The team who was able to generate the most incomes by transferring players to big-5 league clubs is Southampton (120.7 million €). The English team outranks Real Madrid (112 million €) and Chelsea (102.4 million €). The only non big-5 league clubs in the top 10 of the ranking is Porto (83.8 million €). However, a big part of transfer incomes of the Portuguese team was finally due to third-parties that held shares on the economic rights of players transferred.

Among the 46 teams that earned at least 15 million €, only six are not part of big-5 leagues: Benfica, Ajax, Sporting Lisbon, Feyenoord, Dinamo Kiev and Salzburg. More information is available in the 81st issue of the Big-5 Weekly Post.

This year’s predictions take into account the following areas: players’ status, squad cohesion and club ambition. The indicator of players’ status considers minutes played by squad members during the previous season, as well as overall results achieved by their employer club. Squad cohesion refers to the percentage of domestic league minutes played in 2013/14 by footballers who are still at the club, as well as the average number of seasons played by current squad members at the employer team. Finally, club ambition includes the average length of contract duration of first team players, as well as the ratio between the status of new signings and that of footballers released by the club during the last transfer window.

Analysis of the above criteria by the CIES Football Observatory academic team indicates that Chelsea, Barcelona, Paris St-Germain, Bayern Munich and Rome are in the most favourable position to win the title in their respective leagues. Our data also suggests that the runners-up will be Manchester City, Real Madrid, LOSC Lille, Borussia Dortmund and Juventus. Among promoted teams, Leicester City, Burnley, Deportivo La Coruña, Metz and Cologne are well placed to achieve good results. In contrast to this, the following clubs are forecast to struggle in achieving satisfactory results: Crystal Palace, Sunderland, Almería, Nice, Eintracht Frankfurt and Chievo Verona.

Enjoy the season and may the best teams win!

Our ‘right price’ has been calculated as the average between a player’s transfer value both before and after the deal. Significantly, the latter figure also considers the new contract duration of the footballer recruited. Both values have been calculated according to the exclusive CIES Football Observatory statistical model which incorporates nearly 1,500 fee paying transfers completed since 2009 (see below).

Our new data analysis has revealed that overall clubs paid on average 16% more than they invested in the five previous years for players with similar characteristics (add-ons included). This confirms the ongoing inflation trend of the transfer market at the top end of the football pyramid. The inflation trend is mainly due to the sums spent by a handful of wealthy clubs. This was notably the case for Manchester United with regard to Angel Di María (+30 million € between the right price and fee reported), for Paris St-Germain for David Luiz signing (+ 29 million €) and for Real Madrid in the case of James Rodríguez (+25 million €).

At the opposite end of the table, our analysis shows that the existence of buy-out clauses and/or non-sporting related issues allowed Barcelona to reduce their offer for Luis Suárez (-12 million € between the right price and money invested). The same holds true for Chelsea with Diego Costa’s signing (-10 million €). In absolute terms, Mario Balotelli was the most under-paid player (-16 million €).

The full picture for all players transferred for a fee of at least 10 million € (including add-ons) is presented in the 79th edition of the Big-5 Weekly Post. We also kindly remind you that our unique and simple online calculator to estimate the current transfer value of big-5 league players is freely accessible here.

The CIES Football Observatory stays at your disposal for any query or more information. Enjoy the season!

CIES Football Observatory’s statistical model

The CIES Football Observatory academic team has developed an exclusive statistical model to assess the transfer value of players and predict transfer fees. This powerful econometrical model is based on the in-depth analysis of a sample of nearly 1,500 players transferred for a fee from big-5 league teams since the summer transfer window preceding the 2009/10 season. The statistical model developed includes a multitude of variables relating to the following areas: age, length of remaining contract, position, player performance at club level for the most recent and previous seasons, results of the clubs for which players are employed, as well as players’ international experience and results of national team represented.

The new transfer value calculator uses an algorithm created on the basis of nearly 1,500 fee paying transfers occurred during the previous five years at big-5 league clubs. The exclusive algorithm will continue to be updated after every transfer window to take into account the latest market trends.

More information on the statistical model developed by the CIES Football Observatory academic team and detailed analysis of current big-5 league players is available in the latest edition of the CIES Football Observatory Annual Review. A free excerpt of this publication can be downloaded here.

The scientific analysis of player transfer values perfectly complements the two other main CIES Football Observatory research areas: squad composition and pitch performance. All of these areas of study are of high importance to clubs as they are able to assist in raising performance levels from both a sporting and economic perspective.

Moreover, the transfer value calculator will help to increase the level of transparency in the beautiful game as all stakeholders – from club officials to the general public – will be able to compare actual fees paid to those estimated as the fair transfer value by the calculator.

The CIES Football Observatory academic team is at your disposal for more detailed analysis. Its services notably include the elaboration of scenarios for future transfer values. For more information about our products and services, please contact us at football.observatory@cies.ch

The ranking takes into account the number of World Cup participants trained per club, as well as the number of league matches played by footballers per team up to the age of 23. This age limit has been set according to FIFA regulations on training indemnities. Training clubs have been defined according to the UEFA definition of at least three years at the club between the ages of 15 and 21.

At the top of the table is Feyenoord Rotterdam. The Dutch team trained 9 players participating in the World Cup. Two other clubs trained as many footballers as Feyenoord: Barcelona and Deportivo Saprissa. However, World Cup participants played 882 matches at Feyenoord until the age of 23, compared to 783 at Barcelona (not including B-team matches) and 445 at Deportivo Saprissa.

At national association level, France tops the table ahead of England and Germany. This is mainly due to the high number of footballers trained in France playing for other national A-teams, notably Africans. This finding also reflects the high employment rate of U23 players in French clubs. In total, 821 clubs in 59 national associations have contributed to the development of World Cup players. The full list of clubs is available here.

We also remind you that the brand new edition of our Annual Review on the five major European leagues is available for sale from the CIES online shop. A free excerpt is available here.

The Observatory academic team have selected the following indicators for assessing the potential of the 2014 World Cup participants:

• League matches during career
• League matches for the two years preceding the event
• League goals during career
• League goals for the two years preceding the event
• National A-team matches for the two years preceding the event
• World Cup matches during career

The results for each national team are illustrated through a diagram with green or red boxes. A green box means that the value measured for the team is superior to the minimal figure observed for the last four World Cup finalists for the 11 players with the highest values. If this is not the case, the box is red. The greater the proportion of green boxes, the higher the probability of reaching the final stages of the competition. In the case of a tie, we took into account the number of World Cup matches of national teams during the last four editions.

This approach has also allowed us to predict a hypothetical scenario for the outcome of the competition, suggesting that Spain will beat Brazil in the final, with Argentina in 3rd place and France in 4th position. The full analysis is presented in the World Cup Scenario report.