Finding the best young players in 1.HNL – data analysis

Finding the best young players in 1.HNL - data analysis statistics

The Prva Liga (1.HNL) or better known as the Croatian First League has always been a ‘hotbed’ for young, talented football players. With the likes of Real Madrid star Luka Modric or Juventus striker Mario Mandzukic, the league has never failed to spoil the world with elegant style and determined, hard-working players. The production is constant, the clubs aim to sell high and turn the profit into their own future. The fee from one talented youngster can provide enough resource for greater youth intake or building new scouting networks. Therefore the teams are keen to develop the players as best as they possibly can.

In this data analysis, we will focus on creative individuals on the attacking end. We will examine possible future stars under the age of 23 but consider only the ones who played at least 600 minutes during the season. The selected statistics reflect on individual offensive skills regardless of the strength of the team. Even though Dinamo Zagreb dominated in the recent decade, it is pleasing to see that players come from all ten clubs of the league and the most exciting prospects are relatively underpriced.

The perspectives

The 1.HNL consists of ten teams. Just as any other leagues, it was cancelled during the global pandemic so 26 rounds were played during the season. In this timespan, altogether 33 U-23 midfielders, wingers and forwards enjoyed more than 600 minutes on the pitch. This gave enough statistical data to be able to find standout performers in Croatia. The league ranks in the middle with 2.54 when comparing major leagues and the average goals scored per game. Out of the 330 goals, 65 were scored by the previously mentioned players, an encouraging number for the future.

Finding the best young players in 1.HNL - data analysis statistics

Being creative

This analysis aims to put the statistics into perspective and find data pairings that can be combined effectively to determine the players’ individual contribution to the overall attacking performance. As football is a team sport, numbers of passes and passing accuracy in different areas should be considered as top measures to evaluate an attacking-minded player. Then we have to determine the ability to take on defenders one against one. In a podcast, Marko Cindric, head coach of Dinamo Zagreb U-9 team described how training for the youngest generation looks like. Out of four practices per week, two of them focuses solely on dribbling and individual skills. We will see how this affects the statistics.


Various passing statistics exist and sometimes it is not easy to navigate among them. When talking about their directions and their relations to the opposition, it is logical to approach them from the most likely events to the least likely one, which is the assist. In a regular game, this is the ‘evolution’ of a pass, starting from a simple one to the most meaningful assist.

Finding the best young players in 1.HNL - data analysis statistics

In the Croatian League, we examined the indicative passing stats for the young players. The category of forward passes merely suggests the direction of the ball. Meanwhile, progressive passes can be helpful to assess the direct threat of deep-lying playmakers as the ball has to travel at least 30 metres when the pass starts in the team’s own half or at least 10 metres in length in the opponent’s half to be defined as progressive. These two metrics combined could show us what to expect from the youngsters and could reveal how much they were used in the attacking movement. Through balls have to arrive behind the defensive line where the receiving player can have a scoring chance (but won’t necessarily be able to shoot). Finally, narrowing it down to the absolute, we can only determine a pass as key pass if the receiving player finished the attack with a shot of any type.

Finding the best young players in 1.HNL - data analysis statistics

Lovro Majer (8.99 progressive passes per 90 minutes, 17.81 forward passes per 90 minutes) and Nikola Moro (10.57, 18.32) featured in previous Croatian analyses as well. Both of them thrive in Dinamo Zagreb’s possession-based system in central roles. Moro is responsible for the build-up and has generally more defensive work, while Majer takes care of the offensive creativity.

The more surprising contender in the front is Kristijan Jakic from NK Lokomotiva. The 22-year-old defensive midfielder registered three assists and was crucial in the team’s passing play with 9.7 progressive passes and 19.41 forward passes on average.

Petar Bockaj (12.1, 15.37) from NK Osijek and Bruno Goda (9.38, 15.24) from Slaven Belupo both rank high on this chart due to the great number of crosses delivered which we will see later on the ‘crosses’ chart as well.

To deeper examine the players’ abilities to create scoring chances, we moved down the pyramid and considered the two leading measures: key passes and expected assists (xA) per 90 minutes. Some say key passes are overvalued statistical aspects of the game because they only show ball movement that led to a shot. Still, it is an effective way to get an overall idea of how much the player puts to the team’s offensive output.

Finding the best young players in 1.HNL - data analysis statistics

Bockaj is a clear leader in both metrics (0.35 xA and 0.9 key passes per 90 minutes) with two other NK Lokomotiva players appearing on both ends behind him. Lirim Kastrati (0.18 xA, 0.9 key passes) in the key passes while Marko Tolic (0.28 xA, 0.25 key passes) in the expected assists raises above the young group. Kastrati is on loan from Dinamo Zagreb and managed to take advantage of his spell while Tolic became a regular starter for the first time after numerous loan moves.

Amer Gojak (0,21 xA,0.49 key passes) and Luka Ivanusec (0.16 xA, 0.53  key passes) join the already talented group of Dinamo players who feature on the charts but Tonio Teklic (0.21 xA, 0.58 key passes) is slightly above them in both aspects. The Varazdin attacking player should receive attention for his season as he handed out two assists and scored a goal on just 622 minutes.


Finding the best young players in 1.HNL - data analysis statistics

The chart speaks for itself with wingers leading the way in this metric. Often crosses and their success rates alone don’t speak about the quality of those balls. To try to create a more informative picture, the six-yard box or goalie box is included since that area holds the most promising expected goals (xG) value for a striker if the ball finds him.

Bockaj with 6.95 crosses per 90 at a 40% completion rate and 0.9 crosses into the goalie box distances himself from the pack. These are prime numbers. It is advised to directly compare them but Liverpool right-back Trent Alexander-Arnold has 7.06 crosses per 90 (0.82 into the goalie box) by his name. A new name emerges as Bruno Bogojevic (3.48 crosses per 90) is trying to make a case for himself. The 20-year-old right-back from Slaven Belupo delivered the second most crosses into the six-yard box with 0.6 on average.


Finding the best young players in 1.HNL - data analysis statistics

The analysis tries to find the most creative player in the league. Progressive runs with or without dribbling is a good indicator of that. No surprise that Ivanusec (7.09 dribbles, 48% success rate, 3.2 progressive runs per 90) and Kastrati (6.82 dribbles, 45%, 3.17 progressive runs) are in the lead, both coming from Dinamo with a strong focus on individual skills. Behind them, Ivan Posavec (7.48 dribbles, 55%, 2.84 progressive runs) who returned from a short Spanish spell and now fighting for Varazdin to stay up.

As mentioned, in our case dribbling itself is less important than the number of progressive runs, therefore let’s take a look at the lower right corner. Stjepan Loncar (3.69 dribbles, 52%, 2.79 progressive runs) represents HNK Rijeka on the chart. The Bosnian international additionally scored three goals and gave four assists to his teammates this season. A little bit behind him appears the NK Osijek contingent. Both Merveil Ndockyt (4.66 dribbles, 62%, 2.18 progressive runs) and Marin Pilj (4.13 dribbles, 68%, 2.38 progressive runs) are successful dribblers who helped Osijek higher up the league with an entertaining attacking display.

Finding the best young players in 1.HNL - data analysis statistics

Bockaj dominates at this point and the only player who is close to him is Dani Olmo, the recent signing of RB Leipzig. Successful attacking actions per 90 minutes may show the player’s overall quality and technique in attack regardless of the team he plays at.


Finding the best young players in 1.HNL - data analysis statistics

Something that cannot be left out of the equation when talking about creativity is goal scoring. While not a direct metric, more touches inside the box equal more shots and technically more goals. We are helped by the size of the bubbles which represents the respective xG per 90 minutes for the player. The upper right corner consists of all the true central-forwards as well as attacking midfielders who can get in the box effectively. Indrit Tuci gets the most touches (3.71 per game) but it is Ivan Mamut who is the most prolific when it comes to chances (0.41 xG per 90) with fewer touches inside the box.

The left upper corner consists of free-kick takers or midfielders not afraid to shoot from the distance. This also comes with the negative effect that their xG is significantly lower. The lower part of the chart does not hold value, however, Posavec or Loncar gets their chances within the box.

Making case for two players

Throughout this data analysis, two relatively underrated players emerged on the charts. To visualize how they fared this season, each of their chosen statistical values is shown as the percentile rank of the league. The percentile rank of a score is the percentage of scores in its frequency distribution that are equal to or lower than it. All players who played at least 600 minutes were considered, their aggregated numbers gave the ranking. For example, Ivan Mamut’s 0.41 xG counts for the 99th percentile, everyone else is compared to him in this metric. The 1.HNL median was calculated from the players with 600 minutes this season (centre-backs and goalkeepers not included).

The first standout player is Osijek’s architect on the left, Petar Bockaj. The 23-year-old winger is often used as a left-back but here we concentrate on his attacking statistics. He added two goals and two assists to his tally this season as he played 15 games. He ranks highest in crossing metrics and the figures speak for themselves in different passing ranges and locations as well. His expected assists per 90 minutes top everyone else while his numbers combine into the best successful attacking actions rate per 90 minutes in the league.

Finding the best young players in 1.HNL - data analysis statistics

Finding the best young players in 1.HNL - data analysis statistics

Marko Tolic made sure he is recognized this year. He only needed 1134 minutes for his 8 goals achieving a strong 142 minutes per goal ratio. Moreover, there was not a single metric where he ended up below the national average in terms of dribbling, shooting or in offensive duels. Not only was he a direct threat to the goal, but he also contributed to the passing game. His numbers combined with the accuracy he delivered make him an exciting prospect. Despite his presence in the final third, he registered only one assist although his expected assists suggest there are more to come.

Finding the best young players in 1.HNL - data analysis statistics Finding the best young players in 1.HNL - data analysis statistics


In this data analysis, we managed to find hidden gems in every category as the Croatian League can always offer a secure option to European clubs when it comes to searching for talents. It has been proved many times in the past and clubs will continue their successful youth development formula. Despite the domestic dominance of Dinamo, young players from every team featured on the charts, showing how effective the Croatian system is.

To identify talents, we focused on different areas of football creativity rather than actual positions. The difference between certain passing statistics was discussed and one concept out of many on how to combine data pairs. Passing, crossing, dribbling and finishing were identified as the four basic elements of creativity which can be safely examined in analytics.

Finally, we named two players with a lot in common. Bockaj and Tolic are both 23 with their market values under 1 million euros. They both put together a strong season in the numbers and this could mean an increased enquiry for their services from outside of Croatia. As the data cannot tell everything, we will focus on these two players, providing in-depth scout reports in the next two articles.