From 02da5432d3a8d5e5e1b69bd7c24dfd95982ee3b6 Mon Sep 17 00:00:00 2001 From: CiaranFitzsimons Date: Mon, 24 Aug 2026 15:02:26 +0100 Subject: [PATCH] v1.2 including link to published static version --- text.R | 22 ++++++++++++---------- ui.R | 6 ++++-- 2 files changed, 16 insertions(+), 12 deletions(-) diff --git a/text.R b/text.R index 869d435..3799ea9 100644 --- a/text.R +++ b/text.R @@ -111,7 +111,7 @@ hidden_click_to_view_more_detailed_description_of_methodology_two <- "Multiple r hidden_click_to_view_more_detailed_description_of_methodology_three <- "Initially, full models containing all selected variables, principal components, or competitiveness indices were estimated. As a robustness check, additional regressions were then run using only statistically significant variables and those considered theoretically important. Comparing these specifications allowed both model performance and coefficient stability to be assessed. Where appropriate, results presented in this report focus on the best-performing specification, while comparisons between models are used to evaluate the robustness of the findings." #Regression on same -on_league_characteristics_and_same_season_s_european_performance_one <- "Across all three modelling approaches, a consistent theme emerges: domestic league competitiveness appears to be negatively associated with European performance. While the explanatory power of the models is relatively modest, the strongest and most consistent relationships suggest that leagues characterised by greater dominance from their leading clubs tend to perform better in European competitions. Larger performance gaps between top clubs and the rest of the league, higher goal differences among elite teams, and greater concentrations of financial resources are generally associated with stronger European outcomes. Conversely, leagues with tighter competition throughout the table, smaller points gaps, and more evenly distributed resources tend to achieve weaker European performance. Although individual variables and indices produce some mixed findings, the overall evidence points towards elite domestic dominance being more beneficial for European success than broad competitive balance." +on_league_characteristics_and_same_season_s_european_performance_one <- "Across all three modelling approaches, a consistent theme emerges: domestic league competitiveness appears to be negatively associated with European performance. While the explanatory power of the models is relatively modest, the strongest and most consistent relationships suggest that leagues characterised by greater dominance from their leading clubs tend to perform better in European competitions. Larger performance gaps between top clubs and the rest of the league, higher goal differences among elite teams, and greater concentrations of financial resources are generally associated with stronger European outcomes. Conversely, leagues with tighter competition throughout the table, smaller points gaps, and more evenly distributed resources tend to achieve weaker European performance. There is some evidence, however, that greater competitiveness outside the title race, such as smaller points gaps between European qualification and relegation positions, may be beneficial for European success. Although individual variables and indices produce some mixed findings, the overall evidence points towards elite domestic dominance being more beneficial for European success than broad competitive balance." on_league_characteristics_and_same_season_s_european_performance_two <- "The results suggest that European performance is strongest in leagues where the leading clubs are particularly dominant. Larger goal differences among the top four clubs and greater financial inequality are both positively associated with European success, indicating that strong elite clubs and concentrated resources may provide an advantage in continental competitions. Similarly, a larger gap between first and second place suggests that a less competitive title race is associated with improved European performance. However, the negative coefficient for the gap between Champions League qualification and relegation and the negative relationship with top-scorer goals indicate that some forms of competitiveness in the wider league may still be beneficial. Overall, the evidence points towards the strength and dominance of elite clubs being more important than maintaining competitive balance across the league as a whole." on_league_characteristics_and_same_season_s_european_performance_three <- "PC1, the strongest predictor, primarily captures overall league dominance and inequality, particularly through large points gaps and strong performances from top clubs. Its positive relationship with European performance reinforces the conclusion that less competitive domestic leagues tend to produce better European results. PC4, however, introduces some nuance to this finding. This component reflects greater financial equality and lower concentration among goalscorers, while also containing mixed signals regarding competitiveness across different parts of the league table. The negative coefficient for PC4 suggests that some aspects of equality and tighter competition may be associated with reduced European performance, while some tighter points gaps throughout the league may improve performance. Taken together, the PCA results broadly support the findings from the individual-variable models, although the interpretation is less direct because each component combines multiple underlying characteristics." on_league_characteristics_and_same_season_s_european_performance_four <- "The Competitive Balance Index is negatively related to European performance, suggesting that leagues with smaller points gaps, lower top-four goal differences and more evenly distributed wealth generally perform worse in European competition. This finding is supported by the Multi-Level Competitiveness Index, which focuses solely on points differences and also shows a significant negative relationship with performance. Similarly, a more competitive title race is associated with weaker European outcomes. In contrast, the Elite Dominance Index has a positive relationship with European performance, indicating that leagues characterised by dominant top clubs, greater financial concentration and stronger performances from elite teams tend to achieve greater success in Europe. Collectively, these results provide the strongest support for the idea that domestic dominance among elite clubs, rather than league-wide competitive balance, is associated with improved European performance." @@ -161,10 +161,10 @@ regression_competition_text <- list( #Clustering clustering_to_group_similar_seasons_together_one <- "K-means clustering was used as an unsupervised machine learning technique to group together seasons with similar domestic competitiveness characteristics. Unlike panel regression, it does not test the statistical significance of individual variables. Instead, it identifies whether certain combinations of league characteristics naturally appear together across seasons." clustering_to_group_similar_seasons_together_two <- "After the clusters were created, the average European performance and next-season European performance were calculated for each group. The average league characteristics within each cluster were then compared to assess whether certain competitiveness profiles were associated with stronger or weaker European outcomes. This was applied using three approaches: all individual variables, the principal components, and the theory-driven competitiveness indices. The competitiveness indices produced the clearest cluster separation, although all approaches showed broadly similar trends." -clustering_to_group_similar_seasons_together_three <- "Overall, the clustering results support the pattern found in the regression analysis. When the number of clusters was set to two, the distinction was mainly between competitive leagues, with smaller or negative values across most variables, and less competitive leagues, with larger positive values showing greater separation between clubs. The less competitive cluster consistently achieved higher European performance, both in the current season and the following season. However, the differences in average European performance between some clusters are not especially large, so these results should be interpreted as descriptive patterns rather than statistically significant evidence. The clearest exception is that the most competitive cluster is consistently associated with lower European performance, particularly in the following season." -radar_plots_for_clusters_one <- "This group performs best overall, particularly in the following European season. It is characterised by large gaps between first and second place and between first and the Champions League places, suggesting that the leading club is often clearly ahead domestically. However, the gap between Champions League qualification and relegation is relatively small, and the Gini coefficient is low. This suggests a league where the title race may be less competitive, but there is still some competitiveness across the rest of the league. This profile appears to be favourable for European performance, potentially because elite clubs are strong enough to compete in Europe while still operating in a reasonably competitive domestic environment. The clearest example is England in 2004/05, when Chelsea were runaway league winners and set a record for the fewest goals conceded in a Premier League season. Despite Chelsea's dominance, wealth distribution and the points gap between the top four and the rest of the league remained relatively balanced. English clubs also performed strongly in Europe, with Liverpool winning the Champions League and Arsenal reaching the final the following season." -radar_plots_for_clusters_two <- "This group also performs well in the current European season, although its next-season performance is weaker than the cluster above. This group shows signs of stronger elite dominance, with high top-four goal difference, high goals from top scorers, a larger gap between Champions League qualification and relegation, and the highest Gini coefficient. However, the gap between the top two sides is relatively small, reflecting a tight title battle. This suggests a league where a small number of wealthy and high-performing clubs are clearly separated from the rest. The strong current European performance supports the idea that dominant elite clubs can drive continental success, although the weaker performance in the next season suggests this advantage may be less consistent over time. Spain in 2015/16 typifies this cluster. Despite a title race in which the top three teams finished within three points of one another, Barcelona and Real Madrid recorded exceptional goal differences (83 and 76 respectively), while Luis Suárez, Cristiano Ronaldo and Lionel Messi scored a combined 101 league goals. European performance was equally impressive, with Real Madrid and Atlético Madrid contesting the Champions League final, while Sevilla won the Europa League and Villarreal reached the semi-finals." -radar_plots_for_clusters_three <- "This group performs worst in both current and next-season European performance. It has negative values across most characteristics, including smaller points gaps, lower winners' and top-four goal differences, fewer players used, fewer goals from top scorers, and lower wealth inequality. This suggests the most competitively balanced league profile, where clubs are more evenly matched throughout the table. While this may indicate a healthier domestic competitive structure, it appears to be associated with weaker European performance, supporting the wider finding that highly competitive leagues may not necessarily produce the strongest European outcomes. A clear example is the Premier League in 2015/16, when Leicester City won the league for the first time despite beginning the season as outsiders, with the lowest points tally of a winner since 2010/11. The season was characterised by relatively small gaps between clubs and a lack of sustained dominance from the traditional elite teams. English clubs subsequently performed relatively poorly in European competitions both during that season and in the following campaign, making it a strong illustration of this cluster's characteristics." +clustering_to_group_similar_seasons_together_three <- "Overall, the clustering results support the regression analysis. With two clusters, the main distinction was between more competitive leagues, characterised by smaller gaps and lower inequality, and less competitive leagues, characterised by greater separation between clubs. The less competitive cluster consistently achieved higher European performance in both the current and following season. While differences between some clusters are modest and should be interpreted descriptively, the most competitive cluster was consistently associated with weaker European performance, particularly in the following season." +radar_plots_for_clusters_one <- "This profile achieves the strongest European performance, especially in the following season. It is characterised by a dominant league winner, reflected in large gaps at the top of the table, but relatively small differences between Champions League qualification and relegation positions and lower wealth inequality. This suggests a league where the title race may be less competitive, but there is still some competitiveness across the rest of the league. This profile appears to be favourable for European performance, potentially because elite clubs are strong enough to compete in Europe while still operating in a reasonably competitive domestic environment. The clearest example is England in 2004/05, when Chelsea were runaway league winners and set a record for the fewest goals conceded in a Premier League season. Despite Chelsea's dominance, wealth distribution and the points gap between the top four and the rest of the league remained relatively balanced. English clubs also performed strongly in Europe, with Liverpool winning the Champions League and Arsenal reaching the final the following season." +radar_plots_for_clusters_two <- "This profile also performs strongly in Europe, particularly in the current season. It is characterised by high goal differences of top clubs, prolific top scorers, greater separation between elite clubs and the rest of the league, and the highest wealth inequality. However, competition for the title remains relatively close. This suggests a league where a small number of wealthy and high-performing clubs are clearly separated from the rest. The strong current European performance supports the idea that dominant elite clubs can drive continental success, although the weaker performance in the next season suggests this advantage may be less consistent over time. Spain in 2015/16 typifies this cluster. Despite a title race in which the top three teams finished within three points of one another, Barcelona and Real Madrid recorded exceptional goal differences (83 and 76 respectively), while Luis Suárez, Cristiano Ronaldo and Lionel Messi scored a combined 101 league goals. European performance was equally impressive, with Real Madrid and Atlético Madrid contesting the Champions League final, while Sevilla won the Europa League and Villarreal reached the semi-finals." +radar_plots_for_clusters_three <- "This profile records the weakest European performance in both the current and following season. It is characterised by smaller points gaps, lower goal differences, fewer goals from top scorers, and lower wealth inequality, indicating a highly balanced league. This suggests the most competitively balanced league profile, where clubs are more evenly matched throughout the table. While this may indicate a healthier domestic competitive structure, it appears to be associated with weaker European performance, supporting the wider finding that highly competitive leagues may not necessarily produce the strongest European outcomes. A clear example is the Premier League in 2015/16, when Leicester City won the league for the first time despite beginning the season as outsiders, with the lowest points tally of a winner since 2010/11. The season was characterised by relatively small gaps between clubs and a lack of sustained dominance from the traditional elite teams. English clubs subsequently performed relatively poorly in European competitions both during that season and in the following campaign, making it a strong illustration of this cluster's characteristics." radar_plots_for_clusters_overall <- "Taken together, the clustering suggests that the strongest European performance is generally found in leagues that are not fully competitive throughout, but also not necessarily dominated in every area. The best-performing profiles tend to combine some form of elite strength with either a closer gap between the Champions League places and the rest of the league, or a more competitive title race. In contrast, the most balanced leagues, where points gaps, goal differences and wealth inequality are all relatively low, tend to perform worst in Europe. This supports the broader conclusion that European success is more closely associated with the strength and dominance of leading clubs than with domestic competitive balance across the league as a whole." clustering_titles <- c( "Runaway winners with tighter competition throughout", @@ -178,11 +178,13 @@ clustering_text <- list( ) #Conclusion -overall_conclusion_one <- "Across multiple analytical approaches, the findings suggest that the domestic characteristics most closely associated with European success are generally those reflecting lower levels of competitiveness across the league as a whole. Leagues characterised by larger performance gaps, stronger top-club dominance and greater financial concentration tended to achieve higher levels of European performance than leagues where clubs were more evenly matched. However, the relationship is neither universal nor deterministic, and there is no single domestic structure that guarantees success. While competitiveness appears to be one factor associated with European performance, the relatively modest explanatory power of the models suggests that many other sporting, financial and organisational factors also play an important role. While this relationship should not be interpreted as causal, it represents a recurring pattern throughout the period analysed and offers insight into how different competitive environments may relate to success in European football." -overall_conclusion_two <- "The regression analysis found a broadly consistent relationship between European performance and measures associated with lower competitiveness, including larger points gaps, greater top-club goal differences and higher levels of wealth concentration. Conversely, variables and indices representing competitive balance, such as smaller gaps throughout the league table and more equal resource distribution, were often associated with lower European performance. These patterns were evident across the original variables, principal components and theory-driven competitiveness indices, with the latter providing the most consistent results." -overall_conclusion_three <- "An even stronger relationship was found when analysing the relationship between league characteristics and performance in the following European season. This suggests that domestic dominance may not only coincide with European success, but may also help create conditions for future performance. Leagues where top clubs are already dominant domestically may allow those clubs to build confidence, manage squads more effectively, attract and retain stronger players, and sustain performance across multiple competitions." -overall_conclusion_four <- "Analysis by competition further indicated that this relationship is primarily driven by the Champions League. While significant relationships were identified for Champions League performance, no significant relationships were found for Europa League performance. This suggests that domestic league structure has a stronger connection with performance at the highest level of European club football than in secondary competitions." -overall_conclusion_five <- "The clustering analysis reinforced these findings by grouping seasons with similar competitiveness characteristics. The most competitively balanced cluster consistently produced the weakest European performance in both the current and subsequent season. In contrast, clusters characterised by greater separation between clubs generally achieved stronger European outcomes. However, the best-performing clusters were not necessarily those displaying the greatest lack of competitiveness in every dimension. Rather, they tended to combine some degree of domestic dominance with competitiveness in specific areas of the league, such as tighter competition among elite clubs or a smaller gap between European qualification places and the rest of the table." +overall_conclusion_one <- "Across multiple analytical approaches, the findings suggest that the domestic characteristics most closely associated with European success are generally those reflecting lower levels of competitiveness across the league as a whole. Leagues characterised by larger performance gaps, stronger top-club dominance and greater financial concentration tended to achieve higher levels of European performance than leagues where clubs were more evenly matched. This aligns with theories that dominant clubs may benefit from operating in less competitive domestic environments, allowing them to accumulate greater financial resources, attract higher-quality players and devote more attention to European competition. Reduced domestic pressure may also enable elite clubs to rotate squads more effectively and prioritise continental fixtures without significantly compromising league performance." +overall_conclusion_two <- "However, the relationship is neither universal nor deterministic, and there is no single domestic structure that guarantees success. There is some evidence to suggest that a league with tighter competition beneath the dominant elite, through close points gaps from European-to-relegation places, can improve European performance. This may reflect stronger overall league quality and the benefits of clubs regularly competing in challenging domestic matches, while still allowing leading teams to retain sufficient advantages in resources and squad depth." +overall_conclusion_three <- "While competitiveness appears to be one factor associated with European performance, the relatively modest explanatory power of the models suggests that many other sporting, financial and organisational factors also play an important role. While this relationship should not be interpreted as causal, it represents a recurring pattern throughout the period analysed and offers insight into how different competitive environments may shape the balance between domestic competition and European success." +overall_conclusion_four <- "The regression analysis found a broadly consistent relationship between European performance and measures associated with lower competitiveness, including larger points gaps, greater top-club goal differences and higher levels of wealth concentration. Conversely, variables and indices representing competitive balance, such as smaller gaps throughout the league table and more equal resource distribution, were often associated with lower European performance. These patterns were evident across the original variables, principal components and theory-driven competitiveness indices, with the latter providing the most consistent results." +overall_conclusion_five <- "An even stronger relationship was found when analysing the relationship between league characteristics and performance in the following European season. This suggests that domestic dominance may not only coincide with European success, but may also help create conditions for future performance. Leagues where top clubs are already dominant domestically may allow those clubs to build confidence, manage squads more effectively, attract and retain stronger players, and sustain performance across multiple competitions." +overall_conclusion_six <- "Analysis by competition further indicated that this relationship is primarily driven by the Champions League. While significant relationships were identified for Champions League performance, no significant relationships were found for Europa League performance. This suggests that domestic league structure has a stronger connection with performance at the highest level of European club football than in secondary competitions." +overall_conclusion_seven <- "The clustering analysis reinforced these findings by grouping seasons with similar competitiveness characteristics. The most competitively balanced cluster consistently produced the weakest European performance in both the current and subsequent season. In contrast, clusters characterised by greater separation between clubs generally achieved stronger European outcomes. However, the best-performing clusters were not necessarily those displaying the greatest lack of competitiveness in every dimension. Rather, they tended to combine some degree of domestic dominance with competitiveness in specific areas of the league, such as tighter competition among elite clubs or a smaller gap between European qualification places and the rest of the table." #Limitations limitations_one <- "Some limitations should be considered when interpreting the findings of this analysis." diff --git a/ui.R b/ui.R index 22f6eb3..42f822d 100644 --- a/ui.R +++ b/ui.R @@ -50,7 +50,7 @@ ui <- fluidPage( div(id = "contents", class = "toc", tags$h1(title), - tags$a(href = "https://youtu.be/_mnsaDJzpso?si=3EnfpdRqXp4afBiI", tags$strong("Click here for a link to a static version of the report")), + tags$a(href = "https://medium.com/@ctpfitzsimons/football-competitiveness-european-performance-9cfdab897350?sk=c547cac15a5613265187f8124de37283", tags$strong("Click here for a link to a static version of the report")), p(style = 'font-weight: bold; text-align: right; font-size: 1.2em;', "Scroll to begin ▼"), tags$h3("Table of Contents"), tags$ul( @@ -578,7 +578,9 @@ ui <- fluidPage( overall_conclusion_two, overall_conclusion_three, overall_conclusion_four, - overall_conclusion_five + overall_conclusion_five, + overall_conclusion_six, + overall_conclusion_seven ), function(x) { p(