4 3 0 3 6 4.00 0.910
15 45 Latvia 2.3 1 1 1 3 2.00 0.878
16 25 Slovakia 5.4 3 2 1 6 4.67 0.865
17 30 Denmark 5.5 2 2 3 7 4.33 0.793
18 12 Netherlands 16.4 7 5 4 16 11.66 0.712
19 21 Hungary 10.1 3 5 2 10 7.00 0.696
20 57 Lithuania 3.4 0 2 3 5 2.33 0.691
21 79 Armenia 3.0 0 0 6 6 2.00 0.666
22 4 Great Britain 61.0 19 13 15 47 32.66 0.535
23 57 Croatia 4.4 0 2 3 5 2.33 0.525
24 24 Czech Republic 10.3 3 3 0 6 5.00 0.484
25 7 South Korea 48.5 13 10 8 31 22.33 0.460
26 29 Kazakhstan 15.5 2 4 7 13 7.00 0.452
27 34 Switzerland 7.6 2 0 4 6 3.33 0.441
28 44 Finland 5.3 1 1 2 4 2.33 0.441
29 39 Azerbaijan 8.6 1 2 4 7 3.67 0.428
30 10 France 61.7 7 16 17 40 23.32 0.378
31 42 Bulgaria 7.6 1 1 3 5 2.67 0.349
32 5 Germany 82.3 16 10 15 41 27.66 0.336
33 19 Canada 33.0 3 9 6 18 10.99 0.333
34 11 Ukraine 46.4 7 5 15 27 15.33 0.330
35 56 Sweden 9.1 0 4 1 5 3.00 0.328
36 3 Russia 141.6 23 21 28 72 46.32 0.327
37 62 Ireland 4.4 0 1 2 3 1.33 0.305
38 9 Italy 59.4 8 10 10 28 17.99 0.303
39 52 Panama 3.3 1 0 0 1 1.00 0.299
40 14 Spain 44.9 5 10 3 18 12.66 0.282
41 81 Mauritius 1.3 0 0 1 1 0.33 0.264
42 17 Romania 21.5 4 1 3 8 5.67 0.263
43 15 Kenya 37.5 5 5 4 14 9.66 0.257
44 2 United States 301.6 36 38 36 110 73.31 0.243
45 38 Zimbabwe 13.4 1 3 0 4 3.00 0.224
46 20 Poland 38.1 3 6 1 10 7.33 0.193
47 65 Kyrgyzstan 5.2 0 1 1 2 1.00 0.191
48 62 Serbia 7.4 0 1 2 3 1.33 0.180
49 59 Greece 11.2 0 2 2 4 2.00 0.179
50 46 Dominican Republic 9.8 1 1 0 2 1.67 0.171
51 62 Austria 8.3 0 1 2 3 1.33 0.160
52 46 Portugal 10.6 1 1 0 2 1.67 0.157
53 46 Belgium 10.6 1 1 0 2 1.67 0.157
54 33 North Korea 23.8 2 1 3 6 3.67 0.154
55 65 Tajikistan 6.7 0 1 1 2 1.00 0.148
56 71 Singapore 4.6 0 1 0 1 0.67 0.145
57 8 Japan 127.8 9 6 10 25 16.33 0.128
58 40 Uzbekistan 26.9 1 2 3 6 3.33 0.124
59 52 Tunisia 10.2 1 0 0 1 1.00 0.098
60 81 Moldova 3.8 0 0 1 1 0.33 0.088
61 34 Argentina 39.5 2 0 4 6 3.33 0.084
62 18 Ethiopia 79.1 4 1 2 7 5.33 0.067
63 37 Turkey 73.9 1 4 3 8 4.66 0.063
64 80 Chinese Taipei 22.9 0 0 4 4 1.33 0.058
65 1 China 1320.0 51 21 28 100 74.32 0.056
66 52 Cameroon 18.5 1 0 0 1 1.00 0.054
67 31 Thailand 63.8 2 2 0 4 3.33 0.052
68 81 Togo 6.6 0 0 1 1 0.33 0.051
69 71 Ecuador 13.3 0 1 0 1 0.67 0.050
70 81 Israel 7.2 0 0 1 1 0.33 0.046
71 23 Brazil 191.6 3 4 8 15 8.33 0.043
72 71 Chile 16.6 0 1 0 1 0.67 0.040
73 65 Morocco 30.9 0 1 1 2 1.00 0.032
74 65 Algeria 33.9 0 1 1 2 1.00 0.030
75 71 Malaysia 26.6 0 1 0 1 0.67 0.025
76 36 Mexico 105.3 2 0 1 3 2.33 0.022
77 65 Colombia 46.1 0 1 1 2 1.00 0.022
78 51 Iran 71.0 1 0 1 2 1.33 0.019
79 71 Sudan 38.6 0 1 0 1 0.67 0.017
80 71 South Africa 47.6 0 1 0 1 0.67 0.014
81 81 Venezuela 27.5 0 0 1 1 0.33 0.012
82 42 Indonesia 225.6 1 1 3 5 2.67 0.012
83 61 Nigeria 148.0 0 1 3 4 1.67 0.011
84 81 Afghanistan 32.7 0 0 1 1 0.33 0.010
85 71 Vietnam 85.1 0 1 0 1 0.67 0.008
86 81 Egypt 75.5 0 0 1 1 0.33 0.004
87 50 India 1123.3 1 0 2 3 1.67 0.001
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
The data is ranked according to Column (10). The highest number is best Last computed: Sunday, August 24, 2008, 22:30 AEST - THIS IS THE FINAL MEDAL TALLY
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) = 1000*(9)/(4)
Rank Actual Country $GDP Gold Silver Bronze Actual Weighted Weighted Medals
per person (actual medals) Total Total per $US1000
Medals Medals per person
1 33 North Korea 93.3 2 1 3 6 3.67 39.273
2 1 China 2484.9 51 21 28 100 74.32 29.908
3 18 Ethiopia 245.2 4 1 2 7 5.33 21.745
4 15 Kenya 786.3 5 5 4 14 9.66 12.290
5 38 Zimbabwe 255.0 1 3 0 4 3.00 11.756
6 3 Russia 9115.0 23 21 28 72 46.32 5.082
7 11 Ukraine 3028.8 7 5 15 27 15.33 5.061
8 40 Uzbekistan 830.3 1 2 3 6 3.33 4.013
9 28 Cuba 4006.4 2 11 11 24 12.99 3.243
10 16 Belarus 4614.6 4 5 10 19 10.66 2.311
11 31 Mongolia 1490.8 2 2 0 4 3.33 2.235
12 13 Jamaica 4011.6 6 3 2 11 8.66 2.160
13 65 Tajikistan 550.7 0 1 1 2 1.00 1.814
14 27 Georgia 2314.8 3 0 3 6 4.00 1.728
15 2 United States 45789.9 36 38 36 110 73.31 1.601
16 50 India 1042.4 1 0 2 3 1.67 1.599
17 65 Kyrgyzstan 668.5 0 1 1 2 1.00 1.495
18 61 Nigeria 1119.7 0 1 3 4 1.67 1.488
19 42 Indonesia 1918.3 1 1 3 5 2.67 1.390
20 81 Afghanistan 270.1 0 0 1 1 0.33 1.234
21 23 Brazil 6858.9 3 4 8 15 8.33 1.215
22 7 South Korea 19983.4 13 10 8 31 22.33 1.117
23 29 Kazakhstan 6707.6 2 4 7 13 7.00 1.043
24 39 Azerbaijan 3645.8 1 2 4 7 3.67 1.005
25 52 Cameroon 1113.9 1 0 0 1 1.00 0.898
26 81 Togo 378.8 0 0 1 1 0.33 0.880
27 31 Thailand 3851.0 2 2 0 4 3.33 0.865
28 71 Vietnam 836.5 0 1 0 1 0.67 0.796
29 6 Australia 39097.7 14 15 17 46 29.66 0.759
30 17 Romania 7703.2 4 1 3 8 5.67 0.736
31 4 Great Britain 44693.2 19 13 15 47 32.66 0.731
32 5 Germany 40079.2 16 10 15 41 27.66 0.690
33 20 Poland 11043.4 3 6 1 10 7.33 0.664
34 79 Armenia 3058.0 0 0 6 6 2.00 0.654
35 10 France 41523.5 7 16 17 40 23.32 0.562
36 71 Sudan 1235.4 0 1 0 1 0.67 0.539
37 37 Turkey 8893.1 1 4 3 8 4.66 0.524
38 42 Bulgaria 5175.2 1 1 3 5 2.67 0.515
39 21 Hungary 13741.2 3 5 2 10 7.00 0.509
40 9 Italy 35494.4 8 10 10 28 17.99 0.507
41 34 Argentina 6640.8 2 0 4 6 3.33 0.502
42 8 Japan 34254.3 9 6 10 25 16.33 0.477
43 46 Dominican Republic 3761.9 1 1 0 2 1.67 0.443
44 65 Morocco 2374.4 0 1 1 2 1.00 0.421
45 14 Spain 31846.2 5 10 3 18 12.66 0.398
46 51 Iran 3814.9 1 0 1 2 1.33 0.349
47 25 Slovakia 13886.6 3 2 1 6 4.67 0.336
48 24 Czech Republic 16270.8 3 3 0 6 5.00 0.307
49 52 Tunisia 3417.3 1 0 0 1 1.00 0.293
50 81 Moldova 1159.3 0 0 1 1 0.33 0.288
51 36 Mexico 8485.5 2 0 1 3 2.33 0.275
52 19 Canada 40222.5 3 9 6 18 10.99 0.273
53 65 Colombia 3729.2 0 1 1 2 1.00 0.268
54 12 Netherlands 46041.3 7 5 4 16 11.66 0.253
55 65 Algeria 3996.2 0 1 1 2 1.00 0.250
56 62 Serbia 5629.7 0 1 2 3 1.33 0.237
57 57 Lithuania 11353.1 0 2 3 5 2.33 0.205
58 57 Croatia 11554.1 0 2 3 5 2.33 0.202
59 71 Ecuador 3312.1 0 1 0 1 0.67 0.201
60 81 Egypt 1697.4 0 0 1 1 0.33 0.196
61 26 New Zealand 30598.9 3 1 5 9 5.33 0.174
62 52 Panama 5908.4 1 0 0 1 1.00 0.169
63 45 Latvia 11930.6 1 1 1 3 2.00 0.168
64 41 Slovenia 22522.8 1 2 2 5 3.00 0.133
65 71 South Africa 5833.0 0 1 0 1 0.67 0.114
66 46 Estonia 15856.2 1 1 0 2 1.67 0.105
67 71 Malaysia 6806.6 0 1 0 1 0.67 0.098
68 60 Trinidad and Tobago 14990.2 0 2 0 2 1.33 0.089
69 21 Norway 81110.9 3 5 2 10 7.00 0.086
70 46 Portugal 20761.8 1 1 0 2 1.67 0.080
71 30 Denmark 56427.3 2 2 3 7 4.33 0.077
72 71 Chile 9877.4 0 1 0 1 0.67 0.067
73 81 Mauritius 5038.0 0 0 1 1 0.33 0.066
74 59 Greece 32165.7 0 2 2 4 2.00 0.062
75 56 Sweden 48583.6 0 4 1 5 3.00 0.062
76 34 Switzerland 55035.2 2 0 4 6 3.33 0.061
77 65 Bahamas 19897.3 0 1 1 2 1.00 0.050
78 44 Finland 46515.4 1 1 2 4 2.33 0.050
79 52 Bahrain 21302.8 1 0 0 1 1.00 0.047
80 80 Chinese Taipei 30351.3 0 0 4 4 1.33 0.044
81 81 Venezuela 8303.5 0 0 1 1 0.33 0.040
82 46 Belgium 42213.4 1 1 0 2 1.67 0.039
83 62 Austria 45343.1 0 1 2 3 1.33 0.029
84 62 Ireland 58399.0 0 1 2 3 1.33 0.023
85 71 Singapore 35159.5 0 1 0 1 0.67 0.019
86 81 Israel 22563.0 0 0 1 1 0.33 0.015
87 71 Iceland 62733.1 0 1 0 1 0.67 0.011
This measure shows the weighted medal tally per athlete participating (by country). This allows us to see the gender performance of the difference medal tallies. I don't have population splits for gender so the denominator is common for both male and female rankings. It doesn't really matter because the numbers are just relativities. To overcome the issue that the Open/Mixed sports involve (obviously) male and female competitors in teams etc, I did the following adjustment. I prorated the Open/Mixed medals between males and females by simply adding the same medal to the corresponding male tally (gold, silver or bronze) and the corresponding female tally (gold, silver or bronze). This seems a reasonable rule given the difficulty in determining gender responsibility for the joint award. It has the consequence that the total actual medals (male plus female) from the table below will not equal the actual total official medal tally.
The nations are ranked according to Column (7M) for males and Column (7F) for females. The highest number is best. Last computed: Monday, August 25, 2008, 8:10 AEST - THIS IS THE FINAL MEDAL TALLY (ADJUSTED AS PER NOTES)
MALES MALES MALES MALES MALES MALES FEMALES FEMALES FEMALES FEMALES FEMALES
(1M) (2M) (3M) (4M) (5M) (6M) (7M) (1F) (2F) (3F) (4F) (5F) (6F) (7F)
Rank Actual Country POPN Actual Weighted Wght Rank Actual Country POPN Actual Weighted Wght
Medal Mills Total Total Total Medal Mills Total Total Total
Rank Medals Medals per Rank Medals Medals per
million million
persons persons
1 46 Bahamas 0.3 2 1.0 3.018 1 14 Jamaica 2.7 8 5.7 2.116
2 58 Iceland 0.3 1 0.7 2.141 2 4 Australia 21.0 25 16.7 0.793
3 58 Bahrain 0.8 1 1.0 1.328 3 20 Norway 4.7 5 3.0 0.637
4 46 Estonia 1.3 2 1.7 1.241 4 7 Netherlands 16.4 13 10.0 0.610
5 37 Jamaica 2.7 3 3.0 1.121 5 33 Slovenia 2.0 2 1.0 0.495
6 37 Mongolia 2.6 3 2.7 1.021 6 33 New Zealand 4.2 2 2.0 0.473
7 46 Trinidad and Tobago 1.3 2 1.3 0.999 7 12 Cuba 11.3 9 5.0 0.444
8 37 Slovenia 2.0 3 2.0 0.991 8 14 Belarus 9.7 8 4.0 0.412
9 22 Norway 4.7 6 4.3 0.920 9 23 Croatia 4.4 4 1.7 0.375
10 37 Latvia 2.3 3 2.0 0.878 10 33 Finland 5.3 2 1.7 0.315
11 26 Georgia 4.4 5 3.7 0.834 11 33 Slovakia 5.4 2 1.7 0.309
12 19 New Zealand 4.2 7 3.3 0.788 12 27 Denmark 5.5 3 1.7 0.305
13 22 Denmark 5.5 6 4.0 0.732 13 27 Czech Republic 10.3 3 2.7 0.258
14 10 Cuba 11.3 15 8.0 0.710 14 47 Mongolia 2.6 1 0.7 0.255
15 14 Belarus 9.7 11 6.7 0.687 15 17 Romania 21.5 7 5.3 0.247
16 7 Australia 21.0 23 14.3 0.682 16 5 Great Britain 61.0 21 14.0 0.229
17 22 Armenia 3.0 6 2.0 0.666 17 23 Zimbabwe 13.4 4 3.0 0.224
18 30 Slovakia 5.4 4 3.0 0.556 18 33 Bulgaria 7.6 2 1.7 0.218
19 19 Hungary 10.1 7 5.0 0.497 19 27 Hungary 10.1 3 2.0 0.199
20 30 Lithuania 3.4 4 1.7 0.493 20 47 Lithuania 3.4 1 0.7 0.197
21 26 Switzerland 7.6 5 3.0 0.397 21 7 South Korea 48.5 13 9.0 0.185
22 22 Azerbaijan 8.6 6 3.3 0.389 22 12 Canada 33.0 9 5.7 0.172
23 5 Great Britain 61.0 29 20.3 0.333 23 5 Germany 82.3 21 14.0 0.170
24 16 Kazakhstan 15.5 9 5.0 0.323 24 3 Russia 141.6 32 22.3 0.158
25 4 France 61.7 33 19.7 0.318 25 33 Belgium 10.6 2 1.7 0.157
26 37 Ireland 4.4 3 1.3 0.305 26 33 Sweden 9.1 2 1.3 0.146
27 58 Panama 3.3 1 1.0 0.299 27 47 Singapore 4.6 1 0.7 0.145
28 8 South Korea 48.5 19 14.3 0.295 28 9 Ukraine 46.4 12 6.7 0.144
29 58 Mauritius 1.3 1 0.3 0.264 29 20 North Korea 23.8 5 3.3 0.140
30 30 Sweden 9.1 4 2.3 0.255 30 23 Kazakhstan 15.5 4 2.0 0.129
31 12 Spain 44.9 14 10.3 0.230 31 2 United States 301.6 57 38.0 0.126
32 37 Czech Republic 10.3 3 2.3 0.226 32 11 Italy 59.4 11 7.3 0.123
33 6 Germany 82.3 26 18.0 0.219 33 20 Kenya 37.5 5 4.0 0.107
34 14 Canada 33.0 11 7.0 0.212 34 18 Spain 44.9 6 4.0 0.089
35 26 Netherlands 16.4 5 3.3 0.203 35 33 Austria 8.3 2 0.7 0.080
36 46 Kyrgyzstan 5.2 2 1.0 0.191 36 47 Georgia 4.4 1 0.3 0.076
37 10 Ukraine 46.4 15 8.7 0.187 37 14 France 61.7 8 4.0 0.065
38 37 Serbia 7.4 3 1.3 0.180 38 47 Portugal 10.6 1 0.7 0.063
39 9 Italy 59.4 17 10.7 0.180 39 9 Japan 127.8 12 8.0 0.063
40 46 Dominican Republic 9.8 2 1.7 0.171 40 33 Greece 11.2 2 0.7 0.060
41 3 Russia 141.6 40 24.0 0.169 41 47 Cameroon 18.5 1 1.0 0.054
42 16 Kenya 37.5 9 5.7 0.151 42 47 Switzerland 7.6 1 0.3 0.044
43 58 Croatia 4.4 1 0.7 0.150 43 27 Poland 38.1 3 1.7 0.044
44 19 Poland 38.1 7 5.7 0.149 44 47 Azerbaijan 8.6 1 0.3 0.039
45 46 Tajikistan 6.7 2 1.0 0.148 45 23 Turkey 73.9 4 2.7 0.036
46 37 Bulgaria 7.6 3 1.0 0.131 46 1 China 1320.0 58 41.0 0.031
47 1 United States 301.6 57 38.0 0.126 47 27 Ethiopia 79.1 3 2.3 0.029
48 46 Finland 5.3 2 0.7 0.126 48 33 Chinese Taipei 22.9 2 0.7 0.029
49 46 Greece 11.2 2 1.3 0.119 49 33 Thailand 63.8 2 1.7 0.026
50 26 Uzbekistan 26.9 5 3.0 0.112 50 27 Argentina 39.5 3 1.0 0.025
51 58 Tunisia 10.2 1 1.0 0.098 51 18 Brazil 191.6 6 3.7 0.019
52 58 Portugal 10.6 1 1.0 0.094 52 33 Mexico 105.3 2 1.3 0.013
53 58 Moldova 3.8 1 0.3 0.088 53 47 Uzbekistan 26.9 1 0.3 0.012
54 58 Austria 8.3 1 0.7 0.080 54 47 Venezuela 27.5 1 0.3 0.012
55 30 Argentina 39.5 4 2.7 0.067 55 47 Morocco 30.9 1 0.3 0.011
56 13 Japan 127.8 13 8.3 0.065 56 47 Algeria 33.9 1 0.3 0.010
57 58 Togo 6.6 1 0.3 0.051 57 47 Colombia 46.1 1 0.3 0.007
58 58 Ecuador 13.3 1 0.7 0.050 58 33 Nigeria 148.0 2 0.7 0.005
59 58 Israel 7.2 1 0.3 0.046 59 33 Indonesia 225.6 2 1.0 0.004
60 58 Chile 16.6 1 0.7 0.040 60 60 Latvia 2.3 0 0.0 0.000
61 30 Ethiopia 79.1 4 3.0 0.038 61 60 Dominican Republic 9.8 0 0.0 0.000
62 46 Chinese Taipei 22.9 2 0.7 0.029 62 60 Estonia 1.3 0 0.0 0.000
63 30 Turkey 73.9 4 2.0 0.027 63 60 India 1123.3 0 0.0 0.000
64 46 Thailand 63.8 2 1.7 0.026 64 60 Iran 71.0 0 0.0 0.000
65 2 China 1320.0 43 33.7 0.025 65 60 Bahrain 0.8 0 0.0 0.000
66 58 Malaysia 26.6 1 0.7 0.025 66 60 Panama 3.3 0 0.0 0.000
67 16 Brazil 191.6 9 4.7 0.024 67 60 Tunisia 10.2 0 0.0 0.000
68 58 Morocco 30.9 1 0.7 0.022 68 60 Trinidad and Tobago 1.3 0 0.0 0.000
69 58 Algeria 33.9 1 0.7 0.020 69 60 Ireland 4.4 0 0.0 0.000
70 46 Iran 71.0 2 1.3 0.019 70 60 Serbia 7.4 0 0.0 0.000
71 58 Sudan 38.6 1 0.7 0.017 71 60 Bahamas 0.3 0 0.0 0.000
72 58 Romania 21.5 1 0.3 0.015 72 60 Kyrgyzstan 5.2 0 0.0 0.000
73 58 Colombia 46.1 1 0.7 0.014 73 60 Tajikistan 6.7 0 0.0 0.000
74 58 North Korea 23.8 1 0.3 0.014 74 60 Chile 16.6 0 0.0 0.000
75 58 South Africa 47.6 1 0.7 0.014 75 60 Ecuador 13.3 0 0.0 0.000
76 30 Indonesia 225.6 4 2.3 0.010 76 60 Iceland 0.3 0 0.0 0.000
77 58 Afghanistan 32.7 1 0.3 0.010 77 60 Malaysia 26.6 0 0.0 0.000
78 58 Mexico 105.3 1 1.0 0.009 78 60 South Africa 47.6 0 0.0 0.000
79 58 Vietnam 85.1 1 0.7 0.008 79 60 Sudan 38.6 0 0.0 0.000
80 46 Nigeria 148.0 2 1.0 0.007 80 60 Vietnam 85.1 0 0.0 0.000
81 58 Egypt 75.5 1 0.3 0.004 81 60 Armenia 3.0 0 0.0 0.000
82 37 India 1123.3 3 1.7 0.001 82 60 Afghanistan 32.7 0 0.0 0.000
83 59 Zimbabwe 13.4 0 0.0 0.000 83 60 Egypt 75.5 0 0.0 0.000
84 59 Belgium 10.6 0 0.0 0.000 84 60 Israel 7.2 0 0.0 0.000
85 59 Cameroon 18.5 0 0.0 0.000 85 60 Moldova 3.8 0 0.0 0.000
86 59 Singapore 4.6 0 0.0 0.000 86 60 Mauritius 1.3 0 0.0 0.000
87 59 Venezuela 27.5 0 0.0 0.000 87 60 Togo 6.6 0 0.0 0.000
Melbourne (Australia) Radio Station 3AW asked me to breakdown the Great Britain and Australian results into separate English and Queensland results. Then the Melbourne newspaper MX asked me to do the same for the Australian states of Victoria and NSW. Ok, there is nothing sacrosanct about a national border other than the macroeconomic reality that they often define currency boundaries where the national government has a monopoly over the issuance of fiat currency. If you want to know more about the implications of this monopoly go to the CofFEE home page (my research centre)! So given that any spatial disaggregation could be created. I imagine if we did it for Kingston, Jamaica the results would be stunning this OGs. Anyway, the following table gives the results for these special orders. For an explanation see the Population and GDP tables. I simply repeated the exercise for these subnational geographic units. Be warned though - there is nothing valid about any of this. Just a bit of fun. Without further disaggregations being done, and where would you stop, Queensland win the OGs on population rankings. The weighted results are directly comparable with the other tables available (Population and GDP).
Country Population GDP(a) G S B Total Weighted Weighted $USm Rank Rank Actual
Region (2007) 2007 (actual awarded) Medals Medals Medals GDP using using official
millions $USm Total per per POP GDP Rank
million weighted
persons medal
Great Britain 60.9 2,727,806 19 13 15 47 32.65 0.536 83539 22 54 4
England 51.1 1,053,417 15 8 15 38 25.32 0.496 41599 24 42 na
Australia 21.1 821716 14 15 17 46 29.65 1.405 27713 6 36 6
Queensland 4.2 148129 8.5 6.5 8.2 23.2 15.56 3.703 9522 1 18 na
New South Wales 6.9 321325 2.3 2.0 4.6 8.8 5.08 0.735 63247 18 47 na
Victoria 5.2 242595 2.8 4.8 2.3 9.8 6.68 1.278 36320 9 43 na
(a) Note for Queensland, the measure of economic production is Gross State Product supplied by the
Australian Bureau of Statistics then expressed in millions of 2007 USD.
(b) The QLD and England breakdown of the medals was provided by 3AW and I have not independently
verified them. So they might have made them up! :-)
(c) The NSW and Victorian breakdown of the medals was provided by MX newspaper in Melbourne and
I have not independently verified them. So they also might have made them up! :-)
(c) Weighting: Gold = 1, Silver = 0.666, Bronze = 0.3333
Past GDP and Per Capita Rankings
Data Source:Most of the data came from the UN World Development Indicators database, World Bank, July 2008 available in summary form from HERE Defintion: Gross Domestic Product Gross domestic product (GDP) in current prices: GDP is sum of gross value added, at purchaser prices converted at market exchange rates to current U.S. dollars, by all resident producers in the economy plus any product taxes (less subsidies) not included in the valuation of output. It is calculated without deducting for depreciation of fabricated capital assets or for depletion and degradation of natural resources. GDP is equal to GNI less net receipts of primary income. Value added is the net output of an industry after adding up all outputs and subtracting intermediate inputs. The World Bank does not use this measure for classification of countries into income groups or poverty levels, as it is subject to distortions caused by short-term exchange rate fluctuations, policies and interventions. However, GDP measured in constant, local currency units provides the basis for estimates of overall economic growth. |
Bill Mitchell
Professor of Economics
Director, Centre of Full Employment and Equity
University of Newcastle
Callaghan NSW 2308, Australia
Telephone: +61-2-4921 5027
Fax: +61-2-4921 8731
Mobile Phone: 0419-422 422
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