Medals at the Olympic Games: The Relationship Between Won Medals, Gross Domestic Product, Population Size, and the Weight of Sportive Practice

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Medals at the Olympic Games: The Relationship Between Won Medals, Gross Domestic
Product, Population Size, and the Weight of Sportive Practice
Author: Giancarlo Ruggieri
Past affiliation: Center of Nephrology and Dialysis, Department of Nephrology and
Urology ,San Giacomo and ONRM Hospitals, Rome, Italy
Abstract
The number of won medals represents the success of a country in the Olympic Games,
success based fundamentally on the inborn aptitude of the athletes for the sport for which
they won but also greatly on the skills that they acquired during years of training guided by
experienced coaches. All these teams and organizations need to be supported by an
adequate economic availability. At same time, subjects having inborn potential to excel in
athletic activities are not so common in a population; consequently their number could be
greater in a country with a large population adequately interested to practice sports in
young age. As a consequence, countries having a high gross domestic product (GDP) and
also a large population should have better probabilities of excelling in international
competitions. This study aims to evaluate these assumptions, using data from the Olympic
Games of 2016 and the GDPs from 2015. The results, obtained by studying a group of 29
countries that won a number of medals comprised between 121 and 10 and a second
group of 14 countries that won a number of medals comprised between 9 and 5, confirmed
the advanced hypothesis (also by means of comparison of won medals and the GDPs of
the two groups). The conditions probably necessary to gain satisfactory athletic results
notwithstanding moderate GDPs have been discussed together with the beneficial effects
of a diffuse sportive practice on the health of the population.
Introduction
The success of a country in the Olympic Games is measured by the number of medals
attained in competitions in different sports, and by whether they are gold, silver, or bronze
medals. The acquisition of a higher number of Olympic medals is due to the greater
qualities of the selected athletes, certainly most of all resulting from their inborn aptitude to
practice a specific sport but also from an adequate education in that particular activity,
based on years of intensive training guided by coaches at a high level and periodically
tested in competitions of increasingly high levels. This implies that during the development
of each future Olympic athlete, increasing economic support will be necessary to fully
achieve the maximum level of his/her inborn ability. This induces one to think that the
acquisition of a high number of medals should require a greater availability of money in
support of promising athletes and also to facilitate a very widespread practice of sports in
young people. In a country with a large population, this could result in a greater exposure
of subjects potentially gifted with psychophysical, inborn aptitudes for sport performances

at a high level; moreover a high GDP per capita should warrant that possible natural
athletes would grow up having the possibility of adequate nutrition and basic education,
that is to say, the best conditions to attain their possible future targets. These
considerations induced this exploration of the relationships that might exist between
Olympic results, economic availability, and the number of inhabitants of each country. For
this purpose, the number of medals in the most recent Olympic Games (2016), the GDPs,
and the size of the population of the country for the year 2015 were used.
Materials and Methods
The above mentioned data were acquired downloading via Google the number of medals
for each participating country [1]; the populations from World Populations Prospects of
year 2015 from United Nations (UN) [2]; and 2015 GDPs and GDP per capita per country
from the World Bank [3]. Two groups of countries were selected, the first including 29
countries that had won a number of medals between 121 and 10, and the second including
14 countries winning a number of medals comprised between 9 and 5. All base data
concerning won medals, the number of inhabitants, and GDP have been shown in details,
and resumed using their descriptive statics. Athletic results and economic data were
elaborated to point out the possible existence of defined relationships between won
medals and economic resources, as well as between won medals and the number of
inhabitants, using a series of linear regressions, as follows: (1) the number of medals
versus GDP values; (2) the number of medals versus the number of inhabitants ; (3) the
number of medals versus GDP and the number of inhabitants; (4) the number of medals
versus GDP per capita and the number of inhabitants; (5) medals per country as
percentage of total of all medals versus GDP as percentage of the total of GDPs; and (6)
medals per million inhabitants versus GDP. Graphic representations of the relationships
between the data in regressions 1, 2, and 6 were performed to emphasize visually the
obtained results. Because the relevant differences of size between the numerical values of
won medals and the numerical values in millions of inhabitants and of GDPs, the graphics
were based on standardized data. All the statistical tests and the descriptive statistics were
performed using MINITAB 15 software, by Minitab Inc., State College, PA, USA. The
graphics were performed using the graphic tools in Microsoft Excel 2007.
Results
Tables 1 and 2 show the data of the countries in groups 1 and 2 concerning the number of
inhabitants, GDPs (in millions), and won medals per country.
Table 1. Group 1 - Countries winning a number of medals comprised between 121 and 10

Countries
Inhabitants in
millions (UN,
2015)
GDP 2015 in
millions of
US dollars
Medals Countries
Inhabitants in
millions (UN,
2015)
GDP 2015 in
millions of
US dollars
Medals
United States 321.77 17 946 996 121 Cuba 11.39 77 150 11
United
Kingdom 63.14 72 328 67 New Zealand 4.53 173 754 18
China 1376 10 866 444 70 Canada 35.94 1 550 537 22
Russian
Federation 143.5 1 326 015 56 Uzbekistan 29.89 66 733 13
Germany 80.69 3 355 772 42 Kazakhstan 17.62 184 361 17
Japan 126.57 44 307 41 Denmark 5.67 295 164 15
France 64.4 242 168 42 Sweden 9.78 492 618 11
South Korea 50.2 1 377 873 21 Ukraine 44.82 90 615 11
Italy 59.8 1 814 762 28 Azerbaijan 9.75 53 047 18
Australia 23.97 1 339 539 29 Poland 38.61 474 783 11
Netherlands 16.92 752 547 19 Belarus 9.5 54 609 18
Hungary 9.86 120 687 18 Czech
Republic 10.54 181 811 10
Brazil 207.85 1 774 725 19
Spain 46.12 1 199 057 17
Kenya 46,.05 63 398 13
Jamaica 2.79 14 006 11
Croatia 4.24 48 732 10
Table 2. Group 2 - Countries winning a number of medals comprised between 9 and 5
Countries Inhabitants in
millions (UN,
2015)
GDP
2015 in
millions
of US
dollars
Medals Countries
Inhabitant
s in
millions
(UN,
2015)
GDP
2015 in
millions
of US
dollars
Medals
Colombia 48.229 292.08 8 Belarus 9.496 54.61 9
Switzerland 8.299 664.74 7 Turkey 21.238 718.22 8
Iran 79.109 425.33 8 Ethiopia 18.128 61.54 8
Greece 10.955 195.21 6 Romania 16.236 177.95 5
Serbia 8.851 36.51 8 Malaysia 6.11 296.22 5
Thailand 67.959 395.28 6 Mexico 28.013 1144.33 5
Georgia 4 13.97 7 Belgium 11.299 454.039 6
The descriptive statistics of the data in Tables 1 and 2 are shown in Table 3.
Table 3. Descriptive statistics of GDP, inhabitants, and won medals of countries in Group 1 and Group 2
Group 1 - Countries winning medals comprised between 121 and 10
Variable Countries Mean SE Mean TrMean StDev CoefVar Mode N for
Mode Skewness
GDP in millions
of US dollars 29 1 588 088 697 783 1 040 501 3 757 674 236.62 * 0 3.71

Inhabitants 29 99 47.4 55.3 255.3 257.79 * 0 4.8
Medals 29 27.55 4.56 24.74 24.55 89.1 11 5 2.43
Group 2 - Countries winning medals comprised between 9 and 5
Variable N Mean SE Mean TrMean StDev CoefVar Mode N for
Mode Skewness
GDP in millions
of US dollars 14 352.1 85.3 314.3 319.3 90.68 * 0 1.23
Inhabitants 14 24.14 6.38 21.23 23.88 98.93 * 0 1.55
Medals 14 6.857 0.361 6.833 1.351 19.7 8 5 -0.14
Legend: TrMean: trimmed mean, the mean excluding the extreme values of a data set, to avoid the errors due to too small
or too great isolated values. Skewness: this index measures the degree of asymmetry of a distribution. Its value is positive
when directed to the right side of a distribution, negative when directed to its left side.
Comparing the data in Table 3 of group 1 versus group 2 by T-test for two variables, the
results were as follows: no significant difference for inhabitants (T-test value = 1.56, p =
0.128), a significant difference for GDP (T-test value = 2.28, p = 0.031), and a high
significant difference for medals (T-test value = 4.52, p = 0.000). This seems to show the
importance of an elevated GDP for a high Olympic success, but this assumption can be
better appreciated on the basis of the performed regressions.
Table 4. Regressions using the data of Group 1
Variables Statistics
Predictor Responder R R² P
1 GDP values Number of medals 0.832 0.692 0.000
2 Number of inhabitants Number of medals 0.526 0.276 0.0034
3 GDP and inhabitants Number of medals 0.832 0.693 0.034
4GDP per capita and number of
inhabitants Number of medals 0.685 0.469 0.0034
5 GDP as % of total of GDPs Medals as % of total of medals 0.587 0.344 0.001
6 GDP Medals/millions of inhabitants 0.286 0.081 0.133
Table 5. Regressions using the data of Group 2
Variables Statistics
Predictor Responder R R² P
1 GDP values Number of medals 0.345 0.119 0.127
2 Number of inhabitants Number of medals 0.244 0.06 0.4
3 GDP and inhabitants Number of medals 0.402 0.162 0.378
4GDP per capita and number of
inhabitants Number of medals 0.381 0.145 0.422
5 GDP as % of total of GDPs Medals as % of total of medals 0.282 0.08 0.329

6 GDP Medals/millions of inhabitants 0.634 0.402 0.015
It is evident from Table 4 that there is a high correlation between medals and economic
resources, the only exception being regression 6, where GDP does not correlate with the
medals normalized on millions of inhabitants. On the contrary, this was the only positive
correlation with GDP in Table 5 concerning Group 2, while all other correlations between
GDP and medals were negative. The profile of these last regressions seems to show that
GDPs in Group 2 countries are barely sufficient to support a limited number of athletes in a
condition to win medals. This last consideration is based on the comparison of inhabitants,
GDPs, and medals between Group 1 and Group 2, performed above: GDPs and medals
resulted in being significantly different between Group 1 and Group 2, but not different the
populations (T-test value = 1.56, p = 0.128), even evidently lower in Group 2 countries.
Therefore the populations of the two different groups of countries are quite sufficiently
similar to possibly generate a similar number of subjects potentially able to attain Olympic
levels, but in Group 2 countries the economic resources needed to support their athletic
growth and training are very dissimilar from those of Group 1 countries, and therefore they
could very probably be insufficient to cover all the possible candidates. Correlation 6 in
Table 4 for Group 1 was in fact not significant. On this basis, and also taking into account
the high significant correlation between GDP and number of medals in Group 1, the
economic power of a country could be assumed to be the basis for Olympic success, when
interest in the sport should be adequately widespread. Below, what is mathematically
demonstrated by the regressions is presented visually by means of a series of graphics,
showing side by side the same topic for Group 1 and Group 2:
1) Inhabitants and Medals
2) Inhabitants and Medals

3) Medals/inhabitants and GPD
The features in the graphics regarding Group 1 versus those regarding Group 2 are clearly
very different. In the first and second graphic for Group 1, the trends of the lines of the
medals and of the inhabitants quite parallel those of the medals and GDPs, but this clearly
differs for the same trends in Group 2. These observations perfectly agree with the results
of the corresponding regressions. However, note also the better consistency for Group 1
between the medals line and the GDP line with respect to the consistency of the line of
medals versus that of inhabitants, because having a mild best approximation of the lines,
this corresponds to the results of all the regressions in Table 4. The consistency of the
lines is clearly worse in the last graphic for Group 1, “Medals/inhabitants and GDP,” in
comparison with those of the first two graphics. On the contrary, the graphic
“Medals/inhabitants and GDP” for Group 2 presents the best consistency of lines with
respect to the other graphics. This agrees with the positive result of the corresponding
regression for Group 2 and the negative result for Group 1.
Discussion
There are no doubts based on the results above that adequate wealth in a country is a
basis for substantial success in the Olympic Games, and very probably also in different
international athletic competitions. A more in-depth discussion should be possible based
on exact information about the source of money directly supporting the sport in each
country and the different forms in which athletic activities are encouraged and

economically supported. Furthermore, it would be interesting to know how with how much
money sports could directly support themselves by means of paid public exhibitions, and
how much this income should be with respect to the total economic support from other
sources. These paid public exhibitions are common, very frequent, officially organized, and
interesting to millions of persons in many countries for many sports: soccer, basketball,
rugby, baseball, volleyball, boxing, etc. The same athletics that remain the historical core
of the Olympic Games also put on recurrent, paid public exhibitions, and the participating
athletes can be evaluated de facto as professional athletes took up in their job. These paid
sports exhibitions of any form and purpose generally support the athletic activities of those
who have already attained advanced positions in their careers and are performed only on
basis of the personal economic availability of the spectators, that is, based on the GDP per
capita, when this economic parameter should correspond to a real adequate distribution of
economic well-being in the community. In all such cases, it is possible to consider these
sports exhibitions as show performances regularly followed by their fans, exactly as
happens for musical concerts and theatrical plays. Therefore, these forms of support for
sports should be considered somehow a compromise between athletic competitions and
commercial enterprises, or in other terms, commercial enterprises organizing sports
competitions. This includes championship events organized by Olympic organizations or
federal sport authorities, this to be considered a particular form of income of the sport
world. So it would be useful and appropriate to define what could correctly be considered
per se the real and substantial economic support for sports, and probably it could
probably be reasonable to limit its boundaries to what is directed to increase and
encourage the sportive exercise per se, that is to say, all the support directed to create the
basis of a sports world for youth, dedicated to all aspects of athletic activities, as strongly
emphasized by Susanna Geidne et al. in 2013 [4], from which it could very probably be
possible to also find possible future athletes for the Olympic Games. Therefore this
general support should have to be the money spent for a wide diffusion of sport activities
in the population, founding and having care of many technical facilities whose
establishment in each area would place them close to where young people are living, thus
facilitating their desire to follow sport activities, as observed in 2014 by Ann Reimers et al.
for young girls and adolescents in general in Germany [5]. in their study, the number of
approaches to sport facilities was clearly dependent on the distance between the facilities
and where young people were living. These structures, which should be free or low cost,
would give novice athletes the chance to practice sports under the optimal technical

assistance of experienced trainers, and exercise general athletic training for teenagers,
teaching them also the moods for physical care. All these supports, having the aim of
educating youth in physical activity, could be the bases for success in future competitions,
and they should be managed by public associations or by official Olympic organizations.
All this could also be considered a valuable support for the health of the country’s
population, as shown in the accurate review by Darren Warburton et al. [6] on the benefits
for health from the practice of physical activities, particularly in the elderly, decreasing the
risks of cardiovascular and metabolic diseases and significantly delaying the appearance
of disabilities; these last would cause a reduction of personal independence and
consequently increase the need for expensive personal assistance. Therefore, with all this
in mind, the wealth of the country is that which, directly or indirectly by the economic
capability of individuals, supports the development of sport activities at the highest levels.
The weight of national wealth becomes clear chiefly on the occasion of relevant sports
events of national interest, particularly in the case of the Olympic Games, upon which any
form of economic support seems to be lavished. A direct and significant relationship
between won medals and population has also been pointed out, the latter having even a
lower relevance with respect to national wealth. This can be explained by taking into
account that the more a country has a large population, particularly a young population,
the more it could have subjects in conditions to attain relevant athletic targets. The
relationship between the number of inhabitants and won medals is less significant than
that linked to the country’s wealth. The real possibility to have more athletes because
more inhabitants is subjected to many conditions: (a) young subjects should represent an
important percentage of the population, (b) sports activities should attain a sufficiently wide
diffusion to reach a sufficient number of future possible champions, (c) in case of poor
public support by any source for sports activities, this last would depend on the economic
capability of the families or of individuals, according to the age of the possible athlete. In
the last case, individuals should be employed in a job with an income such as to support
them and their athletic training, leaving sufficient time and physical well-being to allow a
not marginal sportive activity. Assuming all these conditions together, it is very probable
that young people able to satisfy all the above and at same time inborn champions are not
so frequent; therefore the size of a population by itself very probably does not represent a
definite significant possibility to realize relevant sportive results.
Conclusions

1) The wealth of a country is the more important component for significant success
in international sports competitions, particularly in the case of the Olympic
Games, when the sports activity is widely practiced.
2) The wide diffusion of the sport’s practice in the population is certainly the second
relevant base for sports success. A country having moderate economic
resources but a high prevalence of young people in its population — when the
government or other organizations give them the best possible sustainable
support for the practice of sport — very probably will attain the required
satisfactory results.
Efforts toward wide diffusion of sports activities in the population could induce a
relevant not secondary benefit on the physical and also economic conditions of the
population, decreasing the risks of chronic diseases that cause disabilities causes
of lower working possibility and greater need for personal assistance.
References
1) Medals won per country in Olympic Games 2016 - Google
2) World Populations Prospects – Key Findings and Advance Tables, Revision 2015 –
United Nations
3) Gross Domestic Product 2015 – Overview per Country – World Bank
4) Geidne S, Quennerstedt M, Eriksson C. The youth sports club as a health-promoting
setting: An integrative review of research. Scandinavian Journal of Public Health 2013;
41: 269–283
5) Reimers aK, Wagner M, Alvanides S et Al. Proximity to sports facilities and sport
participation for adolescents in Germany. Plose one org. 2014; 9: 3 e93059
6) Warburton DER, Whitney CN, Shannon SDB. Health benefits of physical activity : the
evidence: Review. CMAJ 2006; 174: 801 - 809