Transfer values and probabilities: the CIES Football Observatory approach
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CIES Football Observatory Monthly Report
Issue 16 - June 2016
Transfer values and probabilities:
the CIES Football Observatory approach
Drs Raffaele Poli, Loïc Ravenel and Roger Besson
1. Introduction vested. This gap is explained by the inflation
in transfer costs. Insofar as nothing indicates
that the inflation has topped out, a supple-
Transfer fees paid by football clubs to recruit
ment of 10% was applied to each footballer
new players have strongly increased over the
whose transfer value appears in this report.
past few years. With the growth in revenues
This percentage corresponds to the underes-
of the top-flight European teams along with
timated amount observed on average so far.
those of all English Premier League clubs, a
new record for expenditure will most probably Our approach also takes into account the level
be set during the next transfer window. of the team interested in acquiring the servic-
es of a player. A wealthy club such as Man-
The CIES Football Observatory is able to pre-
chester City, for example, should pay more
dict the footballers of the five major European
than West Bromwich Albion for the same play-
leagues who are the most likely to be trans-
er. To simplify, the values presented refer to
ferred for a sum of money during next sum-
the corresponding fee for the team most like-
mer. We are also capable of estimating the
ly to recruit the player in question taking into
transfer value of big-5 league players taking
account his characteristics and performances.
into account the amounts previously paid for
footballers with similar characteristics. This Report first examines the criteria used
to evaluate both players’ transfer values and
Our estimations are based on statistical mod-
probabilities. We then present the big-5 league
els developed from a detailed analysis of deals
footballers most likely to be the object of a
concluded over the last six years. No subjective
paid transfer during next summer. The follow-
data is taken into account. Transfer rumours
ing chapter lists the players with the highest
have no place in our approach. Neither do our
transfer value. In the conclusion, we reiterate
estimates include clauses that fix the fee at
the principle applications possible for the al-
which certain players can be transferred.
gorithms elaborated by the CIES Football Ob-
Since the 2013 summer transfer window, the servatory research group.
correlation between values estimated by our
algorithm and the sums actually paid for the
recruitment of big-5 league players has been
close to 80%. The strength of this correla-
tion shows that, on one hand, the footballers’
transfer market is rational and, on the other,
that its rationality has been well understood
by the econometric model developed by the
CIES Football Observatory academic team.
Moreover, the model estimating the proba-
bilities of paying fee transfers has turned out
to be very accurate. Of the twenty footballers
that we identified as most likely to be trans-
ferred for a fee in June 2015, twelve actual-
ly left, five extended their contract and only
three stayed in their home club without re-
newing their contract.
The estimated transfer values were, on aver-
age, slightly lower than the sums actually in-
1Monthly Report 16 - Transfer values and probabilities
2. Valuation criteria Figure 1: key indicators in estimating transfer
values and probabilities
To determine transfer values and probabilities
on a scientific basis, our academic team first Age
analysed in detail the trajectories of players
rs
Book
ye
Position
having recently participated in the five ma- value
Pla
jor European leagues. Among these are over
2,000 footballers that have been the object of
paying fee transfers since July 2010. Contract Competition
level
Using statistical modelling techniques, we Values
have been able to identify the criteria that af-
fect the determination of transfer fees, as well Probabilities
as the factors influencing the probability of a International Results
status
player being transferred for a sum of money.
These variables refer to both players and their
teams.
ms
Experience Achivements
a
A first group of indicators concerns the char-
Te
Performance
acteristics of players such as age, position,
length of contract remaining and the residu-
al book value. The latter variable is calculated
from the transfer fee amount paid by the em-
ployer club, divided according to the percent-
age of years of contract since the signature.
A second group of indicators takes into ac-
count the players’ performances, notably in
terms of the amount of time played in the dif-
ferent club competitions (domestic leagues,
cups) or, eventually, in national teams. Recent
performances are given more weight than pre-
vious ones.
The last family of indicators refers to the lev-
el of the leagues where the footballers played
their matches, as well as to the results ob-
tained by the employer clubs. The level of the
national team represented is also taken into
account.
2Monthly Report 16 - Transfer values and probabilities
3. Probabilities of fee paying Figure 2: Players with an estimated value greater
than €25 million most likely to be transferred for
transfers money
This chapter presents the rankings of football- 1. Gonzalo Higuaín* 60.9
Napoli (ITA) - fw** - 28 - 2018
ers identified by our model as being the most
likely to be transferred for a fee during the 2. Alexandre Lacazette 41.5
Lyon (FRA) - fw - 25 - 2019
2016 summer transfer window. Players on loan
3. Michy Batshuayi 25.2
have not been included in the analysis. Marseille (FRA) - fw - 22 - 2020
Numerous footballers from relegated clubs 4. Antoine Griezmann 120.2
Atlético Madrid (ESP) - fw - 25 - 2020
figure among those for whom a paid depar-
5. Romelu Lukaku 58.1
ture is the most probable. Indeed, relegation Everton (ENG) - fw - 23 - 2019
obliges teams to compensate decreasing rev-
6. Carlos Bacca 35.4
enues by selling players. This also gives an Milan (ITA) - fw - 29 - 2019
incentive to the players themselves to leave. 7. Bernardo Silva 31.5
Consequently, relegated clubs generally offer Monaco (FRA) - am - 21 - 2020
interesting recruitment possibilities. 8. André Gomes 41.2
Valencia (ESP) - dm - 22 - 2020
There are many top-flight forwards among the 9. Leroy Sané 34.0
players whose transfer value is over €25 mil- Schalke (GER) - am - 20 - 2019
lion and who are most likely to be transferred. 10. Mauro Icardi 49.9
Gonzalo Higuaín heads the rankings. The Inter (ITA) - fw - 23 - 2019
28-year-old Argentinean has only two years of 11. Shkodran Mustafi 29.2
his contract left to run. According to our anal- Valencia (ESP) - cb - 24 - 2019
ysis, it is very probable that he will be signed 12. Ross Barkley 39.7
Everton (ENG) - am - 22 - 2018
by a wealthier club than Naples.
13. Koke Resurrección 50.3
Three other players whose transfer value is Atlético Madrid (ESP) - am - 24 - 2019
over €50 million are likely to leave: Antoine 14. Hakan Çalhanoğlu 27.2
Leverkusen (GER) - am - 22 - 2019
Griezmann and Koke Resurrección from Atléti-
15. Paco Alcácer 31.0
co Madrid, as well as Everton’s Romelu Luka-
Valencia (ESP) - fw - 22 - 2020
ku. Mauro Icardi (Inter) and Alexandre Lacaz-
16. Henrik Mkhitaryan 33.6
atte (Lyon) are also strong contenders for the Dortmund (GER) - am - 27 - 2017
most expensive summer transfers. 17. Mohammed Salah 38.7
Roma (ITA) - fw - 24 - 2019
18. Ilkay Gündoğan 26.4
Dortmund (GER) - dm - 25 - 2017
19. Sadio Mané 35.5
Southampton (ENG) - fw - 24 - 2018
20. Jamie Vardy 34.7
Leicester (ENG) - fw - 29 - 2019
*
Name - Value (million €)
Club (League) - Position - Age - Contract end
**
[gk] : goalkeeper, [cb] : centre back, [fb] : full back,
[dm] : defensive midfielder, [am] : attacking midfielder,
[fw] : forward
3Monthly Report 16 - Transfer values and probabilities
Newcastle’s surprise relegation will probably Numerous talents are among the 20 players
result in the departure of quality players. Ac- with a transfer value between €7.5 and €15
cording to our analysis, four footballers from million who are the most likely to leave their
the club whose value is between €15 and €25 current club. The youngest of them is Stutt-
million are likely to be transferred: Georgin- gart’s Timo Werner. Only Nicola Sansone (Sas-
io Wijnaldum, Aleksander Mitrović, Chancel suolo) is more likely to be transferred for a fee
Mbemba and Jonjo Shelvey. Mario Götze (Bay- than the German striker. Three 21-year-old
ern Munich) is also likely to find a new club as players are also in the top 20: Leon Goretz-
his contract has only one year left to run. ka (Schalke 04), Karim Rekik (Olympique Mar-
seille) and Bruno Fernandes (Udinese).
Figure 3: players with an estimated value
between €15 and €25 million most likely to be Figure 4: players with an estimated value
transferred for money between €7.5 and €15 million most likely to be
transferred for money
1. Georginio Wijnaldum 24.8
Newcastle (ENG) - am - 25 - 2020 1. Nicola Sansone 13.7
2. Mario Götze 24.4 Sassuolo (ITA) - fw - 24 - 2017
Bayern (GER) - am - 24 - 2017 2. Timo Werner 8.5
3. Aleksandar Mitrović 24.2 Stuttgart (GER) - fw - 20 - 2018
Newcastle (ENG) - fw - 21 - 2020 3. Nathan Redmond 9.9
4. Filip Kostić 15.4 Norwich (ENG) - am - 22 - 2017
Stuttgart (GER) - am - 23 - 2019 4. Robert Brady 7.7
5. Maximilian Meyer 22.4 Norwich (ENG) - am - 24 - 2018
Schalke (GER) - am - 20 - 2018 5. Loïc Rémy 8.2
6. André Schürrle 20.8 Chelsea (ENG) - fw - 29 - 2018
Wolfsburg (GER) - am - 25 - 2019 6. Jean Seri 9.8
7. Chancel Mbemba 15.8 Nice (FRA) - dm - 24 - 2019
Newcastle (ENG) - cb - 21 - 2020 7. Fernando Martins 13.8
8. Jonjo Shelvey 16.6 Sampdoria (ITA) - dm - 24 - 2020
Newcastle (ENG) - dm - 24 - 2021 8. Jordan Ayew 10.8
9. Fabinho Tavares 23.5 Aston Villa (ENG) - fw - 24 - 2020
Monaco (FRA) - dm - 22 - 2019 9. Moussa Sissoko 14.8
10. Domenico Berardi 22.5 Newcastle (ENG) - am - 26 - 2019
Sassuolo (ITA) - fw - 21 - 2019 10. Yunus Malli 9.0
11. Max Kruse 16.0 Mainz (GER) - am - 24 - 2018
Wolfsburg (GER) - fw - 28 - 2019 11. Kevin Gameiro 14.0
12. Kevin Volland 16.4 Sevilla (ESP) - fw - 29 - 2018
Hoffenheim (GER) - fw - 23 - 2019 12. Roberto Soriano 14.5
13. Javier Hernández 15.7 Sampdoria (ITA) - dm - 25 - 2020
Leverkusen (GER) - fw - 28 - 2018 13. Saido Berahino 12.1
14. Giacomo Bonaventura 18.4 West Bromwich (ENG) - fw - 22 - 2017
Milan (ITA) - am - 26 - 2019 14. Leon Goretzka 12.8
15. Franco Vázquez 16.9 Schalke (GER) - am - 21 - 2018
Palermo (ITA) - fw - 27 - 2019 15. Karim Rekik 10.1
16. Rodrigo Moreno 19.5 Marseille (FRA) - cb - 21 - 2019
Valencia (ESP) - fw - 25 - 2019 16. Jesé Rodríguez 11.2
17. José María Callejón 17.9 Real Madrid (ESP) - fw - 23 - 2017
Napoli (ITA) - fw - 29 - 2018 17. Bruno Fernandes 8.5
18. Manuel Nolito 20.4 Udinese (ITA) - dm - 21 - 2018
Celta Vigo (ESP) - fw - 29 - 2019 18. Carlos Vela 12.6
19. Antonio Candreva 20.3 Real Sociedad (ESP) - fw - 27 - 2018
Lazio (ITA) - fw - 29 - 2019 19. Rachid Ghezzal 8.4
20. Jorginho Frello 23.6 Lyon (FRA) - am - 24 - 2017
Napoli (ITA) - dm - 24 - 2020 20. Lucas Pérez 14.4
RC Deportivo (ESP) - fw - 27 - 2019
4Monthly Report 16 - Transfer values and probabilities
Players with only one year of contract remain- Eighteen of the 20 players most likely to be
ing are clearly over-represented among foot- transferred for a fee among those whose
ballers valued between €2.5 and €7.5 million transfer value is under €2.5 million have only
most likely to be transferred for a fee. Indeed, one year of contract to run. With the exception
if the player does not want to extend his con- of Lukas Hinterseer (Ingolstadt), they are all
tract, his club is pushed to transfer him to from relegated teams. Heading the list is Ve-
avoid a free departure. This case in point is no- rona’s Artur Ioniță from Moldova. Four players
tably that of Wissam Ben Yedder. The Toulouse from Hanover are also in the top 20 rankings:
striker is ahead of Aïssa Mandi (Stade Reims) Miiko Albornoz, Salif Sané, Kenan Karaman and
and teammate Martin Braithwaite. Lasse Sobiech.
Figure 5: players with an estimated value Figure 6: players with an estimated value lower
between €2.5 and €7.5 million most likely to be than €2.5 million most likely to be transferred
transferred for money for money
1. Wissam Ben Yedder 5.7 1. Artur Ionită 2.3
Toulouse (FRA) - fw - 25 - 2017 Verona (ITA) - dm - 25 - 2017
2. Aïssa Mandi 2.9 2. Jacques Zoua 1.2
Reims (FRA) - cb - 24 - 2017 GFC Ajaccio (FRA) - fw - 24 - 2017
3. Martin Braithwaite 4.5 3. Jozabed Sánchez 1.8
Toulouse (FRA) - fw - 25 - 2017 Rayo Vallecano (ESP) - dm - 25 - 2017
4. Nicolas de Préville 4.5 4. Miiko Albornoz 1.1
Reims (FRA) - fw - 25 - 2018 Hannover (GER) - fb - 25 - 2017
5. Ron-Robert Zieler 3.1 5. Federico Dionisi 1.9
Hannover (GER) - gk - 27 - 2017 Frosinone (ITA) - fw - 29 - 2017
6. Andy Delort 5.9 6. Salif Sané 2.0
Caen (FRA) - fw - 24 - 2019 Hannover (GER) - dm - 25 - 2018
7. Pablo Sarabia 6.6 7. Kenan Karaman 1.2
Getafe (ESP) - am - 24 - 2019 Hannover (GER) - fw - 22 - 2017
8. Raphaël Guerreiro 7.2 8. Matthieu Saunier 0.8
Lorient (FRA) - fb - 22 - 2017 Troyes (FRA) - cb - 26 - 2017
9. Haris Seferović 4.8 9. Mohamed Larbi 1.2
Frankfurt (GER) - fw - 24 - 2017 GFC Ajaccio (FRA) - am - 28 - 2017
10. Pascal Gross 3.4 10. Hamari Traoré 1.6
Ingolstadt (GER) - dm - 25 - 2017 Reims (FRA) - fb - 24 - 2018
11. Youssef El Arabi 3.4 11. Artur Sobiech 0.8
Granada (ESP) - fw - 29 - 2017 Hannover (GER) - fw - 26 - 2017
12. Deyverson Acosta 3.6 12. Eros Pisano 1.2
Levante (ESP) - fw - 25 - 2019 Verona (ITA) - fb - 29 - 2017
13. Jean-Daniel Akpa Akpro 3.2 13. Adri Embarba 1.9
Toulouse (FRA) - dm - 23 - 2017 Rayo Vallecano (ESP) - am - 24 - 2017
14. Nampalys Mendy 7.4 14. Kevin Lasagna 2.4
Nice (FRA) - dm - 24 - 2017 Carpi (ITA) - fw - 23 - 2017
15. Lewis Holtby 5.5 15. Lossémy Karaboué 0.6
Hamburg (GER) - dm - 25 - 2018 Troyes (FRA) - am - 28 - 2017
16. Mathew Leckie 3.2 16. Babacar Gueye 0.6
Ingolstadt (GER) - fw - 25 - 2017 Troyes (FRA) - fw - 21 - 2017
17. Bas Dost 6.1 17. Robert Gucher 1.1
Wolfsburg (GER) - fw - 27 - 2017 Frosinone (ITA) - dm - 25 - 2017
18. Vurnon Anita 2.8 18. Carlos Vigaray 1.8
Newcastle (ENG) - dm - 27 - 2017 Getafe (ESP) - cb - 21 - 2017
19. Jonas Martin 2.7 19. Lukas Hinterseer 2.2
Montpellier (FRA) - dm - 26 - 2017 Ingolstadt (GER) - fw - 25 - 2017
20. Daniel Caligiuri 4.4 20. Przemyslaw Tytoń 1.5
Wolfsburg (GER) - am - 28 - 2017 Stuttgart (GER) - gk - 29 - 2017
5Monthly Report 16 - Transfer values and probabilities
4. Transfer values role, which could lead to clubs pushing up the
bidding price to ensure their services.
This chapter presents the rankings for big-5
league players with the highest transfer values Figure 7: big-5 league players with the highest
as of 1st June 2016. Matches played or con- transfer values, 1st to 20th position
tract extensions occurred after this date have
1. Lionel Messi* 211.1
not been included in the analysis. However, Barcelona (ESP) - fw** - 29 - 2018
the estimations take into account the infla- 2. Neymar Júnior 201.5
tionist trend of transfer fees. Barcelona (ESP) - fw - 24 - 2018
3. Cristiano Ronaldo 137.8
The majority of footballers with the highest Real Madrid (ESP) - fw - 31 - 2018
transfer value play in the top-flight teams, are 4. Antoine Griezmann 120.2
active internationals, have a long-term con- Atlético Madrid (ESP) - fw - 25 - 2020
tract and are less than 27 years of age. As of 5. Harry Kane 112.5
July 2015, Lionel Messi tops the rankings. How- Tottenham (ENG) - fw - 22 - 2020
ever, his top spot is under increasing threat 6. Anthony Martial 111.8
from his teammate Neymar. Given their age Manchester Utd (ENG) - fw - 20 - 2019
difference, a change in the first position seems 7. Luis Suárez 105.8
Barcelona (ESP) - fw - 29 - 2019
unavoidable, especially if the Brazilian renews
his contract with Barcelona. 8. Paulo Dybala 104.5
Juventus (ITA) - fw - 22 - 2020
Cristiano Ronaldo, ranked third, is the only 9. Sergio Agüero 96.8
Manchester City (ENG) - fw - 28 - 2019
player having celebrated his 31st birthday
among the 100 most expensive players. This 10. Paul Pogba 90.4
Juventus (ITA) - dm - 23 - 2019
result is explained by the fact that clubs are
11. Gareth Bale 80.8
prepared to pay substantial transfer fees Real Madrid (ESP) - fw - 26 - 2019
above all when footballers have many years 12. Eden Hazard 78.3
left in the career to play. Chelsea (ENG) - am - 25 - 2020
13. Alexis Sánchez 75.8
In total, eight players have a transfer value of Arsenal (ENG) - fw - 27 - 2018
over €100 million. The youngest of them, An- 14. Dele Alli 75.2
tony Martial, is only 20 years of age. Another Tottenham (ENG) - am - 20 - 2021
Frenchman, Antoine Griezmann, is the most 15. Thomas Müller 73.5
likely to be transferred. A third Frenchman, Bayern (GER) - fw - 26 - 2021
Paul Pogba, has the highest value for central 16. Raheem Sterling 72.8
midfielders. With four players, only the Argen- Manchester City (ENG) - fw - 21 - 2020
tineans outnumber the French in the top 20 17. Robert Lewandowski 67.8
list: Lionel Messi, Paulo Dybala, Sergio Agüero Bayern (GER) - fw - 27 - 2019
and Gonzalo Higuaín. 18. Álvaro Morata 64.2
Juventus (ITA) - fw - 23 - 2020
The vast majority of footballers on the list play 19. Toni Kroos 62.2
for competitive teams. Indeed, good results Real Madrid (ESP) - dm - 26 - 2020
have a positive effect on the value of squad 20. Gonzalo Higuaín 60.9
Napoli (ITA) - fw - 28 - 2018
members. Conversely, poor results do not al-
low clubs to show players under contract in *
Name - Value (million €)
Evolution since January 2016
the best light. Good individual performanc-
Club (League) - Position - Age - Contract end
es can only partially compensate collective **
[gk] : goalkeeper, [cb] : centre back, [fb] : full back,
weaknesses. [dm] : defensive midfielder, [am] : attacking midfielder,
[fw] : forward
Most of the footballers with the highest trans-
fer values play in attacking positions. This
player profile is indeed traditionally the one
for which clubs are prepared to pay the high-
est fees. This result would lead one to believe
that offensive talents are rarer and thus more
sought after. Another possible explanation is
that footballers playing in attack are simply
more visible and admired by spectators than
their colleagues playing in a more defensive
6Monthly Report 16 - Transfer values and probabilities
Three defenders are ranked between the 21st Victory in the English Premier League has al-
and 40th place for big-5 league footballers lowed Leicester City to showcase their play-
with the highest transfer values: Hector Bel- ers. The most expensive among them is the
lerín (Arsenal), David Alaba (Bayern Munich) French neo-international N’Golo Kanté, closely
and Raphaël Varane (Real Madrid). Though followed by the Algerian international Riyad
they are still young, they already have con- Mahrez. According to our analysis, the transfer
siderable international experience. According value of goalkeepers David de Gea (Manches-
to our analysis, Thibault Courtois (Chelsea) is ter United) and Jan Oblak (Atlético Madrid) is
the most expensive goalkeeper: €48.4 million also above 40 million €.
(35th).
Figure 9: big-5 league players with the highest
Figure 8: big-5 league players with the highest transfer values, 41st to 60th position
transfer values, 21st to 40th position
41. David de Gea 46.4
21. Isco Alarcón 60.4 Manchester Utd (ENG) - gk - 25 - 2019
Real Madrid (ESP) - am - 24 - 2018 42. Francesc Fàbregas 45.7
22. Pierre-Emerick Aubameyang 59.5 Chelsea (ENG) - dm - 29 - 2019
Dortmund (GER) - fw - 27 - 2020 43. Nicolás Otamendi 44.9
23. James Rodríguez 58.7 Manchester City (ENG) - cb - 28 - 2020
Real Madrid (ESP) - am - 24 - 2020 44. N'Golo Kanté 44.2
24. Romelu Lukaku 58.1 Leicester (ENG) - dm - 25 - 2019
Everton (ENG) - fw - 23 - 2019 45. Douglas Costa 44.0
25. Héctor Bellerín 55.6 Bayern (GER) - am - 25 - 2020
Arsenal (ENG) - fb - 21 - 2020 46. Memphis Depay 43.5
26. Kevin de Bruyne 55.2 Manchester Utd (ENG) - fw - 22 - 2019
Manchester City (ENG) - am - 25 - 2021 47. Riyad Mahrez 43.1
27. Philippe Coutinho 52.3 Leicester (ENG) - am - 25 - 2019
Liverpool (ENG) - am - 24 - 2020 48. Pedro Rodríguez 42.9
28. Yannick Ferreira Carrasco 50.9 Chelsea (ENG) - am - 28 - 2019
Atlético Madrid (ESP) - am - 22 - 2020 49. Lucas Moura 42.5
29. Willian Borges 50.8 Paris SG (FRA) - fw - 23 - 2019
Chelsea (ENG) - am - 27 - 2018 50. Jérôme Boateng 42.4
30. Koke Resurrección 50.3 Bayern (GER) - cb - 27 - 2021
Atlético Madrid (ESP) - am - 24 - 2019 51. Saúl Ñíguez 42.1
31. Mauro Icardi 49.9 Atlético Madrid (ESP) - dm - 21 - 2021
Inter (ITA) - fw - 23 - 2019 52. Alexandre Lacazette 41.5
32. Diego Costa 49.6 Lyon (FRA) - fw - 25 - 2019
Chelsea (ENG) - fw - 27 - 2019 53. André Gomes 41.2
33. Mesut Özil 48.8 Valencia (ESP) - dm - 22 - 2020
Arsenal (ENG) - am - 27 - 2018 54. Olivier Giroud 40.9
. David Alaba 48.8 Arsenal (ENG) - fw - 29 - 2018
Bayern (GER) - cb - 24 - 2021 55. Jan Oblak 40.8
35. Thibaut Courtois 48.4 Atlético Madrid (ESP) - gk - 23 - 2021
Chelsea (ENG) - gk - 24 - 2019 56. Virgil van Dijk 40.1
36. Eric Dier 48.2 Southampton (ENG) - cb - 24 - 2022
Tottenham (ENG) - dm - 22 - 2020 57. Daley Blind 39.8
37. Karim Benzema 47.7 Manchester Utd (ENG) - cb - 26 - 2018
Real Madrid (ESP) - fw - 28 - 2019 58. Ross Barkley 39.7
38. Sergio Busquets 47.5 Everton (ENG) - am - 22 - 2018
Barcelona (ESP) - dm - 27 - 2021 59. Emre Can 39.5
39. Raphaël Varane 47.0 Liverpool (ENG) - dm - 22 - 2018
Real Madrid (ESP) - cb - 23 - 2020 60. Ivan Rakitić 39.3
40. Christian Eriksen 46.6 Barcelona (ESP) - dm - 28 - 2019
Tottenham (ENG) - am - 24 - 2018
7Monthly Report 16 - Transfer values and probabilities
The transfer values of players ranked between Thanks to the outstanding performances with
61st and 80th place are situated between €34 Dortmund, Henrikh Mkhitaryan is the only play-
and €38 million. Alongside Cristiano Ronal- er with one year of contract remaining among
do, the Bayern Munich world champion Ma- the 100 most expensive big-5 league players.
nuel Neuer (72nd) is the only player in the top Two young German talents also have very high
100 having already celebrated his 30th birth- transfer values: Leroy Sané (€34 million, 81th)
day. The transfer value of Marco Verratti (61st) and Jonathan Tah (€29.4 million, 100th). Given
sharply decreased compared to January due their age and ability to progress, their trans-
to his injury. fer fee could increase even further in a year’s
time, unless a top club decides to act quickly
Figure 10: big-5 league players with the highest as Manchester United did in August 2015 with
transfer values, 61st to 80th position Anthony Martial.
61. Marco Verratti 38.8 Figure 11: big-5 league players with the highest
Paris SG (FRA) - dm - 23 - 2020
transfer values, 81st to 100th position
62. Mohammed Salah 38.7
Roma (ITA) - fw - 24 - 2019
81. Leroy Sané 34.0
63. Leonardo Bonucci 38.6 Schalke (GER) - am - 20 - 2019
Juventus (ITA) - cb - 29 - 2020
82. Marquinhos Aoás 33.6
64. John Stones 38.2 Paris SG (FRA) - cb - 22 - 2019
Everton (ENG) - cb - 22 - 2019
. Henrik Mkhitaryan 33.6
65. Roberto Firmino 38.1 Dortmund (GER) - am - 27 - 2017
Liverpool (ENG) - fw - 24 - 2020
84. Chris Smalling 33.0
66. Aaron Ramsey 37.8 Manchester Utd (ENG) - cb - 26 - 2019
Arsenal (ENG) - dm - 25 - 2019
85. Radja Nainggolan 32.8
67. Erik Lamela 37.7 Roma (ITA) - dm - 28 - 2020
Tottenham (ENG) - am - 24 - 2018
86. Julian Brandt 32.5
68. Nemanja Matić 37.2 Leverkusen (GER) - am - 20 - 2019
Chelsea (ENG) - dm - 27 - 2019
87. Wilfred Zaha 32.3
69. Oscar dos Santos 37.0 Crystal Palace (ENG) - am - 23 - 2020
Chelsea (ENG) - am - 24 - 2019
88. Bernardo Silva 31.5
70. Juan Mata 36.8 Monaco (FRA) - am - 21 - 2020
Manchester Utd (ENG) - am - 28 - 2018
89. Konstantinos Manolas 31.4
71. Gianelli Imbula 35.9 new Roma (ITA) - cb - 25 - 2019
Stoke (ENG) - dm - 23 - 2021
90. Gerard Piqué 31.3
72. Manuel Neuer 35.7 Barcelona (ESP) - cb - 29 - 2019
Bayern (GER) - gk - 30 - 2021
91. Paco Alcácer 31.0
73. Ángel Di María 35.6 Valencia (ESP) - fw - 22 - 2020
Paris SG (FRA) - am - 28 - 2019
. Miralem Pjanić 31.0
74. Sadio Mané 35.5 Roma (ITA) - dm - 26 - 2018
Southampton (ENG) - fw - 24 - 2018
93. Danilo da Silva 30.9
75. Carlos Bacca 35.4 Real Madrid (ESP) - fb - 24 - 2021
Milan (ITA) - fw - 29 - 2019
. Alessandro Florenzi 30.9
. Heung-Min Son 35.4 Roma (ITA) - fb - 25 - 2019
Tottenham (ENG) - fw - 23 - 2020
95. Jordon Ibe 30.3
77. Felipe Anderson 34.8 Liverpool (ENG) - am - 20 - 2020
Lazio (ITA) - fw - 23 - 2020
96. Marco Reus 30.2
78. Jamie Vardy 34.7 Dortmund (GER) - fw - 27 - 2019
Leicester (ENG) - fw - 29 - 2019
97. David Silva 30.0
79. Denis Suárez 34.5 Manchester City (ENG) - am - 30 - 2019
Villarreal (ESP) - am - 22 - 2019
98. Joe Hart 29.8
80. Dimitri Payet 34.3 Manchester City (ENG) - gk - 29 - 2019
West Ham (ENG) - am - 29 - 2021
99. Marcelo Vieira 29.7
Real Madrid (ESP) - fb - 28 - 2020
100.Jonathan Tah 29.4
Leverkusen (GER) - cb - 20 - 2020
8Monthly Report 16 - Transfer values and probabilities
An interesting observation is also the over-rep- ber through injury notably. In order to do this, a
resentation of English Premier League players continual evaluation of the transfer value of a
among those with the highest transfer values: player and the elaboration of different scenar-
7 in the top 20 rankings, 17 in the top 40, 29 ios to estimate his future value are essential.
in the top 60, 41 in the top 80 and 46 in the Thanks to our methodology and independ-
top 100. ence, we are in an ideal position to advise the
different actors in this area.
This result is a reflection of the financial clout
of English clubs that allows them to attract nu- Within the same perspective, the objective es-
merous talents from abroad each year. More- timation of the transfer value of players can
over, transfer costs between Premier League be of considerable interest in obtaining cred-
teams are generally higher than between clubs its. This value can be used as a guarantee to
from other championships. All things being convince banks or other types of creditors
equal, the value of a Premier League player is to grant loans. The algorithm estimating the
thus higher than that of a footballer playing in probability of paying fee transfers can also be
other competitions. used to this effect. Measuring the possibilities
of players’ transfers is notably useful in esti-
mating the risks undertaken. In this case also,
5. Conclusion our services are addressed equally to the dif-
ferent parties involved.
The pioneering approach developed by the The recourse to the statistical models esti-
CIES Football Observatory in the field of eval- mating both transfer values and probabilities
uating transfer probabilities and values of pro- is also very valuable in the framework of ne-
fessional footballers is suitable for multiple gotiation concerning contract extensions. It
applications that we shall briefly illustrate be- notably allows club officials the analysis of
low. different scenarios so as to define the level of
salary that can be offered to players without
Firstly, our approach can be of the utmost use
taking an excessive financial risk. It can also
in transfer negotiations. The estimated value
be useful to determine the optimum length of
can indeed serve as a reference for the dif-
a new contract from an economic perspective.
ferent parties involved: the buying club, the
selling club, as well as the player’s representa- Last but not least, aside from all commercial
tives. Moreover, as the initial valuation is often considerations, we believe that our approach
decisive in the determining of the final price, is of great value for the sustainable develop-
any valid information that one can have ac- ment of professional football. It brings an add-
cess to allow one to have an advantage in the ed degree of transparency and objectivity in
negotiations. transfer operations. Up until the present, no
organisation was indeed in a position to judge
The algorithm developed for transfer values is
on a solid and credible scientific basis whether
also useful in case of litigation. The previous
transactions were sound.
clubs of players very often have a percentage
on the future transfer (“sell-on fee”). If they The principle challenge that awaits us is to
deem themselves to have been wronged and popularise further our approach to become a
wish to contest the amount for which a player more and more widely recognised actor in the
was transferred, they must do this using ob- milieu of players’ transfer market. With this in
jective elements. Our approach has already mind, we aim to make more and more data
proven to be very useful in this domain. We available on our site. The latter is addressed
can also assist clubs entitled to a share of the not only to the game’s professionals, but also
transfer for a player exchanged, even though to the keen football passionate that we are
the exchange has not involved a monetary part of. Do not hesitate to contact us for more
transaction. information.
With the increase of transfer costs and the
growing importance of revenues generated
from transferring players in clubs’ business
model, it has become more and more useful
to take out an insurance that allow teams at
least some partial compensation for the de-
crease in the transfer value of a squad mem-
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