An Economic Analysis of Sports Performance in Africa

The purpose of this study is to develop insight into the socio-economic determinants of African sports performance. Previous studies have argued that a country’s success in sports is directly related to the economic resources that are available for those sports. However, factors that are used to determine the levels of success for developed countries are not necessarily the same, or bear the same weight, as for developing countries. The premise of this study is to identify specific factors that increase success in sports in developing countries by means of several econometric specifications, using cross-sectional data for African countries. This study finds evidence that suggests that Africa’s performance in sports is dependent on a range of socioeconomic factors, which in some respects confirms worldwide studies, but also adds significant nuance.Sports performance, economic determinants, Africa

Economic Prediction of Sport Performances: From Beijing Olympics to 2010 FIFA World Cup in South Africa

This paper uses forecasting techniques to predict outcomes in the Beijing Olympics and 2010 World Cup using economic variables.sport, Olympics, World Cup

CAN WE PREDICT THE OUTCOME OF THE INTERNATIONAL FOOTBALL TOURNAMENTS : THE CASE OF EURO 2000?

This paper statistically analyses and attempts to predict the most likely winners of the Euro 2000 football tournament on the basis of the seasonal coefficients of variation (CVs) of the end-of-season points, which were computed from the top division final standings of participating countries of Euro 2000. The CV values computed from over ten seasons for the respective countries were used as a sole measurement value to rank the countries and to determine the most likely winners of Euro 2000. According to the three scenarios (long-term, mid-term, and short-term) based on the respective CV values of fifteen countries, France appeared to be the most likely country to win Euro 2000 and was closely followed by Spain.Football, Ranking, UEFA, Sports forecasts.

The (non) determinants of Olympic success

This paper empirically examines the determinants of Summer Olympic success during the period 1996-2016. By modifying the panel Tobit estimator using the Mundlak transform, the results find that population size and the host effect are the only statistically significant determinants of Olympic attainment. We also show that participating in front of a home crowd will stimulate athletic performance equally for each gender, but the impact of population differs between the sexes. These findings are confirmed using a hurdle estimator. This relaxes the assumption that the factors determining Olympic success are the same as those that influence the quantity of success

The paradox of measuring success of nations in elite sport

The achievement of international and especially Olympic sporting success is increasingly important to a growing number of countries. It is however not clear how success is defined and can be measured. The number of medals won in Olympics Games and other international sport competitions offers the most self-evident and transparent measure of success in high performance sport. In this article different methods to measure success of nations are compared. Market share was identified as the best measure of absolute success which enables meaningful time series analysis to be conducted. A Linear regression analysis is used to introduce relative success as a measurement of success when controlling for macro determinants such as population and wealth. This method allows comparing nations on more equal grounds, which is necessary if one wants to measure effectiveness of elite sport policies. Similar analysis is done for Olympic Summer and Winter Sports. It is concluded that conflicting results can be given on nations’ success. Defining success therefore depends on the purpose wherefore it is used and on the priorities of individual nations.Les performances sportives au niveau international, et particulièrement au niveau olympique, prennent de plus en plus d’importance pour un nombre croissant de nations. Mais il n’est pas évident de définir ni de mesurer le succès. Le nombre de médailles gagnées lors de Jeux olympiques ou autres compétitions internationales représente la mesure la plus objectivable et la plus transparente du succès dans le sport de haut niveau. Dans cet article, nous comparons différentes méthodes permettant de mesurer ce genre de performances. La part de marché a été identifiée comme la meilleure mesure de succès absolu permettant de procéder à une analyse de séries temporelles significative. Une analyse en régression linéaire est utilisée pour présenter le succès relatif comme mesure du succès lorsqu’on maîtrise des facteurs macro-déterminants tels que la population et la richesse. Cette méthode permet de comparer les différents pays sur des bases plus égales, ce qui est indispensable si l’on veut mesurer l’efficacité des politiques en matière de sport d’élite. Nous procédons ensuite à une analyse similaire pour les Jeux olympiques d’été et d’hiver, avant de conclure que nous parvenons à des résultats contradictoires quant aux performances des différents pays. En effet, le succès dépend du but dans lequel on l’utilise ainsi que des priorités de chaque nation

Can We Predict the Outcome of the International Football Tournaments? : the Case of Euro 2000

Bu çalışma Euro 2000 futbol turnavasını hangi finalist ülkenin kazanabileceğini istatiksel olarak analiz etmeyi amaçlamaktadır. Euro 2000 futbol turnavasına katılan finalist ülkerin birinci lliglerinde oluşan yıl sonu puan tablolarından hesaplanan değişim katsayısı (DK) bu öngörü için kullanılmıştır. Euro 2000 futbol turnuvası öncesi her finalist ülke için hesaplanan son on yılın DK değerleri, finalistlerin futboldaki rekabetçiliklerini sıralamada ve Euro 2000’ni kazanmalarında tek belirleyici değişken olarak kullanılmıştır. On beş finalist ülke için hesaplanan uzun, orta ve kısa dönem DK değerlerinden oluşturulan senaryolara göre Euro 2000’ni Fransa’nın kazanmasının en muhtemel olduğu ve İspanya’nın ise diger bir güçlü aday olduğu öngörülmüştür.This paper statistically analyses and attempts to predict the most likely winners of the Euro 2000 football tournament on the basis of the seasonal coefficients of variation (CVs) of the end-of-season points, which were computed from the top division final standings of participating countries of Euro 2000. The CV values computed from over ten seasons for the respective countries were used as a sole measurement value to rank the countries and to determine the most likely winners of Euro 2000. According to the three scenarios (long-term, mid-term, and short-term) based on the respective CV values of fifteen countries, France appeared to be the most likely country to win Euro 2000 and was closely followed by Spain

Can We Predict the Outcome of the International Football Tournaments? : the Case of Euro 2000

Bu çalışma Euro 2000 futbol turnavasını hangi finalist ülkenin kazanabileceğini istatiksel olarak analiz etmeyi amaçlamaktadır. Euro 2000 futbol turnavasına katılan finalist ülkerin birinci lliglerinde oluşan yıl sonu puan tablolarından hesaplanan değişim katsayısı (DK) bu öngörü için kullanılmıştır. Euro 2000 futbol turnuvası öncesi her finalist ülke için hesaplanan son on yılın DK değerleri, finalistlerin futboldaki rekabetçiliklerini sıralamada ve Euro 2000’ni kazanmalarında tek belirleyici değişken olarak kullanılmıştır. On beş finalist ülke için hesaplanan uzun, orta ve kısa dönem DK değerlerinden oluşturulan senaryolara göre Euro 2000’ni Fransa’nın kazanmasının en muhtemel olduğu ve İspanya’nın ise diger bir güçlü aday olduğu öngörülmüştür.This paper statistically analyses and attempts to predict the most likely winners of the Euro 2000 football tournament on the basis of the seasonal coefficients of variation (CVs) of the end-of-season points, which were computed from the top division final standings of participating countries of Euro 2000. The CV values computed from over ten seasons for the respective countries were used as a sole measurement value to rank the countries and to determine the most likely winners of Euro 2000. According to the three scenarios (long-term, mid-term, and short-term) based on the respective CV values of fifteen countries, France appeared to be the most likely country to win Euro 2000 and was closely followed by Spain