Overview of the respondents from focus group 1.
Contemporary professional football (and sports) entities have embraced technology and data to boost sporting quality. However, this development has gone beyond the playing field as technology and data also start to play a larger role in improving business performances in the football (sports) industry. This chapter looks into how technology and data in the form of sports tracking systems, cf. based on (but not totally limited to) the case of the ZXY sports tracking system, are capable of helping to translate improved sporting performances into enhanced business performances. The intensified commercialization in football from technology and data takes fandom to new heights and bring about new revenue generating opportunities. However, harnessing the increased amounts of data is associated with technical challenges and financial and human resource constraints. In some instances, the context of applying ‘big data’ in football is still premature. Therefore, the technology and data implementation in professional football needs to undergo a qualification process to secure that the applied data co-exists with a context of competent knowledge-sharing, individual and organizational learning in order to positively develop sporting and business performances.
- big data
- sporting performance
- business of sports
- sport experiences
Sports technology and sports data have become integral parts of sports development and performances [1–4]. As seen in relation to how technology and data play a role in improving player development and sporting performances, the business side of sports has also embraced the upsides of technology and data analytics . The purpose of this research is to study the application of sports technology and sports data from the ‘sporting side of sports’, e.g., data from sports tracking systems. In doing so, focus is primarily on football (soccer in the US) but the study also integrates relevant perspectives from this context associated with other sports. In addition to ‘the sport of sports’, the study discusses how sports technology and sports data act as a commercial vehicle, which can guide and drive content production for a sports property’s commercial stakeholders in the ‘business side of sports’, e.g., fans, sponsors and the media.
This chapter is based on case study methodology [6–11], in which the case of the ZXY sports tracking system is the focal point. The chapter also includes data regarding other tracking systems than ZXY for a broader discussion and understanding of the context of sports tracking and how that influences sports, e.g., sporting and business aspects. The chapter involves critical methodological reflections and takes the commercialization and professionalization of the football economy into consideration as vital contextual factors, i.e., incorporating the application of technology and data in relation to sporting performance as well as business performance in professional football (sports). The case study applies an in-depth qualitative approach, which encompasses the dynamic context in which sporting actions and experiences take place . Hence, research cannot be isolated from time and context . The relevance of the case study is grounded in the methodology and its qualitative nature, i.e., based on two semi-structured focus groups and one semi-structured face-to-face interview. The qualitative foundation bridges a knowledge gap in sport management research as this case study goes beyond the explanation of statistics to investigate and understand a dynamic sports context at a time where technology and data are on the rise.
2.1. Case description
The ZXY sports tracking system was originally developed in Norway by ZXY Sport Tracking AS. The system went through a development process in collaboration with Norwegian Olympic Sport, the Norwegian top football club Rosenborg Ballklub and Radionor Communications. The method to develop the data measurement has its roots in technology linked to military radio signals . The first generation of the system was released in 2007 and tested by the collaborative partners. The second generation of the system saw its release in 2012 in relation to a project with the Dutch football powerhouse Ajax Amsterdam. In 2014, the Danish top club FC Midtjylland, which is known around the international football landscape for its strategic data analytics approach [15, 16], invested highly in the ZXY system in order to enhance its sporting decision-making processes  and thus to elevate the quality of the club’s cohesion between sporting and business performances.
In 2014, the American corporation ChyronHego bought ZXY. ChyronHego works on a global scale on broadcast graphics creation, playout and real-time data visualization  and found increased opportunities to develop a stronger and more applicable product by combining ZXY’s very precise1 sets of data with ChyronHego’s existing tracking system Tracab. The latter already functioned as an established part of many football clubs and leagues. In practice, the ZXY solution works by players carrying a belt around their waistline, e.g., incorporated in their shorts. The belt is ultra-light to show regard to the players’ functionality. The system incorporated in the belt sends data to the radio receivers, which are installed in the venue or at the training facility (as the system is functional for game as well as training situations). The quality of the data transmission is enhanced by the fact that data transmission takes place 20 times per second2. The data pool becomes available through the operation of ZXY’s software, which is accessible via an online web site or an app designed specifically to process and present the data (Photo 1).
The user experience is adaptable by allowing physical trainers or other specialist staff at clubs, leagues and federations to determine what to measure and how to apply and present the measurements. Additionally, the system is able to incorporate the use of video cameras to increase the focus on players. Personalized video measurements provide data synchronized in time from body sensors combined with position sensors in the venue or at the training facility. The following are examples of data provided (Figure 1):
Positional updates at least 20 times per second (=20 Hz).
Distance in relation to different types of movement, e.g., jogging, ordinary running, high intensity running, or sprinting.
Acceleration vs. deceleration.
Performance index, e.g., total vs. under acceleration or deceleration.
Frequency of steps.
Speed of turning.
What direction does the player face (e.g., heading).
Run characteristics (offensive or defensive).
Figure 2 below illustrates the added value and functionality from combining Tracab’s position sensor system and ZXY’s body sensor system. The combination of the two technologies helps to automate Tracab as the ZXY system constantly and precisely knows the position of the player on the playing field.
2.2. Research design and data collection
A qualitative methodology was selected as the most applicable practice to explore the experiences and understanding of the meaning related to technology and data in sport [20, 21]. The chosen data collection method is ‘interviewing’ in the form of two semi-structured focus groups and one semi-structured face-to-face interview.
In validating the results of the interviews, it is essential to critically reflect over the fact that it may be challenging to ‘generalize’ the findings of a case study in a larger sport management context . Nevertheless, the purposively selected sampling process [23, 24] in this instrumental case study3 is chosen to enhance the context-specific validity of the findings and thus to expand the interest for and application of the results within the context of technology and data in sports beyond the case of ZXY. However, the intention of this research is to emphasize a paradigm shift in research methodology, which stresses the shift from ‘generalization’ to ‘contextualization’ under the premises that knowledge is heterogeneous and contextual rather than universal or individually unique . Therefore, the metatheoretical nature of this research takes a stance associated with scientific traditions from pragmatism  and symbolic interactionism [26, 27] to explore the experiences, thoughts and meanings of the respondents regarding the application of technology and data in a context of sports and in particular football. The purposive selection of respondents is influenced by the reasoning that these respondents have complementary competences while possessing relevant and applicable contextual, professional and/or educational experience from the football industry.
The respondents from focus group 1 are listed below (anonymous) in Table 1.
|Gender of respondent||Occupation of respondent|
|Respondent 1a: Male||Marketing Manager, professional football club with domestic championship and FA Cup titles, including participation in UEFA Champions League and UEFA Europa League competitions|
|Respondent 1b: Male||CEO, sponsorship agency|
|Respondent 1c: Male||Venue Data Coordinator, UEFA|
|Respondent 1d: Female||Commercial Director, national football association|
|Respondent 1e: Male||CEO & Founder, betting company and football media platforms|
The respondents from focus group 2 are listed below (anonymous) in Table 2.
|Gender of respondent||Occupation of respondent|
|Respondent 2a: Male||Digital Manager, professional football league|
|Respondent 2b: Male||Lawyer & Head of Research, fantasy sports platform|
|Respondent 2c: Male||Partner, sports marketing, branding and communication agency|
|Respondent 2d: Male||Sociologist, university and IT sector|
|Respondent 2e: Male||Digital Manager, national football association|
|Respondent 2f: Male||CEO, investment company|
The respondent from the semi-structured face-to-face interview is listed below (not anonymous) in Table 3.
|Name and gender of respondent||Occupation of respondent|
|William Spearman, Male||Currently the Lead Data Scientist, Liverpool FC and former occupation as Senior Data Scientist, Hudl (a technology and data company specialized in sports performance analysis in sport). Spearman specializes in using tracking data in football to understand passing, open space and scoring opportunities.|
After completing a Ph.D. from Harvard University in physics and inspired by working with tracking data from the English Premier League, Spearman developed a pitch control model, which was presented at the 2016 Opta Pro Forum.
The qualitative design of this research provides insights from experienced industry professionals in the form of their experiences from utilizing technology and data to improve sporting performances and to enhance commercialization in football. This supports the chapter’s production of relevant meaning and realm of understanding in order to inductively construct new suggestions for how to advance and boost the application of technology and data in the form of sports tracking to improve sporting and business performance in football. So, the aim is to let the data speak for themselves, but to do so while systematically, critically and contextually analyzing and interpreting the data. Grounded theory and qualitative open coding are used to analyze the transcribed interview data based on analysis, study, comparison, conceptualization, and categorization of the data [22, 28]. The two focus group interviews were completed in the same venue to accommodate a constructive interaction between all respondents, which is significant for new idea generation and to illustrate meanings and experiences of respondents. The interpretivist research paradigm emphasizes the importance that the coding and data analysis is grounded in context-relevant literature, theories, knowledge and professional experiences and competences. The intent is to create a knowledge-producing process associated with the capability to contextualize and recontextualize a context of technology and data application concerning sporting and business performance improvements in professional football (and other sports). In that regard, the chapter’s discussions are influenced and guided by the methodological stance and the empirical data. Therefore, the discussions are not covering the application of technology and data from a holistic angle; this is a reflection of the fact that many different metrics drive decision-making in football. For instance, there is a difference between the tradeoff between a risky pass versus the consequences of losing possession versus the potential benefit of a scoring chance that may be created just to mention a few focal points from decision- makers in the world of football. The point in this chapter is to illustrate that the use of technology and data may improve on-field performance assessment in football (and sports) and this may also have positive spill-over effects on the sport organization’s business performance.
3. Setting the stage: connecting sport, business, data and technology
Today, professional sports are characterized by the search for new paths concerning how an athlete or a team may apply new technologies and sports performance data to gain the cutting-edge competitive ability that will elevate them to the top of the podium or to win major league or championship titles [29–31]. Therefore, professional sports properties are left with massive data pools that (without giving away competitive sporting advantages) can be utilized to assist athletes and teams in monetizing on their relationships with commercial stakeholders. In reflections over why the application of technology and data is important in sports, there are clear benefits in terms of optimizing decision-making processes on and off the playing field and thus sporting quality. William Spearman notes that
There is no doubt that the application of technology and data is beneficial in professional sports. Kerr and Gladden  argue that connected technological environments to some extent provide an open-source approach for sports teams to interact with their stakeholders. For instance, this may take place via mobile apps of the teams as suggested by Watkins and Lewis . Reasons to go in that direction are clear. One practical example is the current Danish football champions FC Midtjylland that invested in an app solution in 2017 to boost engagement with fans. The idea was to bring fans closer to the club and to produce good fan experiences by providing fans with exclusive news and better insights about the players and their performances. The financial situation of professional sports teams is boosted by good sporting performances. Better sporting performances may be supported by technology and data and can help to enhance the entire business model and the backing from fans and other stakeholders in relation to revenue generation from various sources , e.g., ticket sales, broadcasting contracts, merchandise sales, good sponsorship activation and the increased value of fan engaging content production. Couvelaere and Richelieu  consider the importance of sports teams engaging themselves in a way that is synergistic with the lives of their fans in order to bring the brand of the team to life by letting fans live it. Now, years have passed since the publication of their scientific article. Therefore, it serves a purpose to acknowledge the growing weight of technology and data on people’s lives and in sports , which provides a good grounding for putting additional focus on this intersection as highly identified fans show likeliness to engage with teams, athletes, and other sporting stakeholders via online and digital platforms to gain more in-depth information .
4. Sporting performance
Technology and data have become manifested elements of professional sports in the hunt for enhanced and elevated performance platforms. Additionally, their application reaches beyond that of professional sports and even targets fans and consumers outside the spotlighted playing fields in professional sports. In the aftermath of this development, actors in the professional sports industry underline the importance of technology and data as being directly associated with winning titles. However, the vital role of technology and data in influencing sporting performances is clear but there is reasonable meaning in acknowledging that technology and data are only tools and not a universal quick fix to performance challenges in professional sports. Consequently, technology and data do not solve cultural problem areas in sports. For instance, such complexity is apparent in the management of professional team sports and one may similarly argue that the same difficulties exist in professional individual sports, e.g., tennis or golf, in which the professional athletes are supported by an entire team of physical therapists, coaches, fitness trainers, etc. Yet, the point of this discussion is that technology and data may support decision-making although not being the solution in their isolated capability. Spearman notes that
This illustrates the value of technology and data in lifting sporting performances, but with the hint that sporting tracking and positional data must be ‘qualified’ to be applied intelligently and effectively in order to positively reinforce sporting performances in practice. For instance, it holds essential meaning that the application of technology and data is based on a solid understanding of the interplay between various contextual factors and the importance of timing when executing performance-based decisions, e.g., the technical and tactical capabilities of the individual players in contrast to the team’s tactical game plan, the strength and weaknesses of the opponent or the fact that the coach has only a short window to receive, interpret and execute on data during the game. It is imperative to have a platform of knowledge before decisions are made. This knowledge is often mixed with intuition and passion, e.g., from a coach, in reality in professional sports, which helps to determine the perception of decision-making and therefore adds an extra complexity level in dealing with the intersection between technology, data and sports.
From a critical perspective, the quality of the application of technology and data in professional sports is also subject to bias as there is always a person behind the data. Therefore, applying technology and data may sometimes risk being subject to what Vamplew  coins as ‘reverse research’ in which sport organizations know the desired conclusions beforehand and aim for evidence that will back these conclusions or look to apply conclusions that are not fully backed by the empirical data collection. This may exist when the sport organization applies technology and data to find evidence, which supports predetermined conclusions about a given athlete, who hypothetically underperforms on specific parameters. It may be associated with predetermined conclusions that there are lazy players on the roster for what reason it becomes a way to punish all players with a salary cut. This is a risky management path in sports, which is associated with a negative ‘documentation culture’ and not a sound application of technology and data in sports. Despite this managerial complexity, the application of technology and data adds value to sporting performances in team sports, e.g., football, by offering tracking opportunities concerning the positioning of the athletes and how that changes dynamically in the game and how that affects the possibility of scoring or improving one’s team position over another. This inspires the potential to optimize sporting performances via positive influence on the sporting quality, on the outcome of the game, and the associated learning.
Managing sporting performance through the application of technology and data also stresses the significance of differences between sports. For example, the sport of football is a complex sport. One may argue that it is more complex than some other team sports, e.g., basketball, or definitely more complex than many individual sports, e.g., golf and tennis, as the game of football is characterized by having 11 players on the pitch and rules like offside. This means that the players are not necessarily close to the goal for what reason decision-makers on and off the pitch have to figure out how to get into situations with the opportunity to score. That is different in other team sports such as basketball, baseball or team handball. In football, all of the players except for the goalkeeper have to do all the skills, unlike American baseball, where an outfielder does not really handle ground balls that are moving quickly. Basketball has become more like football in that even big men are expected to be better dribblers, passers, etc. Spearman admitted that football
5. Improving sporting performance needs the right framing
The complexity of some sports over others, e.g., football over basketball and baseball, does not mean that there are no opportunities but merely more work to be done in qualifying the data. There are also more naturally occurring statistics in basketball such as field goal percentage, rebounds, steals, etc., that are more difficult to generate or track in football. Basketball is now tracking passing in a way similar to how football does, which looks at how the pass improves the situation on the field (not just whether it was received or struck cleanly). Moreover, it means that there is a lot of potential for technology and data since there are many opportunities that have yet to be fulfilled. The world of football has not seen the full implementation nor value of investments in technology and ‘big data’.
The points regarding football is rooted in the debates, discussions, decisions (also for qualified application in professional clubs) and consumption5 of the sport. However, technology and data applicants with a deeper understanding of the game know it is fine to run a lot, e.g., football is a ‘running game’ (legs feed the wolf), but they also know that it is not about the quantity! The quantity must be ‘qualified’ in the sense that football is about tactical positioning. Therefore, players should run intelligently. It helps to be fast in football but not if you run out of the stadium with the ball. Spearman supplements in that technology and data should be applied in helping players to strive to avoid an action if
Concerning the sporting performance, technology should not only be a means to collect data to tell a story. The purpose should be to gain a more complete understanding of the sport, e.g., football, and thus how we get in a situation with higher probabilities for scoring or other elements that may increase a team’s winning chances. Football is, as mentioned before, a very complicated game in that sense. For instance, data may reveal that there is evidence that the opponent’s strong left central defender goes aggressively to cover the area around the first post to defend crosses from the right flank. Combined with tactical understanding, the data stimulates other play solutions than the area around the first post when crossing the ball from the right flank. Vamplew  argues that theories or suggestions without validated evidence just function as competing hypotheses. This means that they may assist our understanding but cannot entirely explain the dynamics of a context. It is complicated to guide sport organizations to apply technology and data as there are many elements to be studied; this is especially true in complex sports like football. Therefore, it serves a purpose to critically discuss counterfactual studies. For instance, football and other sports are contexts filled with clichés, e.g., if he/she had been fast, he/she would have become a professional football player or if Denmark did not have Christian Eriksen on their Men’s National football Team, they would not have qualified for the 2018 FIFA World Cup. From a critical stance, one can definitely discuss the validity of studying such hypotheses.
6. Qualifying data
The ‘quantifiable’ element is applicable in the ‘sport of sports’ and in ‘the business of sports’. However, it should be ‘qualified’ to be applied in an effective manner in practice. The guiding premise of this chapter is that one effective roadmap for understanding sporting and business performances in professional football is associated with technology and data. The bridges between new and existing knowledge that are produced within this intersection can be a reinforcing force for future performance levels. So, this chapter will discuss specific approaches to how technology and data in sports can help to facilitate improved sporting and business opportunities in professional sports.
In this context, tracking systems may help to understand the positioning of the athletes in football and how that affects one’s team groundwork to win the game. Qualifying data is vital in that process. The distance covered in a game cannot stand alone and neither can data about a player’s change of direction, the intensity of his/her running, moments when he/she stands still (it may happen because the flow of the game is one-sided) or the areas in which he/she moves. In qualifying the performance data, it makes sense to critically assess the tracking system and thereby how the pool of ‘big data’ is generated, e.g., is the system based on radio receivers (originally the technology of ZXY), GPS (the technology of Tracab) or video cameras (ChyronHego’s acquisition of ZXY opens up for a more holistic tracking solution capable of combining the three technologies)? Decision-making in top football is associated with big business and large amounts of money. A wrong decision may be very costly. Therefore, it is imperative to have a valid notion of whether or not a player performs to the level of his/her ability or below or above the expectations before decisions about substituting a player in a game or buying or selling a player on the transfer market is made. Of course, the decision-making process is influenced by complications as performance in football on the pitch is a reflection of a player’s opportunities to unfold a combination of physical, tactical, technical and mental elements and putting these in play in co-creation with other players.
Technological advancements have brought even more data to the surface in the context of sport and have influenced the evolution of specific sports. Professional football is one example. Years ago, the prevailing statistic measurement was the amount of goals scored. Along came elements like the number of passes and assists. However, contemporary professional football adopts more sophisticated data and metrics. Spearman emphasizes that
Qualification of data to be applied in football is subject to challenges and downsides. More knowledge about these constraints may guide football entities to construct better interactions between technology implementation, data management and sporting and business performances. For instance, if you take a picture but it is fuzzy, then it is beneficial to apply digital technologies because you get instant feedback. Spearman notes
Qualifying data implies the vitality of the interplay or the co-creation8 between ‘human and machine’ in the sense that Spearman stresses that
7. Making sense with technology and data
Taking the qualification of data towards a higher degree of organizational, economic and commercial sense-making, data management works as a vehicle of positive strategic change that sometimes may be associated with some extent of risk aversion. No matter what you’re doing with a sports team, unless you are winning, there’s going to be upset fans. Spearman touches this essential stakeholder consideration when arguing that “
Finding a point in time where technology and data become even more decisive in football is a derived effect of how governing bodies and other rights holders play along. For instance, an extract from
Football’s global governing body FIFA allowed the use of technology and data during the FIFA 2018 World Cup in Russia so that coaches were permitted to receive real-time technology and data support from data analysts throughout the duration of games. However, it should be noted that the teams choosing to use this opportunity had exactly the same capacity to provide visual and statistical data9 to inform in-game decision-making . Therefore, the point of differentiation comes down to how intelligently and competently teams can apply the technology and data to make decisions. As the CNN article points out, the Dutch football legend Johan Cruyff once stated that football is a sport that you play with your brain. However, the current development proves that top football is highly associated with technology and data as supporting performance tools. Although sports tracking data may be optimally applied before and after a game given the complication of the ‘stressed time slot’ for coaches to manage their team comprehensively through data during a game, it is definitely means to an end in terms of fully preparing a team for an upcoming game or for constructive feedback after a game to influence future game preparations. There are always critical moments during a football game. For instance, it is interesting to assess what happens right after a goal scored, what happens right after halftime or what happens in the end of the game. Some players may be tired in the end of the game while others are not. In that sense, sports tracking plays a role in injury prevention but also regarding substitutions where some fresh players with competent offensive skills may enter the pitch with a positive determining impact on the outcome of the game. For example, Craig Duncan, a prominent sports scientist, argued already before the 2012 UEFA European Championship (EURO) that sports tracking systems (i.e., GPS in the case) worn during a match can help to prevent soft-tissue injuries . The focus on technology and data to prevent injuries is backed by leading football physiologist Raymond Verheijen, who worked with Russia’s team during the 2012 EURO. He said that up to 80% of injuries are preventable. Verheijen blames fatigue from overtraining in that matter, which is supported by evidence from a study analyzing 27,000 football matches demonstrating that teams playing after 2 days of recovery and facing opponents with a minimum gap of 3 days were 39% less expected to win at home and 42% less expected to win away .
Consequently, it is vital that players who do not play that much are kept fresh during the duration of a tournament whether it is the World Cup or for a club team; this is especially interesting in contemporary top football where the best domestic teams are expected to do well in domestic as well as international (e.g., UEFA) competitions. Therefore, the methodological constraints in applying technology and data are associated with the quality in which these factors are integrated in the daily operations of the club. For instance, FC Midtjylland bought and installed ChyronHego ZXY sports tracking system in their stadium as well at their training facility. The same technology for data use and data management for games and training session is methodologically important from a practical application standpoint because it makes it easier to compare the performance of players (it is also difficult to compare apples and oranges) while accumulating data for longitudinal studies .
8. Business promotes technology and data application in sports
The intersection between sport, technology and data is also a matter of segmented market places. Sport is dependent on fans. Without fan appeal, top football would not have the same economic scope. Global fan identification makes professional football a relevant commercial cocktail. The scope of the economics of football is very impactful from minimizing the level of player injuries, which may lead to better sporting performances and thus to an improved business model, to taking the data from the application of technology and turning that data into fan relevant content. Spearman believes that the articulation of successful data narratives may lead to additional focus on technology and data management. He notes that
The awareness about the potential of technology and data in football from a holistic perspective, which blends performance on and off the playing field, can affect demand. This is evident in what took place in professional baseball, i.e., when for example the Oakland A’s and baseball became very successful using data, immediately the Red Sox became interested in the exact same ideas, so a team’s success with ‘big data’ thrives in the competitive environments of top sports and business. Respondent 2c continues along this line in that
In critically discussing and considering how to put technology and data to work in professional football in this context, the argument of ‘qualifying’ data becomes even more central as success in competitive settings is a matter of the quality of the process rather than the quality of the outcome. However, technology and data will most likely appear as prominent drivers in professional football in the future. The reasons for that may be contradictory; one stimulating reason may be ‘the fear of missing out’ in professional competitive settings as Spearman notes that
9. Paving the way for more comprehensive sports experiences
Better performances on the playing field and thus higher sporting quality most likely leads to better sporting experiences. Similarly, decisions based on data hold promising potential to establish good synergistic effects between the sporting and business experience. From data on local traffic patterns affecting fan transportation to games measured against scheduled game times and ticket sales and various other revenue generation categories within that context, e.g., merchandise, food and beverage sales etc. , to data on successful sponsorship activation slots during games, there are significant commercial advantages in data management. Building on the ‘qualification’ analogy, sports entities should aim to understand the practice and science of data analytics to sustain competitiveness. In striving for good business opportunities in this context, Spearman points that
10. Comprehensive football experiences equal better fan engagement
Technology and data have a great potential in professional football as there is a good level of fan identification with football brands whether these are linked to governing bodies, e.g., the brand of UEFA (in association with the Champions League as the world’s most prominent club football league), leagues, e.g., the English Premier League, clubs, e.g. Real Madrid, or players, e.g. Lionel Messi . The ‘Psychological Continuum Model’  helps to elaborate on consumption patterns in sports. Its hierarchical structure of four phases: awareness, attraction, attachment and allegiance, provides a framework for how technology and data may serve to take the popularity of football to new heights, e.g., more in-depth insights related to one’s favorite team or player, or to new target groups, e.g., technology and data savvy Millennials. For instance, technology and data from a sports tracking solution, e.g., ZXY, leveraged through a technology platform, e.g., an app, may improve a fan’s knowledge of players from a favorite club, which creates a positive reproduction and reinforcement of the club’s fan culture and fan identification level ending with ‘lifetime fans’. This theoretical framework plays well along with focus group data and vice versa as the theoretical grounding assists in providing better understanding of how to create advancement from the lowest to the highest hierarchical level. However, the different phases of the ‘The Psychological Continuum Model’ should be subject to further qualification and thus not solely be perceived as an isolated hierarchical level, e.g.., being a Chelsea fan (attachment phase) or living for Chelsea (allegiance phase) may hold variations. Interactions are vital in this approach to add meaning to technology and data application to boost comprehensive sport experiences. The opportunities to generate new narratives and in-depth engagement, of which governing bodies including leagues and associations, clubs, media, sponsors and fans may take advantage, are interrelated with an open-source mindset and conscious and unconscious co-creation and co-branding10 between these stakeholders. However, the focus group data reveals an interesting paradox in the fact that some stakeholders in this context are very innovative while others almost need to be pushed. Respondent 1a notes that
What holds meaning concerning technology and data application to enhance sport experiences is the improved quality of the user or fan experience. Respondent 2a views it as a valuable add-on in that
11. Knowledge-sharing between sports and business
Taking the data and connecting it to the game’s multi-dimensional aspects brings an interesting level of content about clubs, players and commercial stakeholders, e.g., Real Madrid has a 70% possession rate and Toni Kroos has 95% successful passes and that plays along with the sponsor activation of Emirates with an average of +95% on-time arrivals. Such narrated content can assist in brand management disciplines by building, developing, and sustaining a strong level of brand equity as a ‘hybrid notion’ of sports branding  and cater a better understanding of the football entities’ decisions and actions. According to Spearman, Opta Sports, a sports data provider, does
A very simple Tweet like that generates a fair rate of engagement in terms of comments, likes and shares so consider the potential in more sophisticated content.
The scope of technology and data in professional football grows when it is inserted in a context of co-creation and knowledge-sharing. SAP was mentioned as an example of adding new dimensions; e.g., the measurement of players’ cognitive skills. How about the creative opportunity of measuring emotions? Such aspects are already in play in the commercial arena of sports, e.g. sponsorship effectiveness enhanced by sentiment analysis or integrated algorithms. Respondent 2f touches this in that
12. Knowledge and co-creation frame the football experience
The discussion becomes a matter of the charm, knowledge level, sporting and business value, which are vital elements attached to the game. In bridging existing knowledge gaps regarding technology and data in football, it is evident [14, 51] that there is an edutainment  element capable of blending education and entertainment at the benefit of enjoyment for the game’s stakeholders. When watching the 2018 World Cup, it was interesting to witness how the media articulated France’s 4–3 win against Argentina in the round of 16 as a celebration of fantastic offensive football. There is no doubt that the game presented excellent finishing skills and fine offensive playing patterns, but one should note that sparkling offensive skills sometimes are derived from questionable defending. If beating Argentina 4–3 in a game with 7 goals, and some great goals esthetically, serves as a quality performance indicator, there is a need for a higher sophistication level. The game was very entertaining for football lovers. However, it is interesting to look at the contrasting perceptions among the media and football fans in a tiny (definitely when measured on population size) football country like Denmark after their team’s 0–0 draw against France, which qualified Denmark for the round of 16. Expressions like boring and destroying defensive football characterized part of the country. Of course, football’s passionate texture covers both extremes, e.g., the very positive and praising manifestations of Denmark’s success of making it through the group stage but also the very negative and complaining manifestations. That’s football and that’s what the passion of sports is capable of. This is something that the football world should embrace as an opportunity. The point here is that the real interesting question(s) in bridging existing knowledge gaps may exist in the form of asking ‘what is at stake here?’. This question includes time and context when asking ‘who are influenced by what is at stake here?’ and ‘what is the meaning of time in that regard?’, e.g., there are relevant moments before, during and after Denmark’s game against Croatia in the round of 16. If one is a football fan but also a professional coach, the dominant contextual factors when asking the question of ‘what are the conditions for the game?’ will entail greater nuances or sophistication. For instance, such a person may have liked more entertaining offensive football from Denmark against France but would also acknowledge the meaning of time and space in football. Thereby, this person would know that France would most likely take advantage of the opportunities if Denmark’s defense was positioned by the midfield line in most of the game instead of being positioned more defensively. So, a good understanding of the game may be positively enhanced by technology and data, e.g., sports tracking data, as an engagement tool in the discussion regarding the World Cup and thus illustrating that a game and the outcome of a game may somewhat be controlled without necessarily having the ball but by controlling the space in which the opponent wants to operate or by ‘tactically tricking’ the opponent to operate in certain spaces in which it is tactically beneficial to conquer the ball. The successful coach José Mourinho won a couple of titles with ‘underdog teams’ in this manner.
Strategic application of technology and data may take different forms, e.g., defensive vs. offensive approaches to winning games on the pitch, data-driven decision-making in the business side to support strategic execution or strategic gamification elements to provide edutainment. Spearman understands that football is a dynamic phenomenon, the importance of momentum on and off the pitch and acknowledged a few vibrant development patterns surrounding the game in adding that
13. Bringing data, knowledge and strategy to life: recontextualizing football economy
The ZXY system is capable of commercially intensifying the knowledge gained from sports technology and data and thereby to help football teams realize their strategies in this sense. Inductively, the research data provides sufficient grounding for proposing a conceptual framework, cf. Figure 3 below, which portrays how technology and data recontextualizes traditional sports (and football) economic models [65–69]. This case of investigating data from sports tracking technology in football shows the point of professional football clubs investing in sports tracking technology and data primarily to improve the conditions for sporting performance. The sporting performance of a football club is based on prevalent dimensions such as physical, technical, tactical and mental dimensions but in this context, it is imperative to underscore that the complexity of football is also linked to football being a team sport. Therefore, the social and hence culturally influencing dimension regarding the cohesion of and the relationships within a team matters in football performances . In this context, so does the sport specific technological dimension. For instance, in cycling or motorsports, it is common to work with minimizing wind resistance to influence performance. In sailing, it is common to look at the construction of the boat. In football, technology (and thereby data) also plays a vital role in influencing performance. However, the difficult part is to work on the social and cultural dimension. The relationship between data, knowledge and actions is vital for football entities. Football entities are working with ‘big data’, i.e., large data sets, which produce lots of knowledge. However, knowledge is not enough in itself. Everything must be qualified and inserted into a set of actions, which in the end determine the outcome of a game. Consider Germany’s football team, which came to the World Cup in Russia as reigning champions. The German team works intensively with data, has qualified and effectual knowledge within this field but the team seemed ‘saturated’ (many players had already won the tournament in 2014 and also played many games throughout the year for the respective top club teams that they represent) and not engaged enough in the actions on the pitch, which may help to partly explain the team’s early exit of the tournament.
Clubs succeeding in enhancing the quality of sporting performances will face improved stakeholder engagement and satisfaction, e.g., higher attendance levels, better media articulation, and increased sponsorship interest. All these elements may serve as positive influence on sporting performances, e.g., happy fans may positively influence the confidence level of players, while also influencing monetization opportunities. For instance, clubs can capitalize on more fans coming to the home games in terms of increased ticket, merchandise, and sponsorship sales. In addition, players that perform above average may be subject to positive articulation and may translate ‘being talk of the league’ into lucrative transfer sums. These capitalization dynamics of a football club lead to cultural production, i.e., a process that may also include negative and positive reproduction of culture , in which the club will invest in shaping the culture of the club, e.g., investing in the roster, the team functions or the club infrastructure. Just like the monetization aspects can be traced back to the stakeholder satisfaction, e.g., better profit margins may spark the club to re-invest in fan engagement solutions, the cultural production also influences the monetization aspect in that a football club constantly evaluates the ‘strength’ of its culture, i.e., if there are irrational investments in the cultural production (buying the wrong players), this fact will affect monetization negatively. The cultural production implicates that investing in the right coaches, the right players and thus building a strong level of cohesion in and around the team with the right relationships on the pitch (in and between the various lines on the pitch) will influence sporting performance positively. Of course, this conceptual framework is a construction, which to some extent takes a ‘ceteris paribus’ perspective, because the practice of running a football club is highly dependent on different parameters. One vital parameter is competition, e.g., there is intensive competition for the best football players, which increases the costs of investment in fully developed quality players (another reason for investing in technology and data to optimize performance enhancing details from this investment such as optimization of talent development or of purchasing fully developed players). Another important parameter is the market size and constraints, e.g., is it a club like FC Bayern Munich, which is operating globally, or is it a club like Werder Bremen with a smaller market size? Additional parameters like the club’s facilities or stadium, its commercial competencies, the strength of its league, the appeal of the league’s competition format, the level of competitive balance in the league, the strength of the league’s media deals may be decisive factors influencing the various parts of the framework. However, the interesting recontextualization aspect of the conceptual framework is associated with technology and data, which constructs a meta-layer that emphasizes the importance of co-creation and co-branding due to the application of technology and data in this performance-related management of the sport and business nexus in football clubs. As mentioned earlier, the qualification of technology and data use (including competence development of the organization) and the derived co-creation and thus the co-branded and ‘hybrid’ branding activities build a fruitful bridge from improved sporting performance to optimized business performance in the club. Thus, the business performance is also depicting an interdependence with the different parts of the conceptual framework, i.e., stakeholder satisfaction, monetization, and cultural production. This is a somewhat artificial construction grounded in the empirical data and in relevant theory but it depicts the demand of the football industry in terms of the constant hunt for performance improvements in a very competitive and dynamic environment, which is highly influenced by technology and data.
This development gets a more lively and vibrant strategic meaning for clubs, players, fans and other sporting and commercial parts of football’s eco-system . All these parts should be interrelated in ways, in which technology and data may bridge the gap to more thoroughly understanding football performance, at the cognitive level and concerning tactical, physical, technical and (perhaps) social17 and technological aspects. One development that Spearman saw influence this context was the framing of pitches in baseball, i.e.,
To strategize this context, there is an obligation for stakeholders in football to intelligently co-create and co-brand. One challenge is that the strategic organ in football organizations is all too often too distanced from the operational and daily contexts to understand how to construct or shape the knowledge and skills, which can guide competent ‘qualification’ processes of data and data-driven decision-making in the organization (if decisions really are made on that foundation?). For instance, there is interesting potential in trying to ‘qualify’ technology and data in a context of ‘hybrid’ sports branding , e.g., taking the economic benefits of finding the ‘right players’ with the ‘right competencies’ but understanding how to leverage the branding interplay. The latter refers to the hybrid element(s), which may beneficially be orchestrated across various platforms when there is a ‘qualified’ construction of the specific player brand in the context of the sport (football), the league, the club, and its commercial stakeholders. This working approach will construct ‘new meaning’ in terms of talent identification, recruitment, and development from a ‘sport of sports’ and from a ‘sports business’ perspective.
Technology and data can help to demonstrate somewhat hidden qualities of players and assist clubs in winning and players in developing and it can be used by the clubs for various sporting and business purposes, e.g., creating positive transformation19 on the transfer market and expanding the club’s economic transfer balance and entire valuation from these transactions . Spearman indicates that
14. Segmented marketplaces and learning to spark football’s innovation
Football is a segmented marketplace. Budzinski and Satzer  argue that the business of sports is characterized as multisided markets, in which there is a strong interdependence between different business markets20, e.g., sponsorship income may be affected by ticket sales and vice versa. Spearman notes the interesting aspect in this in that “
Football clubs are starting to work even more strategically on influencing customer-driven innovation. Spearman notes that
15. Better understanding of sports and increased marketability
Along with the ‘qualification’ discourse in this chapter, technology and data businesses also move into a more crowded market place so simple data does not provide much relevance in terms of marketability and providing more in-depth understanding of football for the coming generations of prosumers. Spearman supplements in
The market expects more from technology and data solutions in football today and that is a relevant interplay. Spearman adds that
In that sense, Spearman also stresses the many opportunities in tracking data influencing the future of technology and data in football.
One of the main changes to the understanding of football, which technology and data provide, is that this context creates a relevant cohesion between the sporting and commercial focal points and how to strategize and capitalize on that. For instance, Spearman mentions that
16. Concluding remarks and future research
Technology and data improve the commercial outcomes for teams, not only by raising the sporting performance of the athletes (and thus winning more often), but also by allowing the data to be commercialized. This includes technological innovation, biostatistics, movement data, and other game-based information, which improve how a football club manages performance and enhances the circumstances for unfolding its talent on and off the pitch. This commercialization creates still more fandom above and beyond what’s driven by the sporting outcomes and thereby opportunities for better comprehensive fan experiences and innovative commercial solutions that can support revenue generation. Currently, though, the sheer amount of data that is becoming available to sporting enterprises is difficult to harness and use effectively both for technical reasons, but also due to a lack of financial and human resources. Yet, the fear of missing out (FOMO) is causing some organizations to prematurely (that’s not good strategic execution) engage the data anyway.
Commercial sub-optimization may be prevented with the use of technology and data. However, what needs to happen is that the data needs to be qualified so that knowledge-sharing, individual and organizational learning co-exist along with the aim to apply technology and data to improve sporting and business performances. If there is a lack of resources, e.g., in terms of financial and human capital, one way to overcome this constraint is to strategically invest in technology and data to optimize the utilization of these forms of capital. In such, technology and data are potent vehicles that can change performance in the sport and business nexus and by catering to new audiences and improving the engagement with existing audiences, there is a good chance of increasing profitability. In the tracking-driven and thus performance-generated commercialization in football, data accuracy is central so qualification should become a matter of: circumstances for data collection (e.g., methodological conditions), persons behind the data (who collected the data?), avoiding to fall in the trap of ‘data for the sake of data’ (quality of data should outshine ‘quantity focus’), and of creating effective platforms for user involvement to bring the data to life in a wider football context.
Future research should include a better understanding of the intellectual property issues of who owns this data—the athletes, the teams, the governing bodies (e.g., FIFA, UEFA, national football associations, and leagues like the English Premier League), media companies, the public (is it public data like boxscores), the technology companies themselves? In some sense, whoever owns or co-owns the data will be able to profit off of it, yet based on the Coase Theorem, the data
- According to ChyronHego, ZXY provides coaches and sports scientists with “the most accurate and repeatable set of performance metrics for any type of Electronic Performance and Tracking System (EPTS) on the market” .
- The ZXY Arena system can be configured to operate with different report rates. The most used is 20 Hz but a 100 Hz setting is also available. Each transponder can be configured independently and dynamically over the wireless control link, which means that if it is raised to special requirements to have a high-resolution sampling, the system user can assign 100 Hz to this user(s).
- The instrumental case study reflects the purpose of gaining more insights in the general question of how applying technology and data based on tracking systems in sports can enhance sporting and business performances in the context of sports .
- WAR is a synonym for ‘wins above replacement’ and articulates how many wins a player provides to a team’s accomplishments related to the likely number of wins the same team would have accomplished with a replacement [40, 41].
- When one watches UEFA Champions League games on television, it is portrayed that Cristiano Ronaldo or Lionel Messi have run a specific distance, have a certain percentage of successful passes or have had a specific maximum speed during the game.
- Bayesian inference is a scientific statistical inference method, which applies probability updates regarding a hypothesis in alignment with the availability of information. The method’s focus on updates considers the active breakdown of series of data, so as new information is available, it updates the model.
- The Fundamental attribution error is the “tendency to focus on the role of personal causes and underestimate the impact of situations on other people’s behavior.” (, p. 106).
- Co-creation in the context of this chapter means a collaborative process between different parties involved in the work with technology and data, e.g. data suppliers, system, data analysts, coaches, players, fans, and sponsors as co-producers, which jointly create mutually beneficial value with the strategic advantages that may be attached [44–46].
- During the 2018 FIFA World Cup, the movement of players could be tracked by two optical cameras. Analysts could send interpreted video clips about the team’s performance to coaches on the bench via a tablet device .
- Co-branding in this context means that the purpose of branding, among other things, is to create value (also from an economic standpoint) and that co-branding becomes a manifestation of this purpose by including a ‘win-win scenario’ aimed to construct synergistic effects based on the branding activities [61, 62].
- The terms ‘gray’ in this context holds the meaning of the players not standing out in a significant negative or positive way.
- The number 12 is just a number used to emphasize that data provide many opportunities (and that these opportunities are not limited to 12).
- An in-game index allows data analysts to break down team video and index clips for team and player performance analysis and thus to visually present highs and lows during a game coupled with in-depth statistics.
- Blow up in this context is an expression of being very emotionally influenced, e.g. a player may work harder or be irrational and commit a stupid foul.
- Kill in this context acts as a figure of speech for being on top of or winning the battles that takes place on the pitch in a professional football match.
- It is a metaphor along the same line of meaning as the ‘kill’ metaphor.
- Football is a team sport so the social capital may be relevant to discuss in relation to how technology and data are integrated to influence sporting and business performance. Putnam articulates the significance of social capital “To build bridging social capital requires that we transcend our social and political and professional identities to connect with people unlike ourselves. This is why team sports provide good venues for social-capital production.” (, p. 411).
- Strategic in the sense that it is aligned with Castrol’s strategic foundation and brand.
- This element of transformation is integrated in the ‘cultural product’ of Figure 3, cf. below.
- “The name ’two-sided’ market was originally chosen to characterize the two sides of demand (customer groups) a supplier on such a market must deal with. However, since every market consists of ‘two sides’ in a different sense (supply and demand), the adequateness of this name is subject to controversy, e.g., . Next to the simple enhancement towards cases of more than two distinct customer groups (‘multisided’ markets), the term ‘platform’ markets is preferred by some. Yet, ‘two-sided’ or ‘multisided’ respectively seem to be the established terms, wherefore we will use them in the following” (, p. 69).
- Look at the outcome of the games in the World Cup, e.g., shots deflected ending in a game-winning goal, the influence of the VAR system, a linesman missing the offside, etc.
- Coase  noted that, under various assumptions, regardless of who owns an asset, that asset will be used in a way to maximize its net value.