Data scouting A-League: finding a striker

Previously I’ve scouted a few leagues on this website with the idea that I wanted to create content that was in Europe, but it did not look at the top-5 leagues (Italy, France, England, Germany and Spain). I’ve thoroughly enjoyed scouting these leagues, as they can prove valuable for clubs in those aforementioned top-5 leagues. Although I’m still writing scout reports and analysis on those European leagues, I’ve found myself wanting to be challenged more and delve further into other continents. That’s why I chose to scout the Australian A-League for a striker.

Australia has a very interesting relationship with football through European eyes. I always thought that we appreciated the Socceroos a lot in terms of the national team, but the domestic competition has been a bit neglected. A domestic league where players go to, in order to spend their last few seasons in their career or players go there who are not good enough for certain European leagues. This is obviously a very euro-centric view of the world and obviously, the A-League has some remarkable talents on display – and that’s why I chose this league to scout in.

Why a striker/central forward? I’ve chosen this position as it’s a vital position for many teams, yet there are so many types of strikers and I wanted to get a better understanding of the sort of strikers that are playing in the A-League. In this data scouting article I will look for strikers: the best overall striker and the best U23 striker. This has two purposes: I can analyse which strikers are the best in the league AND look for a striker with huge potential going forward, who perhaps can make a transfer to a higher profile league in Europe.

The data
The data used in this analysis comes from Wyscout. In the dataset for the strikers, I’ve selected each player who primarily plays on the central forward 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 68 players who qualify in the A-League 2020-2021.

Because I’m looking at the current season (16 games played as I’m writing this), I’m looking at a relatively small sample. For me it’s important that they played at least 600 minutes in this season. Normally I would go for 900 minutes, but as said – a small sample. After looking at that I’m left with 31 players in my dataset and they will go through my analysis process. The data was retrieved on 8th April 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 Maclaren (4,22 shots per 90), Wenzel-Halls (4,34 shots per 90), and Davila (3,76 shots per 90) stand out in terms of the number of shots. Kuol (3,58 shots per 90) and Nabbout (3,55 shots per 90) follow closely with all of these five players averaging over 3,5 shots per game in the 2020-2021 A-League season.

Of those five, Kuol scores best in the shot on target % as just under 60% of his shots go on target with 58,33%. The best performers in terms of the percentage of shots going on target are Danzaki with 60% shots on target, Simon with 62,69% shots on target, and Pierias with 68,42% shots on target. As said above, Kuol scores the best in 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 Maclaren (4,22 shots per 90), Wenzel-Halls (4,34 shots per 90), and Davila (3,76 shots per 90) stand out in terms of the number of shots. Kuol (3,58 shots per 90) and Nabbout (3,55 shots per 90) follow closely with all of these five players averaging over 3,5 shots per game in the 2020-2021 A-League season.

Looking at the expected goals generated per game we see the following players coming on top: Derbyshire with 0,54 xG per 90, Berisha with 0,55 xG per 90, Barbarouses with 0,56 xG per 90, Kuol with 0,6 xG per 90, Hemed with 0,7 xG per 90 and MacLaren with 1,06 xG per 90. MacLaren has the most shots per 90 and also produced the most 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 be underestimated. Especially when you are not play 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: Diamanti with 6,81 dribbles per 90, Armiento with 7,61 dribbles per 90, Noone with 7,92 dribbles per 90, Nabbout with 8,25 dribbles per 90 and Diego Castro with 8,53 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: Nabbout with 62,5% successful dribbles, Davila with 62,5% successful dribbles, Ureña with 63,16% successful dribbles, Duke with 69,23% successful dribbles and Ibini-Isei with 74,42% 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: Juric with 14,67 offensive duels per 90, Diamanti with 14,79 offensive duels per 90, Armiento with 15,95 offensive duels per 90, Fornaroli with 16,20 offensive duels per 90, and Diego Castro with 17,07 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: Kuol with 47,06% offensive duels won, Noone with 53,01% offensive duels won, Davila with 53,62% offensive duels won, Mauk with 54,17% offensive duels won and Nabbout with 56,19% 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. Ibini-Isei has 0,24 expected assists per 90, Nabbout has 0,38 expected assists per 90, Diamanti has 0,42 expected assists per 90 and Noone has 0,46 expected assists per 90.

Looking more closely, we can see that the actual assists per 90 correspond with the four players with the highest expected assists per 90. Noone has 0,38 assists per 90, Ibini-Isei has 0,4 assists per 90, Nabbout has 0,57 assists per 90 and Diamanti has 0,63 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 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: Derbyshire with 0,54 xG per 90, Berisha with 0,55 xG per 90, Barbarouses with 0,56 xG per 90, Kuol with 0,6 xG per 90, Hemed with 0,7 xG per 90 and MacLaren with 1,06 xG per 90. MacLaren has the most shots per 90 and also produced the most xG per 90.

When we look more closely to the actual goals scored per 90 we see that Kuol stands out with 1,04 goals per 90, followed by MacLaren with 0,87 goals per 90. Derbyshire follows behind that with 0,6 goals per 90, Duke with 0,58 goals per 90 and Juric with 0,56 goals per 90.

Shortlist
According to the data as analyed above, five players make the cut for further research:
– Andrew Nabbout (28)
– Alessandro Diamanti (37)
– Jamie MacLaren (27)
– Alou Kuol (19)
– Bernie Ibini-Isei (28)

Alessandro Diamanti is 37 years old, so he will not be included in the follow-up. To be fair, only Alou Kuol is an U23 player in terms of age, but the others are 27/28 years old.

Andrew Nabbout
28 years old
Australia
Melbourne City FC
2020-2021

Jamie MacLaren
27 years old
Australia
Melbourne City FC
2020-2021

Alou Koul
19 years old
Australia/South Sudan
Central Coast Mariners
2020-2021

Bernie Ibini-Isei
28 years old
Australia/Nigeria
Western Sydney Wanderers
2020-2021

Final thoughts
These four attackers are doing quite well in the season so far, but with three of the four striker being 27/28 – they might not be that attractive for teams to scout. They will have 2 or 3 good years in them, but what I found very interesting is that 19-year old Alou Kuolo is arguably the best at the moment and has many years ahead of him. It’s no wonder that he will probably join VfB Stuttgart for the next season. He’s definitely one to watch in the rest of the season and in the years ahead.

Sources
Wyscout
Tableau
Python




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