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Home Data Analysis

Recruitment Analysis: Using data to scout for non-obvious forwards in the top-5 leagues

Lee Scott by Lee Scott
April 7, 2022
in Data Analysis, Player Analysis, Recruitment Analysis
Reading Time: 7 mins read
0
Recruitment Analysis: Using data to scout for non-obvious forwards in the top-5 leagues

We are in the closing stages of most leagues across Europe and the Scandinavian leagues have only just got underway. It is an interesting time to start looking at some of the more interesting young players around the continent with an eye to judging which players clubs may be looking at in terms of summer transfers.

In this article, I am going to specifically look for forward players who are aged 24 or under and who have had a good impact for their sides so far this season.

Before we really get going, however, I should point out that this article is not intended to tell you that the likes of Kylian Mbappe and Erling Haaland have been strong performers this season (spoiler alert; they have) and as such I will not be counting players who are already, in my opinion, elite. Instead, we will look at players who are currently playing for teams who are perhaps in the middle tiers of their leagues but who might well be ready to take the next step in their career.

As ever when performing tasks like this I like to use data in order to make it easier to cut through the noise and identify the players that are performing at a good level. All data is taken from Wyscout although the eagle-eyed amongst you will realise when you look through the article that I use some metrics that I have developed and tested over a period of months  the raw data, however, still comes through from Wyscout.

Involvements

In the first instance, however, I want to look at how involved the players in our data set have been in terms of goals and xG for their teams so far this season. Our data set includes all forwards in the top-5 European leagues who have played at least 450 minutes so far this season. Crucially though when we are approaching this from a recruitment perspective, we do not just want a list of the players in our data set who have scored or assisted the most. Instead, I want to identify the players who are performing strongly in these metrics for these teams. For those of you that have been paying attention I actually wrote an article detailing exactly how I do this on this site just a few weeks ago. If you want to read that piece then you can find it here.

After I have picked out five players who I think are interesting going forward I will use percentile data in order to visualise how those players are performing in their leagues so far this season.

Screenshot 2022 04 07 at 12.06.23

So, the first step is to decide which players we are going to take an in-depth look at. On the left side of the above viz, we have a bar chart that shows the % of each players involvement in terms of goals for their team. This basically means that if a player has scored 5 goals and assisted 5 goals then their goal contributions are 10, then if their team has scored 100 goals then their % involvement would be 10%  simple, right? The same goes for the bar chart on the left-hand side although this time we are looking for the % that each player has been involved in their teams xG. So, again if the player has an xG of 5 and an xA of 5 then their expected goal contribution is 10. Then, if their team has an xG of 100 then their % involvement in team xG is 10%.

There are some interesting names on each list but it is fair to say that Amine Gouiri of Nice has to be one of our players. He has contributed 25% of all team goals and 26.15% of all xG for his team.

Next, we will highli

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    Lee Scott

    Lee Scott

    Lee Scott is an analyst for Total Football Analysis and a professional scout For Southampton FC. You can follow Lee on X @FMAnalysis.

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