Another Olympics comes to a close, and Tokyo 2020 (aka “Tokyo 2021”) has been been a great success despite the many challenges presented by the COVID-19 pandemic. Yes, the stadiums were without crowds, and it was a year late, but the fact that it went ahead at all is amazing. Many naysayers were poo-pooing the Olympics… Tokyo 2020 is specifically for going ahead in the middle of a pandemic, but also the Olympics in general for the financial burden it usually puts on host cities/nations. While I acknowledge that the criticisms of the IOC are well deserved, and the concerns are valid, and am disappointed by the over-commercialisation of sports… whenever the Olympics come around, I prefer to put a pin in my cynicism for two weeks and enjoy the sporting spectacle that I’ve always loved about the Olympics.
Anyway… as I’ve done several times in the past, I’ve had a look at the medal tally for Tokyo 2020/2021 and compiled a tally that I feel better reflects Olympic greatness… the BTUSAF Table.
The BTUSAF’s, or the “Better Than USA Factor” is a non-dimensionalised score used to rank how well a nation’s athletes have done at an Olympics. Often one will see news reports about how a nation “won the Olympics” because it has won more medals, or more gold per capita. Unfortunately, for those writing such articles, a nations population and its Olympic performances do not correlate all that well. What does correlate will, however, is GDP and Olympic performance. This is evident in Table 1 below, however, using Excel’s correlation data analysis tool you can calculate an objective measure of how much more relevant GDP is than population to Olympic success i.e. population a correlation of 0.453, whereas GDP correlates 0.863.
| Medal-rank | Country | Pop-rank | GDP-rank |
|---|---|---|---|
| 1 | United States | 3 | 1 |
| 2 | China | 1 | 2 |
| 3 | Japan | 11 | 3 |
| 4 | United Kingdom/Great Britain | 21 | 5 |
| 5 | Russia/ROC | 9 | 11 |
| 6 | Australia | 53 | 13 |
| 7 | Netherlands | 68 | 17 |
| 8 | France | 20 | 7 |
| 9 | Germany | 19 | 4 |
| 10 | Italy | 25 | 8 |
Table 1 : Comparison of the Population and GDP rankings of the top 10 nations on the Tokyo 2020 medal tally
The other thing I’ve done in the past with BTUSAF tally calculations is to covert the medal haul into something objective… something quantifiable. I do this because there’s no way to determine the value, for the athletes, of making it to the Olympics, or making a final, or winning a medal… that’s very personal and extremely subjective. So, to keep things somewhat scientific, I calculate the value of the metals used in the medals, and that becomes the “value”.
So, according to ___, at Tokyo 2020 the
- Gold Medals contain 6g of gold, and 550g of silver
- Silver Medals contain 550g of silver
- Bronze Medals contain 427.5g of copper and 22.5g of zinc
The current market prices for these metals are:
- Gold = US$58,106.08 per kg
- Silver = US$819.84 per kg
- Copper = US$9.94 per kg
- Zinc = US$3.04 per kg
So, that means that the value of the metals in each of the medals is:
- Gold = US$799.55
- Silver = US$450.92
- Bronze = US$4.32
With these values, we’re now able to calculate how much value, objectively, the athletes have brought back with them, and thereby added to the wealth of their nations (we’re using the GDP as a proxy for the wealth). So a nation with a lower GDP will benefit more from a single medal than a nation with a higher GDP. So as we did in 2004 and 2012, we look at the value of the medal haul as a percentage of the nation’s GDP, and then we normalise it to that of the USA (the USA selected again b/c they once again topped the traditional tally) to come up with the “Better Than USA Factor” (BTUSAF) Tally.
So, here it is, the 2020/2021 Olympic BTUSAF standings:
| BTUSAF Rank | Officual Rank | Country | BTUSAF Score |
|---|---|---|---|
| 1 | 73 | San Marino | 123.40 |
| 2 | 21 | Jamaica | 99.65 |
| 3 | 32 | Georgia | 93.57 |
| 4 | 43 | Kosovo | 86.53 |
| 5 | 62 | Fiji | 62.84 |
| 6 | 42 | Bahamas | 50.68 |
| 7 | 65 | Bermuda | 46.74 |
| 8 | 70 | Kyrgyzstan | 46.12 |
| 9 | 69 | Armenia | 28.65 |
| 10 | 14 | Cuba | 28.47 |
| 11 | 36 | Uganda | 27.11 |
| 12 | 26 | Croatia | 26.78 |
| 13 | 30 | Slovenia | 22.67 |
| 14 | 19 | Kenya | 22.58 |
| 15 | 15 | Hungary | 21.01 |
| 16 | 29 | Bulgaria | 18.11 |
| 17 | 31 | Uzbekistan | 17.88 |
| 18 | 13 | New Zealand | 17.33 |
| 19 | 35 | Serbia | 17.31 |
| 20 | 82 | Namibia | 15.69 |
| 21 | 81 | North Macedonia | 15.28 |
| 22 | 45 | Belarus | 14.77 |
| 23 | 71 | Mongolia | 14.40 |
| 24 | 58 | Tunisia | 13.87 |
| 25 | 67 | Azerbaijan | 12.27 |
| 26 | 61 | Estonia | 10.99 |
| 27 | 60 | Latvia | 10.14 |
| 28 | 44 | Ukraine | 9.95 |
| 29 | 18 | Czech Republic | 8.61 |
| 30 | 37 | Ecuador | 8.21 |
| 31 | 5 | Russia/ROC | 7.30 |
| 32 | 51 | Slovakia | 6.98 |
| 33 | 47 | Venezuela | 6.86 |
| 34 | 68 | Dominican Republic | 6.59 |
| 35 | 7 | Netherlands | 6.39 |
| 36 | 57 | Ethiopia | 5.84 |
| 37 | 6 | Australia | 5.25 |
| 38 | 25 | Denmark | 5.19 |
| 39 | 80 | Bahrain | 5.03 |
| 40 | 76 | Jordan | 4.40 |
| 41 | 20 | Norway | 4.38 |
| 42 | 23 | Sweden | 4.14 |
| 43 | 4 | United Kingdom/Great Britain | 4.13 |
| 44 | 79 | Turkmenistan | 4.02 |
| 45 | 17 | Poland | 3.95 |
| 46 | 41 | Qatar | 3.76 |
| 47 | 46 | Romania | 3.70 |
| 48 | 78 | Lithuania | 3.55 |
| 49 | 40 | Greece | 3.36 |
| 50 | 64 | Puerto Rico | 3.28 |
| 51 | 63 | Morocco | 2.87 |
| 52 | 10 | Italy | 2.70 |
| 53 | 24 | Switzerland | 2.49 |
| 54 | 66 | Colombia | 2.40 |
| 55 | 3 | Japan | 2.37 |
| 56 | 27 | Iran | 2.36 |
| 57 | 28 | Belgium | 2.31 |
| 58 | 56 | Portugal | 2.27 |
| 59 | 33 | Taiwan | 2.20 |
| 60 | 8 | France | 2.13 |
| 61 | 52 | South Africa | 2.08 |
| 62 | 11 | Canada | 2.06 |
| 63 | 50 | Philippines | 2.04 |
| 64 | 49 | Hong Kong | 2.02 |
| 65 | 12 | Brazil | 1.94 |
| 66 | 22 | Spain | 1.86 |
| 67 | 39 | Israel | 1.75 |
| 68 | 16 | South Korea | 1.74 |
| 69 | 38 | Ireland | 1.74 |
| 70 | 54 | Egypt | 1.72 |
| 71 | 93 | Grenada | 1.51 |
| 72 | 9 | Germany | 1.45 |
| 73 | 34 | Turkey | 1.43 |
| 74 | 2 | China | 1.35 |
| 75 | 53 | Austria | 1.23 |
| 76 | 1 | United States | 1.00 |
| 77 | 59 | Thailand | 0.64 |
| 78 | 75 | Malaysia | 0.54 |
| 79 | 55 | Indonesia | 0.49 |
| 80 | 72 | Argentina | 0.44 |
| 81 | 74 | Nigeria | 0.41 |
| 82 | 48 | India | 0.26 |
| 83 | 77 | Saudi Arabia | 0.24 |
| 84 | 92 | Moldova | 0.15 |
| 85 | 91 | Burkina Faso | 0.11 |
| 86 | 90 | Botswana | 0.10 |
| 87 | 89 | Syria | 0.09 |
| 88 | 83 | Kazakhstan | 0.08 |
| 89 | 88 | Ivory Coast | 0.03 |
| 90 | 87 | Ghana | 0.03 |
| 91 | 86 | Kuwait | 0.01 |
| 92 | 85 | Finland | 0.01 |
| 93 | 84 | Mexico | 0.01 |
Table 2 : BTUSAF Table for Tokyo 2020
So, little San Marino, not only pick up their first Olympic medals at Tokyo 2020, but their humble haul of 1 Silver and 2 Bronze has netted them the coveted honour of top spot in the BTUSAF 2021 table. They join the list of other great BTUSAF nations such as South Africa (2016) (I should publish those results… one day maybe), Grenada (2012) and Cuba (2004). I’m not sure who won 2008… another thing for another day.
Finally, to all those Australian journos looking for a way to make Australia #1 on a medal tally, as well as the Value/GDP, San Marino takes out the title for Value/Population, and Medals/Population (with Australia coming 37th, 15th and 14th respectively). If you look at Gold/Population, Bermuda takes the title (Australia are 12th). If however, you were to calculate Value/Population-Density, Australia are top of the table (ahead of Canada, USA, NZ and Russia)… though, there’s almost correlation between Olympic performance and Population Density, and what there is, it’s slightly negative. Guess Australia will just have to be very happy with 6th place on the official medal tally (AUS were 10th in 2016, 8th in 2012, 6th in 2008 and 4th in 2004), and 37th place on the BTUSAF table (AUS were 28th in 2016, 40th in 2012, 15th in 2004… so actually, it’s not that great a result for Australia).