Day 11 of Blogmas and this time I’m going to cover the Dutch 3rd tier. I was very excited that I could find data on this league on Wyscout, because it is an amateur competition within a closed system, but on that latter part, I will write a different article.
In this article, however, I will use data to scout the best strikers in the Tweede Divisie and make a shortlist of which players are worth following in the next months to come.
The data
The data used in this analysis comes from Wyscout. In the dataset for the striker, I’ve selected each player who primarily plays on the striker position. Obviously, there are other players who have played in this position, but I’ve only selected the players that have played as a striker as a dominant position in the current season. This leaves me with 75 players who qualify in the Eliteserien 2021.
Because I’m looking at the current season, which is a full season, I want to make a selection for players that played a decent amount of games for me to assess them. For me, it’s important that they played at least 600 minutes in this season. After looking at that I’m left with 23 players in my dataset and they will go through my analysis process. The data was retrieved on 18th September 2021.
I will look at the following categories and metrics to assess their abilities through data:
- Shots
- Dribbling
- Offensive duels
- Assists
- Goals
After going through the data analysis and visualisation, I will make a shortlist of players who I think are worth keeping your eye on.
Shots
Looking at shot quality can be measured in different things. In the scatterplots below I will look at the volume of the shots and the expected goals that are generated through the shots.
In the shot volume, we can see that Castien (4,69 shots per 90), Van der Moot (3,59 shots per 90), and Brandsma (3,33 shots per 90) stand out in terms of the number of shots.
The best performers in terms of the percentage of shots going on target are Sanchez with 80% shots on target, Bitter with 80% shots on target, and Brandsma with 60% shots on target.
In the scatterplot above you can see the number of shots per 90 of a certain player and the expected goals per 90 of that particular player in question. The reason we look at this is how many shots a player has in a game and how high the probability is of scoring an actual goal.
In the shot volume, we can see that Castien (4,69 shots per 90), Van der Moot (3,59 shots per 90), and Brandsma (3,33 shots per 90) stand out in terms of the number of shots.
Looking at the expected goals generated per game we see the following players coming on top: Van der Linden with 0,77 xG per 90, El Azzouti with 0,64 xG per 90, and Blommestijn with 0,59 xG per 90.
Dribbling
Dribbling often is linked to wide midfielders of wingers, but it can be a valuable aspect of a striker’s game as well. The ability to control the ball, progress on the pitch, and deal positively with a 1v1 situation with an opponent defender, is not to be underestimated. Especially when you are not playing a typical central forward role, but playing with two strikers.
If we look at the number of dribbles per 90, the following players come out on top of their respect metric: Hardijk with 10,18 dribbles per 90, Admiraal with 7,82 dribbles per 90, and Sterling with 7,36 dribbles per 90.
When we look closer to the success rate of the dribbles, we can see that a different set of players scores high – but attempt fewer dribbles per 90: Poepon with 58,52% successful dribbles, Zeldenrust with 57,58% successful dribbles, and Bitter with 56% successful dribbles.
Offensive duels
The importance of offensive duels can be seen in two lights. The first one, is to measure the physicality of a strikers and the ability to win offensive duels to create something out of an attack. The second one, is to engage in the pressing style set out by a team. The ability to press a direct opponent and win the ball can also be found in this metric of offensive duels.
The most offensive duels conducted per 90 are by the following players: Sterling with 16,47 offensive duels per 90, Hardijk with 16,12 offensive duels per 90, and Castien with 15,26 offensive duels per 90.
If we look closer at the players that have the highest percentage of won offensive duels, the following players stand out: Blij with 45,61% offensive duels won, Langedijk with 45% offensive duels won, and Sterling with 43,48% offensive duels won.
Assists
Expected metrics seem simple but can become incredibly complicated when combining things. In the scatterplot above I’ve taken a look at the probability of the pass becoming an assist per 90 minutes and looking at the actual assists of a player per 90 minutes.
If we look at the expected assists per 90, we can see that four players stand out from the crowd with a significantly higher xA per 90 than the rest. Vink has 0,39 expected assists per 90, Kaptein has 0,41 expected assists per 90, and Castien has 0,32 expected assists per 90.
Looking more closely, we can see that the actual assists per 90 don’t correspond with the three players with the highest expected assists per 90. Vink has 0,74 assists per 90, Doesborg has 0.39 assists per 90, and Wouter/Zeldenrust has 0,38 assists per 90.
Goals
In the end the most important thing for a striker is his output: goals. I’m looking at the probability of scoring a goal with a certain short and looking at the actual goals scored by a particular player per 90 minutes.
Looking at the expected goals generated per game we see the following players coming on top: Van der Linden with 0,77 xG per 90, El Azzouti with 0,64 xG per 90, and Blommestijn with 0,59 xG per 90.
When we look more closely to the actual goals scored per 90 we see that Van der Linden stands out with 0,99 goals per 90, followed by Blommestijn with 0,94 goals per 90, and El Azzouti with 0,78 goals per 90.
Short list
Four players have impressed me in terms of data and I have made percentile ranks data visualisations of them, before going further and analysing them through video.
After this phase of data scouting and analysing, we will move into video scouting and assess how well they do in certain game situations. This article was an example of how you use data to make a shortlist.
