How clubs use data to filter their search for the Next Big Thing

The transfer market is more competitive than ever, but clubs need to know what they are looking for

8:30pm on Sunday 30th August 2020
Dougie Wright | Professional Analyst

Football recruitment used to be easier.

Up until the 1990s, it was mostly a local/national business, with clubs only really scouting players from the same country.

Over the past 20 years, the Bosman ruling has combined with an increasing amount of commercial Interest in the game to create an explosion in International transfers, and the vast majority of clubs are now looking beyond their own borders in search of the next superstar.

Of the 50 most expensive football transfers, all have came since the year 2000, and only three of them have taken place where the buying club, selling club and player all came from the same country (Kylian Mbappe, Harry Maguire and Raheem Sterling). Football at the top level has become completely and utterly globalised.

This is problematic for those wedded to the old school: with over 65,000 registered professional footballers, it is simply not practical to lay eyes on even a small percentage of that figure, let alone watch them enough times to recommend one for a signing.

This leaves clubs with two potential approaches to find the few needles in the haystack capable of improving their first team.

Deep and Narrow

The first is to go narrow and deep in specific markets. For example, Real Madrid employ a lot of resource in Brazil - a strategy that has seen them sign Reinier, Vinicius Jr and Rodrygo in recent years. The main disadvantage to this is that generally the level of talent in a country ebbs and flows with time. If all of your eggs are in one basket, what happens when the basket breaks?


Reinier, Rodrygo, Vinicius, and Real Madrid's clear switch in transfer policy

Furthermore, if your target is your domestic market (as is still the case with many clubs), then the chances of your scout stumbling upon a gem who you will then be able to sign for your club without any competition are minimal.

Even the most dull development games will have a dozen scouts in attendance. This means the best talent is invariably hoovered up by those that can pay, while the rest find the level they deserve.

The alternative approach is trying to be as omniscient as possible: to be alert to as many talented players achievable for your club at any given time. For this approach to be reliable, you need data.

Two of Madrid's Brazilian contingent - Vinicius Jr and Rodrygo

Data should act in the first instance as a filter. For each position on the pitch, clubs can design an identikit for what they’re after. If you want your centre backs to be aerially dominant, you might say the defenders on your shortlist must have a minimum 65% success rate winning balls in the air.

If you are set on making a profit on player trading, you might want the defender to be age 26 or below. If you’re an English club at the mercy of work permit rules, you’re probably only Interested in players with a European passport as well.

From these three simple filters, you can dramatically decrease the list of Interesting players from tens of thousands to a couple hundred. Factor in playing time, injury/disciplinary history and maybe a couple of other stylistic measures (forward passing, dribbles), then you will most likely end up with a manageable scouting shortlist.

Of course, the data cannot be treated as gospel. In a fluid team sport, many of a player’s individual stats will be influenced by factors outside of their control: quality of team-mates, positioning of opponents and tactical direction are all important. How would Robert Lewandowski’s xG differ if he had 10 Tranmere Rovers players behind him instead of his Bayern team-mates?

31 yrs - S (C) - Bayern
JavaScript chart by amChartsLDefendingCreativePassingAttackingShootingDecisiveAerialsPhysical10-10-5051015100%
Played matches
Shots P90
Shots On target P90
Successful passing %
Duels won P90

Furthermore, there may be factors in your player identikit that simply are not possible to scout via stats. Attitude and awareness are probably beyond the realms of even the most impressive of data science teams.

This is the stage where the eyes come in: to validate the context of the stats that flagged the player in the first place and to check the boxes that the stats couldn’t give you.

However, instead of applying these checks to thousands of players, the scout’s attention is focused on those players where there is already something to like. This process means that teams can avoid wasting time, money and effort scouting players who will ultimately not fit for any number of reasons.

It’s not a perfect system, and as ever, there are a lot of egos competing for power. However, in clubs’ ongoing pursuit to find The Next Big Thing, the question is not data or eyes: it is how to best harmonise both.


Reinier, Rodrygo, Vinicius, and Real Madrid's clear switch in transfer policy

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