As the 2024/2025 Croatian Football League season reaches the first quarter, it's a good time to look back at how the teams have performed so far. This analysis uses data from the fbref website to explore various statistics, giving us a clearer picture of how clubs are playing in different areas of the game. We will focus on statistics based on a 90-minute performance, which will help us understand each team's attacking and defensive abilities. By looking at these numbers, we can spot trends, strengths, and areas that need improvement as the season continues. Let’s take a closer look at how the teams are doing in this early part of the season.

Graph 1. Average Points per Match - Home vs. Away

The following chart shows the average points each team in the Prva HNL earned at home compared to their away performances throughout the season. Dinamo Zagreb once again demonstrated their strength at home, with an average of 2.40 points per game, while earning a more modest 1.75 points away. Despite this difference, Dinamo remains one of the most consistent teams in the league. On the other hand, Rijeka managed to balance their home and away performances, securing 2.20 points at home and 2 points away, underscoring their solid form regardless of the venue. The biggest contrast can be seen with Hajduk, who earned an impressive 3.00 points per game at home, making them the most dominant home team. However, their away performance was significantly weaker, with just 1.5 points per game. Šibenik and Varaždin showed similar patterns, with stronger results at home while securing just 1 point per game on the road. On the other hand, Istra 1961 also displayed a significant difference between their home and away performances, with 1.75 points at home but only 0.8 points away. Gorica stood out as the team with the most struggles on the road, having failed to earn any points away from home, while averaging 1.60 points at home. Lokomotiva and Osijek had interesting trends, with Lokomotiva performing better on the road (1 point) than at home (0.80 points). Osijek, on the other hand, had relatively balanced results, with 1.20 points at home and 1 point away. Slaven Belupo, though solid at home with 1.25 points, was unable to secure any points away, which heavily impacted their overall standing.

Graph 2. Wins vs. % of Matches with Clean Sheet

Graph 2 shows the relationship between the number of victories and the percentage of matches where teams managed to keep a clean sheet, highlighting that a solid defense often forms the foundation of success in the league. One of the most striking examples is Rijeka, who, despite securing 5 victories, maintained an incredible 89% clean sheet rate. This demonstrates that Rijeka's defensive organization played a crucial role in their competitiveness. Hajduk Split and Dinamo Zagreb led the league with 6 wins each. However, while Hajduk kept a clean sheet in 44% of their matches, Dinamo recorded a slightly lower percentage of 33%. Varaždin also deserves recognition for their defensive performances, achieving a clean sheet in 67% of their games, despite having only 3 wins. This shows that with more offensive efficiency, Varaždin could potentially convert their defensive solidity into additional victories. On the other hand, teams like Osijek, Istra 1961, and Lokomotiva shared similar win totals, with 3, 3, and 2 victories respectively. However, their clean sheet percentages—22% for Osijek and Istra, and 22% for Lokomotiva—highlighted common defensive vulnerabilities, preventing them from achieving more consistent results. Šibenik, with 3 victories and a clean sheet rate of 44%, displayed a balanced approach between defense and attack, but they will need improvements in both areas if they hope to rise in the standings. At the bottom end of the table, Gorica and Slaven Belupo struggled considerably, with Gorica managing only 2 wins and Slaven Belupo securing just 1. Both teams also suffered defensively, with a clean sheet percentage of just 11%, which played a significant role in their inability to gather points.

Graph 3. Goals Scored vs. Conceded per Match

The graph above provides insight into how each HNL club performed this season in terms of goals scored and conceded. Dinamo Zagreb stands out with an impressive average of 2.22 goals scored per match, coupled with a solid defense that conceded only 1.00 goal per match. This strong performance underscores their effectiveness in both attacking and defensive phases of the game. Rijeka also displayed remarkable statistics, with a striking average of just 0.11 goals conceded per match, the best in the league. Their offensive output of 1.67 goals scored indicates a well-rounded team capable of dominating matches while maintaining defensive stability. Hajduk Split demonstrated solid form as well, scoring an average of 1.78 goals per match while conceding only 0.56. This impressive defensive record positions them as one of the top teams in the league, but there remains a slight gap in scoring compared to Dinamo and Rijeka. At the other end of the spectrum, Šibenik and Varaždin struggled offensively, averaging only 0.67 goals scored per match. Despite conceding 1.44 and 0.56 goals per match, respectively, their negative goal differential indicates a need for significant improvements in their attacking play to become more competitive. Istra 1961 faces challenges with both scoring and conceding, averaging 0.67 goals scored and 1.67 goals conceded. This negative difference highlights the necessity for enhancements in both their attack and defense. Gorica and Lokomotiva also exhibited concerning statistics, conceding 1.67 goals per match while scoring 1.00 and 0.89, respectively. Their struggles suggest a need to bolster their defensive units to prevent further damage in future matches. Osijek scored a decent 1.00 goals per match but conceded 1.33, pointing to a relatively open style of play that requires attention to defensive vulnerabilities. Lastly, Slaven Belupo averaged 0.89 goals scored while conceding 1.44, underscoring the importance of improving both their offensive output and defensive solidity.

DEFENSIVE ANALYSIS

Graph 4. Expected Goals vs. Expected Goals Against per Match

This graph illustrates the relationship between expected goals scored (XG) and expected goals conceded (XGA) per match for each team in the HNL. XG quantifies the quality of a team’s scoring chances, while XGA measures the likelihood of goals conceded based on opponent chances. Dinamo Zagreb leads the league with an average of 1.81 expected goals scored per match, showcasing their strong offensive capabilities. They also have a solid defensive record, conceding an average of 1.12 expected goals, reinforcing their status as a well-rounded team. Rijeka follows with 1.41 expected goals scored per match and a low 1.00 expected goals against. This combination highlights their ability to create scoring opportunities while maintaining a strong defense. Hajduk Split records 1.52 expected goals per match alongside 1.17 expected goals conceded. This suggests a balanced performance, though there is still room for improvement in their defensive organization. Varaždin also demonstrates effectiveness, with 1.41 expected goals scored per match and a slightly lower expected goals against at 1.09, indicating a solid attacking strategy and reasonable defensive stability. Osijek presents an interesting case, scoring 1.48 expected goals while conceding 1.44, suggesting a somewhat open playing style where they prioritize attacking but may need to tighten their defense. At the lower end, Šibenik, Gorica, and Istra 1961 face challenges, with expected goals against figures significantly higher than their expected goals scored. Šibenik registers 1.02 expected goals scored while conceding 1.74, indicating a need for improvement in both their attacking and defensive strategies.

Graph 5. Goals Conceded per Match vs. GK Save %

The following graph illustrates the correlation between the number of goals conceded per match and the goalkeeper save percentage for each team. Rijeka stands out with an impressive average of just 0.11 goals conceded per match and an outstanding save percentage of 90%. This indicates a remarkably strong defense and exceptional goalkeeping. Hajduk Split follows closely, conceding 0.56 goals per match while maintaining a solid goalkeeper save percentage of 82%. This combination highlights their effective defensive capabilities. Varaždin also concedes 0.56 goals per match, paired with a save percentage of 69%. While their defense is competitive, further improvement in save efficiency could enhance their overall performance. Dinamo Zagreb, on the other hand, allows an average of 1.00 goal per match with a goalkeeper save percentage of 63%. This shows that, despite a strong overall record, there are opportunities for enhancing their defensive solidity. Moving down the table, Osijek concedes 1.33 goals per match, along with a save percentage of 69%, indicating a need for better defensive organization. At the lower end of the rankings, Šibenik and Slaven Belupo each allow 1.44 goals per match, suggesting significant defensive vulnerabilities. Meanwhile, Istra 1961, Gorica, and Lokomotiva all concede 1.67 goals per match, emphasizing critical areas for improvement in their defensive strategies.

Graph 6. Goalkeeper Save % vs. Clean Sheet %

The next graph illustrates the correlation between the goalkeeper’s save percentage and the percentage of matches in which each team does not concede a goal. Rijeka stands out with an impressive goalkeeper save percentage of 90% alongside a remarkable clean sheet percentage of 89%. This suggests a formidable defense, indicating that not only are fewer goals conceded, but their goalkeeper is also highly effective in stopping shots. Hajduk follows closely with a solid save percentage of 82% and a clean sheet percentage of 44%. This performance reflects a strong ability to block potential goals while still allowing some to slip through. Dinamo, while slightly behind in clean sheet percentage at 33%, maintains a goalkeeper save percentage of 63%, indicating a decent level of defensive capability. In contrast, Varaždin has a save percentage of 69% and an impressive clean sheet percentage of 67%, highlighting their ability to maintain defensive stability. Šibenik records a save percentage of 69% and a clean sheet percentage of 44%, showcasing a reasonable level of defensive performance. Gorica and Lokomotiva have lower clean sheet percentages at 11% and 22%, respectively. Their goalkeepers demonstrate decent efficiency, with save percentages of 73% and 61%. This implies that while their goalkeepers can stop many shots, the teams struggle to maintain clean sheets. Osijek has a goalkeeper save percentage of 69% but also faces challenges in keeping clean sheets, achieving only 22%. Slaven Belupo, with a save percentage of 71%, has a clean sheet percentage of just 11%, indicating significant room for improvement in their defensive strategies.

Graph 7. Fouls Commited vs. Fouls Suffered per Match

This graph illustrates the relationship between the number of fouls committed and the number of fouls suffered by each team per match. Dinamo Zagreb stands out prominently in this analysis. They commit significantly fewer fouls than most teams, averaging 12.33 fouls per match, while being the most fouled team, suffering an average of 13.11 fouls per match. This contrast suggests that Dinamo not only plays with a disciplined approach but also faces aggressive tactics from opponents. Istra 1961 emerges as a team that commits the most fouls per match, averaging 16.44, while enduring a notable number of fouls suffered at 12.89. This indicates a more aggressive style of play, both in committing fouls and experiencing them. Rijeka and Lokomotiva also show significant numbers in their fouls committed, averaging 13.44 and 13.78, respectively, while suffering a similar number of fouls per match. This suggests a balanced dynamic in their gameplay, as they both engage heavily in physical contests. On the other hand, Hajduk Split, Gorica, and Osijek display a more moderate approach to fouls committed and suffered. Hajduk averages 11.56 committed fouls and 10.22 suffered, while Gorica averages 9.78 committed and 12.11 suffered. This reflects a tendency towards focusing more on maintaining possession and creating scoring opportunities rather than engaging in physical challenges.

Graph 8. Cards vs. Fouls per Match

This graph illustrates the relationship between the number of cards each team receives and the number of fouls they commit per match. Dinamo Zagreb is noteworthy for their disciplined playing style, receiving an average of 1.67 cards per match while committing 12.33 fouls. This suggests a controlled approach on the field, where they manage to maintain discipline while remaining competitive. In contrast, Istra 1961 stands out with a significantly higher average of 3.00 cards per match, which correlates with their high number of fouls committed at 16.44. This indicates a more aggressive playing style, where their intensity sometimes leads to disciplinary action from referees. Hajduk Split and Lokomotiva also show a tendency towards higher card counts, with averages of 2.56 cards and 2.56 cards per match, respectively. Their foul counts are 11.56 and 13.78, reflecting a competitive nature that can lead to disciplinary measures. Slaven Belupo emerges as another team with a high number of cards per match, averaging 2.78 alongside 14.67 fouls committed. This further emphasizes their aggressive approach on the field. Rijeka and Varaždin display moderate statistics, receiving 1.33 cards with 13.44 fouls and 1.44 cards with 11.11 fouls, respectively. Their performance suggests a balance between competitiveness and discipline. Šibenik stands out for its relatively lower disciplinary record, averaging 1.78 cards and committing 10.00 fouls per match, which indicates a more measured approach. Finally, Gorica stands out for its disciplined approach, averaging 1.78 cards and 9.78 fouls per match. This indicates a lower level of aggression in their gameplay compared to other teams.

Graph 9. Team's Shots vs. Opponent's Shots per Match

This graph illustrates the relationship between the number of shots each team takes and the number of shots they allow opponents per match. Dinamo Zagreb and Rijeka stand out prominently in this analysis. Dinamo leads the league with an average of 15.44 shots per match while allowing only 9 shots to their opponents, indicating both a proactive offensive approach and strong defensive performance. Similarly, Rijeka averages 12.89 shots taken per match and also limits opponents to 9 shots, showcasing their effectiveness at both ends of the field. Lokomotiva demonstrates a strong offensive presence with 14.33 shots per match, though they allow a significant 13.56 shots to opponents, suggesting some defensive vulnerabilities. On the other hand, Hajduk Split and Varaždin exhibit a more balanced approach. Hajduk averages 11.33 shots taken and allows 9.44 shots from opponents, while Varaždin takes 12 shots and concedes only 7, reflecting a competitive yet cautious style. Osijek maintains a respectable average of 12.56 shots while allowing 12.11 shots, suggesting a well-rounded performance in both attacking and defensive aspects. Istra 1961 shows a more moderate offensive output with 10 shots taken and allows 12 shots from opponents, indicating a focus on maintaining defensive stability while looking for offensive opportunities. Šibenik struggles with 8.22 shots taken per match while allowing a high 15.56 shots to opponents, highlighting significant areas for improvement in both offense and defense. Gorica has the lowest average of shots taken, with only 7.33 per match, while allowing 16.11 shots from opponents, indicating substantial weaknesses on both ends of the field. Finally, Slaven Belupo averages 12 shots taken and allows 12.33 shots, reflecting a need for strategic adjustments to enhance their overall competitiveness.

OFFENSIVE ANALYSIS

Graph 10. Expected Goals vs. Actual Goals per Match

In the analysis of expected goals (XG) versus actual goals scored per match, several significant trends emerge across different teams. Dinamo Zagreb leads the way, boasting an impressive average of 2.22 actual goals per match compared to their 1.81 expected goals. This highlights their effectiveness in converting opportunities into goals, reflecting a clinical approach in their attacking play. Hajduk Split also demonstrates a strong performance, scoring an average of 1.78 goals from 1.52 expected goals. Their ability to exceed expectations showcases a potent offensive capability, making them a consistent threat in front of goal. Rijeka falls into a more balanced category, with 1.41 expected goals leading to 1.67 actual goals per match. This indicates a commendable efficiency in their finishing, closely aligning with their expected performance. Osijek performs similarly, with 1.48 expected goals translating to 1.00 actual goals, suggesting a moderate efficiency but still leaving room for improvement in their goal-scoring output.In contrast, Lokomotiva exhibits a slight underperformance, scoring only 0.89 goals despite having an average of 1.52 expected goals. This indicates missed opportunities that could potentially improve their standings. Šibenik and Varaždin struggle significantly in this aspect, with both teams averaging 1.02 and 1.41 expected goals, respectively, but managing to score only 0.67 goals each. Their inability to convert chances into goals reflects ongoing challenges in their attacking strategies. Istra 1961 and Gorica present a mixed bag. While Istra's 1.12 expected goals yield only 0.67 actual goals, Gorica manages to score a mere 1.00 goal from 1.03 expected goals, indicating similar issues in finishing. Finally, Slaven Belupo shares the same fate as Lokomotiva and Istra, averaging 1.45 expected goals but only finding the back of the net 0.89 times. This highlights a clear need for improvement in their offensive execution.

Graph 11. Goals vs. Assisted Goals per Match

This graph illustrates the relationship between goals scored and assisted goals per match for different teams, providing insights into their attacking efficiency and teamwork. Dinamo Zagreb stands out as the leading team, averaging 2.22 goals per match with 1.78 assisted goals. This impressive performance highlights their strong offensive capabilities and effective collaboration in creating scoring opportunities. Rijeka follows closely, scoring an average of 1.67 goals and achieving 1.44 assisted goals per match. Their balanced approach reflects a solid attacking strategy, where players not only convert chances but also assist each other effectively. Hajduk Split also demonstrates commendable attacking prowess, with an average of 1.78 goals and 1.33 assisted goals per match. This indicates a well-functioning attack that benefits from teamwork, allowing them to capitalize on various goal-scoring opportunities. In contrast, Šibenik and Varaždin struggle significantly in their offensive outputs. Both teams average 0.67 goals per match, with Šibenik recording 0.33 assisted goals and Varaždin only 0.22 assisted goals. This suggests a need for improvement in their attacking strategies and greater collaboration among players to enhance goal-scoring potential. Istra 1961 shows an even lower performance, managing just 0.44 goals and 0.33 assisted goals per match. Their challenges in both categories underscore the urgency for strategic enhancements in their offensive play. Gorica finds a moderate balance, averaging 1.00 goal and 0.56 assisted goals per match. While they are somewhat effective in their scoring, there is room for improvement in the assistance department to further elevate their attacking game. Lokomotiva and Slaven Belupo exhibit similar trends, with both teams averaging 0.89 goals per match. Lokomotiva has 0.44 assisted goals, while Slaven Belupo tallies 0.56 assisted goals. This highlights a need for better integration and teamwork in their attacking movements to increase their effectiveness in front of goal. Lastly, Osijek averages 1.00 goal with 0.89 assisted goals per match, indicating a slightly better performance in collaboration but still suggesting areas for development. In conclusion, this analysis reveals a distinct disparity between teams that excel in scoring and assisting, such as Dinamo Zagreb and Rijeka, and those that face challenges, like Istra 1961 and Varaždin. Enhancing teamwork and refining offensive strategies will be essential for the latter teams to improve their performance in future matches.

Graph 12. Shots vs. Goals per Match

This graph provides a comprehensive comparison between the number of shots taken and the goals scored per match by various teams, offering valuable insights into their attacking efficiency. Dinamo Zagreb showcases strong performance with an impressive average of 15.44 shots per match and 2.22 goals. This highlights their attacking prowess and suggests a high conversion rate, reflecting their efficiency in front of goal. Hajduk Split presents a solid attacking front as well, with 11.33 shots and 1.78 goals per match. This indicates that they are not only generating chances but are also effective at turning those chances into goals. Rijeka continues to stand out, averaging 12.89 shots per match and scoring 1.67 goals. Their ability to maintain a high volume of shots while averaging nearly 1.7 goals per match indicates a well-rounded attacking strategy. Osijek, with 12.56 shots and 1 goal per match, shows that while they generate a decent number of chances, there is room for improvement in their finishing efficiency. On the other hand, teams like Šibenik and Varaždin struggled significantly in both categories, averaging just 8.22 shots and 0.67 goals and 12 shots with 0.67 goals, respectively. Their low goal-scoring efficiency points to potential issues in their attacking strategies and finishing abilities. Istra 1961 faced similar challenges, with a low average of 10 shots and only 0.44 goals, indicating difficulties in capitalizing on their limited opportunities. Gorica, despite a moderate number of shots at 7.33, managed to score 1 goal, suggesting a level of efficiency given their lower shot count. Lokomotiva and Slaven Belupo demonstrated varying performance levels, with 14.33 shots and 0.89 goals for Lokomotiva, and 12 shots with 0.89 goals for Slaven Belupo. This inconsistency underscores the complexities of translating shot attempts into successful goals.

Graph 13. Shots on Target vs. Goals per Match

This graph illustrates the relationship between the number of shots on target and goals scored per match for various teams, offering valuable insights into their attacking precision and efficiency. Dinamo Zagreb continues to dominate with an impressive average of 6 shots on target per match, resulting in 2.22 goals scored. This showcases their aggressive attacking approach and ability to convert chances into goals effectively. Rijeka also displayed strong performance metrics, averaging 4.22 shots on target and scoring 1.67 goals per match. This indicates a solid efficiency in their attack, as they are able to turn a significant proportion of their shots into goals. Hajduk Split recorded an average of 4.89 shots on target per match, leading to 1.78 goals scored. This reflects their capacity to create opportunities, although their conversion rate slightly trails behind that of Dinamo and Rijeka. Osijek had 3.56 shots on target and scored 1 goal per match. Despite the lower number of shots on target compared to the top teams, their ability to find the net indicates a potential for greater efficiency in their attacking play. Conversely, teams like Rudeš, Istra 1961, and Gorica faced challenges in both shots on target and goals scored. Istra 1961, for example, managed only 1.78 shots on target and 0.44 goals per match, highlighting significant areas for improvement in their attacking strategy. Lokomotiva and Slaven Belupo exhibited a similar trend, with 4.11 and 3.89 shots on target respectively, both scoring 0.89 goals per match. This suggests that while they create a reasonable number of chances, converting them into goals remains a challenge. Finally, Šibenik and Varaždin also showed low efficiency levels, with averages of 2.33 and 3.44 shots on target leading to only 0.67 goals per match each. This clearly indicates a need for both teams to enhance their attacking precision and overall effectiveness in front of goal.

CONCLUSION