Cies Footobs Eng

11. Introduction

Statistics is a science which aims to quantify real-ity and facilitate its understanding. It allows us to both explain past events and forecast future ones. For this purpose, since 2005, the academic team of the Football Observatory within the Interna-tional Centre for Sports Studies (CIES)1 has de-veloped a database on the career paths and pitch performance of professional football players.

The rigorous and systematic collection of data has enabled us to develop fully comparable sta-tistical indicators and monitor them season by season. From a squad management perspective, these indicators focus on, for example, the age of players, their experience and contract duration, or the stability of teams (chapter 2).

A thorough study of the data set produced by our partners Opta has also allowed us to identify key performance indicators in six complementary ar-eas of the game: shooting, chance creation, take on, distribution, recovery and rigour (chapter 3).

Paths to sustainable success. The experience of the CIES Football Observatory.

Drs Raffaele Poli, Loc Ravenel and Roger BessonCIES Football Observatory, International Centre for Sports Studies (CIES), Neuchtel (Switzerland)

Finally, from the analysis of transfer fees paid by clubs, we have developed an econometric model through which we are able to predict with a high degree of accuracy the transfer value of players. In other words, our model is able to forecast the amount that a team should be willing to invest in signing a new player. The correlation between estimated values and fees actually paid is greater than 80% (chapter 4).

By combining these different approaches, our research group contributes to a better under-standing of the football players transfer and la-bour market. From a macroscopic perspective, our data allows football officials to deepen their understanding of the environment in which they operate. Moreover, it provides a wide array of de-cision-makers with the ability to anticipate new trends. More specifically, our studies facilitate the understanding of the key criteria of success - both from a sporting (squad composition, in-dividual and collective performance, etc.) and an economic perspective (identification of transfer opportunities, best value for money, etc.).

CIES Football Observatorys investigation areas from the perspective of sustainable success

SustainableSuccess

SquadManagement

PitchPerformance

TransferValue

1 For more information, please refer to www.football-observatory.com and www.cies.ch

Last update: 09/12/2014

Paths to sustainable success

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For each of these three areas of investigation, this synthesis details the approach followed and pro-vides illustrations by means of specific examples.

2. Squad management

Our studies show that the best performing clubs have well balanced squads. Indeed, a good mix of different age groups and levels of experience allows young talents to progress alongside more experienced players and eventually become the new pillars of the team. Balanced age and expe-rience structures are thus also a prerequisite for maintaining a sufficient level of stability over the long term.

Also from a stability perspective, our studies in-dicate that the transfer policy of a club must con-centrate on specific profiles of players. In other words, in the area of transfers, quality should al-

ways be preferred over quantity. The recruitment strategy should focus on players whose demo-graphic and playing characteristics will maxim-ise their possibility to make a positive contribu-tion to the team over the long term.

From this point of view, it is also necessary to demonstrate confidence in new signings, as well as youth academy players, by offering them long-term contracts (at least three years, if possible with automatic extension options). This is bene-ficial not only from a sporting point of view, but also financially in the event of a transfer.

SquadManagement

ContractualPolicy

StabilityTransfers

Experience

AgeStructure

Key areas of squad management according to the CIES Football Observatory

2 See notably the CIES Annual Review, nine editions (2006-2014); and the CIES Demographic Study, six editions (2009-2014).


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The importance of squad planning and stabili-ty in achieving sustainable success is clearly il-lustrated by our analysis on the average stay of players in the first team squad of their employer club. Between 2009/10 and 2013/14, players in Champions League finalist teams had an average stay of 3.9 years during the season in which their club reached the last stage of the competition. This figure was three years for other Champions League participants and only 2.3 years for do-mestic league competitors of participating teams.

The data on the age of recruitment3 of squad members in big-5 league clubs also demonstrates the importance of focusing on the signing of relatively young players for sustainable success. Clubs currently ranked in the top six positions of their respective league recruited on average play-ers aged 24.1 years. This figure is 24.5 for mid-dle-ranked teams and 24.9 for bottom-ranked ones.

Average stay in the first team squad, according to club status (2009-2014)

Domestic leaguecompetitors

Champions Leaguecompetitors

Champions Leaguenalists 3.85

3.02

2.33

2 For players recruited from a youth academy, age at first match in the domestic league.

Average age at recruitment of squad members according to club ranking (big-5 leagues, 2014/15)

24.07

24.48

24.86Bottom-ranked

Middle-ranked

Top-ranked


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The analysis of the ratio between players average stay and age at recruitment (ASAR ratio) at big-5 league level shows that 12 of the 16 best values are for teams qualified for European Cup com-petitions. Among clubs in the top 16 of the rank-ing, only Real Sociedad, Montpellier, Manchester United and Cagliari are not participating in the Champions or Europa League. Our analysis sug-gests that they are well placed to improve results in the short term.

Best ASAR values for big-5 league clubs, 2014/15

AverageStay

Age atRecruitment

ASARRatio

1. Real Sociedad de Ftbol 5.26 21.93 0.240

2. Real Madrid CF 4.32 22.63 0.191 CL3. Athletic Club Bilbao 4.25 22.92 0.185 CL4. FC Barcelona 4.04 22.53 0.179 CL5. Borussia Dortmund 3.89 22.52 0.173 CL6. FC Bayern Mnchen 3.88 23.64 0.164 CL7. VfL Borussia Mnchengladbach 3.82 23.65 0.161 EL8. Montpellier Hrault SC 3.69 23.47 0.157

9. Everton FC 3.67 24.28 0.151 EL10. Arsenal FC 3.44 23.23 0.148 CL11. Manchester United FC 3.36 22.78 0.147

12. Cagliari Calcio 3.26 22.54 0.145

13. Bayer 04 Leverkusen 3.21 22.73 0.141 CL14. Chelsea FC 3.39 24.35 0.139 CL15. Liverpool FC 3.20 23.13 0.138 CL16. Juventus FC 3.58 25.88 0.138 CL

CL: Club qualified for the Champions League - EL: Club qualified for the Europa League


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3. Pitch performance

Team performance depends largely on the tech-nical and tactical complementarity between teammates. Historically, all of the great teams have been able to integrate individual talent in to the collective effort of the team. As stated by all coaches worthy of the name, individual talent should serve the collective, not the inverse.

This key principle was used by the CIES Football Observatory academic team as the basic premise in developing an innovative approach to meas-ure pitch performance. We started by identifying through cluster analysis six complementary areas of play that any ambitious club should take into consideration when aiming to obtain top-lev-el results. These areas relate to attack (shooting, chance creation, take on), passing (distribution) and defence (recovery, rigour).

Six key pitch performance areas according to the CIES Football Observatory

Pitch Performance

Recovery

Shooting

ChanceCreation

Take on

Distribution

Rigour

Each key area of the game requires footballers with specific skills. Shooting refers to the ability of players to take advantage of goal opportunities through accurate shooting. Chance creation is the ability to put teammates in a good position to score. Take on refers to the ability to create dan-gerous situations by successfully challenging op-ponents. Distribution is the ability to keep a hold on the game through efficient passing. Finally, recovery and rigour refer to the ability to mini-mise goal opportunities for opponents through proficient interception work, and respectively robust duelling.

To maximise their relevance and correlation with results achieved by clubs, these key performance indicators combine systematically the volume of actions undertaken and their outcome (i.e. num-ber of tackles and % which were successful, the number of shots and % of shots on target, etc.).


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The importance and range of skills required by players varies considerably according to their position. The table below sums up the results of our statistical analysis by highlighting the best performing big-5 league players per position. The approach developed permits us to identify not only the top performing players in absolute terms, but also the footballers who have per-formed the best with respect to teammates. This allows us to unveil the hidden potential of play-ers who are not yet part of the most competitive clubs.

KPIs per position according to the CIES Football Observatory

Position KPIs Best player (absolute)4 Best player (relative)Centre back Rigour

Recovery Distribution

Angelo Ogbonna (Juventus)

Abdoulaye Ba (Rayo Vallecano)

Full back Rigour Recovery Distribution Take on

Dani Alves (Barcelona)

Sergio Escudero (Getafe)

Defensive/Central midfielder

RigourRecovery DistributionChance creation

Francesc Fbregas (Chelsea)

NGolo Kant (Caen)

Attacking midfielder DistributionPercussionChance creationShooting

Kevin de Bruyne (Wolfsburg)

Daniel Wass (Evian)

Forward Take onChance creationShooting

Cristiano Ronaldo (Real Madrid)

Andreas Weimann (Aston Villa)

4 Situation on 18th November 2014. Only footballers who played at least 66% of minutes since the start of the season.


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Depending on the style of game played or in-tended by a team, it is also important to target footballers with different characteristics for the same generic position. That is why we have iden-tified two to four different profiles for each out-field position considered. The KPIs for the differ-ent areas of the game are weighted specifically for each player profile in order to avoid as much as possible multicollinearity issues.

Pitch positions and vocation according to the CIES Football Observatory

Position Vocation Abreviation Best (absolute)Defense Centre back (right/left) Coverage CBC A. Ogbonna

Marking CBM J. Tomkins

Full back (right/left) Defensive FBD J. Manquillo

Attacking FBA L. Baines

Midfield Central midfielder Defensive CMD G. Fernndez

Playmaker CMP X. Alonso

Box-to-box CMB F. Fbregas

Attacking CMA K. de Bruyne

Wide midfielder (right/left) Defensive WMD P. Pogba

Attacking WMA E. Hazard

Attack Winger (right/left) Attacking W J. Cuadrado

Striker Main MS C. Ronaldo

Second SS L. Messi

FBD

WMAWMA

W

CMPWMD WMDCMB

CMA

SSMS

W

FBA

CMD

FBD

FBA

CBC CBCCBM CBM

For footballers who play in different positions, we considered the one most often played in. If the position for a given game is too distinct from the usual one, we exclude the match from the analysis. This allows us to avoid, for the most part, possible bias. However, this situation is more an exception than the rule.

In total, we defined 20 pitch positions: 8 defend-ers, 8 midfielders and 4 forwards. Goalkeepers are not included in our analysis.


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Vela

Hazard

KurzawaAlba

Dante BaManquillo

AlvesTomkinsOgbonna

de Bruyne CazorlaPogbaNainggolan

X. Alonso GabiFbregas

RonaldoCuadradoMessi

The first diagram below presents the best per-forming big-5 league players since the start of the 2014/15 season for each of the 20 positions identified. However, the profile of the most suit-able footballers greatly varies according to the type of formation and the style of play intended. For example, as detailed in the second and third diagram below, distribution skills will be very important for a 4-3-3 based on possession. Con-versely, a 4-3-3 based on counter-attack requires highly skilled players in the areas of take on (no-tably for wide midfielders and wingers). Finally, only three players would be selected for both for-mations (Messi, Ronaldo and X. Alonso).

Best performing big-5 league players per profile according to the CIES Football Observatory, 2014/15

Messi

Kurzawa Ogbonna Ba Manquillo

PogbaCazorlaX. Alonso

de BruyneRonaldoMessi

Alba AlvesMertesackerChiellini

VerrattiFbregas X. Alonso

BenzemaRonaldo

Best performing big-5 league players per profile according to a 4-3-3 based on possession, 2014/15

Best performing big-5 league players per profile according to a 4-3-3 based on counter-attack, 2014/15


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4. Transfer value

The business model of many clubs depends heav-ily on transfers. Players have become assets on the balance sheet. They are increasingly consid-ered as financial products on whom to speculate. The magnitude of transfer fees means that any error in this area can have serious consequences. This holds true for the vast majority of clubs, in-cluding the wealthiest ones.

Optimising recruitment strategies requires not only an analysis of the potential of a player, his suitability for the style of game played or intend-ed (see chapter 3) and his complementarity with teammates (see chapter 2); but also a thorough understanding of the economic value of players when assessing transfers in or out of the club managed.

To determine the transfer value of players, we have analysed in detail the characteristics of more than 1,500 footballers transferred for a fee from big-5 league clubs since 2009. This analysis allowed us to identify six categories of indicators that are of key importance when explaining mar-

Key categories of indicators to estimate the transfer value of players

TransferValue

Age

Position

Contract

Competitionlevel

Results

Performance

ket logics and predicting future transfer fees. These indicators relate both to players (age, position, con-tract, performance) and the teams in which they play (competition level and results of clubs or na-tional sides).

In the summer of 2014, the econometric model de-veloped allowed us to predict 81% of the price dif-ferences between players transferred for a fee from big-5 league clubs. The high correlation between fees estimated and those actually paid demonstrates that the market for football players is to a large ex-tent rational. However, a more detailed analysis can also identify market bias that can be exploited by transferring overvalued players or recruiting those who are undervalued.

Player Team


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During the 2014 summer transfer window, clubs paid on average 16% more than the amounts in-vested during the previous five seasons to recruit players with similar characteristics. Despite this inflationary trend, some teams have been able to transfer players for a lower fee than expect-ed. This was notably the case with the transfer of Diego Costa from Atltico Madrid to Chelsea thanks to the existence of a buy-out clause. This example shows that it is not only important to shrewdly negotiate transfers, but also to antici-pate future issues by establishing transfer clauses in the most judicious manner.

Correlation between estimated values and fees paid for big-5 league players (2014 summer transfer window)

The website of the CIES Football Observatory includes an online tool to estimate the transfer value of big-5 league players using basic variables accessible to the general public. Our academ-ic teams has also developed more sophisticated models to undertake specific analysis on current or future transfer values of professional foot-ballers at worldwide level, as well as to estimate transfer probabilities.

In other words, we are not only able to estimate the amount that a club would be ready to pay to sign a player, but also the probability that a fee paying transfer would occur according to the amount of the offer.

The transfer value calculator of the CIES Football Observatory

R = 81%

0.1

1

10

100

0.1 1 10 100

Repo

rted

fee (

mill

ion

)

Estimated value (million )


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5. Conclusion

In their quest for higher performance, profes-sional football clubs are constantly progressing. This holds particularly true from the perspective of technical staff available: medical staff, fitness coaches, rehabilitation specialists, nutritionists, psychologists, video or data analysts, etc.

From a management perspective, however, the experience of the CIES Football Observatory shows that much remains to be done to create the most favorable environment to support the ex-pression and development of player talent.

Our research allows forward-thinking leaders to take a step back from their daily duties and fully develop their strategic role. Our in-depth knowl-edge of the various issues that clubs are faced with as described in this synthesis, as well as the in-sights gathered through innovative outside the box research we have conducted for almost ten years, provide powerful evidence to help teams embark on a more sustainable path to success. This is valid from both a sporting and economic perspective, as well as regardless of clubs status or competition level.

While this article is confined to the fundamen-tal principles which have guided the work of our academic team since 2005, many other develop-ments are underway. Usefulness, relevance and innovation are our priorities. For further infor-mation or consultancies, please do not hesitate to contact the CIES Football Observatory academic team at [email protected].

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