In this article, I will use data to scout the best strikers in the French D1 Arkema. In doing so I will look at the players who are worth following in the next months or years to come.
The data used in this analysis comes from Wyscout. In the dataset for the striker, I’ve selected each player who primarily plays in the striker position. 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 57 players who qualify in the D1 Arkema 2021/2022.
Because I’m looking at the current season, which isn’t a full season. I want to make a selection for players that played a decent amount of games for me to assess them. It’s important that they have played at least 500 minutes in the current season. After looking at that I’m left with 37 players in my dataset and they will go through my analysis process. The data was retrieved on 1st of May 2022.
I will look at the following categories and metrics to assess their abilities through data:
- Offensive duels
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 the following players do well. Hegerberg (3,89 shots per 90), Malard (4,21 shots per 90), and Macario (4,59 shots per 90) stand out in terms of the number of shots in D1 Arkema.
The best performers in terms of the percentage of shots going on target are the following. Peniguel/Fowler with 60% shots on target, Malard with 62,26% shots on target, and Karczewska with 65% shots on target.
In the scatterplot above you can see the number of shots per 90 of a certain player. We also see 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 Hegerberg (3,89 shots per 90), Malard (4,21 shots per 90), and Macario (4,59 shots per 90) stand out.
Looking at the expected goals generated per game we see the following players coming on top. Riberdera/Macario with 0,66 xG per 90, Hegerberg with 0,79 xG per 90, and Malard with 0,92 xG per 90.
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 in D1 Arkema, the following players come out on top of their respect metric: Okoronkwo with 6,34 dribbles per 90, Fowler with 6,53 dribbles per 90, and Kouassi with 8,04 dribbles per 90.
When we look closer at the success rate of the dribbles, we can see that a different set of players scores high – but attempt fewer dribbles per 90: Borgella with 61,11% successful dribbles, Mondesir with 64,91% successful dribbles, and Coquard with 83,33% successful dribbles.
The importance of offensive duels can be seen in two lights. The first one is to measure the physicality of a striker 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: Ribadeira with 19,10 offensive duels per 90, Mondesir with 19,64 offensive duels per 90, and Bourdieu with 20,54 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: Ouchene with 41,86% offensive duels won, Mondesir with 42,31% offensive duels won, and Coquard with 58,33% offensive duels won.
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 a few players stand out from the crowd with a significantly higher xA per 90 than the rest. Lavogez has 0,2 expected assists per 90, Macario has 0,27 expected assists per 90, and Snoeijs has 0,27 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. Mondesir has 0,32 assists per 90, Snoeijs has 0,32 assists per 90, and Hegerberg has 0,52 assists per 90.
In the end, the most important thing for a striker is her 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: Riberdera/Macario with 0,66 xG per 90, Hegerberg with 0,79 xG per 90, and Malard with 0,92 xG per 90.
When we look more closely at the actual goals scored per 90 we see that Macario/Hegerberg have 0,90 goals per 90, followed by Malard with 0,93 goals per 90, and Katoto with 1,05 goals per 90.
In the data analysis above we have seen a few key elements of a striker’s attacking play. In every aspect of those key elements we have seen which players have been the best and which players we would do well to track.