The Numbers Game A Qualitative Study on Big Data Analytics and Performance Metrics in Sports. 11107766 Kyra Teklu Faculty of Humanities MA New Media and Digital Cultures Thesis Supervisor: Dr. N.A.J.M. van Doorn 2 Table of Contents Chapter 1. Introduction 3 Chapter 2. The Influence of Statistics 7 2.1 The Role of Quantification 7 2.2. The Role of Statistics and Metrics 10 2.3. Data and The Databases 16 Chapter 3. The Commercialisation of Sports 25 3.1. The Early Years 25 3.2. Media Rights and Sponsorship 29 3.3. Big Data shapes the Sport Industry 38 Chapter 4. Methodology 43 Chapter 5. Findings 54 5.1. The Tools 54 5.2. Player Recruitment 61 5.3 Rise in More Interesting Data 67 5.4. Unpredictability of Data 72 5.4. Economic Value 74 Chapter 6. Conclusion 78 References. 81 Chapter 7. Appendices 93 Appendix A-Examples of Metrics 93 Appendix B-Description of Participants 94 Appendix C-Participant Demographic Table 96 Appendix D-Transcripts 97 3 Chapter 1. Introduction A New Science of Winning The image you see on the first page of this thesis is a visualization of passes. This web depicts the England football teams passes during the first half of a game.1 The blue arrows indicate successful passes and their direction. Red indicates the failed attempts. Such examples of statistical visualizations focusing on performance are not uncommon nowadays, due to the advanced nature of data analytics and performance metrics within the professional sports industry. This is perhaps best indicated by the fact, today, 19 of the 20 Premier League2 3 teams use Prozone (Medeiros 2014). Prozone is a performance analytical company, which in their own words; “empower data with meaning to deliver insights that create competitive advantage on and off the field” (Prozone Sports 2016).). Prozone highlights a competitive nature that is innate in sport, whilst also alert to a gain ‘off’ the field. These gains are economic, monetary and even moral. To this end this research seeks to gauge how current uses of data in sport are impacting the sports industry as a whole, from sports management to the game itself. This research provides a theoretical perspective to quantification and how the practice of quantifying; turning qualitative differences, phenomena, into numerical information, enables measuring (Espeland and Sauder 2007). Today, society is awash in quantification and measurement, but these practices facilitate ‘ordering’ (Beer 2015), which encourages the ‘ranking’ (Guyer 2010) and ‘comparison’ of individuals (Espeland and Stevens 2008). It is through the collection of quantified information that individuals can use this information in statistical analysis (Porter 1995). The use of statistics4 is key to this research in the commercial and technological influence it is has on the sports industry. This key influence comes in the introduction of ‘metrics’. 1 On 11 October, 2013, England played a World Cup qualifier against Montenegro at Wembley Stadium, here are some insights on the game from Prozone’s analysis. 2 The Premier League is the highest English professional league for men’s association football. 3 Further to this, each club has its own team of performance analysts and data scientists looking for the indicators that quantify player performance, the events that determine matches and trends that characterize seasons (Medeiros 2014) 4 Statistics is a branch of mathematics concerned with collection, classification, analysis, and interpretation for numerical facts and for drawing inferences on the basis of their quantifiable likelihood (probability) (Business Dictionary 2016). 4 This specific enquiry looks at the role of big data and performance metrics, and how these concepts facilitate measuring, leading to a new ‘value’ of data., Rob Kitchin (2013) details that Big Data is: “huge in volume, consisting of terabytes or petabytes of data; high in velocity, being created in or near real-time; diverse in variety, being structured and unstructured in nature; exhaustive in scope, striving to capture entire populations or systems” (262). By performance metrics; I refer to ‘systems’ of measurement that sportsmen are assessed by (Beer 2015). For example, in football metrics such as ‘passing accuracy’5 and ‘player shooting accuracy’6 are common place. Fundamentally, metrics are statistical formula (Tracy 2016). The commercialisation of the sports industry will be detailed to strengthen the scope for discovering how and why data analytics7 and metrics descend from old forms of quantification and statistics. I describe the commercial development of American professional sports; baseball, basketball and American football, as the three contain rich commercial histories, and are most influential in the introduction and commercialisation of statistical analysis to sport. With a historization of the amalgamation of commerce, sports and data, I provide a framework for critiquing the impacts of big data analytics and performance metrics on the sports industry as a whole. The merger of quantification, statistics and metrics with the commercialization of the sports industry will provide a framework to answer what is really being done with data, outside of the immediately obvious: scoring a goal, or making a touchdown. Furthermore, the sport of football will be looked at closer in The Netherlands as football is often cited as the most participated and consumed sport in Europe. In the empirical study I undertake, a selection of individuals are interviewed based in The Eredivisie.8 This research focuses on the individuals who collect, analyse and organize data, as these are the data professionals in the field whom use data day-to-day in influential ways. 5 Percentage of attempted passes that successfully found a fellow teammate (WhoScored 2016) (Squawka 2016). 6 A calculation of Shots (goal attempt) on target divided by all shots (excluding blocked attempts) (Opta Sports 2016). 7 Analytics is the process of analyzing /studying information (data) (Gartner 2016) 8 The Eredivisie is the highest league of professional football in the Netherlands. 5 I undertook this research topic due to being an enthusiast of sports and career experience in the industry. However, a lack of insight into the ‘science’ behind sport led to curiosity into how this element is being used today. With a growing economic debate behind data, and with sports already a formidable economic contributor, this proved an in-depth area of study. The significance of the social aspect of sport, a nation past time that now endorses new media technologies, is intriguing, as to what extent are these technologies changing the sport sphere? In big data studies there is little focus on individual sports, industries in themselves, that use big data. Therefore, the Dutch Context in which my research focuses on football, is a comprehensive study toward the impact of big data and metrics on the sports industry. The Research Question: “What is the socio-economic impact of big data analytics and performance metrics on the sports industry?” Chapter 2 introduces a framework to the study of big data and performance analytics. The concepts of quantification, statistics and metrics provide a socio- economic approach that allows to unravel big data and performance metrics that are constituted today. Additionally, these concepts will convey the increased importance of quantification and why this led to statistics. Crucial ideas such as ‘ranking’ and ‘comparison’ will highlight the difference in uses of statistics and metrics, past and present. In terms of the present, I then align the turn to data, big data and databases to reflect a shift in technological infrastructures for measurement. I then move on to focus on the sports industry and how the latter concepts hold impetus in Chapter 3. Chapter 3 focuses on the significance of the professionalization of sports and how financial incentives; entry fees, sponsorship etc. allowed for the progression of the commercialisation of sports. Statistics has a powerful commercial role and this will be isolated in this chapter. I will depict how statistics came to be introduced into sports and how statistics thus helped commercialize sports. The shift from statistics to big data in sport is a key economical shift that will be isolated, as big data begins to shape the sports industry. Chapter 4 offers an extensive methodological framework. This chapter follows the revelations of chapter 3, in the economic significance of big data and metrics. The main research method conducted was interviews. This method allowed for an inclusive 6 understanding of how data professionals whom work in football, collect, analyse, and ultimately use data. Additionally, this chapter notes the details of my research, and the limits to my research method. Following the trail of data shaping the sports industry in Chapter 3 and the influence of the economy on sports, Chapter 5 describes the relation between contextualized literature in Chapter 1 and key concepts in Chapter 2. This chapter is devoted to discussing the results of my empirical research. Sections illustrate the main themes connected to my research question, and how these themes define a new value of data. Chapter 6 concludes my thesis by answering what is being done with data that is collected, as opposed to how teams are winning world sporting competitions with advanced statistics and metrics. These results provided an explanation and offered a critique on a new discipline of statistics, far from the days of ‘traditional’ statistical analysis, to today, where data has a different source and provenance. How this data is made valuable is key to uncovering the current foundation of the sports industry amidst analytical fruition. 7 Chapter 2. The Influence of Statistics 2.1 The Role of Quantification This chapter will introduce the subject, firstly by briefly explaining the difference between cardinal and ordinal numbers (Guyer 2014), and how the two types of number function differently. Following on from this realization I will discuss the concept of ‘quantification’, associated with the arguments of Wendy Espeland and Michael Sauder (2007).