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Measuring Olympic success

By Professor David Forrest
Sports economist

A group of academics have predicted that the British Olympic team will bring home 44 medals from Beijing.

Sydney 2000 Olympic medals
How many factors actually influence a country's medal haul?

This figure is not based on how many medals Britain won last year or even the physical prowess of our athletes this time around.

It is based on an evaluation of influences that effect Britain as a country and how these can be used to indicate the nation's potential to succeed.

The Sports Economics Research Group, based in Madrid, has produced new research aimed at increasing understanding of the factors that drive countries' performances.

Based on data from the 1992, 1996, 2000 and 2004 Games, they take into account:

• a country's GDP (bigger economies win more medals)

• a country's population (not so important)

• a country's public spending on recreation in the four years up to the Games (significant; but with a lot of extra spending needed for each extra medal)

• whether a country had been a member of the Soviet bloc (ex-communist countries are still over-performing)

• which country is host (worth about 20 medals)

• whether a country had been a previous host

• which country will be the next host

• how many medals a country had won at the last Games (momentum is important)

Model origins

Work by two American academics, Andrew Bernard and Meghan Busse, published in 2000 and 2004, sought to pinpoint the key factors that generate medal totals.

Governments could indeed boost national performance with a bigger budget
Examining data from Games between 1960 and 1996, they found that the size of a country's economy (its GDP) was the single most important predictor of how many medals it achieved.

Other factors were the host effect (a country holding the event over-achieved relative to GDP) and whether the country was or had been a member of the communist bloc (communist countries considerably over-achieved).

The model proved remarkably successful in predicting the final table at Sydney in 2000.

Throwing money

The Spanish Sports Economics Group aimed to make the research more relevant to policy makers by taking into account the amount of money spent on sport in each country.

From 1990, there was data available from UN sources on total government spending on "recreation". This was taken as a proxy for spending on sport (although it includes other activities as well) and found that governments could indeed boost national performance with a bigger budget.

They also tested for the effect of being the next host or a previous host. Countries due to hold the Games the next time showed significantly elevated performance at the current Games, but the benefits from having been a previous host nation faded quickly.

Medals per million

The table below takes one of the factors already mentioned, GDP, and uses it to illustrate how each country that went home with one medal or more in the 2004 Games, actually performed in terms of medals per US$ million million of its gross domestic product.

Out of the 25 leading countries in the medal table, of particular note are good performances from Australia, the communist and ex-communist countries and the hosts, Greece.

Country Medals won in 2004 Games GDP ($US million million) Medals per $US million million GDP
Zimbabwe 3 0.002 1,500.00
Trinidad and Tobago 1 0.0024 416.67
Eritrea 1 0.0036 277.78
Jamaica 5 0.02 250.00
Bahamas 2 0.008 250.00
Georgia 4 0.02 200.00
Belarus 15 0.1 150.00
Bulgaria 12 0.09 133.33
N. Korea 5 0.04 125.00
Mongolia 1 0.0084 119.05
Ethiopa 7 0.06 116.67
Kenya 7 0.06 116.67
Syria 1 0.0087 114.94
Latvia 4 0.04 100.00
Estonia 3 0.03 100.00
Hungary 17 0.19 89.47
Uzbekistan 5 0.06 83.33
Azerbaijan 5 0.06 83.33
Slovenia 4 0.05 80.00
Romania 19 0.25 76.00
Ukraine 23 0.32 71.88
Croatia 5 0.07 71.43
Australia 49 0.76 64.47
Slovakia 6 0.11 54.55
Cuba 27 0.51 52.94
Greece 16 0.32 50.00
Lithuania 3 0.06 50.00
Kazakhstan 8 0.17 47.06
NZ 5 0.11 45.45
Russia 92 2.09 44.02
Denmark 8 0.2 40.00
Paraguay 1 0.027 37.04
Netherlands 22 0.64 34.38
Czech Rep 8 0.25 32.00
S. Korea 30 1.2 25.00
Cameroon 1 0.04 25.00
Norway 6 0.25 24.00
Morocco 3 0.13 23.08
Serbia 2 0.09 22.22
Austria 7 0.32 21.88
Sweden 7 0.33 21.21
Italy 32 1.79 17.88
Germany 48 2.81 17.08
Switzerland 5 0.3 16.67
Dominican Rep 1 0.06 16.67
Poland 10 0.62 16.13
France 33 2.05 16.10
Thailand 8 0.52 15.38
Spain 19 1.35 14.07
GB 30 2.14 14.02
Chile 3 0.23 13.04
Portugal 3 0.23 13.04
SA 6 0.47 12.77
Argentina 6 0.52 11.54
Turkey 10 0.89 11.24
Egypt 5 0.45 11.11
Israel 2 0.19 10.53
Finland 2 0.19 10.53
Canada 12 1.27 9.45
China 63 6.99 9.01
Japan 37 4.29 8.62
Iran 6 0.75 8.00
Belgium 3 0.38 7.89
USA 103 13.84 7.44
Taiwan 5 0.7 7.14
Nigeria 2 0.29 6.90
Venezuela 2 0.33 6.06
UAE 1 0.17 5.88
Brazil 10 1.84 5.43
Ireland 1 0.19 5.26
Indonesia 4 0.84 4.76
HK 1 0.3 3.33
Colombia 1 0.32 3.13
Mexico 4 1.35 2.96
India 1 2.81 0.36

The Sports Economics Research Group team for this project comprises: Ramón Flores (Universidad Carlos III), David Forrest (University of Salford), Ismael Sanz (Universidad Complutense de Madrid) and Juan de Dios Tena (Universidad Carlos III).




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