Age Trends and Performance in European Football

Abstract

This analysis explores the trend of top-tier European football clubs investing heavily in young talents, such as Bellingham, Haaland, Leny Yoro and Endrick, with the hope of shaping future legends like Pelé, Ronaldinho, Figo, Cristiano Ronaldo, or Messi. The motivation behind this research is to investigate whether clubs that primarily focus on younger players achieve better performance overall. Additionally, it examines whether this approach is exclusive to wealthy clubs or if clubs with smaller budgets also adopt similar strategies. This examination provides insights into the impact of youth-centric team building on football success.

Introduction

Football clubs across Europe continue to captivate fans with their strategies, especially in the 2023-2024 season of major leagues such as the Bundesliga, Premier League, Serie A, La Liga, and Ligue 1. Among these strategies, a growing focus on young talent raises intriguing questions about performance and team-building approaches. Players like Bellingham, Haaland, Leny Yoro and Endrick symbolize this trend, representing investments in future potential over proven experience.

Understanding whether clubs where young players play a vital role in their rotation achieve better results could reshape how teams approach transfers and squad development. Moreover, examining these leagues highlights whether this trend is confined to financially dominant clubs or if smaller teams also adopt similar practices. This analysis sheds light on how youth-oriented strategies influence football’s competitive landscape, offering valuable insights into the evolving dynamics of the sport.

Data & Methodology

The data for this analysis was sourced from fbref.com, a comprehensive platform offering detailed information on team performances and individual player statistics. This dataset is highly meaningful as it provides reliable and structured insights into key metrics, allowing for an in-depth examination of age-related trends and their impact on team performance.

Minimal data preparation was required, as the dataset was clean and well-structured. However, minor adjustments were made, such as standardizing player and team names by removing formatting inconsistencies. We primarily employed statistical techniques to examine metrics such as the distribution of team and player ages. Specifically, we analyzed how these values fell within the range of -1 to +1 standard deviations.

These methods were chosen for their simplicity and effectiveness, enabling clear identification of trends and patterns that reveal the role of youth-centric strategies in football.

Results

Age Diversity Across Europe’s Top Football Leagues

Figure 1 illustrates the distribution of squad ages across the top five European football leagues: Premier League, La Liga, Ligue 1, Bundesliga, and Serie A. Using box plots, it shows the range, median, and interquartile range of team ages in each league, with red markers indicating the mean age. This visualization highlights how team compositions vary in terms of player age across the leagues. For example, La Liga exhibits the widest range of ages, suggesting diverse team structures, while the Premier League and Serie A shows a more compact distribution, indicating less variation in team age.

La Liga stands out with the oldest teams on average, aligning with the league’s less physically intense and more technical, possession-based style of play. In contrast, Ligue 1 features the youngest teams among Europe’s top leagues, a surprising insight given its competitive nature and the physical demands often associated with French football.

The results are particularly intriguing as they show structural differences across leagues, which might reflect varying recruitment strategies, playing styles, or league requirements. For instance, the broader age range in La Liga may suggest a mix of experienced and younger players, while the Premier League and Ligue 1 seem more consistent in their age profiles. These differences could potentially influence league dynamics and team performance.

Figure 2 shows the relationship between team average ages and the points they earned during the 2023-2024 season, grouped by league. The x-axis represents the average age of the teams, and the y-axis shows the points they accumulated, with leagues differentiated by color. The graph reveals no clear pattern suggesting that younger or older teams consistently achieve higher points. Notable outliers include Inter Milan, with an average age of over 29 years, and PSG, which stands out as one of the youngest teams in terms of average age.

The Influence of Squad Age on Team Performance

The results are intriguing because they challenge common assumptions about the impact of age on team performance. Inter Milan’s older age profile may reflect valuable experience but raises sustainability concerns for the coming years. On the other hand, PSG’s investment in young talent might promise a strong future but could explain their struggles in high-stakes competitions like the Champions League, where experience plays a crucial role. While the graph highlights key trends, it does not account for external factors such as squad depth, injuries, or tactical strategies, which could also significantly influence team success.

Goal Distribution in La Liga

Figure 3 illustrates the goal distribution among players in La Liga during the 2023-2024 season. The x-axis shows the number of goals scored, while the y-axis represents the number of players achieving those totals. Key thresholds like the mean (1.60 goals), one standard deviation (4.73 goals), and two standard deviations (7.86 goals) are marked. Notable players include young players like Samu Omorodion, Fermin Lopez, Savio, and Jude Bellingham, as well as seasoned veterans like Robert Lewandowski, Ante Budimir, and Iago Aspas, all of whom scored beyond two standard deviations from the mean. Lewandowski’s exceptional performance even places him third place in the scorer list.

This result highlights the diverse talent in La Liga. Rising stars like Bellingham and Lopez have already made significant impacts at elite clubs like Real Madrid and Barcelona, while players such as Savinho moved to Manchester City. These transitions reflect their growing potential and the trust clubs place in young talent. Meanwhile, experienced players like Lewandowski, Aspas and Budimir continue to deliver peak performances, showcasing their enduring skill and importance in the league. This interplay between youth and experience makes La Liga’s goal distribution particularly fascinating.

Age and Goal-Scoring Efficiency

Figure 4 illustrates the relationship between age and goal-scoring efficiency (measured as goals per minute played) among players in the top five European leagues who scored at least 7 goals during the season. The x-axis represents the players’ ages, while the y-axis shows their goals-per-minute ratio. Key thresholds, such as the mean age (25.61 years), one standard deviation (29.82 years), and two standard deviations (34.37 years), are indicated with vertical dashed lines for context.

The scatter plot highlights that consistent top scorers are predominantly within the typical age range of 21 to 29 years, aligning with the expected prime years for professional footballers. Interestingly, there is no evident correlation suggesting that younger players outperform older ones in terms of scoring efficiency. Instead, the data reinforces the notion that players across this standard age range maintain high levels of performance.

This analysis emphasizes the importance of maturity and experience in achieving consistent goal-scoring efficiency, while also dispelling any bias towards assuming younger players are inherently more prolific scorers.

Conclusion

The analysis reveals that teams with a mix of young talents and experienced players tend to perform better overall. Notable results include Ligue 1 having the youngest teams, La Liga hosting the oldest, and leagues like the Premier League and Serie A featuring teams with more balanced age ranges. A future exploration could examine how older teams perform over the current or upcoming season. For instance, Manchester City, with one of the relatively older squads in the Premier League, has faced numerous injuries, raising the question of whether such challenges are more common among older teams or players.

Data source: www.fbref.com

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