This is the final instalment of a three-part data analysis series that I have been writing this week concentrating on using data to identify potential strikers in the second tiers of the top 5 leagues.
In the first part of the series, we were looking at potential targets in the centre of defence.
That was followed by the second part in which we looked for a new central midfielder with a set profile to search for.
The premise behind the series is simple, we have joined a new club as a recruitment analyst and we have been immediately set a task to identify targets for the upcoming transfer window.
In order to achieve this, we are, in the first instance, using raw data to identify players that are performing well this season.
This is not a means to produce a final list of recruitment target but rather to take a large set of players and filter it down to a more manageable shortlist that we can then drill down into using video and live scouting that go more into the tactics around each player.
We have applied certain filters to the data in order to concentrate our search.
The first is obviously to only consider players in the second tier of England, France, Italy, Spain and Germany.
We then filter the results to players who are under the age of 23 and who have played at least 1500 minutes so far this season.
In terms of the player profile that we are looking for, it is reasonably simple.
We want a player for the ‘9’ position who is capable of playing as a lone forward.
At the end of this data analysis, we plan to have a shortlist of five players that can be put forward for further checking.
Recruitment First Steps
The initial step to the process is to find and export the data that we want from Wyscout.
This data is then collated into a single spreadsheet with all of the players that we are potentially interested in.
Then, that is imported into the public version of Tableau and we can use the tools available there to produce visualisations that present our data.
You can find the result below with a scatter graph.
xG per 90 Vs Shots Per 90
The first check that we run is a relatively simple one.
We are comparing a player’s expected goals (xG) per 90 and their shots per 90.
This is to look for players that are volume shooters who also shoot from good positions.
The logic is that a player who takes more shots from positions that yield a high x, should score more.
This is especially true if you are able to identify players that meet these parameters while playing for a weaker club.
If you take that player and put him in a team with more talented teammates, the hope is that their statistical input can improve.
The first player that stands out from this graph is the 23-year-old VfL Bochum player Silvere Ganvoula.
The Democratic Republic of Congo international is currently averaging 3.09 shots per 90 with an xG of 0.53.
Next up is Luis Suárez (no, not that one), a Colombian striker currently playing in Spain for Real Zaragoza on loan from Premier League side, Watford.
Suárez is currently averaging 3.06 shots per 90 with an xG of 0.53.
The third player that stands out is Darwin Núñez, a 20-year-old who currently plays in Spain for Almería.
The Uruguayan striker is averaging 2.79 shots per 90 with an xG of 0.59.
Next up is Janni Serra a German forward currently playing for Holstein Kiel.
The 22-year-old is averaging 2.78 shots per 90 and has an xG of 0.47.
The final player that I picked out here is Simon Banza a 23-year-old playing for RC Lens.
The French forward is currently taking 2.5 shots per 90 with an xG of 0.53.
Goal Conversion % Vs Shots Per 90
This time we are taking shots per 90, again, and comparing that with the % of shots that a player converts into goals.
This gives a slightly different slant on the data as we start to consider which players can finish a high proportion of the shots that they take.
Once again we are looking to build a picture of the players that we could take and improve their shot locations.
The first player that interests me above is Yoane Wissa, a French forward with Ligue 1 side FC Lorient.
The 23-year-old plays typically from the left of a front three but he profiles as someone who could play as a ‘9’. He is averaging 2.26 shots per 90 with a conversion rate of 26.79%.
Next up we have Darwin Núñez again.
The Uruguayan has 2.79 shots per 90 with a conversion rate of 24%.
The next player that interests me is Adrian Grbic, a 23-year-old Austrian forward currently with Clermont in France.
He is averaging 2.83 shots per 90 with a conversion rate of 22.37%.
We should also discuss the other outlier in the data: the 21-year-old Argentinean forward Nicolás González of VfB Stuttgart.
The 21-year-old has the highest amount of shots per 90 at 3.24 per 90 but his conversion rate of 13.33% is below average.
The final look at the data in this manner is something that I like to use when looking for a fixed striker and that is to compare touches in the opposition area per 90 and xG per 90.
The first thing to note is that there are a lot of familiar names there with Darwin Núñez as one of the standouts with an xG of 0.59 and 4.58 touches in the opposition box per 90.
Next up is Simon Banza again with an xG of 0.53 and 4.53 touches in the opposition box per 90.
Janni Serra is also there again with an xG of 0.47 and 4.08 touches in the opposition area.
Once again Nicolás González is an outlier with an xG of 0.37 but the highest number of touches in the opposition penalty area in 5.76.
Our next step is to identify the players that we have discussed that will be shortlisted to take forward to the next stage.
Darwin Núñez Data Analysis
Darwin Núñez is, for me, the standout player.
He is currently outperforming his xG with 0.59 and 0.67 goals per 90.
The Uruguayan takes a lot of shots, 2.79 per 90, and has a decent conversion rate of 24%.
He averages 4.58 touches in the penalty area per 90 but also attempts 3.79 dribbles per 90 minutes.
Núñez is extremely effective at attacking in transition and leads the line well for his team.
Silvere Ganvoula Data Analysis
Silvere Ganvoula at Bochum is also an interesting player.
He is currently underperforming his xG with 0.47 shots per 90 from an xG of 0.53 per 90.
The 23-year-old is taking 3.09 shots per 90 but his goal conversion lets him down at 15.07%.
He averages 3.56 touches in the opposition box but attempts an impressive 4.36 dribbles per 90 minutes.
Ganvoula plays more as a target striker that looks to hold up the ball and bring others into the game.
Luis Suárez Data Analysis
Luis Suárez is the next player to make it on to our shortlist and as with Darwin Nunez, he is outperforming his xG.
His current xG is sitting at 0.53 with 0.60 goals per 90.
The Colombian is taking 3.06 shots per 90 with a conversion rate of 19.54.
He is capable of leading the line or playing as the second striker attacking from a slightly withdrawn position.
Luis Suárez is a dangerous carrier of the ball and is averaging 5.45 dribbles per 90 minutes.
Simon Banza Data Analysis
Simon Banza is a player that I have been tracking for a while.
The Frenchman is currently underperforming his xG with 0.43 goals per 90 compared with an xG of 0.47.
His shots per 90 are relatively low at 2.78 but he has a decent conversion rate of 15.56%.
His 4.08 touches in the opposition box are unsurprising given his tendency to look to lead the line for his side.
Yoane Wissa Data Analysis
I have included Yoane Wissa in this list because I find his versatility and skill set fascinating.
The 23-year-old is outperforming his xG with 0.61 goals per 90 from an xG of 0.40.
This could partially be explained by his tendency to shoot from the corner of the penalty area having cut inside from the left-hand side onto his right foot.
He is taking 2.26 shots per 90 with an impressive conversion rate of 26.79%.
The French forward also attempts 4.36 dribbles per 90 minutes.
Wissa plays predominantly from the left-side but I feel that he is capable of leading the line and would prove dangerous when moving from deeper areas and threatening to break the defensive line of the opposition.
Conclusion
So, there we have it.
A shortlist of five attacking players that have interesting data so far this season.
They all provide slightly different skill sets but are ready for the next step in their careers.
We would then look to provide this list to our scouts and video scouts who would start to monitor them and build out a report with data as the basis.
