Data scouting Austrian Bundesliga: finding the best strikers of 2020/2021

In the last data scouting piece I spoke about the fact that I wanted to look further than the usual countries in Europe and scouted the Russian Premjer liga. Although I still stand by those words and wanted to broad my view, I came to realise that I’ve not really looked into certain countries in Europe that are worth looking into. My eye will focus more closely to the leagues in Portugal, Russia, Austria and Turkey in the next weeks. Last time I spoke about Russia, today I will delve into the Austrian Bundesliga.

I don’t know why, but looking at Russian clubs is always about the club that feature in European competitions, but there are so much more clubs than just Red Bull Salzburg. That’s one of the reasons I would like to dig into the wonderful world that is Austrian football.

In this scouting piece I’m going to look for a striker who’s good in the box, has volume in shots per 90 and looks to match or overachieve his expected goals ratio.

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 85 players who qualify in the Austrian Bundesliga 2020-2021.

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 900 minutes in this 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 18th June 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.

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 Baden-Frederiksen (3.95 shots per 90), Daka (4.22 shots per 90), and Koita (3,4.9276 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 Schmidt with 59,18% shots on target, Davies with 63,16% shots on target, and Hoffer with 63,64% shots on target. Overall, Koita scores the best as we combine both metrics.

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 Baden-Frederiksen (3.95 shots per 90), Daka (4.22 shots per 90), and Koita (4.92 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: Kara with 0,71 xG per 90, Daka with 0,96 xG per 90, and Koita with 1,17 xG per 90. Koita has the most shots per 90 and also produced the most 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, the following players come out on top of their respect metric: Balic with 6,54 dribbles per 90, Röcher with 6,7 dribbles per 90, and Adeyemi with 7,75 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: Nutz with 60% successful dribbles, Wooten with 60,87% successful dribbles, and Koita with 62,71% 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: Pichler with 15,15 offensive duels per 90, Grüll with 15,42 offensive duels per 90, and Röcher with 15,44 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: Balic with 42,05% offensive duels won, Rep with 42,99% offensive duels won, and Koita with 46,60% 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 four players stand out from the crowd with a significantly higher xA per 90 than the rest. Fitz has 0,31 expected assists per 90, Attanga has 0,36 expected assists per 90, and Adeyemi has 0,4 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. Hugi has 0,31 assists per 90, Koita has 0,39 assists per 90, and Adeyemi has 0,53 assists per 90.


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 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: Kara with 0,71 xG per 90, Daka with 0,96 xG per 90, and Koita with 1,17 xG per 90.

When we look more closely to the actual goals scored per 90 we see that Baden-Frederiksen stands out with 0,69 goals per 90, followed by Daka with 1,19 goals per 90,  and Juric with 1,38 goals per 90.

Final thoughts
Every year there are a few players doing extremely well and they play for Red Bull Salburg, and this season is nothing different with both Koita and Daka leading the goalscoring charts. Behind them I would recommend looking at Adeyemi (also Salzburg), Ercan Kara (Rapid Wien) and Balic from LASK Linz.


Geef een antwoord

Het e-mailadres wordt niet gepubliceerd. Vereiste velden zijn gemarkeerd met *