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Going for Gold Medals: Factors affecting Olympic Performance
Abstract
This particular study titled " Going for Gold Medals: Factors affecting Olympic Performance was carried out with special reference to 2000 Olympic Games. This study was thoroughly undertaken by the researchers by focusing on the problem that why countries show different performance in Olympics? There were three objectives set to be achieved by this study, which include a key objective namely 'To examine the influences of factors affecting the Olympic performance and two specific objectives such as (i) To produce a mathematical model facilitating to predict the Olympic tally (ii) To identify the degree of factors influenced on the Olympic performance. The researchers carried out an extensive literature review to provide a conceptual background of the study, to develop a conceptual model, and to formulate hypotheses for the study. Olympic Games in 2000, 80 countries and 921 medals were selected for the survey. Certain conclusions were made from the study after carrying out detailed scientific analysis of data using appropriate statistical tools. The conclusions are that the factors such as size of population of countries, GDP per capita, HDI, communist background and host city advantages of certain countries in the particular Olympic year. It showed significant relationship with some variations between these variables and Olympic performance. Based on the findings of the study, recommendations were made to the sport authorities and researchers in the field of sport to improve sport performance in their countries in future.
... Notwithstanding the relevance of the individual predictors on sports performance [40,41], previous studies investigated the role of demographic, cultural, geographic, and economic predictors on success in international sports [14], and results indicated that larger population size, higher values on the Human Development Index, and GDP were directly associated with the number of medals won in Olympic games [20,[42][43][44]. These variables express both the economic power and demographic characteristics of the countries, such as their capacity of human capital and athletic development, as well as sports investment, and they are generally used when aiming to understand the differences in results between nations at international competitions such as the Olympic Games [45]. ...
... This indicates that investment in sports at both mass participation and elite levels may improve conditions related to athletes' training, career support for athletes, and programs for talent identification and development. Furthermore, investing in higher-level qualifications and training for coaches, increased numbers of accessible sports facilities and competitive sporting events, and scientific sports research contributes to elite level athletic success and increases the number of amateur participants in the sport, from whom it is possible to recruit professional/elite athletes [14,42,46]. For example, a possible explanation regarding the fact that the UK was the most represented in the top 10 ranking could be due to economic investments in sports development and achieving better positions in the Olympic Games, such as the World Class Performance Programme (implemented after the Atlanta 1996 Olympic Games) [47]. ...
... A plausible explanation for this association could be that found for similar results observed during the Olympic Games. The host country of the sporting event tends to present a higher likelihood of obtaining the best results, due to economic investment and public support related to athletes' development [42,50]. Moreover, when competing in their own countries, athletes have some "advantages", such as knowledge about the place of the competition (ground, route), adaptation to the climate and weather conditions, and crowd support, given that they are competing "at home" [51]. ...
Background: The environment can play a relevant role in performance in runners. This study aimed to verify the distribution of the best European road runners across the continent, and to investigate variables related to country representatives in the European Senior outdoor top list 2019. Methods: The sample comprised 563 European runners, aged 18-48 years, ranked in the European Senior outdoor top list 2019 for distances of 10-42 km. Country-related variables were gross domestic product (GDP), competition place, population size, and sports investment. The countries were categorized as "top ten countries" or "other countries". Binary logistic regression was used for analysis. Results: The United Kingdom showed the highest prevalence of runners in the ranking (men-17.6%; women-23.0%), followed by Spain (male ranking-12.1%) and Germany (female ranking-8.6%). For men, sports investment (OR = 1.13; CI95% = 1.03-1.28) and country GDP (OR = 0.96; CI95% = 0.93-0.98) showed an association with the chances of the athlete to reach the Top 10 ranking, while among women, the only variable significantly related was the competition venue (OR = 3.97; CI95% = 1.40-11.23). Conclusion: As in other sports considered "non-expensive", the economic and demographic characteristics of the place where athletes train can provide advantages in performance.
... Thus, at least for the Masters' category, the nation's frequency in the World Masters Ranking could be a strong indicator of HDI, since an association was found among them. It has already been demonstrated that recreational physical activity and sport performance are positively associated with the socioeconomic status both in children [3,14], and adults [15,16]. Similarly to the present study, Jayantha, Ubayachandra [16] demonstrated that variables such as size of population, GDP per capita, HDI, political system (whether communist or not) and host country advantages greatly influence the Olympic success (gold medals). ...
... It has already been demonstrated that recreational physical activity and sport performance are positively associated with the socioeconomic status both in children [3,14], and adults [15,16]. Similarly to the present study, Jayantha, Ubayachandra [16] demonstrated that variables such as size of population, GDP per capita, HDI, political system (whether communist or not) and host country advantages greatly influence the Olympic success (gold medals). However, sports practice is also determined by the culture surrounding the society [17]. ...
Introduction
The influence of socioeconomic factors in the achievement of sport success is still a matter of debate. Due to the popularity and low-cost practice, analyses of the Athletics World Ranking (AWR) may provide valuable information. Therefore, we investigated the frequency of different socioeconomic status in the AWR for two events (100 m and 10 k) in three categories: Junior, Elite Professionals and Masters.
Method
Data of 5,011 athletes from 99 nationalities were obtained from the official websites of International Association of Athletics Federations, and World Masters Rankings in the years of 2006–2016. The Human Development Index (HDI) for each nationality was used as a marker of socioeconomic status.
Results
An HDI × age group association was observed (χ² = 0.001, p = 0.001, φC = 0.322), where the analysis of frequency rate demonstrated a high prevalence of very elevated and elevated HDI in the AWR for the 100 m. For the endurance 10 k race analysis, the HDI × age group association was also observed, with a high prevalence of moderate and low HDI in Junior and Professionals. Regarding the Masters, the prevalence of moderate and low HDI is almost zero. In addition, multiple linear regressions indicate that the HDI, gross domestic product per capita (GDP/capita) and population can predict the frequency of a country in athletics ranking.
Conclusions
There is a high prevalence of elevated and very elevated HDI nationalities in the AWR in sprint races in all age groups. For endurance races, Junior and Professionals had a great prevalence of low/moderate HDI, and Masters are dominated by very elevated HDI. A nation’s frequency in the World Masters Ranking could be indicative of HDI, since an association was found among them.
... The Gini coefficient did not prove to be useful predictor; the HDI also had a low explanation power (R 2 is about 0.13). Vagenas and Vlachokyriakou (2012) found health expenditure as a good explanatory variable while Jayantha and Ubayachandra (2015) identified schooling as a possible factor affecting Olympic performance. The authors of this current study investigated not only the HDI as a composite indicator, but the parts of the HDI as well (Schooling and Life Expectancy) to examine the social hypothesis in more details. ...
"The exploration of factors underpinning Olympic success (number of medals won) extended to the Human Development Index (HDI). Analysis of the Rio Olympic Games supported the influence of geographic and social variables. Schooling was one of the most important predictors and together with population explained 64%; when adding geographic variables (North-West and temperature) 67% of Olympic medals won were explained. This relationship was validated in the last four Olympic Games (from 2004 to 2016). This is the first study ever to demonstrate that specific social and geographical factors determine more than two thirds of the variance in Olympic success. Keywords: Olympic medals, HDI, schooling, population size."
... Az arányosítatlan GDP-adatok mellett is szólnak érvek. Ezek közül a legfontosabb pont az olimpiai eredménytáblázat, ahol látható, hogy elsősorban a magas GDP-vel rendelkező országok szerepelnek kimagaslóan, nem pedig a magas egy főre jutó GDP-vel rendelkező államok (Jayantha-Ubayachandra [2015]). Ennek több oka is lehet: egyrészt az eredmények átpolitizáltsága, amelynek következtében a kimagasló GDP-vel rendelkező országok, az ún. ...
... Dentro de las variables personales destacan: las antropométricas, la genética, las destrezas psicológicas, las destrezas técnico-tácticas y la personalidad (González-García, 2017;Robazza y Bortoli, 2007;González-García, Pelegrín y Carballo, 2018). Dentro de las variables ambientales destacan: los padres, los profesores, los entrenadores, los mánagers, los programas de desarrollo de talentos, la competición, las facilidades en el entrenamiento, las características del país, etc. (Jayantha y Ubayachandra, 2015;Pezzoli et al., 2015;Rubin y Rosser, 2014;Siegel y Laursen, 2012). En este caso, la ira es un factor más de la amplia cantidad de variables que conforman los factores que inciden en el desempeño deportivo (Davis, 2011;Davis, Woodman y Callow, 2010;Parrott, 2001;Tamir, Mitchell y Gross, 2008;Woodman et al., 2009). ...
Introduction
Anger is a variable that can have an important influence on sport performance and many other related variables. Therefore, its relationship with competition level, sport and professional athletes, is has become an interesting field in scientific research.
Objectives
1) To verify the relationship between anger and the level of sport competition; 2) to investigate the link between anger and sport success; and 3) to identify the relationship between anger and professional athletes.
Method
The sample was composed of 502 athletes.
Material
A socio-demographic questionnaire ad hoc, the State-Trait Anger Expression Inventory (STAXI-2) and The Oviedo Scale of Infrequency of Response (INF-OV) were administered.
Results
Close to significant differences were found amongst those athletes who compete at an international level, because they had lower levels of trait anger and temperament than their counterparts. On the other hand, regression analyses showed a slight tendency to compete at lower levels in those cases where trait anger was high (p<.05).
Conclusions
It was concluded that anger may have an influence on the level of competition, because higher anger levels were more present at a lower rather than a higher level of competition.
... Dentro de las variables personales destacan: las antropométricas, la genética, las destrezas psicológicas, las destrezas técnico-tácticas y la personalidad (Elferink-Gemser y Visscher, 2012;Menéndez-Santurio y Fernández-Río, 2015;Robazza y Bortoli, 2007). Por otra parte, dentro de las variables ambientales destacan: los padres, los profesores, los entrenadores, los managers, los programas de desarrollo de talentos, la competición, las facilidades en el entrenamiento y las características del país (Jayantha y Ubayachandra, 2015;Medic, Mack, Wilson y Starkes, 2007). ...
The objectives of this research were to check the differences in the level of sport competition depending on parental education styles, and to know what the differences are in parental education styles in terms of sport success. In order to measure the different variables an ad hoc socio-demographic questionnaire, the Multifactor Self-Assessment Test of Child Adjustment (TAMAI) and the Oviedo Scale of Infrequency of Response (INF-OV) were carried out. The sample consisted of 502 Spanish athletes. The results showed that athletes without international successes obtained significant differences and higher results in mother's restriction. On the other hand, the fact that mothers educate their children towards protectionism showed significant differences in benefit of athletes who do not compete internationally. It was concluded that protective mothers are not related to having children who compete internationally and restrictive mothers are not related to having children who achieve international success.
Aim: In this study, it is aimed to contribute to the literature by analyzing the success of Turkey participating in the Para Taekwondo World Championships. Methods: In the study, Turkey's success over the years, which participated in the World Para Taekwondo Championships, the first of which was held in 2009 and the last in 2019, has been made. For this purpose, tables were created by using document analysis, one of the qualitative research methods. Results: In the findings section, an evaluation was made by tabulating the years the championships were held and the number of participants in Turkey, the number of medals won and the world rankings of these years .As a result of the research, it was found that with the increasing number of participants in each championship, there was an increase in the number of medals won. Conclusion: In the conclusion part, with the call of the Scientific and Technological Research Council of Turkey (TUBITAK)'s 1001-Scientific and Technological Research Projects Support Program "Sports Research", attention was drawn to the project studies aimed at improving disabled athletes and sports for the disabled. It was emphasized that research and project studies on para taekwondo branch could increase the number of elite athletes and thus the successes in the international World Para Taekwondo Championships could be continued increasingly. Keywords: Para Taekwondo, Document analysis, World Para Taekwondo Championships
Sports performance is a multifactorial trait resulting from the interplay of individual, environmental, and task characteristics. Due to its complex, dynamic, and multidimensional nature , understanding the performance variability among athletes requires the adoption of a holistic perspective, that considers the integration of the levels, interacting at different scales during the performance. The idea that performance is determined by genes, i.e., that athletes are born to be succeed is one of the most complex and enduring controversial debates in sports science. However, previous studies have shown that beyond athlete's characteristics (such as physiological index and traits, anthropometric variables, training commitment), it should also be considered the pivotal role of environmental constraints when analysing sports performance. Indeed, one of the most neglected aspects, when studying sports performance, is the "external environment", which comprises, for example, the financial support, sociodemographic variables, training facilities, and local public policies. In this context, studies have reported an apparent relationship between gross domestic product, population size, and human development index with international sports success , even in sports where the "economic factor" is not usually signaled as a determinant. Bosscher, et al. highlight that sports success is influenced by a set of variables hierarchically organized into three interacting systems, namely: the "micro-level" (individual characteristics), "meso-level" (public policies), and "macro-level" (sociodemographic characteristics, cultural aspects). Focusing on the "meso-level", a conceptual model composed of 9 pillars was developed, involving factors that can be promoted through public policies in the medium and long term. Such an approach amplified the discussion related to how sports success can be developed. Especially at an international level, the spotlight has moved from "who has more financial resources?" to 1) "how the available resources are oriented for high sports performance?" and mainly 2) "how much, and how is performed the investment of available resources for sport promotion and development?". Despite advances in theoretical and practical approaches allied with an increased understanding of variables that predict sports success, the answer for the question "what does determine sports performance", still remains unknown, meaning that the unpredictability in sport persists as its striking feature. The purpose is to present a brief idea about the understanding of sports performance through the lens of systems theories. [1] [2] [3] [4][5] [6][7][8] [9][10] [11] [12] References 1. 2. 3. 4. Cote, J.; Macdonald, D.J.; Baker, J.; Abernethy, B. When "where" is more important than "when": birthplace and birthdate effects on the achievement of sporting expertise.
Rekabetin giderek arttığı günümüz spor dünyasında, uluslararası müsabakalarda elde edilen başarılar, tüm dünyada büyük yankı uyandırmaktadır. Sporun toplum üzerindeki etkisini artırması ve medyanın her geçen gün spora daha fazla ilgi göstermesi, bu müsabakaların önemini giderek artırarak, başarılı ülkeler için gurur ve prestij kaynağı oluşturmaktadır. Literatürde birçok araştırma, Olimpiyatlar gibi üst düzey müsabakalarda elde edilen başarıları etkileyen faktörleri ortaya koymuştur. Genel olarak, nüfus ve ekonomik şartlar gibi faktörlerin sportif başarıda etkisi olmakla birlikte, ülkeler arasında rekabetin artması, özellikle elit sporcu yetiştirme ve geliştirmede stratejik yöntemlerin kullanılmasına olan ihtiyacı artırmıştır. Makro düzeyde etkisi olan faktörlerden farklı olarak, hükümetler tarafından kontrol edilebilir ve değiştirilebilir, sporda uzun vadeli başarı getirebilecek sistem ve politikaların geliştirilmesi, bu noktada büyük önem taşımaktadır. Bu araştırmada, Türkiye’nin Bakü’de düzenlenmiş olan 1. Avrupa Oyunları’nda göstermiş olduğu sportif performansını, literatürdeki araştırmalar ışığında ve kendi spor sistemine göre değerlendirilmesi amaçlanmaktadır. Türkiye’nin uluslararası düzeyde sportif başarıyı yakalayabilmesi için ülkedeki bireylerin spordan en verimli şekilde yararlanmalarını sağlayan, bilimsel gerçekliklere ve kültürel farklılıklara dayandırılmış geliştirilebilir ve uygulanabilir spor politikalarına ihtiyaç duyulmaktadır.
The goal is to identify the differences in trait anger among athletes and people who practice sports in
general who considered their body structure and physical characteristics had an influence on their athletic
performance. The sample consisted of 366 athletes and people who practice sports in general with an age
range from 18 to 64 years old (M = 27.76; SD = 9.11). An ad hoc sociodemographic questionnaire and the
Trait-State Anger Expression Inventory (STAXI 2) were used to measure the different variables. Results
showed that participants who believed that their physical morphology had a negative influence on their
performance showed greater levels of: trait anger (p < .05), temperament (p < .01), internal expression
(p < .01), external expression (p < .01) and expression index (p < .01). A negative perception of one’s own
body structure and physical characteristics was associated with higher levels of anger. This result may
either be due to the higher levels of anger which may distort one’s perception of his/her body structure
and physical characteristics, or that a biased perception of the latter may be responsible for the high
levels of anger.
To gain a better understanding of factors perceived to have positively and/or negatively influenced Olympic athlete performance and to examine differences in performance factors cited by athletes who met or exceeded performance expectations and athletes who failed to meet expectations, 8 Atlanta and 7 Nagano Olympians were interviewed. Interviews were conducted via telephone, tape recorded, transcribed, and content analyzed by three investigators. Major factors perceived to have positively influenced performance included mental skills and preparation, attitude towards the Olympics, support services and support facilitation, multifaceted preparation, physical preparation, and coaching. Major factors perceived to have negatively influenced performance included departing from normal routine, media distractions, coach issues, overtraining, and injury. The two groups, those who met or exceeded expectations and those who did not meet expectations, differed on only a few positive performance factors, including attitude towards the games, Olympic housing, and team unity. Negative factors that differed between the groups included team selection, coaching, lack of support, and team issues.
As the Olympic Games developed and their popularity and relevance grew, winning medals also became important and a matter of national and political prestige. Despite the International Olympic Committee's refusal to recognize country rankings by medals, the medal table is updated on a regular basis and plays a dominant role in media coverage and public interest (Rathke & Woitek, 2007). This has led researchers to explore the socio-economic, cultural and geographic background of Olympic achievements. The aim of this paper was to review the current state of the research on factors that influence national Olympic Games success. The majority of studies consider variables like: population size, GDP and GDP per capita, hosting or neighbouring country advantage, political system, sports system, health expenditure per capita, climate, etc., as factors that potentially have impact on a country's medal count. The research has shown that the economic factor, mainly GDP per capita, and political system have a statistically significant influence on the explanation of the numbers of medals won by a certain country at the Olympic Games, but the influence of population size was not confirmed. Keeping in mind the mentioned factors, it is unlikely for Croatia to increase significantly its number of Olympic medals in the future.
This paper uses forecasting techniques to predict outcomes in the Beijing Olympics and 2010 World Cup using economic variables.
This paper investigates the relationship between a country's Olympic performance and its overall economic condition, including population, economic resources, and political structures. A panel data set comprising the yearly data of 1996, 2000, and 2004 are estimated by using a fixed-effect Tobit regression model. Following previous studies on this topic, population size and economic resources are measured by using population and per capita GDP. One major focus of this research is the influence of political structure on national Olympic performance. Instead of using a socialist and non-socialist dummy variable like most previous studies, I used continuous variables, political freedom (PF) and civil liberty (CL), to estimate the impact of political structure.Consistent with previous studies on this topic, the regression results indicate that countries with a larger population and more abundant economic resources are more likely to perform better in the Olympic arena. Countries that are politically "Not Free" generally seem to perform better in the Olympics by winning more medals than the rest of the world. One interesting finding is that the results suggest weakly that political freedom variables, both political freedom and civil liberty, display a V-shaped relationship with respect to medal shares. Being "Partly Free", has a negative effect on national Olympic performance as compared to countries that are "Free" and "Not Free".
This paper examines determinants of Olympic success at the country level. Does the United States win its fair share of Olympic medals? Why does China win only 6% of the medals even though it has one-fifth of the world's population? We consider the role of population and economic resources in determining medal totals from 1960 to 1996. At the margin, population and income per capita have similar effects, suggesting that both a large population and high per capita GDP are needed to generate high medal totals. We also provide out-of-sample predictions for the 2000 Olympics in Sydney. Copyright (c) 2004 President and Fellows of Harvard College and the Massachusetts Institute of Technology.
Not everyone in our country has equal access to competitive sports. Many are not effective participants on account of ignorance or disinterest, disability or deterrence. This analysis considers two separate arenas for enlarging the pool of effective participants, one related to sports and other to social mobility. In both cases, this paper finds the plausibility of an explanation based on effective participation rates. It examines what country characteristics are associated with greater success in the Olympics at the macro level by considering indicators such as health, education, and especially three variables of information and access (road length per unit of land area, the share of urban population and radios per capita). It also analyses the opportunities and achievements in the villages of two states, Karnataka and Rajasthan.
Demographic and economic characteristics have been shown to provide important predictive power for determining a country's success in the Olympic Games. This paper extends such research, providing a set of predictions for the gold medals and total medals each country will win at the 2006 Winter Olympics. We expected Germany to win the most medals, followed by the United States, Norway, Italy, Austria, and Canada. For total medals, the overall correlation between the predictions and the actual results was 0.934. While Germany and the United States did finish in the top two places, there were some surprises as Canada, Austria, and Russia performed better than expected, while Norway and Italy did not live up to expectations.
In this paper, we construct several models that try to predict a country’s success at the Summer Olympic Games. Our data set consists of total scores for over 271 sporting events for 195 countries that were represented at the 1996 Summer Games and information we gathered on 17 independent variables. We build linear regression models and neural network models and compare the predictions of both types of models. Overall, the best neural network model outperformed the best regression model.Scope and purposeEvery four years, an enormous amount of attention is focused on the Summer Olympic Games. Sports fans and analysts do their best to predict the outcomes with respect to many sporting events and the overall performance of nations competing at the Olympics. In this paper, we develop and compare socio-economic-based models for predicting the success of nations at the Summer Olympics.
This paper examines determinants of Olympic success at the country level. Does the U.S. win its fair share of Olympic medals? Why does China win 6% of the medals even though it has 1/5 of the world's population? We consider the role of population and economic development in determining medal totals from 1960-1996. We also provide out of sample predictions for the 2000 Olympics in Sydney.