FIFA Ranking Research Articles

Comparing physical, technical and tactical performances in the World Cup Qatar 2022

The main objective of this study was to compare the physical, technical, and tactical performances of the 32 teams that participated in the FIFA World Cup Qatar 2022™ concerning the confederation to which they belong and the FIFA ranking. Key statistics from the 64 matches played during the FIFA World Cup Qatar 2022™ were analysed. The data from these matches were encoded and calculated by a multi-camera optical tracking system (TRACAB Gen5, ChyronHego). Significant differences were identified between Rank 1-15th vs. Rank 16-35th and Rank 1-15th vs. Rank 36-61st for possession, total attempts at goal, total attempts on target, total passes, total complete passes, passes completion possession, completed line breaks, defensive line breaks, receptions in the final third, and ball progressions. However, defensive line breaks were different only between Rank 1-15th vs. Rank 36-61st, and ball progressions was only different between Rank 1-15th vs. Rank 16-35th. Africa and Europe national confederation showed significant differences (all p < .05) for possession, total attempts on target, total passes, total complete passes, passes completion, completed line breaks, and receptions in the final third, except for total attempts on target, whose differences are between Asian and South American confederation (p < .05). When considering the FIFA ranking and the confederations, there are significant differences key performance indicator of the teams.

Football migration in the Czech Republic: A multi-level analysis of football migration in a semi-peripheral European Nation

ABSTRACT Football migration, including flows and effects, is measured over the first 27 years of the independent Czech Football League. Hierarchical multi-level analysis is used to test previous sport migration effects. Particular attention is paid to the economic and sport position of both sending and receiving nations by examining results through the world-systems theory. Though the number of football migrants continues to rapidly increase, the statistical results of this study indicate that receiving football migrants into the semi-periphery nation of Czech, where football is a primary sport, may increase winning percentage in the short term, but it does not lead to increases in fan attendance or improve the nation’s FIFA rankings. Longer term deliberation needs to be taken by individual club teams, as well as national federations, in order maximize the benefits of migration flows in the future.

Key factors contributing to the rise of Northeast in Indian football

This article highlights the achievements of Northeast in Indian football and the underlying reasons for the same. Northeast India has been a torchbearer in sports and Indian football in particular, has been characterized by dominance of players from Northeast region of India. Work by All Indian Football Federation (AIFF), lack of cricket fanaticism, upward economic mobility and the lure of government jobs, state and local interest towards the game, nature of football, tenacity of the players, and suitable climate are some reasons behind the ascendency of Northeast in Indian football. For further development of football in the regions, steps like monetary incentives, development of strategic and talent academics, world class infrastructure, foreign trips and recruitment of professionals should be undertaken. There is still a long way to go, for India to be called a sports superpower. One way for the nation to own the tag is through football which is the most popular game and has one of the highest viewership in the world. Although the nation’s FIFA ranking stands at a dismal 106, despite a population of 1.4 billion, Indian football can look forward for its improvement and eventual dominance by deriving the benefits of talents and quality Northeast has been consistently producing. With the right steps and directions, we may not need to wait for too long to cheer for our own country in the coming editions of FIFA World cup.

Gender Equality and Institutions as the Driving Force of Football Performance: Women vs Men

Gender equality should be a necessity in every developed economy of the world. Despite this assumption, this is not the case. The field of sports is no exception. This study addresses the relationship between gender equality, institutions and football performance of national teams. Correlation and regression analysis is used to determine the relationship between variables. The results suggest that higher gender equality leads to better performance for footballers on the fields. Countries with higher gender equality perform better (more FIFA points). The economic condition of the country has a similar effect on performance. Estimates have shown a statistically significant positive relationship between economic prosperity and performance on the pitch. Climate and age of players do not affect the performance of national teams. Institutional factors significantly affect players’ performance. Members of the European Union perform significantly higher than those that are not in the EU. As well as countries in which there was no communist regime in the past . Keywords: gender inequality index, FIFA ranking, men, women, institutions

The Economy of Greece and the FIFA Ranking of its National Football Team

The purpose of this study is to compare the performance of the Greek economy with the FIFA ranking of the Greek National Football Team in order to find out whether there exists some sort of statistical association. The period under consideration starts with the establishment of the European and Monetary Union in 1992 and ends with the current year of 2021. In 1992, FIFA started to rank national football teams which restricts the extent of time to be used in this study. The descriptive evidence presented in this paper shows that there exists strong positive association between the level of real Gross Domestic Product (GDP) of Greece and the ranking of its national football team. Keywords: FIFA, Greece, Football, GDP, European Union, National Teams.

A Forecasting Model of Success at the Euro Tournaments: The Role of Team’s Performance at Qualifying Games

The European Football Championship (Euro) is different from any other soccer competition in the world in that it has a long and homogeneous qualifying period for all teams. Using data from every tournament that has taken place in history, a step logit model is estimated to quantify the role of team’s earlier qualifying performance in the likelihood of success at the final stage. Considering only the information available at the date preceding each of the last three Euros, we test the model’s ability to forecast the winner at future tournaments. The model correctly predicted Spain to win it in 2008 and 2012, as well as Portugal to take the Cup in 2016. Teams’ efficacy during qualification is found to be a key contributor to the model’s forecasting performance. Our results have strong implications about the current FIFA ranking system as a way to gauge teams’ relative strength, as well as about which information a sophisticated bettor should process in order to beat the odds and make a profit out of the betting market. In that regard, we conclude that the betting market is possibly not efficient when pricing teams at the Euros.

Competitive balance within CONCACAF: a longitudinal and comparative descriptive review of the seasons 2002/2003–2017/2018

ABSTRACTRationale/Purpose: This article examines the trend in competitive balance and its association with end-of-year FIFA rankings among CONCACAF football associates.Design/methodology/approach: Secondary data were collected from the football domestic league tables for the seasons 2002/2003–2017/2018 of Costa Rica, Mexico, USA, Panama, Jamaica, Honduras, Trinidad and Tobago and Canada. Competitive balance was assessed using the Five-Club Concentration Ratio Index of Competitive Balance (C5ICB), Herfindahl Index of Competitive Balance (HICB) and Lorenz Seasonal Balance Curve. Linear regression modeling was used to assess the relationship between end-of-year FIFA ranking and competitive balance.Findings: The most competitive league was the USA, Honduras and Mexico, while the least competitive leagues were Trinidad and Tobago, Canada and Panama. For the 2017/2018 season within CONCACAF it was seen that the football leagues of the Jamaica, USA, Mexico and Panama were the most competitive balance leagues. The HICB and C5ICB were both significant predictors of a change in CONCACAF countries end-of-year FIFA rankings.Practical Implications: Competitive balance continues to be a vital component in assessing the viability and competitiveness of a football league which may have direct impacts on league authorities, marketing revenue streams and spectator attractions.Research Contribution: This is the first study to describe competitive balance in CONCACAF.

An analytics approach to the FIFA ranking procedure and the World Cup final draw

This paper analyzes the procedure used by FIFA up until 2018 to rank national football teams and define by random draw the groups for the initial phase of the World Cup finals. A predictive model is calibrated to form a reference ranking to evaluate the performance of a series of simple changes to that procedure. These proposed modifications are guided by a qualitative and statistical analysis of the FIFA ranking. We then analyze the use of this ranking to determine the groups for the World Cup finals. After enumerating a series of deficiencies in the group assignments for the 2014 World Cup, a mixed integer linear programming model is developed and used to balance the difficulty levels of the groups.

Elite sport policies and international sporting success: a panel data analysis of European women’s national football team performance

ABSTRACT Research question: While national sporting governing bodies are encouraged to implement programmes which seek to enhance their international sporting success, comparative studies on elite sport policies have provided limited empirical evidence in support of the relationship between such programmes and the achievement of sporting outcomes. Following the SPLISS framework, this study examines the longitudinal impact of four programme-level factors – financial support, human resources, coaching provision and foundation phase activity – on the international success of women’s national football teams. Research methods: Data from 55 Union of European Football Associations’ (UEFA) members were collected over a seven-year-period (2011-2017). The associations between programme-level factors and FIFA ranking points are verified through panel regression analyses. Controls for economic, talent pool, political, socio-cultural, climate and men’s football legacy variables are included. Results and Findings: The results reveal that highly specialised coaching provision has a significant and positive impact on international success in women’s football, while our proxies for financial support, human resources and foundation phase activity have no notable explanatory power for the success of women’s national teams. A country’s economic development, talent pool, climate and men’s football legacy are significant predictors of its women’s football performance level. Implications: This paper offers practical insights into the organisation and management of women’s football in UEFA nations and contributes to the theoretical debate on comparative analysis of the sporting performance of countries. This article confirms that an exclusively quantitative approach does not permit definitive conclusions to be drawn on the complex relationship between elite sport policies and international sporting outcomes.

The schedule of World Cup and its impact on the team

This paper discusses the organization of the World Cup competition, in which through the establishment of a number of scheduling model, the use of analytic hierarchy process and stochastic simulation and other methods to solve this problem and obtain a more reasonable arrangement of the competition. For the arrangement of the Order of the game, first of all, the existing competition is studied. On the premise of the increase in the number of teams and the previous arrangement of the group points, it is considered from the appropriateness of the field, whether the schedule is wonderful, whether the arrangement is simple and whether the ranking is reasonable. 3 new competition competitions are proposed for the improvement of the original competition. Then, the analytic hierarchy process is used to compare and analyze the 3 new competition methods, and the optimal competition method is selected. Finally, under the previously established game, FIFA’s integral algorithm formula is used to analyze and calculate the impact of the results produced under the competition on FIFA rankings. In the application of formula calculation, the stochastic factor is introduced, and the results are simulated by computer, which can get the approximate upward trend of the team in different ranking intervals.

Predicting matches in international football tournaments with random forests

Many approaches that analyse and predict results of international matches in football are based on statistical models incorporating several potentially influential covariates with respect to a national team's success, such as the bookmakers’ ratings or the FIFA ranking. Based on all matches from the four previous FIFA World Cups 2002–2014, we compare the most common regression models that are based on the teams’ covariate information with regard to their predictive performances with an alternative modelling class, the so-called random forests. Random forests can be seen as a mixture between machine learning and statistical modelling and are known for their high predictive power. Here, we consider two different types of random forests depending on the choice of response. One type of random forests predicts the precise numbers of goals, while the other type considers the three match outcomes—win, draw and loss—using special algorithms for ordinal responses. To account for the specific data structure of football matches, in particular at FIFA World Cups, the random forest methods are slightly altered compared to their standard versions and adapted to the specific needs of the application to FIFA World Cup data.

Социальный капитал — фактор спортивных достижений (на примере национальных сборных по футболу)

Social capital defined as an ability to act cooperatively towards a common goal plays important economic role. This research aims at defining the nature and quantifying the degree of social capital impact on outcome of collective actions, having analysed the case of national football teams. The measure of national football teams' social capital is based on the national level indicators, extracted from the European Social Survey for 34 countries from 2004 to 2014. For the purpose of the study the defined social capital measures are classified into variables of efficiency of collective actions and prosocial motivation. Such differentiation allows us to distinguish between the two mechanisms of social capital influence on national football team performance: ability of players to interact effectively within a team and importance of a team win for them. National football team success is measured by an official FIFA ranking, while talent of a team is estimated as a sum of players' market values. The econometric analysis, which includes an interaction term of social capital and talent, allows us to confirm the hypothesis of positive and complementary effect of social capital and talent on national football team performance. The obtained result confirms the general thesis about the significant role of social capital in collective actions problem and provides a deeper understanding of preconditions of success in team sports, and football in particular.

Testing the Wisdom of Crowds in the field: Transfermarkt valuations and international soccer results

This paper investigates the value of collective judgments which stem from settings that have not been designed explicitly to elicit the ‘Wisdom of Crowds’. In particular, I investigate information obtained from transfermarkt.de, an online platform where a crowd of registered users assess the value of professional soccer players. I show that forecasts of international soccer results based on the crowd’s valuations are more accurate than those based on standard predictors, such as the FIFA ranking and the ELO rating. When this improvement in forecasting performance is applied to betting strategies, it leads to sizable monetary gains. I further exploit information on the preferences of individual crowd members in order to investigate whether wishful thinking hampers the accuracy of crowd valuations, but fail to find evidence that such is the case.

Politics and international fandom in a fringe nation: La Albiceleste, Maradona, and Marxist Kolkata

Despite India’s disappointing position in the FIFA rankings and the nation’s failure to make it to the biggest stage of Soccer, it has a rich historic tradition in the field of football. With India never competing in the World Cup, it was with the giants of Latin American football, Brazil and Argentina, who the fans from Kolkata developed a sense of bonding with. In Pelé and Maradona they discovered heroes who they could identify, worship and empathize with. This essay will focus on how after the departure of Pelé the La Albiceleste or Argentina successfully penetrated the ‘Brazilian colony’ of Kolkata. The essay concentrates on the figure of Maradona and examines how, for more than a decade, Kolkata’s passion for him was built around his football ability, personal life and political beliefs, by analysing literary output and support activities. It concludes with a study of Maradona’s visit to Kolkata in 2008. It thus shows to what extent do the reception of world football and global icons provide a unique opportunity to understand the complexity of fandom as a global process.

How to improve a team's position in the FIFA ranking? A simulation study

In this paper, we study the efficacy of the official ranking for international football teams compiled by FIFA, the body governing football competition around the globe. We present strategies for improving a team's position in the ranking. By combining several statistical techniques, we derive an objective function in a decision problem of optimal scheduling of future matches. The presented results display how a team's position can be improved. Along the way, we compare the official procedure to the famous Elo rating system. Although it originates from chess, it has been successfully tailored to ranking football teams as well.

Competitiveness of Young Football Players in the Japan Football Association Social Action Program

Conditions affecting the competitiveness of young group athletes in different countries were investigated through a comparative evaluation of opinions expressed by coaches and instructors dispatched overseas through the JFA Social Action Program in Asia. Results of a one-way analysis of variance on responses scores related to football teams in different countries, which was conducted after calculating group means and standard deviations indicated that physical strength and mental strength scores were significantly higher in teams of the high ranking group than in teams of low the ranking group classified according to FIFA rankings. These results suggest that there is an urgent need to establish football teams on a school wide basis and to become affiliated organizations of professional football clubs in countries in the low ranking group, in order to develop continuous training for each category of young athletes. Such training would be necessary to increase physical strength and decrease differences in physical strength between low and high ranking groups of countries. Similarly, it would be important for young athletes continue training, participate in games, and feel a sense of improvement and fulfillment in order to bridge the gap in mental strength scores between low and high ranking groups. A comprehensive balance between training, playing games, and a sense of fulfillment is expected to lead to prioritized training and to the development of a sense of pride among young athletes representing their country by playing football.

Is Football an Indicator of Development at the International Level?

The aim of this paper is to examine whether football can be considered an indicator of development at the international level. An empirical econometric model is designed in order to analyse development in terms of GDP per capita as well as in terms of the Human Development Index. Cross-sectional and time-series information are used. The results suggest that FIFA rankings of national teams can be used to complement our understanding of multidimensional development, in particular, in those countries where the availability of information is not as good as researchers would like.

A Model Based Ranking System for Soccer Teams

In competitive sports, the design of an effective ranking system attracts increasing interests. For sports with 2-way results, the Bradley-Terry model has proven to be an effective approach. However, a well-known limitation of standard Bradley-Terry models is that they cannot be applied to sports which allow to end with a tie after regular playing time. During the past decades various methods have been explored to model soccer games in the literature. In this paper, a new extended Bradley-Terry model with various covariates is devised to construct a more advanced ranking system for international soccer teams based on their games played within the past 4 years. First a standard likelihood (ML) estimation method was employed. A weighted likelihood (WML) estimation procedure was run for further improvement. Finally an evolutional model was developed to capture the dynamic trend in performance during big events. This paper examines the extent to which our ranking differs from the existing FIFA ranking. In addition, the 2012 UEFA European Football Championships was analyzed.

The predictive power of ranking systems in association football

We provide an overview and comparison of predictive capabilities of several methods for ranking association football teams. The main benchmark used is the official FIFA ranking for national teams. The ranking points of teams are turned into predictions that are next evaluated based on their accuracy. This enables us to determine which ranking method is more accurate. The best performing algorithm is a version of the famous Elo rating system that originates from chess player ratings, but several other methods (and method versions) provide better predictive performance than the official ranking method. Being able to predict match outcomes better than the official method might have implications for, e.g., a team’s strategy to schedule friendly games.

An Ordinary Country

South Africans see themselves as a nation that loves sport, but with the World Cup in football imminent, there appears to be a sense of exhaustion both in the media and among the population. One important reason is that football does not dominate the public imagination of sport, as cricket and rugby do. The game is played and loved in the black townships, the fortunes of African football-playing nations are followed devotedly, and players such as Didier Drogba have a larger-than-life standing in the country. But football has not become a metaphor for the nation, as rugby and cricket have become. Whether this reflects a racial affiliation alone is hard to get at, because the local team, Bafana (which could be genially translated as “the boys”), are eighty-eighth in the FIFA rankings, without a ghost of a chance of winning the Cup, while at rugby and cricket, South Africa are world beaters.