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"Soccer -- Management -- Europe"
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Who owns football? : the governance and management of the club game worldwide
\"The commercialisation of football in Europe since the 1990s has had a number of consequences for the game, not all of them beneficial to its wellbeing. The market forces that have defined these developments have impacted upon the financial future of clubs as key social and cultural institutions and some continue to see their existence threatened. The inevitable result is enforced sale of club assets for commercial development; their relocation to towns and cities many miles from their original locale, or the acquisition of clubs by individuals of whose motives many fans are rightly suspicious. In recent years one of the most high profile responses to these developments has been for groups of supporters to join together and purchase ownership of part of the club, or in some cases the entire club, to run it on a non-commercial basis. It mimics the successful membership model deployed by FC Barcelona and upon which entire organisations, like the Gaelic Athletic Association (GAA) has successfully existed for 125 years. This book will explore the background to this movement and its practical outworking by providing individual case studies from several European countries. This book was published as a special issue of Soccer and Society. \" --rear cover.
Book
The Organisation and Governance of Top Football Across Europe
This book aims to provide an extensive overview of how football is organized and managed on a European level and in individual European countries, and to account for the evolution of the national, international and transnational management of football over the last decades.
eBook
The organisation and governance of top football across Europe : an institutional perspective
This title aims to provide an extensive overview of how football is organized and managed on a European level and in individual European countries, and to account for the evolution of the national, international and transnational management of football over the last decades.
Book
Data-driven understanding on soccer team tactics and ranking trends: Elo rating-based trends on European soccer leagues
In modern soccer, strategy and tactics significantly impact team success. In this study, the application of these methodologies within the domain of association soccer is examined, with a particular focus on predicting team strategies via team trend analysis. Using a dataset comprising matches from the top five European soccer leagues, we analyzed team performance trends over time using the Elo rating system and rolling regression. Predicting strategies from soccer match datasets is a challenging. In our study, we propose methods based on count and rank to address these challenges. For the count-based method, the number of forwards, midfielders, and defenders is used to calculate respective defense and attack scores. For the rank-based method, teams are classified into various levels based on their rankings, and strategies are evaluated accordingly. This approach provides a more detailed perspective on strategic tendencies by considering team composition and performance at each level. Experimental results demonstrate the potential of our proposed methods to accurately identify and predict team strategies, offering significant implications for tactical decision-making in professional soccer. The findings indicate that the accuracy of predicting defensive strategies using count-based predictions was approximately 85%, while the performance of predicting aggressive strategies through rank-based predictions was 89%. Our methodology can be extended to the development of a predictive model aimed at forecasting team strategies, thereby assisting coaches with more effective preparation for upcoming matches.
Journal Article
Multicultural teams: Does national diversity associate with performance in professional soccer?
This study examines whether the national diversity of players in multicultural teams affects the performance of professional soccer clubs. I analyze data from the top-tier leagues of six European countries – England, Belgium, Germany, Cyprus, Latvia, and the Netherlands – covering the 2015/2016–2020/2021 seasons. These leagues were selected because they impose no limits on the number of foreign players in senior squads, providing a clear view of this phenomenon. Using Ordinary Least Squares (OLS) estimations in a forward stepwise approach, I find that national diversity does not correlate with club performance. However, the total number of foreign players is positively associated with performance, with each additional foreign player correlating with a 0.42% increase in win percentage. Moreover, the most complete model also indicates that an additional domestic league title is associated with a 0.99% increase in win percentage per title, while participation in the UEFA Champions League is associated with a 13.6% higher win percentage. Future research should explore the causal mechanisms underlying this relationship, examining how specific attributes of foreign players, such as playing style and experience, contribute to performance. Additionally, studies could investigate how management practices, particularly the adaptation of foreign players to a new country and culture, influence their impact on club success.
Journal Article
Expectations as Reference Points: Field Evidence from Professional Soccer
We show that professional soccer players and their coaches exhibit reference-dependent behavior during matches. Controlling for the state of the match and for unobserved heterogeneity, we show on a minute-by-minute basis that players breach the rules of the game, measured by the referee’s assignment of cards, significantly more often if their teams are behind the expected match outcome, measured by preplay betting odds of large professional bookmakers. We further show that coaches implement significantly more offensive substitutions if their teams are behind expectations. Both types of behaviors impair the expected ultimate match outcome of the team, which shows that our findings do not simply reflect fully rational responses to reference-dependent incentive schemes of favorite teams to falling behind. We derive these results in a data set that contains more than 8,200 matches from 12 seasons of the German Bundesliga and 12 seasons of the English Premier League.
This paper was accepted by Uri Gneezy, behavioral economics.
Journal Article
Why do football clubs fail financially? A financial distress prediction model for European professional football industry
The study of financial distress has been the focus of financial research in recent decades and has led to the development of models for predicting financial distress that help assess the financial situation and the risks faced by companies. These models have focused exclusively on industrial and financial companies. However, a specific model that reflects the special characteristics of the football industry has not yet been created. Since recently the governing bodies of the football industry have increased the financial control of the clubs, as in the case of UEFA with the approval of the Financial Fair Play Regulation and demand a pronouncement on going concern in the annual financial statements of clubs as well as presenting a break-even deficit caused by losses, it seems necessary to have a model adapted to the characteristics of this industry. The present study provides a new model of prediction of financial distress for the football industry with an accuracy that exceeds 90%. It also offers a vision of the challenges facing the football industry in financial matters, helping the different interest groups to assess the financial solvency expectations of the clubs.
Journal Article
Beyond xG: A Dual Prediction Model for Analyzing Player Performance Through Expected and Actual Goals in European Soccer Leagues
Soccer is evolving into a science rather than just a sport, driven by intense competition between professional teams. This transformation requires efforts beyond physical training, including strategic planning, data analysis, and advanced metrics. Coaches and teams increasingly use sophisticated methods and data-driven insights to enhance decision-making. Analyzing team performance is crucial to prepare players and coaches, enabling targeted training and strategic adjustments. Expected goals (xG) analysis plays a key role in assessing team and individual player performance, providing nuanced insights into on-field actions and opportunities. This approach allows coaches to optimize tactics and lineup choices beyond traditional scorelines. However, relying solely on xG might not provide a full picture of player performance, as a higher xG does not always translate into more goals due to the intricacies and variabilities of in-game situations. This paper seeks to refine performance assessments by incorporating predictions for both expected goals (xG) and actual goals (aG). Using this new model, we consider a wider variety of factors to provide a more comprehensive evaluation of players and teams. Another major focus of our study is to present a method for selecting and categorizing players based on their predicted xG and aG performance. Additionally, this paper discusses expected goals and actual goals for each individual game; consequently, we use expected goals per game (xGg) and actual goals per game (aGg) to reflect them. Moreover, we employ regression machine learning models, particularly ridge regression, which demonstrates strong performance in forecasting xGg and aGg, outperforming other models in our comparative assessment. Ridge regression’s ability to handle overlapping and correlated variables makes it an ideal choice for our analysis. This approach improves prediction accuracy and provides actionable insights for coaches and analysts to optimize team performance. By using constructed features from various methods in the dataset, we improve our model’s performance by as much as 12%. These features offer a more detailed understanding of player performance in specific leagues and roles, improving the model’s accuracy from 83% to nearly 95%, as indicated by the R-squared metric. Furthermore, our research introduces a player selection methodology based on their predicted xG and aG, as determined by our proposed model. According to our model’s classification, we categorize top players into two groups: efficient scorers and consistent performers. These precise forecasts can guide strategic decisions, player selection, and training approaches, ultimately enhancing team performance and success.
Journal Article
Entrepreneurial orientation in sports entrepreneurship - a mixed methods analysis of professional soccer clubs in the German-speaking countries
In recent years, sports entrepreneurship has emerged as a promising discipline in the field of sports management research. However, the research field is still fragmented. This study gives an overview of sports entrepreneurship and coopetition research and is the first work analyzing EO and performance in professional sports. First, quantitative results about EO, organizational performance and coopetition of 22 professional soccer clubs were obtained. Following the mixed method approach, the data was then extended by qualitative expert interviews. Entrepreneurial orientation had a significant positive relationship with both financial and sporting performance of professional soccer clubs in German-speaking countries during the 2017/18 season. We suggest coopetition as a promising strategy for professional soccer clubs to succeed. Hence, our study fosters the concept of sports entrepreneurship and offers evidence that entrepreneurial orientation is a well-suited managerial approach to enhance organizational performance in professional soccer.
Journal Article
Bibliometric indices as a measure of performance and competitive balance in the knockout stage of the UEFA Champions League
We argue for the application of bibliometric indices to quantify the long-term uncertainty of outcome in sports. The Euclidean index is proposed to reward quality over quantity, while the rectangle index can be an appropriate measure of core performance. Their differences are highlighted through an axiomatic analysis and several examples. Our approach also requires a weighting scheme to compare different achievements. The methodology is illustrated by studying the knockout stage of the UEFA Champions League in the 20 seasons played between 2003 and 2023: club and country performances as well as three types of competitive balance are considered. Measuring competition at the level of national associations is a novelty. All results are remarkably robust concerning the bibliometric index and the assigned weights. Since the performances of national associations are more stable than the results of individual clubs, it would be better to build the seeding in the UEFA Champions League group stage upon association coefficients adjusted for league finishing positions rather than club coefficients.
Journal Article