Fan identification in football: professional football players and clubs competing for fan loyalty

With more than five billion fans spread over all continents Football is the world's most popular sport and has grown into an international billion-dollar business (FIFA, 2020; Nielsen, 2018). The 20 largest clubs worldwide alone generated 8.2 billion euros in turnover in the 19/20 financial year (Deloitte, 2021). Nevertheless, a change in the behaviour of football fans can be observed (FIFA, 2020). The advancement of technology and the associated high connectivity of mobile devices allow users to enjoy numerous benefits. This applies to social connections consistently at any time and place, instant communication, information and entertainment (Leung and Zhang, 2016). These technological developments are not stopping at football either and influence fans' behaviour (FIFA, 2020). Today, players and fans are directly connected through social media, enabling a dynamic two-way exchange of user-generated content (Kaplan and Haenlein, 2010), a previously impossible form of reciprocal communication between both parties (Pegoraro, 2010). A related effect is the possibility to follow the performance of one's favourite league, team or player regardless of geographical boundaries and to be able to access content that goes beyond the actual game. Social Media is becoming increasingly important for stakeholders in the sports business as it is becoming a focal point to communicate with sports consumers (Mahan, 2011). In addition, social media is also of growing importance for sports sponsors and sponsorship activation (Koronios et al., 2022). In line with Sutton et al. (1997) this new way of connecting athletes and fans offers the possibility for a higher identification of fans to the sport. Also from a club perspective, social media is a valuable tool as it enables personalised communication with fans and is thus a relevant tool to increase identification with the team (Meng et al., 2015). As star players transform into popular cultural products through the commercialization of the sports industry, this remarkable increase in information available to football fans makes it easier for them to identify with certain individual players (Gilchrist, 2005; Summers and Johnson Morgan, 2008). However, individual players form not only a brand on their own but represent a key product of their team's brand (Bauer et al., 2008). Traditionally, football fans are supporters of a single favourite team, which leads them to support the players that are part of that club's squad. However, recent transfers of stars like Cristiano Ronaldo provide evidence that many fans are willing to move along with those players and become fans of their new team (ESPN, 2018; Lewis, 2018). Alonso-Dos-Santos et al. (2018) identified relationship quality as one of the most important variables influencing customer engagement with sponsors. This emphasises the importance of understanding the relationship quality and thus the identification of fans with clubs and individual players for the stakeholders involved. International sport marketing is growing in importance and an understanding of fan interests is vital in ensuring effective marketing. Information on trends in fan interests allows clubs and sponsors to align their strategies to fit those interests. Furthermore, insights into typical demographic characteristics of high-identification football fans can be exploited for creating fan profiles and targeting highly engaged fan groups. The impact of different demographic variables on identification levels is of particular interest. This paper therefore uses an online survey to investigate whether the increasing accessibility of star athletes leads fans to feel more connected to individual players or whether it is more important for them to be a loyal supporter of a particular team. Furthermore, it will be explored to what extent a fan's loyalty towards their favourite team (referred to as “fan loyalty”) is impacted by both their identification level as well as other demographic variables. By adding an additional perspective to better understand sports fans, this research contributes to the growing body of publications in the field of sports consumer research (e.g. Dos Santos and Moreno, 2018; Fujak et al., 2018; Funk, 2017). This paper can serve as a gateway to further studies on the antecedents and drivers of fan identification and pinpointing a trend in fan identification levels through longitudinal studies. It bridges the gap between the well-studied fields of team identification and athlete brand image by adding the dimension of fan identification to individual athletes and comparing it to team identification, as well as assessing the impact on fan loyalty. Despite numerous studies on fan identification and athlete brand, there appears to be a lack of research on the relationship between team identification and single athlete fan identification and prioritization between the two. The purpose of this study is to investigate the level of identification fans show towards their favourite team compared to their favourite player. The level of identification of a fan towards their favourite team will be referred to as “team identification’, while the term “player identification” describes a fan's level of identification with their favourite player.

In relation to sport, identification is referred to as “an orientation of the self in regard to other objects including a person or a group that results in feelings or sentiments of close attachment” (Trail et al., 2000). Sport as an industry has many unique features (Mullin et al., 2000) among which is the ability to generate a feeling of personal connection with supporters by stimulating personal emotional responses (Sutton et al., 1997). This is true to the point where certain fans see being a “fan’ as part of their identity and personality (Tapp, 2004; Wann and Branscombe, 1993). The clear distinction between the terms “spectator” and “fan” needs to be highlighted. While spectators take part in watching games, their connection to the team usually fades once the event has finished. Fans, on the other hand, feel a much stronger connection to their favourite team or player which remains outside matchdays (Wann, 2006). The high identification of a fan requires a certain level of psychological commitment like the psychological connection to a brand (Bauer, 2008; Beatty and Kahle, 1988). This study is underpinned by Wann and Branscombe's (1993) Sport Spectator Identification Scale (SSIS) as well as Bauer et al., which serves as the foundation of the approaches used in this work. The SSIS manages to incorporate both the fans' cognitive and emotional identification with their favourite team, which can be transferred onto their favourite player to offer grounds for comparison. The identification with a certain club can help a person define themselves through self-categorization (Hogg et al., 1995), and supporting their team can become a vital part of their social identity (Wann et al., 2000). Therefore, social identification was discussed heavily in relation to team identification (Carlson et al., 2009; Kwon et al., 2007; Madrigal and Chen, 2008). On this note, several researchers suggested that the “need to belong” is an antecedent of fan identification (Gwinner and Swanson, 2003; Wann and Pierce, 2003).

When looking at existing literature, it becomes apparent that several studies have been conducted on the topic of fan identification related to sports teams (Bauer et al., 2005; Gladden and Funk, 2001; Meng et al., 2015; Wann and Branscombe, 1993; Theodorakis et al., 2012). According to Sutton et al. (1997), identification to a team is influenced by four main variables: team characteristics, organisational characteristics, affiliation characteristics and activity characteristics. Both the antecedents and the outcomes of fan identification have been discussed in several studies (Gwinner and Swanson, 2003; Koronios et al., 2021; Matsuoka et al., 2003; Nassis et al., 2012; Wann, 2006). Wann et al. (2006) linked high fan identification levels to an increase in psychological well-being, while negative consequences like the high tendency to respond aggressively were also examined (Wann et al., 1999). Donavan et al. (2005) identified sports fan affiliation motivation to be positively influencing team identification. The drivers of fan identification have also been analysed in the context of successful and unsuccessful teams, together with the consumption of team-related goods (e.g. merchandise) (Fisher and Wakefield, 1998). Similarly, performance-dependent fluctuations in identification and association levels were discovered among sports fans (Cialdini et al., 1976; Tajfel, 1981). It was found that fans saw themselves as part of the collective much more when their team was winning compared to when performance was poor. Fans tend to use the terms “we” or “us” when the team is doing well, wanting to be associated with the team. However, many referred to the team as “them” when performance was poor, distancing themselves from an association with failure. This phenomenon was described as “BIRGing” (basking-in-reflected-glory) in the case of success, and CORFing (cutting-off-reflected-failure) in the case of negative results (Cialdini et al., 1976). Since a large percentage of sports fans follow sports through media from home, social media as an additional channel alongside traditional media are an important strategic tool for sports managers to engage with their respective target audience (Koronios et al., 2020). Meng et al. (2015) demonstrated in their study of the NBA that social media provides an opportunity to increase team identification away from the sporting action through targeted, relevant and personalised communication opportunities. This offers many additional opportunities for club managers, especially in the off-season. Traditionally, fans of team sports support a certain team rather than a certain athlete and the economic situation of many clubs relies on this fact (Fink et al., 2002). As athlete brands are gaining in reach and significance, it is important to assess whether football teams remain the primary identification focus of fans. This leads to the first two hypotheses:

In addition to this, research (Koch and Wann, 2016) has focused further on gender-dependent differences in team identification and its drivers (Wann et al., 2001). Besides gender, Branscombe and Wann (1991) brought forward the impact of a fan's geographical distance to their favourite team on the result-dependent nature of their support. Other authors discussed the identification of fans supporting distant teams in the context of club relocation in the United States (Foster and Hyatt, 2007; Kraszewski, 2008). They found that fans can maintain high identification levels through different methods, despite the geographical distance separating them from their favourite team. Geographical distance of fans to their club and its influence on fan identification has also been studied using the example of Chinese people who follow both the Chinese and the American basketball league (Menefee and Casper, 2011). The authors found that the identification levels were higher towards the American league despite the geographical distance. This study was limited by focusing on only two leagues with large dissimilarities in level, size and attractiveness. To test this finding on a larger, more international scale, the following hypothesis is proposed:

Concerning fan identification to individual players, studies have mostly been closely linked to athlete brand and dividing it into different dimensions (e.g. Arai et al., 2013). The MABI model (Arai et al., 2014) divides athlete brand image into three dimensions: athletic performance, attractive appearance and marketable lifestyle. Little research has focused on the attachment of fans to single athletes, as it was often seen as a mere extension and additional element of team identification (Trail et al., 2000; Robinson et al., 2004). Another important element, the drivers of fan loyalty, have been thoroughly discussed (Funk and James, 2006). Fan identification to both club and player has been studied in relation to trust and vicarious achievement motive (Wu et al., 2012). Identification to individual players strongly depends on the players' performance and is likely to fluctuate as the performance improves and deteriorates (Chung et al., 2019; Wu et al., 2012). Hoegele et al. (2014) identified that football stars have a significant impact on the degree to which fans identify with their team. According to Robinson et al. (2004), association is sparked much easier with a single athlete than it is with a more abstract concept like a football club. Players are more tangible and can stand out through bursts of excellent performance grabbing a spectator's attention. However, the players of the team are a valuable factor to help reach new audiences and develop a relationship with the team brand (Wong and Hung, 2023). A study by Wu et al. (2012) incorporated the relationship between fans and a club as well as individual players. While this study looked into the antecedents of re-patronage intention, it was heavily focused on establishing trust as a key indicator during the measurement of fan identification levels.

However, little attention has been given to the difference in both team identification and player identification levels depending on the favourite player's club. Robinson and Trail (2005) discovered that the identification of sports fans to a certain player can carry over to their general identification with the sport. Player identification has been shown to positively influence the identification levels of a club (Hong et al., 2005). Carlson and Donavan (2013) applied social identity theory to analyse the impact of athlete brand on fan identification. Ultimately, identification to single players could increase consumption behaviour related to a whole club. The finding that identification with the player affects identification with the team raises the question of whether identification with both is increased when player and club overlap (Carlson et al., 2009). This leads us to the examination of the level of interrelation between identification to both a club and a single athlete, formulated as follows:

Oliver (1999, p. 34) defined loyalty as “a deeply held commitment to re-buy or re-patronise a preferred product/service consistently in the future, thereby causing repetitive same brand set purchasing, despite situational influences and marketing efforts having the potential to cause switching behaviour”. In a sporting context, fan loyalty creates a constant presence of fans regardless of the club's performance (Gladden and Funk, 2001). The differentiation between the attitudinal and behavioural aspects of loyalty has been repeatedly brought forward (Jacoby and Chestnut, 1978; Baldinger and Rubinson, 1996; Funk and Pastore, 2000; Jensen and Hansen, 2006). Attitudinal loyalty quantifies the degree of attachment, commitment and general positive attitude towards a brand (Jacoby and Chestnut, 1978; Olsen, 2007; Bauer et al., 2008). Attitudinal loyalty often takes the role of a mediating variable between different kinds of predictors and customer behaviour (Maderer et al., 2016). Previous studies on attitudinal behaviour separated three main segments: persistence, resistance and inner attachment (Gladden and Funk, 2001; Mahony et al., 2000). O'Reilly and Chatman (1986) claim that the individual view on the importance of long-term success plays an important part in quantifying their commitment. Behavioural loyalty, on the other hand, focuses on interactions with the brand and can be expressed through game attendance, the purchase of merchandise, displaying the club emblem and colours, following club-related content in the news or on social media, etc (Funk and Pastore, 2000; Gladden and Funk, 2001; Mahony et al., 2000; Sumida et al., 2014). Both attitudinal and behavioural loyalty is essential when measuring fan loyalty, as neither of them can capture the full spectrum of fan loyalty as a standalone concept (Irianto and Kartikasari, 2020; Jacoby and Chestnut, 1978). Both elements have previously been used by researchers as joint concepts (Gladden and Funk, 2001; Mahony et al., 2000; Bauer et al., 2008). This same approach is used in this study. A connection has been established between identification and loyalty by multiple studies (Tajfel and Turner, 1986; Sloan, 1989; Wann and Branscombe, 1993). Moreover, identification was found to impact several factors such as increased consumption (Kwon et al., 2007) and higher viewership both on television and in terms of attendance (Carlson et al., 2009), all of which can be considered indicators of loyalty. Over a quarter century after Wann and Branscombe's (1993) Sport Spectator Identification Scale was created, applying it to a significantly larger and more diverse group of participants could prove beneficial. This leads us to the following hypothesis:

Figure 1 presents the model that links the individual hypotheses of this study.

An online survey was developed to test the hypotheses and the unit of analysis was the individual. The distribution of the survey to participants took place in football-related online forums on reddit (e.g. r/futbol; r/footballmanagergames; r/FIFA; r/FantasyPL; r/soccer) as well as on specific club related subreddits (e.g. r/schalke04, r/gunners, r/asroma, etc.) over a period of 5 weeks, between April 2020 and May 2020. Reddit was chosen as the platform consists of thousands of active communities (subreddits) dealing with specific interests and topics. These diverse and specialised communities were an advantage for this research project, as international football fans were needed for this survey. Furthermore, Reddit has a diverse user base from all over the world, which is advantageous for the present international approach of the study. As data collection took place in online football forums, participants are more likely to show higher identification levels due to being active users of the forums. While this data collection method may have potentially caused a slight bias of the collected data, it provided the study with bigger accessibility and reach, benefitting the study in many ways and adding value to the different findings.

The original survey was created in English and later translated into German, French, Spanish, Italian and Portuguese to make it accessible to a more international audience and maximize the number of potential participants. Backward translation by different bilingual translators (with the material translated from English into the respective language and back into English; versions compared; discrepancies resolved) was used to ensure consistency between the original English version and the individual survey translations (Mullen, 1995). A potential limitation of this study is the distribution of the translated questionnaires. Most of the distribution took place in predominantly English-speaking forums which, making several of the translated versions of the questionnaire almost redundant as very few participants made use of them. This was reinforced by the lack of visibility of the option to change the language on the mobile version of the questionnaire. Making the questionnaire available through an alternative platform with better visibility and adopting specific distribution methods depending on the version of the questionnaire could help resolve these issues. Furthermore, it should be noted that the sample is not representative, which may limit the interpretations of the results. It cannot be ruled out that filling out the survey online resulted in a larger number of young and female participants in the sample. Therefore, the sample suffers from selection bias (Heckman, 1979) as 89.4% of the respondents are 33 years old, or younger (see Table 1). It should also be mentioned that the sample has a high proportion of American and Luxembourgish respondents.

The questionnaire was developed by adapting existing questions that had been validated by other researchers. A five-point Likert scale was used in each case with the response categories 1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree. Team identification and Player identification were each measured using a 9-item scale adapted from the Sport Spectator Identification Scale (SSIS) of Wann and Branscombe's (1993). This instrument is widely used, adapted to a sports context and is appropriate to be used in a cross-national study (Wann et al., 2001; Wann, 2006). Sample questions for Team identification are, for example (a) It is very important to me that my favourite team wins; (b) My friends strongly see myself as a fan of my favourite team; (c) Being a fan of my favourite team is very important to me. Sample questions for Player identification are, for example (a) It is very important to me that my favourite player wins; (b) My friends strongly see myself as a fan of my favourite player; (c) Being a fan of my favourite player is very important to me.

Fan loyalty was evaluated using a 13-item scale based on behaviour loyalty and psychological commitment drawn from Bauer et al. (2008). These items aimed to identify the level of commitment of participants towards their favourite club and their willingness to abandon it. Sample questions were, for example (1) I would defend my favourite team in public even if this caused problems; (2) I will not change my affiliation from my favourite club to another club in the future just because it is not successful anymore. (3) I purchase a lot of club-related merchandise. The Cronbach's alpha of all three instruments indicated appropriate reliability with 0.77 for Team identification, 0.87 for Player identification and 0.78 for Fan loyalty.

Participants were asked to give information about their gender, age and nationality.

Respondents were asked to indicate their favourite team and player and whether their favourite player plays for their favourite team (yes or no), or if their favourite player has played for their favourite team in the past (yes or no).

The vast majority of the world's most popular players (e.g. measured by market value, salary and social media followers) play in European leagues for the world's most valuable European clubs (Nielsen, 2018; Deloitte, 2021). Due to this prominent position, these clubs and leagues are interesting for fans from outside Europe, which is why there is growth potential for European football there. Information about fans from non-European countries and differences between them and European fans is therefore of interest to football managers in Europe and important for their internationalisation strategies. For this reason, all participants who stated that they were from a European country were placed in one group, all other participants were placed in the non-European group.

All individuals born in the big-five league countries (i.e. UK, Spain, Germany, Italy and France) were clustered into one group. All other individuals were clustered in non-big-five league countries.

The target group of this study was football fans in general. A total of 4,707 respondents started the survey and 4,706 were included in the data analysis after data cleaning.

The final sample consisted of 4,706 participants from 121 different countries. People from the England (18.9%, n = 18.9) and the United States (17.9%, n = 17.9) were most represented. Male respondents represented 96.7% of the sample (n = 4,551), whereas female respondents represented only 2.8% of participants (n = 130). A total of 0.5% (n = 25) of participants identified as neither male nor female or preferred not to indicate their gender. The socio-demographic profile of the survey participants is presented in Table 1. On average, the amount of time to fill out the survey was five minutes and thirty-five seconds.

Descriptive statistics and multilevel regression analyses were conducted using SPSS 25 for Mac. Multilevel models were used to predict team identification, player identification and fan loyalty. These multilevel models allow to account for compositional variation of individuals (level one) living in different countries (level two) (Hox, 2002). Regression coefficients and variance components are estimated with the full maximum likelihood (FML) method. The average sum-score of the scales of team identification, player identification and fan loyalty were used in the analyses. Following four models were sequentially developed. For team and player identification only Model 4 will be shown, for fan loyalty the full four models will be depicted (see Table 2).

For all analysis, significance was set at p = 0.05.

Table 3 shows the ten most popular players and clubs. Lionel Messi (8.7%, n = 408) and Cristiano Ronaldo with (7.5%, n = 351) were by far the most mentioned players. Among the ten most popular players, two pairs of players who play for the same club are represented: Cristiano Ronaldo and Paulo Dybala (Juventus Turin) and Thomas Müller and Robert Lewandowski (Bayern Munich). Lionel Messi, Paulo Dybala (Argentina) and Kevin De Bruyne, Eden Hazard (Belgium) are the only players in the list who have the same nationality. Bayern Munich, the only German club on the list, is the most mentioned with 10.9% (n = 517). In seventh place, with 4.1% (n = 192), FC Porto is the only club outside of Europe's big-five leagues. The other clubs in the list all come from England or Italy.

Table 4 represents the factor analyses of the used scales in this study: Team identification; Player identification; Fan loyalty. All factor loadings exceeded 0.4 indicating good scale reliability.

Table 5 presents the final multilevel models for team identification and player identification. For both variables these multilevel models were better models than the single-level models, indicating that where respondents come from is an important aspect to take into account to know how much they identify with their team.

Results of the final multilevel-model of team identification showed that (a) male respondents are more likely to identify with their team than female respondents (β = −0.105; p < 0.05); (b) younger respondents identify more with their team than older respondents (β = −0.104; p < 0.001). (c) respondents with alignment between their favourite player and team have a higher identification with their team (β = −0.167; p < 0.001). No second-level predictors could be noted.

Results of the final multilevel-model of player identification showed that (a) female respondents are more likely to identify with their favourite player than men (β = 0.184; p < 0.01); (b) younger respondents are more likely to identify with their favourite player than older respondents (β = −0.262; p < 0.001); (c) Respondents who's favourite player plays for their favourite team have a higher player identification (β = −0.340; p < 0.001). On the second level it was noted that (a) people outside Europe identify more with players than people inside Europe (β = 0.174; p < 0.01). People not living in one of the big-five league countries are more likely to identify with their favourite players than people inside one of the big-five league countries (β = 0.194; p < 0.05).

Table 6 presents the results of the different multilevel models in the order they were developed. The second model improved significantly compared to the first model (p < 0.001), indicating that a part of the variability of fan loyalty is located at the second level. The covariance parameters of the random effects of model 2 show that 97.6% of the variance in fan loyalty is situated at the individual level, meaning that 2.4% is located at the level of the country where the respondent is from.

Model 3A demonstrates significant associations of age with fan loyalty: young adults (younger than 25) report higher levels of fan loyalty (p < 0.001). Model 3B added the variable whether team and player were aligned; respondents who indicated that their favourite player is currently playing for their favourite team indicated to have a higher fan loyalty (p < 0.001). Model 3C added player and team identification as predictors. These are both very strong predictors of fan loyalty (p < 0.001). Together player and team identification account for 60% of the variance on the first level of fan loyalty. This means that whether a fan will remain loyal will depend largely on how he identifies with his favourite team and with his favourite player. Additionally, it is seen that age is no longer a significant predictor of fan loyalty after adding team and player identification was added to the model.

Model 4 adds the second level predictors. It is noted that if a fan lives in a country from one of the big-five leagues (i.e. UK, Germany, Italy, Spain and France) the fan loyalty is higher (p < 0.01). This accounts for 15% of the variance on the second level. The amount someone identified with his/her team and favourite player accounted for 71% of the variance on the 2nd level.

The main results of the final multilevel model can be summarized as such: (a) Team identification (β = 0.623; p < 0.001) was the strongest predictor of all variables, this means that the more somebody identifies with his/her favourite team the stronger the loyalty of the fan will be. (b) Player identification (β = 0.044; p < 0.001) was also a strong predictor of fan loyalty. (c) alignment between favourite fan and team (β = −0.026; p < 0.01) was also a significant predictor of fan loyalty. (d) no sociodemographic variables were significant predictors of fan loyalty. (e) respondents coming from the big-five league-countries (β = −0.054; p < 0.01) had a higher fan loyalty.

The results provide support for all tested hypotheses (H1, H2, H3, H4, H5, H6). The confirmation of H1 indicates a positive correlation between team identification and loyalty. Fans who have a strong emotional bond with their favourite sports team and identify with it are accordingly more likely to show higher loyalty to that team. This finding has implications for the management of sports teams, as it suggests that building strong fan identification with the team can lead to greater loyalty, which in turn leads to greater support for the team and greater fan engagement, and therefore potentially more revenue for the sports team. This should be taken into account in the development of targeted strategies to cultivate and strengthen fans' emotional bonds, which ultimately leads to a more engaged and supportive fan base and can make sporting organisations less dependent on sporting results.

The confirmation of H2 shows that overall, football fans identify more with their favourite team than their favourite player. Although athlete brands are on the rise with some boasting more social media followers than the team they play for, they generally remain short of competing with their club in terms of fan identification by quite a long distance. Aligned with findings by Pegaroro et al. (2010), athletes might not be sufficiently taking advantage of their large social media audience to build their brand, building identification among their followers.

The confirmation of H3 supports previous research made on the impact of the geographical position of fans compared to their favourite team (Menefee and Casper, 2011). Participants supporting a foreign club have shown significantly higher team identification levels than those supporting a local club. In fact, descriptive statistics showed that their mean score was higher for each of the items, besides item 5 (“I closely follow my favourite team in the newspaper and in magazines.”) which is likely simply the case due to the lack of such possibilities in countries different from the club's home country. This finding is specifically valuable for clubs, as it displays the devotion and potential of foreign market consumers. A specifically large difference was found for item 9 (“I often display my favourite team's name or insignia on my clothing, where I live or at my place of work.”) (μ = 3.22 for local fans compared to μ = 2.78 for fans living further away). The reason for this finding might be the fact that fans living further away from their favourite club are trying to express their support through the purchase of merchandise since they are often unable to attend live games or even follow them on the television. As one would expect, local fans scored significantly higher for item 33 (“I often attend games of my favourite team live in the stadium.”) since the opportunity to attend games is significantly larger for them than it is for fans living abroad.

Another major finding is the confirmation of the impact a player's club has on the identification of their fans, and vice-versa. This was confirmed through H4 and H5. A fan's identification towards their favourite club could potentially be able to rub off onto their connection with their favourite player. Fans have a weaker connection with their favourite player if he has never played for their favourite team. The same applies to their team identification. Therefore, it could be assumed that identification can be transferred between teams and players. Additionally, fans whose favourite player has previously played for their favourite team also showed higher identification levels towards both player and club than those whose favourite player never played for their favourite club. This may show that the transfer of identification onto another actor (team → player; player → team) is long-lasting, even after the combination of both actors has been dissolved. This would correspond to findings related to fans of relocated clubs (Foster and Hyatt, 2007; Kraszewski, 2008). However, neither team identification nor player identification is quite as high as those of fans whose favourite player and club are connected (favourite player plays for favourite club).

The correlation between fan identification and fan loyalty was confirmed through H6, supporting the findings of previous studies on the connection between identification and both attitudinal and behavioural loyalty (Tajfel and Turner, 1986; Stevens and Rosenberger, 2012). Fans who feel a closer connection towards their favourite team are more likely to remain a fan regardless of the team's performance. Questionnaire sections on team identification and fan loyalty both included items concerning participants' consumption of club-related content, which makes a correlation between both concepts appear rather straight-forward.

In addition to this, differences were found when comparing the identification levels of fans between 18 and 33 years old to those of fans over 33. It becomes apparent that younger fans show higher identification to both their favourite team and their favourite player. The questionnaire used in this study focused on active players only for measuring player identification, since the current club of that player was another crucial variable which was collected. Therefore, the large difference in player identification levels between younger and older fans may be partly due to the fact that older fans might have a favourite player that has retired from football. Because of this, they were forced to pick a different, currently active player which they might not support to the same degree. Higher player identification levels of younger participants could be connected to their increased use of social media, where athletes are emerging as individual brands and connection with supporters.

Meaningful differences were also detected between fans from countries hosting the big-five leagues in European football (England, Germany, France, Spain and Italy) compared to fans from countries whose local competitions are outside of the top leagues. The latter group showed higher levels of identification towards both their favourite team and player compared to those from big-five leagues. The difference in player identification levels is specifically noticeable, showing that fans from countries with less reputable leagues are likely to feel a stronger connection towards their favourite player. This finding could be a consequence of the confirmation of H3, as people from countries with less reputable leagues are likely to support bigger foreign clubs, which influences their behaviour as a fan and relates back to H3. When it comes to fan loyalty, no difference was found between both groups.

Despite the male-dominated participant sample, a gender-related difference in identification was identified. While the fan loyalty index was similar for both genders, female participants showed significantly higher levels of player identification compared to men. This finding could be explained by the impact of physical attraction to athletes of the opposite gender. The mean level of team identification was slightly higher among male participants.

This research adds not exclusively from a theoretical perspective to the growing body of publications in the field of sports consumer research (e.g. Magnussen et al., 2012; Na et al., 2020; Tinson et al., 2017) it furthermore assists managers in developing a better understanding of the quality of relationships and thus the identification of fans with clubs and individual players. The results provide insights of fan interests, which is essential for effective marketing, as information on trends in fan interests allows for a better tailored strategy for clubs and sponsors. The results of this study show that football fans identify more with their favourite team than with their favourite player. Although athletes' brands are on the rise and some of them have more followers on social media than the team they play for, they usually cannot keep up with their club when it comes to the level of identification of fans.

The fact that this study demonstrated that the relationship between a fan's favourite team and favourite player has a significant impact on the level of identification with both can provide useful guidance to club managers for their squad planning and the design of marketing campaigns involving the club's players. Interesting specifically with regard to potential international partnerships between advertising brands and clubs is also the finding that fans who support a foreign club show significantly stronger team identification than those who support a club from their own country or region.

Future research is encouraged to further investigate differences in fan identification among different age groups and to analyse trends in player identification compared to team identification. Furthermore, the effects of a transfer of a fan's favourite player to another club on their identification levels are proposed as a research focus. While this study was able to find differences in identification depending on the player's club, no data was collected on identification levels previous to a player's departure or arrival. Pinpointing a shift in identification during the event of a player transfer could prove very insightful. Again, longitudinal study design can be applied to measure a fan's identification before and after their favourite player transfers to a different club, including the fans' intention of patronage. Of further interest could also be a more specific analysis of the impact of geographical factors on team identification. Here, trends between certain countries could be analysed while focusing on certain leagues. Further, researchers are encouraged to look into the specifics of gender differences in fan identification. The motivation behind gender-dependent preferences, specifically the preference to support single athletes among female fans, could be examined further.

To conclude, the findings of this study shed light on trends in fan identification with teams and individual athletes. Despite the ongoing emergence of social media and increased accessibility to athletes, clubs remain the focal point of sports fans' identification. This is of great importance as clubs heavily rely on fan-generated revenue streams like the sale of tickets and licensed merchandise. Fans who are separated from their favourite club by geographical distance tend to show higher identification than local fans. Furthermore, identification levels towards both a team and a single player are significantly higher if they collide, meaning if the player is under contract at that same club. In this case, both actors seem to be reinforcing one another by potentially boosting the other's identification levels. The practical implication to this finding is the fact that both clubs and athletes need to be aware that their brands are influencing each other and defining how strongly fans feel connected to them. Player transfers away from a club can weaken identification felt towards the player as well as the club. On the other hand, the player and their new club may benefit from joining forces.