Football IQ Observatory

European Transfers 2018

Performance data: a key driver for recruitment

Introduction

Use of data-analytics in football has been steadily increasing over the course of years. We’ve reached the point where it is now obvious that more and more teams are actually trying to use big-data to benefit their scouting and recruitment processes.  

With the season in most European countries approaching to an end and the summer transfer window approaching, we decided to do our fair bit of research, in an effort to benchmark selection patterns against performance metrics of transferred players.

Approach

The sample consists of 1.725 transfers from 10 European competitions and includes transfers from the summer 2018 and winter 2018 transfer windows. Goalkeepers have not been included.

We used our 5 summary KPIs to benchmark against the main pool of players. More in-depth KPIs (passing overalls, attacking overalls, defending overalls) were used to analyze transfers and relevant performance profiles per position. 

Data for each transferred player depict his performance in the domestic competition he participated with the team he was signed from and go back to the previous (summer signings) and/or current (winter signings) season.

Summary KPIs

Overall DPI

The most “potent” of our performance indicators, incorporating overalls across all categories (passing, attacking, defending). It is directly associated with the level of versatility of each player and it is widely used to sort players who have exhibited high levels of performance in more than one areas.

Att Passing

Att Passing depicts how dangerous a player’s passing is for the opposition. It incorporates key metrics such as Assists and xA, Crossing, Passes In Box, Intelligent passes as well as all final passes that should/could have been converted by teammates. 

It is primarily used to identify attacking midfielders and wingers, whose passing ability and vision have an impact in chance creation.

While Att Passing is about providing that “final” pass and is predominantly linked with passes in the final third, Crt Passing is about getting the ball to teammates in the final third, efficiently creating from the back. 

Crt Passing

Crt Passing depicts the capacity of a player to effectively participate in build-up play and/or promote possession in a way that sets foundations for the creation of promising situations.

It incorporates different passing metrics (Short/Long/To Advanced positions) as well as Tunnel passes (passes between opposition lines).

Attacking

Attacking is a summary KPI incorporating all aspects of attacking metrics. Among other things, it includes Dribbling, Finishing, xG and Presence in Danger Zones. 

It is one of the key metrics we use when examining a player’s overall attacking capacity, providing important insights about a player’s attacking versatility.

Defending

Defending is a summary KPI incorporating all aspects of defending metrics. Among other things, it includes Defensive Workrate, Defensive Contests, Anticipation & Aerial Ability.

It is one of the key metrics used when examining a player’s defensive versatility, with defensive midfielders, full-backs and center-backs usually topping the rankings. 

Given the fact that each of the above mentioned KPIs indicates high levels of performance in specific areas, we identified the % of players who -before getting transferred- exhibited performance above 70 in at least one of the 5 summary KPIs. 

Top-5 European Competitions

Competition

Performers Signed

Total Transfers

% of Players with 70+ in at least 1/5 KPIs

Premier League

England

  • 105
  • 119 Transfers
88%
Ligue 1

France

  • 132
  • 157 Transfers
84.1%
Bundesliga

Germany

  • 115
  • 141 Transfers
81.5%
Primera Division

Spain

  • 161
  • 207 Transfers
77.7%
Serie A

Italy

  • 188
  • 252 Transfers
74.6%
Avg

Top-5 European Competitions

  • 140
  • 175 Transfers
81.2%
  • More than 4/5 (81.2%) of the players transferred in Europe's top-5 competitions during the latest two transfer windows were previously identified as top performers (70+ in at least 1/5 KPIs).
  • Despite recording the lowest number of total transfers EPL, probably the most heavily data-analytics influenced competition, is topping the charts indicative of their strategy to carefully select proven performers.
  • Ligue 1 and Bundesliga are in the same path, whereas Primera Division and Serie A below 80% as a consequence of their highly saturated markets.

Go for quantity, lose in quality: When number of transfers increases, quality drops.

Other European Competitions

Competition

Performers Signed

Total Transfers

% of Players with 70+ in at least 1/5 KPIs

Premier League

Russia

  • 117
  • 149 Transfers
78.5%
Super League

Greece

  • 130
  • 167 Transfers
77.8%
Eredivisie

Netherlands

  • 121
  • 160 Transfers
75.6%
First Division

Belgium

  • 120
  • 159 Transfers
75.5%
Primeira Liga

Portugal

  • 159
  • 214 Transfers
74.3%
Avg

Other European Competitions

  • 129
  • 170 Transfers
76.3%
  • Evidently, selecting performers is not a privilege of just the top-5. On average more than 3/4 (76.3%) of players signed by clubs in other European competitions during the latest two transfer windows were previously identified as top performers (70+ in at least 1/5 KPIs).
  • Russian teams lead the group with 78.5% with Greece in close proximity with 77.8%.
  • Belgium First Division and Eredivisie are central Europe's "twins" exhibiting similar behavior, while Portugal largely because of the high number of transfers falls a bit under 75%.

Go for quantity, lose in quality: When number of transfers increases, quality drops.

Competition

Performers Signed

Total Transfers

% of Players with 70+ in at least 1/5 KPIs

Avg

10 European Competitions

  • 1348
  • 1725 Transfers
78.1%

Numbers do not lie. The correlation between performance and recruitment is evident. We’ve documented that 81%  of transfer signings of teams from the top-5 European competitions are players with proven track record in terms of performance. The rest of Europe are not far behind with 76% on average. 

Challenges

Validating the link between performance & selection provides the foundations for further focus on key aspects of transfer signings such as overall quality. 70+ in at least one of the 5 KPIs is a good starting point, however the transferred players’ 5 KPIs average is considerably low (we shall be exploring the topic thoroughly in a future project), an indication that mono-dimensionality is preferred over versatility.

When the number of transfers increases, quality drops exponentially, an indication that a high number of teams are still facing difficulties with maintaining a consistent & viable workflow.  There are examples where clubs might invest in players who have not exhibited a proven performance record, such as youngsters signed to be loaned out shortly afterwards, but this factor alone cannot justify the perseverance of the pattern.

Potential also needs to be taken into consideration. There are many examples of players going under the radar, usually youngsters who took off slowly or even seasoned professionals who didn’t fit in properly to the new manager’s desired game-style, under-performing as a result. Which brings us to suitability, probably the single most important factor for determining whether a transfer will turn out to be a  “success” or not.