The Virtual Meets the Real in Sports World: Is There a Circular Effect Between Traditional Sports and eSports Fan Identification?

Abstract

This study was designed to investigate the influence of eSports fan identification on traditional sports teams and vice-versa, specifically in cases where there is an intersection of soccer teams and the eSports world. The Points of Attachment Index was applied with the theoretical background used mainly being the Social Identity Theory (Tajfel & Turner, 1979). Four substantive hypotheses were translated into a conceptual model. Surveys were collected during eSports events in the city of Rio de Janeiro in 2019. Valid questionnaires collected reached 1,420. Data analysis was completed by applying descriptive analysis, exploratory factor analysis, and confirmatory factor analysis, to verify the reliability of the constructs, as well as the convergent and discriminant validity. The Structural Equation Modeling technique was used to test the substantive hypotheses. The empirical outcomes suggest that the identification of a fan with a soccer club exerts a positive influence on the identification of the fan with the club’s eSports team, but the opposite cannot be stated.

Keywords:
Sports; Sponsorship; Esports; Soccer; Fan Identification

Resumo

O estudo foi desenhado para investigar a influência da identificação do fã de eSports em times esportivos tradicionais e vice-versa, especificamente nos casos em que há uma interseção de times de futebol e o mundo dos eSports. A escala PAI (Points of Attachment Index) foi aplicada, utilizando-se a Teoria da Identidade Social (Tajfel & Turner, 1979) como principal referencial teórico. Quatro hipóteses substantivas foram traduzidas em um modelo conceitual. Os dados da pesquisa foram coletados durante eventos de eSports na cidade do Rio de Janeiro no ano de 2019. Os questionários válidos coletados chegaram a 1.420. A análise dos dados foi concluída por meio de análise descritiva, análise fatorial exploratória e análise fatorial confirmatória para verificar a confiabilidade dos construtos, bem como a sua validade convergente e discriminante. A técnica de Modelagem de Equações Estruturais foi utilizada para testar as hipóteses substantivas. Os resultados empíricos sugerem que a identificação do fã com um clube de futebol exerce influência positiva na identificação do fã com o time de eSports do mesmo clube, mas não se pode afirmar o contrário.

Palavras-Chave:
Esportes; Patrocínio; Esports; Futebol; Identificacão do Fã

1. Introduction & Objectives

The emergence of eSports as an industry factor in youth culture is quite often described as an omnipresent cultural phenomenon of worldwide importance. Currently, an increasing number of people recognize eSports as large gaming events where millions of spectators watch thousands of people play over various online streaming channels (Borowy, 2012). In the most recent years, the growth in eSports spectatorship and player engagement has raised eSports into the mainstream culture, legitimating the matches to the level of professional sports, with a substantial global audience and engagement (Goldman Sachs, 2018).

The outlook for the eSports market is impressive. Global eSports revenues are expected to grow to US$ 1.38 billion in 2022, a year-on-year growth of 16.4%. Moreover, revenues are expected to reach US$ 1.87 billion by 2025. China is responsible for the largest share of the global revenues, generating nearly a third of the total revenue. Southeast Asia, Central Southern Asia, and Latin America are the fastest-growing regions with 2020-2025 compound annual growth rate of 27.6%, 23.4%, and 19%, respectively. In 2022, sponsorship is the highest-grossing global revenue stream related to eSports, which is expected to generate US$ 837.3 million, or nearly 60% of the entire market. Audience from eSports is expected to reach approximately 532 million people globally in 2022, an increase of 22.1% compared with 2020. In addition, the audience is expected to reach 640.8 million people by 2025. In 2022, 2.47 billion people will be aware of eSports worldwide (Newzoo, 2022).

As a consequence of the large volume of financial resources handled by eSports, and the growing sponsorship of non-endemic brands within the electronic sports industry, the amount of research on eSports in the academic management and marketing research fields is growing. Another point that reinforces the necessity of further research on eSports is the increasing trend of sports clubs that embrace eSports (Bento, 2019). In this regard, it becomes a natural requirement to examine and understand better the reasons why the audience enjoys the eSports genre as a spectatative, engaging, activity.

With these two aspects in mind, this study aims to use the Social Identity Theory (SIT) to understand the identification of fans with their club when there is such intersection of soccer teams and the eSports world, specifically when creating a team for competing in eSports. The SIT was developed by Tajfel and Turner throughout the 1970s, having been consolidated in 1979 as An Integrative Theory of Intergroup conflict (Tajfel & Turner, 1979). The social identity approach contributes to the understanding of belonging and identification with a sport or sports team since the individuals are intrinsically motivated to seek positive distinction (Tajfel & Turner, 1979) and are prone to identify and sort themselves and others within social categories, such as membership in organizations, religious affiliations and age groups (Ashforth & Mael, 1989).

From a eSports perspective, most of studies addressing eSports fan behavior is related to eSports spectatorship motivation (Pizzo, et al., 2018; Hamari & Sjöblom, 2017; Sjöblom et al., 2017; Lee et al., 2014; Lee & Schoenstedt, 2011) and only recently are scholars looking for other kinds of reasons for spectatorship (Qian et al., 2019; Choi, 2019). The necessity to understand the eSports fan behavior from an identification standpoint is imperative to contribute to the literature about eSports and Social Identity Theory.

Ultimately, this study aims to answer the following general research question: Can fan identification with traditional sports positively influence fan identification with eSports for the same sports club, and vice-versa?

2. Theoretical Background

2.1. The Social Identity Theory

The Social Identity Theory (SIT) was developed by Tajfel and Turner throughout the 1970s, from the results of various experiments conducted with small groups of individuals (Tajfel, 1970; Tajfel et al., 1971; Tajfel, 1974) and was consolidated in 1979 as An Integrative Theory of Intergroup Conflict (Tajfel & Turner, 1979). Tajfel arrived at the social identity concept in a study from 1972. The concept has been defined as an individual’s sense of self identification based on relations with other individuals he or she normally engage with and groups of people he or she might be a member of (or even dislike). The SIT comprises three mental processes: (i) social categorization, (ii) social identification, and (iii) social comparison, which are the base for the in-group/out-group classifications (Tajfel & Turner, 1979; Tajfel, 1982).

The first process is the social categorization and by this process individuals are organized into social groups in order to understand their social world, thus enabling to classify individuals based on the groups to which they belong. It is typical, at least in a first moment, to overlook individual characteristics, and classify persons by looking at their social groups (Tajfel et al., 1971; Tajfel & Turner, 1979). According to SIT, social categorization has two functions: to simplify the organization of the social context for the individual, which is usually done with the help of stereotypes associated with belonging to each social category, and to extract a sense of self-worth by finding “his or her place” in society through a sense of belonging to that category.

The second process, social identification, considers those aspects of individuals’ self-concept that they derive from the social categories or groups of which they feel a part and is based on three premises (Tajfel & Turner, 1979). First, people will attempt very strongly to keep or improve their own self-esteem, thus always seeking to uphold a positive self-concept. Second, social groups are associated with positive or negative value connotations, positive or negative social identity, according to the evaluations of the groups that contribute to the social identity of the individual. Third, an individual’s assessment of a group to which he or she feels a part is determined related to other comparison groups in some comparable dimension or attribute. Positive discrepancies result in high prestige and status, while negative discrepancies result in low prestige (Tajfel & Turner, 1986).

The third and last process from Social Identity Theory is the social comparison, where individuals compare their own group with other groups. This comparison is mainly associated with the assessment of the levels of prestige and social standing from each group against each other. To maintain a higher self-esteem, the individual strives to perceive his or her in-group as a better group than the out-group, in terms of prestige and social standing (Vinney, 2019). The Social Identity Theory considers social status not as a resource or commodity, but as the specific result of a comparison process among groups by individuals. Social status reflects the relative position of one group in relation to other comparison groups. The individual who identifies with a group often seeks to make favorable comparisons in order to realize the relative superiority of the group of which he or she feels a part of in relation to others, and thus acquire a positive social identity (Tajfel & Turner, 1979; Turner, 1985).

2.2. Social Identity Theory and Traditional Sports Fans

The Social Identity Theory is one of the most important theories in the area of Sports Marketing as it articulates important concepts such as identification, self-esteem, self-concept, and their influence on the behavior of individuals. Identification with sports is a specific instance of social identification where the individual feels a connection with a particular sport or team. The social identity approach contributes toward understanding this identification with a sport or team, since the individual is intrinsically motivated to accomplish or uphold a positive social identity, which is, to a large extent, based on group comparisons between the individual´s in-group and out-groups (Tajfel & Turner, 1979) with people tending to classify themselves and others within other social categories such as membership of organizations, religious affiliations, and age groups (Ashforth & Mael, 1989).

The positive association that fans create with their team is a type of in-group favoritism that helps individuals to uphold a positive social identity by being associated with a group that has importance and meaning to them (Tajfel & Turner, 1979). In the case of sports fans, identification with a particular group provides strengthening self-esteem through the pursuit of a positive distinction by emphasizing the positive aspects of the identification group and minimizing or belittling the negative aspects of that group (Gwinner & Bennett, 2008). Thus, in addition to the benefits of self-esteem, fan identity, like any group identity, is beneficial to the individual by providing a sense of community and of becoming a member of a conglomeration, forming a collective identity and providing the individual with a sense of belonging to a group (Jacobson, 2003).

Nevertheless, Trail et al. (2003) and Robinson and Trail (2005) noted that attachment to a sports team is just one of several possible points of attachment for fans in the sports context. From a study that investigated the relationship between sports fan motivation and the various links with sports, Trail et al. (2003)identified 7 possible links: team, sport, players, coach, community, university, and sport level (professional, amateur, and college), originating the Points of Attachment Index (PAI). Robinson and Trail (2005) reinforced the fact that fans are attached not only to the team, but also to the community, the university, the hometown, the sport, players, and coaches.

2.3. eSports and eSports Fans

The eSports concept is described as an area of sport activities in which players develop and train mental or physical abilities in the use of information and communication technologies (Wagner, 2006). In addition, different from traditional video-games where the player plays for the story (Buchanan‐Oliver & Seo, 2012) or as a hobby to relax from daily stressful routines (Molesworth, 2009), eSports are essentially played as a form of competition against other players and other groups of fans (Seo, 2013). With its rapid growth, the eSports industry has attracted the attention of a younger audience and, with its innovative way of approaching virtual tournaments, represents competition for traditional competitions and sports (Peša et al., 2017).

Despite the controversy about its comparison with traditional sports, eSports have come to imitate its assumed archetype. The eSports also counts with defined leagues, live broadcasts (mainly via streaming), collegiate programs, and growing doping controls, similar to the current professional organization of traditional sports (Karhulahti, 2017). An additional important feature of eSports is the importance of communication and interaction tools to demonstrate the connection of fans with teams in terms of importance and meaning, which is achieved by using approaches similar to traditional sports such as symbols, signs, and rituals (Adamus, 2012). Like traditional sports, it all starts with unstructured competitions, which, in due time, change into well thought out tournaments involving sponsors, spectators (in person and virtually), and attention from the media. One of the main factors for the development and success of the eSports, is the emergence of gaming teams, or clans (names vary from game to game) and the existence of sponsors willing to be associated with these teams or clans (Peša et al., 2017). With so much attention on eSports by millennial spectators, eSports presents an exciting opportunity for sponsors. Millennials are young, affluent, globalized, technologically driven, but increasingly challenging for brands to engage with from a traditional sense of the word (Deller & Thew, 2017).

Traditional sport fans and eSports fans have comparable sport consumption motives, nevertheless fans from each type of event have displayed different motives for predicting game attendance frequency (Pizzo, et al., 2018). As in the case of traditional sport fans, eSports fans may be seeking social gathering moments, seizing opportunities to watch their preferred teams and players perform, and to be a part of a generally exciting experience (Eventbrite, 2015). As in traditional sports, big-name professional players are a beacon for attracting fans to the venues (Lucifora & Simmons, 2003), and results show that eSports fan also appreciate seeing in action the best names of the eSports scene, as an appreciation for their talent (Pizzo, et al., 2018). Other previous researches have also contributed to identifying a logical equivalence between eSports and traditional sports which allow different disciplines studies to use this equivalence in order to further analyze this emerging field of activity (Cunningham, et al., 2018; Funk et al., 2018; Hallmann & Giel, 2018; Heere, 2018).

3. Hypotheses and a Conceptual Model

3.1. The influence of fan identification with a traditional sport on the fan identification with a sport team

Through social categorization, individuals give emphasis on the similarities with in-group individuals and the differences between out-group individuals (Tajfel & Turner, 1979). Social identification can explain the need for reinforcement of self-esteem, which occurs through belonging to a group that has values and meaning praised by the individual (in-group), when compared to out-groups (Ashforth & Mael, 1989). Consequently, their self-esteem as an individual suffers influence from the status of the in-group when compared to out-groups (Tajfel, 1974; Tajfel & Turner, 1979). Thus, individuals are prone to reinforce their own self-esteem by accentuating positive (and often minimizing negative) characteristics of the in-group (Tajfel & Turner, 1979).

From a sports marketing perspective, many studies have been using the framework of Social Identity Theory to better contextualize fan identification in terms of sport type (Gwinner & Bennett, 2008), sport event (Deitz et al., 2012), sport teams (Gwinner et al., 2009; Davies et al., 2006; Sutton et al., 1997; Wann & Branscombe, 1993). The need to affiliate is an underlying motive for fans to follow a sport or a team, or attending a public event (Lee & Armstrong, 2008; Wann et al., 2008), so, in that sense, it is expected that the fan identification with soccer positively affects the identification with a soccer team.

• H1: Fan identification with a traditional sport positively influences the fan identification with a sport team.

3.2. The influence of fan identification with an eSport on the fan identification with an eSports team.

Like hypothesis H1, it is expected that fan identification with electronic sports positively affects their identification with an eSports team. The same aspects of social categorization, social identification, and social comparison can also be applied, which are analog to H1. Other previous studies have contributed to identifying a logical equivalence between eSports and traditional sports, making it possible to use traditional sports scales in eSports (Cunningham, et al., 2018; Funk et al., 2018; Hallmann & Giel, 2018; Heere, 2018). In that sense, it is expected that fan identification with electronic sports positively affects their identification with an eSports team.

• H2: Fan identification with an eSport positively influences fan identification with an eSports team.

3.3. The influence of fan identification with a traditional sport team on the fan identification with the same club´s eSports team

Social identification, a component of SIT, is understood as the individual’s self-concept that is heavily influenced from the in-groups her or she identify with (Tajfel & Turner, 1979), while identification with the team refers to the individuals’ connection with the team (Ashforth & Mael, 1989). Social identification helps to explain why individuals become emotionally invested in their in-group, and how their self-esteem is impacted when comparing with out-groups (Tajfel & Turner, 1979). If individuals believe that their team is perceived as superior to others in terms of status, they build attitudes and behaviors to strengthen their association with the team (Murrell & Dietz, 1992). Fans who are strongly identified with teams have emotional ties to sports organizations (Sutton et al., 1997), fostering these sports organizations as a central piece of their identity as individuals (Gwinner & Bennett, 2008). Moreover, identifying a fan with the team can even transcend a taste for sports with identification with the sport and identification with the team being separate components of the individual’s self-concept (Wann, 2002).

Other previous researches have contributed to identify a logical equivalence between eSports and traditional sports, making it possible to use traditional sports scales in eSports (Cunningham, et al., 2018; Funk et al., 2018; Hallmann & Giel, 2018; Heere, 2018). In that sense it is expected that fan identification with a traditional sport team positively affects the identification with an eSports team.

• H3: Fan identification with a traditional sport team positively influences fan identification with the same club´s eSports team.

3.4. The influence of fan identification with an eSports team on fan identification with the same club´s traditional sport team

Like hypothesis H3, it is expected that fan identification with an eSports team positively affects identification with a traditional sports team.

• H4: Fan identification with an eSports team positively influences fan identification with the same club´s traditional sport team.

Figure 1 displays the designed conceptual model with the study´s hypotheses.

Figure 1.
Conceptual model.

4. Methodology

Firstly, it was decided to study the influence of fan identification in the context of a sports club with presence both in soccer, a very traditional sport in Brazil, as well as in eSports. Flamengo is a Brazilian multi-sport organization with a team in soccer as well as one in League of Legends, also known as LoL (Puiati, 2019). Founded on November 15, 1895, in Rio de Janeiro, Clube de Regatas do Flamengo is undoubtedly one of the biggest names in Brazilian sports. Present in 12 modalities besides soccer, the team has more than 32.5 million fans across the entire country, besides being the club with the highest turnover in Brazil with a revenue of R$ 648 million in 2017 (Mackus, 2018). Recent surveys have shown that Flamengo is the soccer team with the biggest fan base in Brazil, with a fifth of adult Brazilians (20%) spontaneously declaring cheering for the team. Next is Corinthians with 14%, São Paulo with 8%, Palmeiras with 6%, Vasco with 4%, Cruzeiro with 4%, Grêmio with 4%, Santos with 3%, and Internacional with 3%, among other less prominent teams (Datafolha, 2019). As this study aims to elaborate on the contribution of Flamengo’s fan identification with the popular club, this choice delimited the data collection area to Rio de Janeiro where a relevant part of Flamengo´s fan base is located.

Secondly, the modalities chosen for the study are the two of the most popular modalities in sports and eSports: soccer and League of Legends respectively. Soccer is the most traditional sports in the world while LoL is a competitive Multiplayer Online Battle Arena (MOBA) game that mixes the speed and intensity of a Real Time Strategy (RTS) game with Role-Playing Game (RPG) elements. In LoL, two teams composed of characters created specifically for the game with unique design and style, called champions, fight on various virtual battlefields and game modes. With a continuous expanding cast of characters, regular updates, and an active competitive scene, League of Legends is a source of fun and challenge for players (League of Legends Brasil, 2019). The competitive landscape of League of Legends is one of the most consolidated in the eSports world both in Brazil and internationally. With two world events per year and 14 regional leagues organized by game developer Riot Games, the closed circuit promotes stability for investment as the participating teams are pre-defined and continue in the league for an entire season (Mackus, 2018). The fact that Flamengo is present in these two popular games was a key factor for setting the scope of the study.

Thirdly, the option was made to analyze the perspective of in-person spectators of eSports events, which are not so common in the city of Rio de Janeiro, by using a survey. Finally, the occasions elected for the data collection were the Game XP 2019 event and the 2019 CBLoL Finals, the Brazilian championship tournament for League of Legends.

4.1. Design and Procedures

The conceptual model proposed in this study consists of two types of variables: exogenous variables and endogenous variables. The exogenous variables of the study are identification with traditional sports, in this case soccer (IwS), identification with eSports, in this case League of Legends (IwLoL), with the endogenous variables being fan identification with the traditional sport team (Flamengo in Soccer or IwFS) and fan identification with the same club´s eSports team (Flamengo eSports or IwFeS).

Four constructs were operationalized: (a) identification with a traditional sport, (b) identification with a traditional sports team, (c) identification with eSports and (d) identification with an eSports team. The operationalization of the variables was performed favoring the use of a pre-existing scale that has been previously tested in the sports context and in Brazil. All items of the scale used were measured using 7-point Likert scales. To operationalize identification with the sport and the team, the PAI scale (Robinson & Trail, 2005; Trail et al., 2003) was used. The PAI dimensions used were sport and team, both used twice. The sport dimension was used for soccer and LoL, while the team dimension was used for Flamengo in soccer and Flamengo eSports, which is focused on LoL. The PAI has already been used in Brazil by Rocha and Fleury (2017), Amorim and Almeida (2015), and Rocha and Fink (2015) for the team dimension. For the sport dimension, a review proposed by Braunstein et al. (2011) on the original PAI was used.

The pre-tested questionnaires were applied around the entrance of the Game XP 2019 event, which took place at the Rio de Janeiro Olympic Park from June 25^th to June 28^th, 2019, and the 2019 CBLoL Finals that took place at the Jeunesse Arena in Rio de Janeiro on September 7^th, 2019. A total of 1,000 questionnaires were collected during the 4 days of the Game XP event and 440 questionnaires were collected at the CBLoL, resulting in a total of 1,440 questionnaires collected.

Exploratory Factor Analysis (EFA) was executed with the software SPSS Statistics (subscription version). The Principal Component method with Oblimin Rotation Factor was used for the extraction. The methodology proposed by Hair et al. (2010) was followed to deploy the Measurement Systems Analysis (MSA) to run an EFA fit analysis. The Confirmatory Factor Analysis (CFA) was achieved through AMOS software version 26. The multinormality of the variables was assessed, item-by-item, according to an independent kurtosis and multivariate kurtosis. Given the fact the authors were not able to assume the multinormality of the data, the choice was to use CFA with an Asymptotic Distribution-Free (ADF) method, which does not set a normal distribution of the data premise (Kline, 2005). The measurement models for each of the scales were appraised using the subsequent fit quality indices: χ2, χ2/gl, GFI (Goodness of Fit), RMSEA (Root Mean Square Error of Approximation), PCLOSE (p of Close Fit), and CFI (Comparative Fit Index). The Construct Reliability (CR) indicator was used to evaluate the construct reliability. Convergent validity was verified for each construct by examining the standardized coefficient of each item and the Average Variance Extracted (AVE) of each construct. Discriminant validity was verified by comparing the square of the correlation between the constructs with the AVE of each construct.

Estimation of dependent relationships, latent variables, and measurement error was enabled by the use of Structural Equation Modeling (SEM) to perform a substantive hypothesis test. The authors also examined conceptual model hypothesized paths, to test the hypotheses. The model proposed is non-recursive model, i.e., when there is a feedback effect or reciprocal causality since there are reciprocal paths between two endogenous variables in the model (Bowen & Guo, 2011). As in non-recursive models, identification problems may appear more frequently than in recursive models, making the identification more difficult to assess only by visual inspection and use of simple rules (Blunch, 2013), hence, to ensure identification in these cases the authors tested the model in order to check if it was able to satisfy the order condition and the rank condition (Kline, 2005).

5. Results and Discussion

Out of the 1,440 questionnaires collected, 20 were eliminated as a result of the identification of missing answers or errors during the filling process, providing a final number of 1,420 valid questionnaires, which, 1,255 were answered by men (88%) and 165 were answered by women (12%). Of the total respondents, 1,327 (93%) declared that they were supporters of Flamengo in soccer before starting to follow Flamengo in eSports (See Table 1). Considering the greater popularity of soccer and LoL among the male audience, and despite the unavailability of official data that confirms the frequency of these audiences in the events studied, it is possible to consider the reported gender imbalance as a reflection of the frequency observed for the events.

Table 1
Sample Profile

Item	Number	%
Respondents	1,420	100%
Male	1,255	88%
Female	165	12%
Was already a supporter of Flamengo in soccer before starting to follow Flamengo in eSports	1,327	93%

• Source: Own elaboration.

The scales used endured an initial Exploratory Factor Analysis with the resulting matrix revealing that instead of the generation of four factors, as the literature on the used scales suggests, only three factors were generated in the exercise. The explained variance of this initial run was 77.7%. A cross-loading was identified between IwFS and IwFeS dimensions, causing a new round of exploratory factor analysis to be performed. In the second run, the number of factors were fixed at 4, with the items’ explained variance increasing to 84.3%. In this EFA, factor loading scores for all items were superior to 0.50 with no identified overlap among factors and no identified cross-loadings. The items of each one of the scales generated one single factor, an indication of that the extent of common method variance is limited.

A CFA was used to confirm the measurement model. To decide the estimation technique to be used, histograms of all variables were generated and an analysis of kurtosis and multivariate kurtosis indicators (item-by-item) was performed. The CR obtained in the analysis was 74.5, which did not allow to support the multinormality of the data, therefore the ADF technique was the best alternative for performing the CFA. The number of estimated parameters was 30, which means that with a sample of 1,420 cases, there are 47.33 cases per parameter.

The Chi-square, normalized Chi-square, GFI, CFI, RMSEA, and PCLOSE fit indicators were analyzed. GFI and CFI were in line with expectation and divergences in the parameters p-value, normalized Chi-square, RMSEA, and PCLOSE were marginal (Table 2). It was concluded that this model with correlated errors shows adequate fit to the underlying data structure.

Table 2
Structural Model Fit Summary (Game XP and CBLoL combined)

Fit Indicators	χ2	p-value	χ2/df	GFI	CFI	RMSEA	PCLOSE
Structural Model	227.129	0.000a	4.732a	0.971	0.956	0.051a	0.364a
Suggested limits	< possible	> 0.05	< 3.0	> 0.9	> 0.9	< 0.05	> 0.5

• Note:^a Parameter outside expected limits.
• Source: Own elaboration.

The reliability of the model’s constructs was verified using the CR indicator. All constructs in the model showed values greater than 0.875, which suggests the reliability of the constructs. The standardized coefficients of the items of the measurement model scale generated by the CFA were analyzed to verify the convergent validity. All items showed satisfactory convergent validity, above 0.60. The AVE, greater than 0.50, suggests adequate convergence for all items (Table 3).

The discriminant validity was then analyzed by observing the correlation coefficients between the constructs (upper part of diagonal in Table 3), which do not exceed the 0.85 limit. Additionally, the square of the correlation between the constructs is always lower than the AVE of each construct (lower part of diagonal in Table 3), therefore supporting the discriminant validity.

Table 3
Confirmatory Factor Analysis

Confirmatory Factor Analysis | Asymptotically Distribution-free Estimates
Points of Attachment Index (PAI)
	Identification with Sport (Soccer)	Identification with Team (Flamengo)	Identification with eSport (LoL)	Identification with Team (Flamengo eSports)
Variable	CR = 0.922	CR = 0.896	CR = 0.966	CR = 0.876
IwS1	0.931
IwS2	0.875
IwS3	0.874
IwFS1		0.808
IwFS2		0.826
IwFS3		0.945
IwLoL1			0.954
IwLoL2			0.941
IwLoL3			0.957
IwFeS1				0.793
IwFeS2				0.791
IwFeS3				0.925
IwS	0.799	0.695	-0.194	0.136
IwFS	0.483	0.743	-0.120	0.293
IwLoL	0.038	0.014	0.904	0.617
IwFeS	0.018	0.086	0.381	0.703

• Note: Numbers diagonally in bold show the AVE; Numbers underneath the diagonal show the square of the correlations between constructs; Numbers on the top of the diagonal show the correlations among constructs.
• Source: Own Elaboration.

The test of the hypotheses of the study was carried out using the SEM technique, which estimates the structural paths hypothesized in the conceptual model. The structural model is shown in Figure 2.

Figure 2.
Structural Model

The explained variance of the endogenous latent variables was 49.1% for Identification with Flamengo in Soccer (Traditional sport team) and 51.7% for Identification with Flamengo eSports. The paths analyzed between the latent variables were significant for the relationships between (i) Identification with LoL and Identification with Flamengo eSports, (ii) Identification with Soccer and Identification with Flamengo in Soccer, and (iii) Identification with Flamengo in Soccer and Identification with Flamengo eSports. Thus, hypotheses H1, H2, and H3 were supported. The direct influence of Identification with Flamengo eSports and Identification with Flamengo in soccer was not verified, therefore hypothesis H4 was not supported.

As it is a non-recursive model, identification problems may appear more frequently (Blunch, 2013), therefore, to ensure identification in these cases, it is necessary to satisfy the order condition and the rank condition (Kline, 2005). As in the proposed model there are two endogenous variables that participate in the loop, each of them must have at least one (2 - 1) excluded variable, which has no effect of an endogenous variable. Thus, for identification with Flamengo soccer team, there is identification with soccer, and for identification with Flamengo eSports team, there is identification with League of Legends. Therefore, the order condition is met. The rank condition was also met as the effect patterns of the Identification with Flamengo Soccer team are different from the effect patterns of the Identification with Flamengo eSports team. Thus, the sufficient condition for the identification of non-recursive systems would be that each non-recursive causal variable, the variables in looping, be an entry point for an instrumental variable that has no other entry points in the non-recursive system. With that, all structural coefficients in the system will be identified (Mulak, 2009).

The testing of substantive hypotheses was carried out by examining the significance of the paths among the constructs for the verification of hypotheses. The results of this test are detailed in Table 4.

The results obtained allow a positive answer to the first hypothesis, supporting the direct effect of the influence of the identification of the fan with soccer on the identification of the fan with Flamengo soccer team. The explained variance of the fan identification with Flamengo in soccer is 49% for the combined samples from the events. This result is in line with the Social Identity Theory. Through the social identification, a group of individuals can reinforce their own self-esteem by belonging to a group which is valued by the individual (Ashforth & Mael, 1989). In addition, through social categorization, individuals give emphasis to in-group similarities and common values while highlighting differences in regards to out-groups, also known as intergroup discrimination (Tajfel & Turner, 1979). Among the sports fans, the need to affiliate is a common factor underlying the desire of following a sport, team, or player (Lee & Armstrong, 2008; Wann et al., 2008). Therefore, it makes sense that individuals that are soccer fans seek to participate on a team that reinforces the same individual behavior.

Table 4
Hypotheses Test H1, H2, H3, and H4

Hypotheses	Path	Hypothetical Relationship	Standardized Coefficient	CR	p-value	Outcome
H1		(+)	0.691	21.859	***	Supported
H2	Identification with Flamengo eSports Identification with LoL	(+)	0.662	28.101	***	Supported
H3	Identification with Flamengo eSports Identification with Flamengo in Soccer	(+)	0.381	11.489	***	Supported
H4	Identification with Flamengo in Soccer Identification with Flamengo eSports	(+)	0.023	0.751	0.453	Not supported
	Identification with Flamengo in Soccer	0.491a
	Identification with Flamengo eSports	0.517a

• Note:a (R2) - explained variance of the latent variable.
• Source: Own elaboration.

In regards to the second hypothesis, the results obtained allowed a positive answer as well, supporting the direct effect of the influence of the identification of the fan with LoL on the identification of the fan with Flamengo e-Sports. The explained variance of the fan identification with Flamengo eSports is 52% for the combined event samples. This result is in line with the answer to the first hypothesis and shows similar behaviors for both relationships. The influence of fan identification with an electronic sport modality on the fan identification with an eSports team is similar to the influence of fan identification with a traditional sport modality on the fan identification with a sport team. Other previous studies have also contributed to identifying a logical equivalence between eSports and traditional sports that allows scholars from different fields to further study eSports from a traditional sport framework (Cunningham, et al., 2018; Funk et al., 2018; Hallmann & Giel, 2018; Heere, 2018). The present study agrees with these previous studies as the application of the PAI Index was successful for measuring the identification of an eSports modality and the identification of an eSports team.

The results also suggest that the fan’s identification with the Flamengo soccer team influences the fan’s identification with the Flamengo eSports (hypothesis 3). Speculations can be made after checking some of the answers to the open-ended questions that the brand Flamengo (in soccer) is in the hearts and minds of many of the respondents, even if they do not follow the soccer scenario so closely. For many of the respondents, having an eSports team carrying the name of Flamengo, which is a familiar brand to many of them, is seen as positive. This is in line with social identification as it is understood that those aspects of an individual’s self-concept derive from the social categories or groups of which they feel part (Tajfel & Turner, 1979). Many respondents said they were Flamengo fans, even those who do not follow soccer very closely. With the LoL team, many expressed that now they could support Flamengo on a regular basis. As Wann (2002) states, identification of a fan with the team can even transcend a taste for sports with identification with the sport and identification with the team being separate components of the individual’s self-concept.

Finally, the results of the present study for the fourth hypothesis suggest that the influence of fan identification with a Flamengo eSports team does not affect the fan identification with the Flamengo soccer team, even if they are part of the same sports club, from the perspective of those interviewed at the Game XP 2019, nor from the perspective of those interviewed at the 2019 CBLoL Finals.

This result is counterintuitive at many levels. The Social Identity Theory, through the social identification, understands that individuals become emotionally invested when it comes to in-groups (Vinney, 2019). If individuals believes that their team is perceived as superior to others in terms of status, they create attitudes and behaviors to strengthen their association with the team (Murrell & Dietz, 1992). Fans who strongly identified with teams have emotional ties to sports organizations (Sutton et al., 1997), having these organizations as a key part of their self-concept (Gwinner & Bennett, 2008). Moreover, identifying a fan with the team can even transcend a taste for sports with identification with the sport and identification with the team being separate components of the individual’s self-concept (Wann, 2002).

One can speculate about it in terms of the influence of the Flamengo eSports over the Flamengo soccer team. Flamengo soccer team is a centenary brand, and in 2019 it was living a very good phase from a competitive standpoint. The year of 2019 is marked in the memory of Flamengo fans as one of the greatest moments in the history of the club as it won three important championships (the Carioca, the Brasileiro, and the Libertadores da América). Although it could be said that Flamengo eSports had a positive 2019 as well, winning the CBLoL for the first time after a very strong season performance. Different from its counterpart in soccer, the eSports team is in its infancy as it was founded only in 2017 and has won only one title up to 2019. Because of this fact, it is hard to compare how the identification with a newly formed team in a rising eSports modality would influence the fan identification with a centenary, highly traditional, award-winning soccer club.

The assessment also needs to take into consideration that a generational gap exists, given that eSports fans are normally young and familiar with digital technologies, which means that Flamengo’s eSports fans may have totally different characteristics from the fans of Flamengo’s soccer team, which creates difficulty to a parcel of older fans related to the new branch of Flamengo in eSports.

This result also seems to go against the belief of the club itself. Entering the eSports arena came from a demand from the younger fans who asked when Flamengo would be present in the eSports scene, but since the beginning the Flamengo eSports project divided the opinions among the fans. While many of Flamengo’s eSports fans were clamoring for the club’s entry into the scene and reacting very well to the initiative, a fraction of the traditional sports fans did not receive well the idea of their team “spending soccer money” by investing in video game athletes (Mackus, 2018).

6. Conclusion

The study was designed to investigate the influence of eSports fans’ identification on traditional sports teams and vice-versa, specifically in cases where there is an intersection of soccer teams and the eSports world. The empirical results allow supporting three of the four substantive hypotheses of the study, more specifically: (i) the influence of fan identification with a traditional sport on the fan identification with a sport team and; (ii) the influence of fan identification with an eSport on the fan identification with an eSports team; (iii) the influence of fan identification with a traditional sport team on the fan identification with the same club´s eSports team. The fourth substantive hypothesis, the influence of fan identification with an eSports team on the fan identification with the same club´s traditional sport team, could not be supported. In regards to the marketing strategy supporting Flamengo eSports, the interest of the club was to enter in the new field of eSports, to structure a project for the creation of an eSports team, to attract endemic or non-endemic sponsors to undertake the project, which should be self-sustaining from the beginning, in order to meet the demand of the younger public (Mackus, 2018). However, this study shows that fan identification with a Flamengo eSports team do not affect fans’ identification with Flamengo soccer team, therefore marketing professionals should be aware of this behavior and seek to maximize their investments taking into consideration the level of influence of one team on another. One can speculate that brands sponsoring the soccer team might have more influence on Flamengo eSports´ fans than brands sponsoring the LoL team would on Flamengo soccer team´s fans.

For professionals linked to sports clubs, the main reflection provided by the results of this study is related to the observed influence of the identification of the soccer team on the eSports team and the non-observation of the influence of the identification of the eSports team on the soccer team. Although it is known that fan identification is a combination of many other associations, it is important to recognize the direct effect, or not, of fan identification between teams within the same club.

In Flamengo´s case, the decision to open a branch in eSports was taken following the stated objectives to: (i) expand Flamengo´s area of operation in line with market trends, especially aiming young people, (ii) to win over an already captive audience of Flamengo in soccer and other sports, but lacking a presence from Flamengo in one of their audience’s other passions, electronic games, and (iii) winning over audiences which are potential Flamengo fans, mainly because they find, in electronic games, elements of connection with friends and family, who are more connected with traditional sports (Pacete, 2017). In that sense, the study shows that the identification with the soccer team can indeed bring a captive audience of Flamengo in soccer to eSports, however the contrary cannot be seen, as the identification with Flamengo eSports was not proved to influence identification with the Flamengo soccer team. Therefore, the clubs need to understand that relationship and take it into consideration when formulating their own objectives to create an eSports team.

For Flamengo, the recommendation is to reassess the reasons and objectives for the creation of the eSports team. If Flamengo seeks to increase the younger fan base of the club, the strategy makes sense, as eSports is a phenomenon of mostly younger generations, being the average age of a League of Legends player of 21 years old (ESPN Stats & Info, 2017). However, if Flamengo´s intention is to migrate the LoL fans to their soccer team, the strategy may be not effective, as per the result of this research.

It is suggested that further studies be carried out to investigate this relationship, which is especially important for sports sponsorship managers and sports club managers who need to evaluate the possibility of sponsoring or even creating an eSports team with the intention reaching new audiences and increasing identification with other sports.

6.1. Suggestions for Future Studies

This study investigated the influence of Fan Identification with the sport modality and the team in the context of professional soccer and League of Legends championships in Brazil. Due to this sample profile, it is suggested that future studies validate the conceptual model proposed in the present study within other sports or eSports, such as basketball, volleyball, CS:GO, and FIFA Soccer, among others.

Given that the fourth substantive hypothesis (the influence of fan identification with an eSports team on the fan identification with the same club´s traditional sport team) could not be supported, a qualitative analysis on Flamengo fans is also recommended. The recommendation is due to the fact that this result is counterintuitive at many levels and the quantitative research does not provide the full context in order to understand this outcome. Qualitative research could also expand the reach of the underlying theory applied herein.

It is also important to mention that in the present study, it was chosen to control the sample, restricting the collection of data to soccer and LoL fans from Flamengo, with all interviews being conducted in the city of Rio de Janeiro. It is suggested that future studies validate the conceptual model proposed in the study for other sports teams which have a presence in traditional sports and eSports; those with headquarters in other cities, or even in other countries.

The conceptual model proposed in this study could be tested in other situations for a multi-sport club. The identification can be measured between two sports, such as soccer and basketball, or two eSports like LoL and CS:GO for example. There are many examples of multi-sport clubs, like Flamengo itself. Teams with presence within more than one electronic sport can also be verified. INTZ is an example of that, with presence in LoL, CS:GO, Fortnite, Rainbow Six Siege, among other eSports.

Still on the conceptual model, to ensure the nomological validity of it, it was chosen by the authors to use constructs established in the sports literature. However, the use of measurement scales of the aforementioned constructs for the domain of eSports should still be taken with some caution. Thus, if, on the one hand, the present study contributes to the field of research through the use and testing of scales in the eSports domain, on the other hand, there is an opportunity to explore new ways of measuring these constructs. It is therefore recommended to carry out exploratory research to obtain insights into new variables that could better reflect the identification of the eSports fan.

Moreover, it is perceived an opportunity to explore whether and to what extent the compulsive consumption behavior of traditional sports and eSports could influence the proposed model. Therefore, the authors recommend the use of the “Compulsive Sport Consumption” scale by Aiken et al. (2018) to test this possible influence. Finally, in view of the mostly young and male profile of eSports fans, it is suggested testing possible moderation effects of the variables “Age Group” and “Gender”.

6.2. Limitations

This study shows limitations in regards to the methodology used, given the model does not consider the totality the variables that explain the fan’s identification with the sport modality or team. The reverse translation process has limitations since it is considered that it is almost impossible to develop a perfect translation as some items may differ in interpretation in different cultures. As the data collection was assisted and performed through interviews conducted orally by a group of interviewers, even though all interviewers were trained for the task, it implies in the possibility of the occurrence of bias caused by the interviewer, which represents another limitation of the present study.

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Publication Dates

• Publication in this collection
  17 Apr 2023
• Date of issue
  Mar-Apr 2023

History

• Received
  22 June 2021
• Reviewed
  02 Sept 2022
• Accepted
  28 Apr 2022
• Published
  19 Dec 2022