Search results

This chapter will develop an understanding of what the logical conclusion of having English football clubs primarily existing as businesses: namely, those instances where clubs are treated not as community institutions but as any other business with set assets that can be disposed of at a profit. There is an unfortunate history of clubs being owned based on the value of the assets they possess (such as their stadium or training), a trend that has only seemed to accelerate in recent decades. The various forms asset stripping takes can be explored by examining what happened to clubs like Blackpool FC and Wimbledon FC, as well as many others. This chapter is an exploration of what happens when the entity that fans assume is something more than a business is dismantled for profit, the harshest of reality checks, and a reminder that football clubs in these contexts are little more than business assets.

This research aimed to measure the influence of resource dependency (trading and/or shareholder's dependencies) squad age structure by building archetypes to identify strategic dominant schemes.

Based on the Ligue 1 football clubs from the 2009/2010 season to the 2018/2019 data, the authors use the k-means classification to build archetypes of resource dependency and squad structure variables. The influence of resource dependency on squad structure is then analysed through a table of contingency.

Firstly, the authors identify archetypes of resource dependency with some clubs that are dependent on the transfer market and others that do not count on sales to balance their account. Secondly, they provide different archetypes of squad structure choices. The contingency between those archetypes allows to identify three main strategic schemes (avoidance, shaping and adaptation).

The research tests an original relationship between resource dependency of clubs and their human resource strategy to respond to it. This paper can help to provide detailed profiles for big clubs looking for affiliate clubs to know which clubs have efficient academy or player development capacities.

Moving away from the stories of financial disaster we encountered in Chapter 2, Chapter 3 examines what it means for fans when their club is suddenly awash with more financial muscle than some nation-states due to the generosity of a wealthy benefactor who is seemingly more interested in sporting glory than in financial gain. This chapter engages with the notion of the football club as a billionaire’s plaything. Roman Abramovich’s acquisition of Chelsea in 2003 saw the West London club embark on an eye-watering spending spree and a sustained period of on-field successes, one that was unknown in the club’s history to that point. As a result, we take Chelsea during the Abramovich era as a starting point for considering how this model of ownership affects the relationship between fans and the connection that they have with their club. The evident success that financial muscle can bring shows owners what a happy fanbase is capable of, what they are capable of doing, and what they are capable of ignoring. The success of the financially doped teams of the 2000s created a precedent for winning over a fanbase with a successful football club, but nevertheless sat awkwardly with the normative ideals of how a football club should exist in the world and relate to its supporters.

This chapter builds upon the analysis of the last chapter, as fans have to deal with the issues that arise from their team’s financial superiority. Here, we question what happens when that financial superiority is accompanied by significant moral and ethical issues. Recent involvement of state actors in the ownership of English football has been evidencable and occasionally appears clear. Various reflexes and cognitive distancing occur from fandoms when football club ownership engages in practices that, according to the normative models that fans ascribe to their clubs, are mutually exclusive with the values of the fanbase and the club’s history. A common form of fan reflex often takes the form of distancing the players on the pitch from the club’s institutional structures, effectively teasing out the matchday experience from the structures that benefit from the raw emotion it generates. Another reflex is questioning why the fan should surrender their club when a morally, ethically problematic ownership model has acquired it. Here we have perhaps the greatest challenge to the normative model and, rather than negotiating that tension, as often as not the response is to try and ignore it.

In recent years, the relationship between Manchester United fans and their club has been put under the spotlight due to the contentious relationship between the fanbase and the club’s American owners, the Glazer family. However, the commercialisation of Manchester United and their ramping up of their associated brand accelerated massively during the 1990s, as a result of the coincident timing of the country’s glamour club returning to dominance during a period of ever-greater financial returns for top-flight success. As the undoubted commercial trailblazers in English football (and the first English club to be listed on the Stock Exchange), analysing their development during the 1990s is, arguably, the best way of understanding how and why top-flight football clubs operate the way they do and, in a knock-on effect on the league’s competitiveness, why the clubs below them can so easily fall away.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

This introduction provides the methodological framework for the book, approaching the business of football through the lens of its most reliable consumers – the fanbase. Fan cultures necessarily inform the normative understanding of a football club, due to the popularly held belief that it is the fan’s – or some reified idea of the fan – that is the permanent feature of a football club and that provides its identity. Players and owners come and go, but the relationship between the club and the fan is, theoretically, never-ending. In truth, this is never a real fan who could exist, but a constructed image of the fan built out of other narratives and that, at some level, football fans associate themselves. This fan is no one in particular, but is drawn from a close reading of football culture and identifying the directives of the traditional fan. Utilising a combination of critical theory and the existing literature on football club ownership, our goal is to reveal the distinction between how people talk about the social dimension of football clubs, and how they actually relate to their fans and the wider world in the era of late capitalism. A club is not simply the romanticised notions held by those within the games, but, as with all businesses, it is also the product of it conducts itself in a series of other networks of exchange. Often irreconcilable with the aforementioned romantic notions, these networks often get hidden by the prevailing discourse.

Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.

Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.

The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.

Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.

Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.

Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.

The purpose of this research is to explore how one unsanctioned community sport organization (CSO), AM Hockey, sought to acquire legitimacy in a highly institutionalized minor hockey marketplace at various points in its organizational life cycle.

This study was guided by instrumental case study methodology. Twenty (20) AM Hockey stakeholders from a variety of roles (e.g. executives, program directors and coaches) were interviewed. Document analysis was also utilized to supplement the interviewees. Internal and public documents reflective of the CSO's creation and growth were obtained.

Findings revealed that the CSO had to navigate distinct phases of evolution including the Building, Growth, Competition and Stabilization phases. Although the four life cycle phases identified in this study share similarities with the phases identified by Lester et al. (2003), findings indicated that institutional work mechanisms must be understood in their context as they can vary over the life cycle of an organization. Therefore, start-up sports organizations must approach the pursuit of legitimacy as a continual process rather than something acquired and defended through maintenance work.

Developing legitimacy remains a central challenge for CSOs that seek to deliver alternative sport programming, yet it continues to be understudied. Ultimately, the long-term viability of an unsanctioned CSO in a federated sports system relies, in part, on its ability to continually determine the actions needed to achieve legitimacy within its environment.

Professional sports teams employ highly paid managers and coaches to train players and make tactical and strategic team decisions. A large literature analyzes the impact of manager decisions on team outcomes. Empirical analysis of manager decisions requires a quantifiable proxy variable for manager decisions. Previous research focused on manager dismissals, tenure on teams, the number of substitutions made in games or the number of healthy players on rosters held out of games for rest, generally finding small positive impacts of manager decisions on team success.

The authors quantify manager decisions by developing a novel measure of game-specific coaching decisions: the Herfindahl–Hirschman Index (HHI) of playing-time across players on a team roster over the course of a season.

Evidence from two-way fixed effects regression models explaining observed variation in National Basketball Association team winning percentage over the 1999–2000 to 2018–2019 seasons show a significant association between managers’ allocation of playing time and team success. A one standard deviation change in playing-time HHI that reflects a flattened distribution of player talent is associated with between one and two additional wins per season, holding the talent of players on the team roster constant. Heterogeneity exists in the impact across teams with different player talent.

This is one of the first papers to examine playing-time concentration in the NBA. The results are important for understanding how managerial decisions about resource allocation lead to sustained competitive advantage. Linking coaching decisions to wins can help teams to better promote this core product.