Player recruitment in football is never an easy process.
Even if you are recruiting for a club at the top level of the game and can choose from an almost unlimited pool of players, certain limitations still make the process more difficult.
Let’s take Liverpool as an example.
With the exception of players at maybe two or three clubs, Liverpool is able to attract players from anywhere in the footballing world.
This does not mean, however, that there are no limitations in place on Liverpool in the market.
While almost any player would welcome the opportunity to play for the English club, very few meet the criteria.
To play for Liverpool, a player needs to be able to play at a certain standard and to be the correct age and position to meet the club’s impressive succession plan.
From a pool of thousands, we then come down to a pool of players around the 100 mark, and within that, the criteria will reduce the pool of potential players even more.
If we flip the spotlight slightly but remain in the top flight of England and consider the available player pool for a team like Brighton, then the picture is perhaps different; arguably, those 100 or so players that Liverpool could potentially target will be out of reach for Brighton.
The tier of players at the next level down, where Brighton could realistically shop, is much broader, though, with more variation and the potential to find a bargain.
My examples above may be a little facetious, though, as Liverpool have consistently shown themselves capable of recruiting from outside their apparent pool of available players and making interesting signings.
We saw this previously with the signings of Andrew Robertson and Georginio Wijnaldum, both of whom came from relegated clubs, and now with the signings of Diogo Jota and Luis Diaz.
I would argue, however, that Liverpool has developed its recruitment process to the point that it is now identifying and signing players who could be in that tier of 100 or so players. It has the bravery and trust in the process to sign players from outside the obvious market.
Liverpool is generally held up as an excellent example of a club that knows who it is from a footballing perspective and understands how to translate that information into a cohesive recruitment strategy.
What do we mean by this, though?
Let’s take a closer look using two teams in the French top-tier as examples.
When recruiting players for the first-team level at any club, several important factors must be understood.
Firstly, what does our current squad look like? If we have three players capable of playing right-back, then that position is not a priority, while if we have only one recognised centre-forward, then that position becomes one that we have to look at closely.
What does our squad look like regarding player ages and contract lengths? Are there positions in which we have ageing players who have expiring contracts? If so then we need to put some work in there.
Then how are we performing and what do the budgets look like?
All of the above makes sense, right?
But what about the style of play and general tendencies?
For this, we can rely on what is verbalised in the media.
Coaches will say they want their team to “keep the ball on the ground” and “work the ball into the area to create chances.”
But does this kind of language actually match what we see on the pitch?
As we often do, we can use data to explain exactly a team’s style of play.
As part of this case study, we will examine two clubs in the French top flight, Rennes and Lorient, and show how we would recruit a striker based on their performance on the pitch.
Let’s start with Rennes.
Stade Rennais Recruitment Analysis
Here we have a simple radar plot containing several key metrics in the game’s attacking and passing/ball progression sides plotted to show Rennes’ output and the league average for the French top-flight.
I should point out that this radar does not capture the specific metrics that I would use at my current club, but it does provide an interesting example.
The first thing to note is that when looking at the ball progression aspect of our radar Rennes are largely league average with the exception of slightly more passes per 90 and progressive passes per 90 and a slightly increased passing rate (passing rate shows tempo by telling us how many passes a team is playing over a set period of time).
However, when we consider the attacking aspect of the graph, the picture starts to shift.
Rennes are above average in all metrics but significantly above average in terms of touches in the opposition area per 90, shots per 90, xG per 90 and, importantly, goals per 90.
So, what does this tell us about our approach to finding potential forward players to scout and perhaps recruit?
Well, we know that Rennes are creating significant goalscoring opportunities.
As such, we need to concentrate on finding a forward who can make the most of those opportunities when they are created.
Next, we can start visualising how this would look within a dataset.
For example, I have chosen to look at forwards in the top-5 South American leagues. In keeping with the general trends in the French top flight, we will concentrate on players who are 26 years old or under and who have played at least 650 minutes this season.
The metrics on the scatter graph are intended to quickly visualise a group of players who might fit our needs.
However, this would only be part of the process. Once I have an initial shortlist from this process, I would then take the data and calculate the player’s performance for their team as a percentage of involvement in the key metrics.
I have written previously on this subject here.
We are looking for forwards who can effectively finish the opportunities that Rennes are obviously creating.
As such, we will look at shots on target % on the vertical axis and xG per shot on the horizontal axis.
This tells us which players are getting into good areas and are hitting the target when doing so.
Immediately then we start to see which players are most likely to be able to convert the chances that Rennes are creating.
As you can see I have picked out a couple of players to highlight further within the data.
But what if your team are not performing well, as Rennes are, and are not at the top end of the table and challenging for Europe, as Rennes are? Well, the process is the same with some slight alterations.
FC Lorient Recruitment Analysis
This time we will look at Lorient who are battling at the other end of the Ligue 1 table.
Once again, the first part of the process is to consider team data, and we see a side perhaps more direct in the build-up phase than Rennes and struggling across the board, apart from with crosses per 90, as compared to the league average.
Whilst for Rennes we considered forwards who could add to what they already had in terms of getting into areas that could take advantage of the chances that were already being created, we have to be more creative for Lorient.
They aren’t creating enough as a team and as such, we would need a forward who showed the clear ability not to take shots from good areas but to convert those chances when they were eventually created.
We can keep the horizontal axis constant, but this time, we use goal conversion percentage (the percentage of shots converted to goals) as the horizontal axis to hone in on the forwards capable of converting chances even if they are limited.
Once again, I have highlighted a couple of players within the data who may be interesting to a team like Lorient.
Conclusion
The above is, of course, just an example and a way to visualise the theory.
When you are working at a club within the recruitment department or even when you are writing recruitment-related pieces, you must understand firstly what the coaching staff are trying to do, translate that into relevant data and metrics, and then understand what is actually happening using those same metrics so that you can start to use data as an effective part of the recruitment process.
