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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.

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 exclusive algorithm created on the basis of nearly 1,500 fee paying transfers whihc have 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 2014 edition of the CIES Football Observatory Annual Review, published this month. A free excerpt of this flagship 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.

A comparison of the most recent fee paying transfers of big-5 league players is available in the 78th edition of the Big-5 Weekly Post. Estimated fees refer to the situation on 1st June 2014 as published in the CIES Football Observatory Annual Review. The very high correlation (r² = 87%) confirms the accuracy of our approach and its predictive power.

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.

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.

The CIES Football Observatory Annual Review is an essential tool for all forward-thinking teams to benchmark themselves against rivals and implement the most suitable strategies for sustainable success. The analysis provided is also of great interest for professionals involved in the transfer market operations, media and the general public. An excerpt of this 96-page landmark publication can be downloaded here. The paperback report is available for purchase from the CIES online shop.

As of June 2013, Lionel Messi is the big-5 league footballer with the highest market value. According to the CIES Football Observatory’s exclusive econometrical model, the estimated value of Barcelona’s player is almost twice as high as for Cristiano Ronaldo: € 216 versus € 114 million. This is mainly related to the younger age of the Argentinian prodigy. However, contrary to Ronaldo’s market value, Messi’s decreased during last year due to lower performance levels (- € 19 million).

The comparison between transfer fees paid by clubs to sign new players at the start or during the 2013/14 season and their current market value allows us to assess the best and worst recruitments from a financial perspective. The highest negative gap was recorded for Gareth Bale (€ -37 million). This finding reflects the fact that Real Madrid clearly paid over the odds to convince Tottenham to release the player. In 2013/14, the Castilian team broke the record for the most expensive line-ups fielded with an average transfer expenditure per player of € 32.3 million in their Champions League winning campaign.

Results achieved by Spanish title winners Atlético Madrid were outstanding with an average transfer fee of “only” about € 4.3 million per player on the pitch. From an economic perspective, it is also worth highlighting results obtained by some of the clubs that were among those that spent the least to sign players fielded such as Crystal Palace in England, Elche in Spain, Guingamp in France, Augsburg in Germany and Hellas Verona in Italy. This publication will allow you to understand what factors permitted these clubs to over-perform.

While not directly focused on national teams, the findings presented in this publication can also be interpreted in the light of the upcoming World Cup. For example, our analysis of the pitch performance of players suggests that it will be very difficult to score against Brazil. Indeed, Thiago Silva, Dante, Dani Alves, Maxwell, Marcelo and Maicon are among the best performing players in their respective position. Felipe Scolari could even afford not to select other very productive and efficient defenders such as Rafinha and Luis Filipe.

However, our analysis also shows that Brazilian players are less represented among the best performing midfielders and forwards. Spain appears thus to have a more complete squad with at least one player in the top 10 of the rankings for each position. Of course, the outstanding talent of the four best performing forwards, Cristiano Ronaldo (Portugal), Luis Suárez (Uruguay), Ciro Immobile (Italy) and Lionel Messi (Argentina), could prove to be a lethal weapon for opponents. Within one week, the CIES Football Observatory will also disclose its World Cup predictions using a brand new methodology.

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