Hip throw biomechanics analysis for wrestling sports

Postgraduate student E.V. Gorokhova
Lomonosov Moscow State University, Moscow

Keywords: Olympic Games, Olympic success, forecast of results, regression analysis.

Introduction. The modern Olympic Games were created by Baron Pierre de Coubertin as a competition between athletes. However, throughout the 20th century, the influence of political factors was on the rise and the Games began to be perceived, by spectators, more like competitions between countries rather than between athletes.

Traditionally, since the mid-20th century, national medal totals in the Olympic Games have been counted in order to determine the most successful countries. Former president of the International Olympic Committee, Avery Brundage, stressed that the comparison between countries contradicts the ideals of the Olympic Movement. This is incorrect due to the differences between countries in the level of socio-economic development [2].

Methods and structure of the study. What is Olympic success? It is possible to distinguish absolute and relative Olympic success. Absolute success is estimated by the total number of medals or points scored by a country. Relative success, taking into account the specifics of the country, is estimated relative to any indicator. It is often calculated as the ratio of the number of medals (points) to the number of athletes in the Olympic team.

While the biggest sports powers are competing for Olympic gold, for the majority of countries, the participation in the Olympic Games is already a kind of success.

Objective of the study was to identify factors to influence the development of sports in a country and its move to the international sports level, and the methods used to assess their influence by analysing previous scientific studies of this problem.

Results and discussion. Researches are based on correlation, regression analysis and other statistical methods. German expert in the field of sports medicine, Ernst Jokl, was one of the first who was interested in the subject of dependence of absolute Olympic success on various factors. In his work on the analysis of the Olympic Games in Helsinki in 1952 [8], he examined the dependence of national Olympic success on the following factors: income per capita, nutrition, mortality and climate.

More researches on this topic were conducted in the 1960s. These scientific studies explained Olympic success by different independent variables: income per capita and number of people doing sports. Urban population and educated people were proved to be more engaged in sports compared to  rural population [12]. The most relevant studies made in the 1970s belong to Donald W. Ball and, Russian experts A.M. Maksimenko and A.D. Novikov.

D.W. Ball [2] analyzed the relationship between 55 different socio-economic indicators and Olympic success using Fisher's Exact Test, which assesses the significance of the relationship between two variables. His research was based on the results of the Olympic Games of 1964 in Tokyo. All the variables were divided into 3 groups: "demography", "economy" and "politics". In the demography group, the influence of such factors was the level of urbanization, education, national homogeneity and religious heterogeneity and low population growth. In the economy group, the most significant variables were the following: total Gross Domestic Product (GDP), GDP per capita and international financial status of the country. Analysing the indicators of the politics group, D.W. Ball noted that developed Western countries with a democratic political structure are usually the most successful at the Olympic Games.

A.M. Maksimenko and A.D. Novikov [12] pointed to Olympic success of athletes from the socialist countries. Their advantage was explained by centralization and planned management system that contributes to better organization of physical education and sport services in the country. Using the correlation analysis, the significant relationships between absolute national Olympic success and national income per capita, calories consumed by the population, average life expectancy of the population, percentage of illiterate population, level of urbanization and population size have been proved.

After the dependence of Olympic success on a number of socio-economic factors was determined, since the end of the 1970s, researchers were trying to identify a set of factors and their ratio, which is significantly related to Olympic national success, by using a more sophisticated econometric method - regression analysis.

According to Finnish experts P. Kviyaho and P. Makela [9] studying relative national Olympic success does not take into account the volume of sports resources. However, its analysis can be used to assess the effectiveness of exploiting resources to achieve Olympic victories. Obviously, socio-economic factors are also related to relative Olympic success, but its impact is different. Relative and absolute Olympic success are not correlated. According to the results of the regression analysis, economic development, population size and country’s economic system together are significant for absolute Olympic success. In turn, relative Olympic success is explained by the regression model with such variables as population density and religious culture at 46%. It is extremely difficult for small countries to achieve high absolute success, but they can become leaders in sport, which is promoted by their culture, traditions and natural resources [9].

Sport and the Olympic movement are continuously developing. The modern Games are very different from what they were in the beginning and even in the middle of the 20th century. Obviously, the set of the factors and its impact on the Olympic success can change with time.

Before the Second World War, serious restrictions regarding the participation in the Games were lacking. However, the economic situation of the country and the distance to the Games host-city played a significant role. Economic and geographical factors often played a much greater role than physical training of athletes [11].

Researches note the great advantages of home Games. This factor, as a dummy variable in regression models is taken into account in many studies. Home advantage has a positive effect on participation; the host country’s participation is almost doubled. The distance from country to host country is significant as well; the participation increases by 25% [7] and total medals increases by 1.2% [3].

In addition to the standard variables traditionally used in such studies, J. Cooper and E. Sterken [10] added indicators of the current trends in the Olympic Games to the regression model. Considering the growth of the female participation in the Games, a new variable was added to the model, which is female labor participation. The second trend is the growth of media and television attention to the Olympic Games. Taking this into account, the additional variable in the model was the TV-sets per capita.

Some researchers use other statistical methods. For example, A. Bernard and M. Busse [3] considered Olympic success as "value of production" of the country's sports system. Using the Cobb-Douglas production function, they considered GDP per capita (capital) and population size (labor) as factors productivity:

Olympic success = A * GDP per capitaa * population sizeb.

Studies based on prediction of the future Olympic Games. The regression models of the relationships between Olympic success and various variables contributed to the development of predictions of Olympic Games results. One of the most famous experts in this field is Wladimir Andreff from France. He made quite accurate predictions of the 2008 Beijing Games and the 2014 Sochi Winter Games [1]. Given the model of A. Bernard and M. Busse, [3] W.Andreff changed it slightly and modified it to predict the Olympic Winter Games.

Andreff proposed using four variables considering the current differences between the former socialist countries instead of one dummy variable taking into account the impact of the socialist regime in the country.

In order to predict the Olympic Winter Games results, W. Andreff added a variable considering average degree of annual snow coverage since special geographical conditions are necessary for the development of winter sports. Athletes from African countries have never won medals in the Olympic Winter Games, and athletes from snowless countries have never been ranked higher than 14th [6].

The economic wealth is crucial in the development of winter sports. For example, one can find indoor ski resorts in Qatar and the UAE [13]. So W. Andreff added a variable considering the availability of ski resorts and other winter sports infrastructure.

Studies on the analysis of the effectiveness of national sports policies. The models of relationships between national Olympic success and various indicators are used in order to assess the effectiveness of the national team training system. V. Boscher, B. Heidels, M. Bottenburg and S. Shibli [4] noted that Olympic success is explained by socio-economic indicators in average at 50%. The other half depends on the state sports policy and an effective national team training system. The indicators of sports policy include recognition of physical education and sports in the country's legislation, the practice of identifying talented children in schools, professional coach training and development system, availability of financial support programs in the sport sector, development of top level sports medicine and sports infrastructure.

The project "Sports Policy factors leading to international sporting success" (SPLISS) was created to study and compare countries in that field [5]. This project is an international network of studies aimed at interaction and exchange of experience in the analysis of national sports policy with 15 countries involved in the project. The results of the work are published in reports where the systems of organizing sports are compared according to certain parameters.

D. Reich applied a different approach to this problem in his book "Success and Failure of Countries at the Olympic Games" [13]. Instead of analyzing the sports policy, he used the so-called "WISE" formula. In this formula, he takes into account the following factors that have impact on the national Olympic success: women’s participation in sports (W - women), established sport management institutions (I - institutionalization), specialization in medals sports (S-specialization) and development of new sport disciplines (E - early adaptation).

Conclusions. The studies on the relationships between the national Olympic success and various factors appeared in the middle of the 20th century. At that time, a transition from individual competition between athletes to a competition between countries, which emphasized their international status and significance, was in process.

The first studies described the dependence of Olympic success on various socio-economic factors using correlation analysis. Gradually, more complex econometric methods were applied. Using regression analysis, the models determined the relationships between Olympic success or number of participants in the national team and a certain set of independent variables, represented by socio-economic, natural and political indicators. Over time, some researchers were able to predict the results of the future Olympic Games, using the regression analysis.

Nowadays, we can note the transition from the use of quantitative methods to qualitative ones. As the studies focus on analysis, the effectiveness of the sports policy is becoming more popular.

Thus, Olympic success depends on a huge number of factors. Its prediction requires using various quantitative and qualitative methods in view of the specifics of individual countries and sports.

Referenses

  1. Andreff W. Economic development as major determinant of Olympic medal wins: predicting performances of Russian and Chinese teams at Sochi Games. Int.J.Economic Policy in Emerging Economies, 2013, vol. 6, no. 4, P. 314–340.
  2. Ball D. W. Olympic Games Competition: Structural Correlates of National Success. International Journal of Comparative Sociology, 1972, vol. 13, no. 3–4, pp. 186–200.
  3. Bernard A. B. Busse M. R. Who wins the Olympic Games: Economic Development and Medal Totals. Review of Economics and Statistics, 2004, vol. 86, no. 1, pp. 413–417.
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  5. De Bosscher V., Shibli S. H. Westerbeek H., van Bottenburg M. Successful Elite Sport Policy. An international comparison of the Sport Policy Factors Leading to International Sporting Success (SPLIS 2.0) in 15 nations. (1 st). 2015. Maidenhead: Mayer & Mayer Sports (UK) Ltd.
  6. Johnson D., Ali A. Tale of Two Seasons: Participation and Medal Counts at the Summer and Winter Olympic Games. Social Science Quarterly, 2004, vol. 85, no. 4, pp. 974–993.
  7. Johnson D., Ali A. Coming to play or coming to win: Participation and success at the Olympic Games. 2000, vol. 2000–10. P.21.
  8. Jokl E. Sports in the cultural pattern of the world: a study of the 1952 Olympic Games at Helsinki. Helsinki, Finland: Institute of Occupational Health, 1956.
  9. Kiviaho P., Makela P. Olympic Success: A sum of Non-Material and Material Factors. International Review of Sport sociology, 1978, no. 2, pp. 5–17.
  10. Kuper G., Sterken E. Olympic participation and performance since 1896. Mimeo. Department of Economics, University of Groningen. 2001.
  11. Kuper G., Sterken E. Determinants of participation and success at the earlier modern Olympic Games. Journal of Olympic History, 2001, no.19, pp. 20–29.
  12. Novikov A. D., Maksimenko A. M. The influence of Selected Socio-Economic Factors on the Level of Sports Achievements in the Various Countries. International Review of Sport Sociology, 1972, vol. 7, pp. 27–40
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Corresponding author: e.gorokhova@geogr.msu.ru

Abstract

While the leading sport nations of the world compete for the Olympic gold, many other nations dream of at least qualifying for the Olympics considering such a qualification a great success. What are the factors of influence on the modern national sports, their access to the global arenas, and how the influences may be rated? The study overviews and analyzes the progress criteria and rating methods applicable for studies of a variety of factors of influence on the national competitive accomplishments in the Olympics and numbers of the national qualifiers for the event. The first studies in this field applied correlation analyses which were later on replaced by more complex econometrics, and lately the analyses made a transition from the quantitative to qualitative rating methods.