Going for gold. a unit of work for 14 to 16-year-olds by Dr. Grant Kleeman Macquarie University, Sydney

Going for gold a unit of work for 14 to 16-year-olds by Dr. Grant Kleeman Macquarie University, Sydney CONTENTS Overview of the unit and rationale Introduction Preparation and introductory activities Activity 1: Factors affecting sporting success in Olympic competition Activity Resource Sheet D1: Factors affecting sporting success in Olympic competition Activity Resource Sheet D2: The Summer Olympics a truly global event Table 1: Top five gold medal-winning nations 1988 to 2004 Figure 2A: Number of countries participating in the Summer Olympic Games 1968 to 2004 Figure 2B: Number of athletes participating in the Summer Olympic Games 1968 to 2004 Figure 2C: Number of sporting events contested in the Summer Olympic Games 1968 to 2004 Figure 3: Changing Summer Olympic Games gold medal distribution 1988 to 2004 Activity Resource Sheet D3: The relationship between gold medal tally and population size Figure 4: Population and gold medal distribution by continent, Athens 2004 Table 2: Top 10 gold medal-winning countries adjusted for population, Athens 2004 Figure 5: Semi-logarithmic scatter graph showing the relationship between gold medal tally and population, Athens 2004 Activity Resource Sheet D4: The relationship between gold medal tally and relative wealth Figure 6: The relationship between Gross Domestic Product PPP per capita and the number of gold medals won (by region), Athens 2004 Olympic Games Table 3: Top 10 gold medal-winning countries adjusted for GNI PPP per capita, Athens 2004 Figure 7: Semi-logarithmic scatter graph showing the relationship between gold medal tally and GDP PPP per capita, Athens 2004 Activity Resource Sheet D5: Student tasks Drawing the lessons together and ideas for follow-up and assessment Activity Resource Sheet D6: Supplementary data

SPORTS GEOGRAPHY THE BEIJING GAMES GOING FOR GOLD THE BEIJING GAMES Going for gold Dr. Grant Kleeman Macquarie University, Sydney Overview In this activity we focus on global inequalities in sporting achievement as measured by the medal tally at successive Summer Olympic Games Sydney 2000, Athens 2004, and now, Beijing 2008. In doing so we have an opportunity to develop our understanding of global inequalities and practice a range of geographical skills including: the interpretation of column and line graphs, choropleth maps, proportional circle graphs, pie graphs and semi-logarithmic graphs. Rationale Geographers have always been interested in the spatial patterns that occur across the earth s surface. Of particular interest are the enormous variations in the quality of life experienced by people living in different parts of the world. In trying to understand and explain these differences, countries are often classified as either developed or developing. Geographers use a range of indicators to classify countries using these categories. These indicators include Gross National Income (GNI) per capita, the United Nation s Human Development Index (HDI), life expectancy, fertility rates, infant mortality, access to clean water and sanitation, and a range of health and education-related indicators. These data, compiled by various international bodies, can be mapped to identify spatial patterns or graphed to determine relationships between individual indicators. The question at the core of this activity is the extent to which sporting success, as measured by the medal tally at an Olympic Games, is related to a nation s population and/or level of development or wealth. Key questions include: Which countries and regions of the world are the most successful in winning medals at the Summer Olympic Games? Do countries with larger populations win more medals? Do the world s developed countries win more medals than developing countries? Introduction While the International Olympic Committee (IOC) discourages the ranking of countries according to the number of medals won at either the Summer or Winter Olympic Games, many media organisations seek to turn the games into an international contest by publishing daily tallies of medals won. These data are now readily available on the internet. The competition between nations for Olympic glory reached a peak during the Cold War when the Olympic Games became a defacto battleground for the competing ideologies of capitalism and communism. During this era vast resources were poured into sporting programs by some countries with the goal being greater international recognition and prestige through sporting success. Constructing such medal tallies is not, however, as straightforward as it might seem. Simply adding up and publishing the number of medals won by specific countries ignores the great variations in the populations from which winning athletes are drawn and wealth available to support and promote sporting achievement. In crude terms, the United States came out on top at the 2004 Athens games, with 36 gold medals, followed by China (32) and Russia (27) (see Table 1). Obviously, countries with large populations tend to do well because the sheer weight of numbers inevitably produces athletes with exceptional ability. There are, of course, always exceptions to this generalisation. Australia, with only 21 million people, was ranked fourth with 17 gold medals while India with a population of a billion won just a single silver medal. The Bahamas with fewer than 300,000 people came out well ahead on a population per medal basis, followed by Norway, Australia, Hungary and Cuba (see Table 2). The USA ranked 34th, Russia 23rd, the UK 29th, Canada 37th and China 51st. So population size alone is not a good predictor of Olympic success. The relationship between gold medal tallies and population size is examined in Table 2 and Figure 5. 1

THE BEIJING GAMES GOING FOR GOLD SPORTS GEOGRAPHY THE BEIJING GAMES 2 What about wealth then? Modern sport requires a lot of expensive infrastructure stadiums, swimming pools, velodromes, etc in order for national success to be achieved. So while athletes from developing countries find success on the track, especially in middle and long-distance running dominated by countries such as Ethiopia and Kenya, there were few non- European athletes wining medals in the pool or in canoeing, cycling, equestrian, fencing, rowing, shooting and yachting events. On the other hand, Asian competitors tend to dominate in some sports, especially badminton and table tennis, and the various martial arts disciplines such as judo and archery. Even in this instance it tends to be the industrialised Asian nations of Japan, South Korea and Taiwan that dominate. While there does appear to be a link between wealth and the distribution of medals there are, again, some notable exemptions. Switzerland, one of the world s wealthiest countries, could only manage a single gold medal, while tiny Luxembourg, which enjoys the world s highest per capita national income, could not manage a medal of any type. Then there are those countries which excel in winter sports rather than those featured in the Summer Olympics. The relationship between gold medal tallies and national (and regional) wealth is examined in Figures 6 and 7, and in Table 3. One way of taking into account both population size and income is to divide the number of medals won by national income per head, when adjusted for purchasing power parity (PPP). So how can we tell who has done well, adjusted for size and income? Just dividing medals by total national income does not say much, because that does not account for population size. One answer is to use national income per head, adjusted for purchasing power parity. This is the measure of the relative purchasing power of different countries currencies for the same types of goods and services. When we divide the number of gold medals won by an country s individual national income, we establish a point of comparison that takes into account cost of living differences between the wealthy and the less well off but which does not penalise large developing countries. It also accommodates the different performances between the wealthy countries. This approach reveals a number of interesting results. China, rather than the USA, tops the medal tally the country s immense population size more than compensating for its relatively low income. Cuba s modest population size (11.4 million) and relatively low income highlights what an achievement its nine gold, seven silver and eleven bronze medals - mostly won in Olympic boxing - really is. The same goes for Ethiopia (2 gold) and Kenya (1 gold). The gold medal haul of USA (36) and Australia (17) remains impressive by any measure and demonstrates the extent to which a national obsession with sporting achievement can fuel Olympic success. Preparation and introductory activities Before beginning this study students should be familiar with a range of development related concepts including development, spatial inequality, infrastructure, purchasing power per capita and demography, and possess a general awareness of the global pattern of social and economic wellbeing. This awareness can be achieved by having students study atlas maps showing a range of development related indicators including: GNI per capita, the UN s Human Development Index (an index combining indicators of real purchasing power, education, and health), life expectancy, total fertility, infant mortality, education, access to clean water and sanitation and human rights, including the status of women and minorities. Students also need to consider the factors likely to affect sporting success in the Olympic Games. This can be achieved by having the class complete the following activity: Activity Study Figure 1. As a class, discuss the factors affecting sporting success in Olympic competition. Can you identify any additional factors? Which of the factors listed do you think are the most important? Be prepared to justify your choice. The data required for the activities included with this study are presented on the following pages.

SPORTS GEOGRAPHY THE BEIJING GAMES GOING FOR GOLD THE BEIJING GAMES Activity Resource Sheet D1: Factors affecting sporting success in Olympic competition Figure 1: Factors affecting sporting success in Olympic competition Resources: The financial resources available to support athletes and provide training and competition venues. These can be provided by governments and/or the corporate sector through grants, sponsorship agreements and donations. Climate: Cold climate countries dominate the Winter Olympics, but do not feature so prominently when it comes to the medal tally at the Summer Olympic Games. Temperate and warm climates favour other sports. For example, Australia s strength in swimming and other water-based sports can, at least in part, be explained by the country s climate and beach culture The race for Olympic gold National identity: The relationship between sport and national identity is, in some instances, very strong. Americans and Australians, for example, are often seen as being sports obsessed. The sporting culture of such countries is seen as being central to the way its people see themselves collectively and portray their society to the world Culture: Some sports are closely linked to the culture of a particular nation or region. For example, table tennis is closely associated with China, basketball and baseball with the USA, swimming with Australia and the USA, boxing with Cuba, gymnastics with Eastern European countries, and long-distance running with Ethiopia and Kenya. 3 Table 1: Top five gold medal-winning nations 1988 to 2004 Seoul 1988 Barcelona 1992 Atlanta 1996 Sydney 2000 Athens 2004 Beijing 2008 1 USSR Russia* USA USA USA 2 East Germany USA Russia Russia China 3 USA Germany Germany China Russia 4 South Korea China China Australia Australia 5 West Germany Cuba France Germany Japan * competing as the Unified Team (former USSR)

THE BEIJING GAMES GOING FOR GOLD Activity Resource Sheet D2: The Summer Olympics a truly global event Figure 2A: Number of countries participating in the Summer Olympic Games, 1968 to 2004 Number of participating countries 250 Figure 2B: Numbers of athletes participating in the Summer Olympic Games, 1968 to 2004 Number of participating athletes 12000 200 10000 150 8000 SPORTS GEOGRAPHY THE BEIJING GAMES 4 100 50 0 Mexico City 1968 Munich 1972 Montreal 1976 Moscow 1980 Los Angeles 1984 Seoul 1988 Barcelona 1992 Atlanta 1996 Sydney 2000 Athens 2004 Beijing 2008 6000 4000 2000 0 Mexico City 1968 Munich 1972 Montreal 1976 Moscow 1980 Los Angeles 1984 Seoul 1988 Barcelona 1992 Atlanta 1996 Sydney 2000 Athens 2004 Beijing 2008 Figure 2C: Number of sporting events contested in the Summer Olympic Games, 1968 to 2004 Figure 3: Changing Summer Olympic Games gold medal distribution, 1988 to 2004 Number of events contested 350 300 Share of gold medals won by athletes from the top 5 medal-winning countries per cent 70 Number of gold medal-winning countries per cent 60 250 60 50 200 150 50 40 100 50 0 Mexico City 1968 Munich 1972 Montreal 1976 Moscow 1980 Los Angeles 1984 Seoul 1988 Barcelona 1992 Atlanta 1996 Sydney 2000 Athens 2004 Beijing 2008 40 30 Seoul 1988 Barcelona 1992 Atlanta 1996 Sydney 2000 Athens 2004 Beijing 2008 30 20

SPORTS GEOGRAPHY THE BEIJING GAMES GOING FOR GOLD THE BEIJING GAMES Activity Resource Sheet D3: Relationship between gold medal tally and population size Figure 4: Population and gold medal distribution by continent, Athens 2004 Central America & Caribbean Western Asia Oceania North America South America South Central Asia South East Asia Europe East Asia Africa Western Asia South Central Asia South America South East Asia Africa Central America & Caribbean Oceania North America East Asia Europe 5 Total population = 6,625 million Total number of gold medals awarded = 301 Source: International Olympic Committee (IOC) and World Population Bureau, World Population Data Sheet 2007. Table 2: Top 10 gold medal-winning countries adjusted for population, Athens 2004 Rank Country Number of Population per gold medal gold medals ( 000) 1 Bahamas 1 317 2 Norway 5 910 3 Australia 17 1,186 4 Hungary 8 1,229 5 Cuba 9 1,258 6 New Zealand 3 1,301 7 Jamaica 2 1,339 8 Greece 6 1,827 9 Sweden 4 2,222 10 Georgia 2 2,537 Source: Australian Bureau of Statistics, 30 August 2004

THE BEIJING GAMES GOING FOR GOLD SPORTS GEOGRAPHY THE BEIJING GAMES 6 Activity Resource Sheet D3: Relationship between gold medal tally and population size Figure 5: Semi-logarithmic scatter graph showing the relationship between gold medal tally and population, Athens 2004 Gold medal tally 40 USA 35 China Russia Country codes UAE = United Arab Emirates Il = Israel Ch = Switzerland Az = Azerbaijan Do = Dominican Republic Cz = Czech Republic Be = Belgium Zw = Zimbabwe Kz = Kazhakstan Cm = Cameroon 30 25 20 Australia Japan 15 Germany France Italy Cuba Ukraine United Kingdom Hungary Romania South Korea 10 Greece Norway Brazil Sweden Netherlands Poland Thailand New Zealand Bulgaria Austria Canada Spain Turkey Jamaica Georgia Denmark Belarus Chile Taiwan Morocco Iran Argentina Ethiopia Bahamas Lithuania Slovakia Zw Cm Uzbekistan Indonesia Croatia UAE Az Do Il Ch Cz Be Kz Kenya South Africa Egypt 5 0 0.10 0.25 0.50 1.00 2.50 5.00 10.00 25.00 50.00 100.00 250.00 500.00 1000.00 2500.00 Population (millions)

THE BEIJING GAMES Source: IOC, United Nations Development Program: Human Development Report and World Population Bureau: World Population Data Sheet SPORTS GEOGRAPHY Activity Resource Sheet D4: Relationship between gold medal tally and relative wealth (GDP per capita in US$ adjusted for purchasing power parity) Figure 6: Relationship between Gross Domestic Product PPP per capita or relative wealth and the number of gold medals won (by region), Athens 2004 Olympic Games GOING FOR GOLD THE BEIJING GAMES 7

THE BEIJING GAMES GOING FOR GOLD Table 3: Top 10 gold medal-winning countries adjusted for GNI PPP per capita, Athens 2004 Rank Country Number of gold medals 1 China 32 2 Russia 27 3 Ethiopia 2 4 Kenya 1 5 Ukraine 9 6 Uzbekistan 2 7 Romania 8 8 USA 36 9 Brazil 5 10 Georgia 2 SPORTS GEOGRAPHY THE BEIJING GAMES 8 Figure 7: Semi-logarithmic scatter graph showing the relationship between gold medal tally and GDP PPP per capita, Athens 2004 40 35 30 25 Key to country codes Az = Azerbaijan Kz = Kazhakstan Do = Dominican Republic Bu = Bukgaria SA = South Africa Cr = Croatia Li = Lithuania Cz = Czech Republic UAE = United Arab Emirates Be = Belgium China Russia USA 20 15 Australia Japan Germany 10 Cuba Ukraine Romania South Korea Hungary France Italy United Kingdom 5 0 Thailand Jamaica Ethiopia Ethiopia Uzbekistan Georgia Kenya Indonesia Zimbabwe Cameroon Az Egypt Do Source: IOC, United Nations Development Program: Human Development Report and World Population Bureau: World Population Data Sheet Brazil Belarus Iran Bu Kz Greece Norway New Sweden Netherlands Zealand Spain Canada Chile Slovakia Taiwan Austria Argentina Cz UAE Be Denmark SA Li Switzerland Cr Bahamas Israel Thailand Spain 200 500 1000 2000 5000 10,000 20,000 50,000 100,000 GDP per capita US$ PPP (adjusted for purchasing power parity)

SPORTS GEOGRAPHY THE BEIJING GAMES GOING FOR GOLD THE BEIJING GAMES Activity Resource Sheet D5: Student tasks 1. Study Figures 2a c and then complete the following tasks: a. Outline the trend in the number of countries competing in the Summer Olympic Games since 1968. As a class discuss the possible reasons for the trend identified. b. Use the internet to investigate the boycotts of the Montreal and Moscow Olympics. Write a paragraph outlining the reasons for each of the boycotts. c. Using data from the graphs, describe the trends in the number of participating athletes and the number of sporting events contested at the Summer Olympic Games between 1968 and 2004. 2. Study Figure 3. Outline the trends in the number of gold medal-winning countries and the share of gold medals won by athletes from the top five medal-winning countries between 1988 and 2004. As a class discuss the possible reasons for the trends identified. 3. Study Figure 4 and then complete the following tasks: a. State the percentage of gold medals won by European athletes in 2004. b. State the percentage of the world s population that lives in Europe. c. State the percentage of gold medals were won by athletes from South Central Asia in 2004. d. State the percentage of the world s population that lives in South Central Asia. e. Identify those regions of the world that win a share of gold medals greater than its relative share of the world s population. f. Identify those regions of the world that win a share of gold medals smaller than its relative share of the world s population. g. What do the answers to tasks 3a 3f suggest about the relationship between Olympic success and population at the regional scale? 4. Study Figure 5 and then answer then complete the following tasks: a. Draw a line of best fit on Figure 5. There should be approximately equal numbers of countries above and below the line. b. Identify at least three countries that fit into the following patterns: i. Large population, many gold medals ii. Medium population, many gold medals won iii.small population, many gold medals won. iv. Large population, few medal won. v. Identify at least three countries that did better than you might expect, i.e. those countries that lie above the line of best fit. vi. Identify at least three countries that did worse than you might expect, i.e those countries that lie below the line of best fit. c. Describe the nature of the relationship between gold medal tally and population. Suggest possible reasons for this relationship. Is the correlation relatively strong or weak? 5. Study Figure 6 and then complete the following tasks: a. With the aid of an atlas identify those regions of the world with GDP PPP per capita greater than US$10,000. b. With the aid of an atlas identify those regions of the world with GDP PPP per capita of less than US$1,000. c. Estimate the number of gold medals won by the countries of: i. North America. ii. East Asia. iii.western Europe. iv. Oceania. v. Africa. vi. South America. d. Drawing on your answers to tasks 5a 5c, describe the relationship between the gold medal tally and the general pattern of wealth (as measured by GNP PPP per capita) for the regions identified. 6. Study Figure 7 and then complete the following tasks: a. Draw a line of best fit on Figure 7. There should be approximately equal numbers of countries above and below the line. b. Identify at least three countries that fit into the following patterns: i. Large GDP PPP per capita, many gold medals. ii. Medium GDP PPP per capita, many gold medals won. iii.low GDP PPP per capita, many gold medals won. iv. Large GDP PPP per capita, few medals won. v. Identify at least three countries that did better than you might expect, i.e. those countries that lie above the line of best fit. vi. Identify at least three countries that did worse than you might expect, i.e those countries that lie below the line of best fit. c. Describe the nature of the relationship between gold medal tally and wealth (as measured by GNI PPP per capita). Is the correlation relatively strong or weak? 7. Study Table 1, 2 and 3. Compare the countries listed in Tables 2 and 3 with those in Table 1 and then consider the following questions: a. Are there any countries which appear in more than one ranking? b. Which do you consider the most appropriate method for ranking countries? Be prepared to justify your choice. 9

THE BEIJING GAMES GOING FOR GOLD SPORTS GEOGRAPHY THE BEIJING GAMES 10 Drawing the lesson together Having completed these activities students should be able to identify the countries and regions of the world that are the most successful in wining medals at the Summer Olympic Games. They should be able to respond in an informed way to the suggestion that countries with larger populations and greater wealth win more gold medals. They should, however, also appreciate that there are dangers in making sweeping generalisations regarding the relationship between Olympic success and factors such as population size and wealth. There are, as noted in the Introduction, some important exceptions to this generalisation. It should also be apparent that the gold medal domination of the traditional sporting superpowers has waned at little since the 1960s and that the world s changing political geography is mirrored in Olympic competition. Ideas for follow-up Extension activity 1 Access the International Olympic Committee (IOC) website following the Beijing Games and add the relevant data to the tables and graphs included in this study. Using GDP per capita US$ PPP data from the UN Human Development Report 2007 08, construct your own semi-logarithmic graph using Figure 5 or Figure 7 as a model. Having completed these tasks, determine whether the trends identified in this study are confirmed by the data generated from the competition in Beijing. Extension activity 2 Investigate the extent to which the growth in the number of countries participating in the Summer Olympic Games (see Figure 2a) and the changes in the countries dominating the top five positions of the gold medal tally (see Table 1) reflect the world s geopolitical changes in the late twentieth century. Extension activity 4 This activity will suit older or more able students, particularly those who work quickly with handling data. Hand out Activity Resource Sheet D6: Supplementary data. Organise students in groups of two to three and tell them that you would like them to do the following: 1. Devise two hypotheses that will test the relationship between any two of the variables in the table, i.e. gold medal tally, GDP per capita (US$ PPP) and population. 2. Produce scatter graphs, complete with lines of best fit, to illustrate the relationships. 3. Using these graphs, test whether the hypotheses are accepted or not. 4. Write up the investigation individually using these headings aim of the investigation, method used, presentation of results and conclusion. 5. Consider what other data might help to find out more about testing your hypotheses further. Ideas for assessment Students can be assessed on their ability to interpret the types of graphs and maps included in this Olympic Games-based activity. Teachers can also generate additional questions using the stimulus material featured. Questioning, discussion and written tasks can be used to ascertain the level of student understanding and evaluate the general effectiveness of the activity. References International Olympic Committee <www.olympic.org/uk/index_uk.asp> Australian Bureau of Statistics, 2004, Medal tally by world population, <www.abs.gov.au/ausstats/ abs@.nsf/mediareleasesbytitle/be9f47591541e29 ECA256EF40004F25A?OpenDocument> Population Reference Bureau <www.prb.org/>. Extension activity 3 Locate an atlas map showing the global pattern of economic and social wellbeing (as measured by the United Nations Human Development Index). Investigate whether the conclusions drawn in Activities 5 and 6 remain valid when this measure of development is considered.

SPORTS GEOGRAPHY THE BEIJING GAMES GOING FOR GOLD THE BEIJING GAMES Activity Resource Sheet D6: Supplementary data Country Gold medal tally Population 2004 Popuation 2004 GDP per capita GDP per capita Athens 2004 Logarithm US$ PPP 2004 Logarithm USA 36 295,400,000 8.4704 39676 4.5985 China 32 1,308,000,000 9.1166 6757 3.8298 Russia 27 143,900,000 8.1580 10845 4.0352 Australia 17 19,900,000 7.2988 30331 4.4819 Japan 16 127,900,000 8.1068 29251 4.4661 Germany 13 82,600,000 7.9169 28303 4.4518 France 11 60,300,000 7.7803 29300 4.4669 Italy 10 58,000,000 7.7634 28180 4.4499 Korea 9 47,600,000 7.6776 20499 4.3117 United Kingdom 9 59,500,000 7.7745 30821 4.4888 Cuba 9 11,200,000 7.0492 2950 3.4698 Ukraine 9 47,000,000 7.6721 6394 3.8058 Hungary 8 10,100,000 7.0043 16814 4.2257 Romania 8 21,800,000 7.3385 8480 3.9284 Greece 6 11,100,000 7.0453 22205 4.3464 Brazil 5 183,900,000 8.2646 8195 3.9135 Norway 5 4,600,000 6.6628 38454 4.5849 Netherlands 4 16,200,000 7.2095 31789 4.5023 Sweden 4 9,000,000 6.9542 29541 4.4704 Spain 3 42,600,000 7.6294 25047 4.3988 Canada 3 32,000,000 7.5051 31263 4.4950 Turkey 3 72,200,000 7.8585 7753 3.8895 Poland 3 38,600,000 7.5866 12974 4.1131 New Zealand 3 4,000,000 6.6021 23413 4.3695 Thailand 3 63,700,000 7.8041 8090 3.9079 Belarus 2 9,800,000 6.9912 6970 3.8432 Austria 2 8,200,000 6.9138 32276 4.5089 Ethiopia 2 75,600,000 7.8785 756 2.8785 Iran 2 68,800,000 7.8376 7525 3.8765 Slovakia 2 5,400,000 6.7324 14623 4.1650 Taiwan 2 22,900,000 7.3598 25330 4.4036 Georgia 2 4,500,000 6.6532 2844 3.4539 Bulgaria 2 7,800,000 6.8921 8078 3.9073 Jamaica 2 2,600,000 6.4150 4163 3.6194 Uzbekistan 2 26,200,000 7.4183 1869 3.2716 11

THE BEIJING GAMES GOING FOR GOLD Country Gold medal tally Population 2004 Popuation 2004 GDP per capita GDP per capita Athens 2004 Logarithm US$ PPP 2004 Logarithm Morocco 2 31,000,000 7.4914 4309 3.6344 Denmark 2 5,400,000 6.7324 31914 4.5040 Argentina 2 38,400,000 7.5843 13298 4.1238 Chile 2 16,100,000 7.2068 10874 4.0364 Kazakhstan 1 14,800,000 7.1703 7440 3.8716 Kenya 1 33,500,000 7.5250 1140 3.0569 Czech Republic 1 10,200,000 7.0086 19408 4.2880 South Africa 1 47,200,000 7.6739 11192 4.0489 Croatia 1 4,500,000 6.6532 12191 4.0860 SPORTS GEOGRAPHY THE BEIJING GAMES 12 Lithuania 1 3,400,000 6.5315 13107 4.1175 Egypt 1 72,600,000 7.8609 4211 3.6244 Switzerland 1 7,200,000 6.8573 33040 4.5190 Indonesia 1 220,100,000 8.3426 3609 3.5574 Zimbabwe 1 12,900,000 7.1106 2065 3.3149 Azerbaijan 1 8,400,000 6.9243 4153 3.6184 Belgium 1 10,400,000 7.0170 31096 4.4927 Bahamas 1 300,000 5.4771 17843 4.2515 Israel 1 6,600,000 6.8195 24382 4.3871 Cameroon 1 16,000,000 7.2041 2174 3.3373 Dominican Republic 1 8,800,000 6.9445 7449 3.8721 United Arab Emirates 1 4,300,000 6.6335 24056 4.3812