Socioeconomic position and sports in the US today: the economic and cultural capital of sports followers

Abstract

Purpose

This study aims to explore the relationship between social class and sports following in the United States, addressing a gap in research that has largely overlooked spectator sports in sociocultural analyses. The paper seeks to be an expanded update on previous work focusing on how socioeconomic factors such as income and education interact with sports engagement.

Design/methodology/approach

Employing 2023 national survey data from the United States, this study analyzes the following of 31 different spectator sports in relation to income and education. The methods include the use of Cramer’s V statistic to assess associations between sports following and socioeconomic variables and multiple logistic regression analysis to understand the relative predictive power of these variables on sports following.

Findings

The study reveals significant socioeconomic associations in sports consumption patterns in American society, with higher income and education levels generally predicting an increased likelihood of following a wide range of sports. Notably, international soccer leagues like the English Premier League and La Liga showed the strongest associations with higher socioeconomic status, suggesting their following might serve as particularly potent markers of sociocultural distinction.

Originality/value

This research provides a contemporary empirical update to the study of social class and spectator sports in the US, expanding the understanding of the evolving landscape of sports consumption and its socioeconomic connections. It underscores the importance of considering sports following as a vital aspect of cultural engagement, reflecting and reproducing broader socioeconomic stratifications. The findings offer new insights into how factors of social class shape sports consumption today, highlighting the role of sports in the cultural life of different social classes in the US.

Citation

Gemar, A. (2024), "Socioeconomic position and sports in the US today: the economic and cultural capital of sports followers", Equality, Diversity and Inclusion, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/EDI-02-2024-0066

Introduction

Social research has long recognized the engagement and “consumption” of cultural forms and leisure practices as an indicator of social status, a concept explored by numerous scholars of society, culture, and social class (e.g. Adorno and Horkheimer, 1944/2016; Bourdieu, 1984; Bennett et al., 2009; Gans, 1974; Savage et al., 2015; Veblen, 1899/1934; Weber, 1922/1978). However, the relative social position of this cultural engagement and its ability to reflect and reproduce social position vary across time and geography, with ongoing debates about how patterns of cultural engagement are stratified within societies. An oft-ignored or missing element of culture within this intellectual tradition is sport (Gemar, 2019a; Kahma, 2012).

More than two decades ago, Thomas Wilson (2002) published a highly influential article on the relationship between socioeconomic position and sports engagement in the United States. The data used for that foundational research is now more than thirty years old, and the prominent survey program that it relied on, the General Social Survey from the National Opinion Research Center (NORC) of the University of Chicago, has, in the decades since not asked Americans questions about their sports engagement. This latter fact illustrates the lack of mainstream consideration of sports' place in society within social sciences and social researchers, while the need to update the former illustrates the lack of scholarly investigation into the relationship between sport and social class (Cunningham, 2023). This relative lack of scholarly work is even more pronounced in its absence from the American context, where sport has among the highest levels of cultural salience and social penetration. However, academic assessments of socioeconomic position in general and concerning sports are less common than in other contexts.

Both professional and collegiate (university) sports have large followings in the United States and are big business. The largest professional sports leagues, such as the National Football League (NFL) and National Basketball Association (NBA), command significant attention and comparative revenue globally, despite their relatively more localized appeal than international sports like soccer. With its growing market in China and increasing popularity in Europe and Africa, the NBA stands as an exception (Neelakandan, 2023). The Super Bowl, the annual NFL championship event, consistently ranks as the most watched US television program, as do other live sporting events, highlighting sports’ strong cultural penetration in an otherwise fragmented media landscape (Sherman, 2021). Recent trends, like the surge in sports betting, suggest even further potential growth in sports' cultural saliency in the American context. Depending on the source, context, and the specific metric employed, findings offer evidence that more people engage with these spectator sports than directly participate in sports or exercise activities (Elgaddal et al., 2022; Gemar, 2019a) and that people watch more sports than they directly practice (Warde, 2006). However, much more is known about the relationship between social class and socioeconomic position regarding this direct participation than engagement with spectator sports. This paper seeks to provide a current and comprehensive investigation into the socioeconomic patterns of sports followers in the sports-rich environment of the contemporary United States to help remedy this knowledge gap regarding the socioeconomic place of spectator sports in American society and the social place of spectator sports more broadly.

Using a nearly exhaustive list of widely followed sports in the American context, it also seeks to be an important empirical update to Wilson’s work on the United States, with data exactly thirty years more recent (2023 vs. 1993) and with a specific focus on the following of spectator sports. This article focuses on the socioeconomic relationships of Americans to spectator sports, following Wilson’s (2002) emphasis on using economic and cultural capital to assess socioeconomic position. While scholars of culture have broached more comprehensive understandings of social class or used social class interchangeably with socioeconomic position, in the American context, as in others, class and status also have strong relationships to both race and gender, with social judgments about one’s social position intersecting with these and other identities to produce more robust subjective judgments of class position (Moore-Berg and Karpinski, 2019). While controlling for race and gender in the empirical analysis of this paper, we focus primarily on income and education in understanding socioeconomic position, even as future work can and should explore more comprehensive conceptualizations of social status in relation to spectator sports consumption. To accomplish the aims of this paper, we seek to answer the following three research questions:

RQ1.

What are the relationships between sport following in the United States and the socioeconomic variables of income and education?

RQ2.

Do these relationships differ between different sports or socioeconomic variables?

RQ3.

What do these findings tell us about the relationship between socioeconomic position and sports following in the US today?

Socioeconomic position and spectator sport engagement

Social class and sport as a cultural form

The intellectual tradition of the sociology of culture has produced much work focused on social position and cultural engagement. Some of this work investigates broad cultural consumption patterns that may include a broad sport or physical activity category, but many do not. Sports are generally sidelined in this scholarly tradition and these scholarly discussions. While recent scholarship is beginning to address this gap, it is still studied much more modestly than other cultural forms like music and food (Borgers et al., 2015; Gemar, 2019b; Kahma, 2012; Widdop et al., 2016). Aspects of sports fandom, especially across multiple sports, have yet to be explored similarly (Gemar and Pope, 2022).

In sociology and other social sciences, Bourdieu’s influential “La Distinction” (1984) profoundly contributed to understanding the relationship between cultural consumption and social position. Bourdieu’s analysis of French society in the 1960s revealed that higher social class fractions prefer culturally esteemed activities, while lower class fractions gravitate towards less valued forms. Bourdieu categorizes capital into economic, cultural, and social forms, each integral to an individual’s social standing (Bourdieu, 1986). Economic capital links to income and wealth, cultural capital to educational qualifications, and social capital to the extent and status of social connections by which advantages can accrue. These capitals are interchangeable, collectively shaping an individual’s social position while enabling social class position reproduction. In Bourdieu’s work, this is primarily defined by one’s possession of economic and cultural capital, as his conceptualization of social capital is less developed (Gemar, 2024), often only deployed when he desires it to do specific conceptual work (Warde, 2004), and never operationalized (Pinxten and Lievens, 2014). This paper likewise uses operationalizations of economic and cultural capital (see also Data and Methods section).

Regarding sport, both Bourdieu and others studying culture have found direct sports participation positively associated with elevated cultural capital (Bennett et al., 2009; Bourdieu, 1978, 1984; Gemar, 2021a; Widdop and Cutts, 2013; Wilson, 2002), as well as the bodily aesthetic that results from physical activity (Bennett et al., 2009; Bourdieu, 1984; Warde, 2006). Conversely, Bourdieu (1978) viewed professional sports consumption as a lower form of cultural activity, appealing mostly to the lower social classes and aligning with the consumption of other forms of popular culture. This perspective, shaped during a time before the widespread proliferation of sports media, becomes even more relevant today as professional sports have evolved into major spectacles, largely consumed through broadcast (Bourdieu, 1978; Gemar, 2019a). However, even going back to the time of Bourdieu, there was a distinction between in-person attendance and television consumption, with the former often being associated with a higher social position (Fürtjes, 2016).

While sport is often left out in both cultural theory and studies of cultural engagement, scholarly studies that address sports and elements of social class often corroborate the notion that those of higher socioeconomic status participate more in sports and frequently attend sporting events. These studies commonly find that direct participation in sports is closely linked to one’s social class position (Collins, 2003, Collins and Kay, 2014; Scheerder et al., 2002, 2005; Sugden and Tomlinson, 2000; Stempel, 2005, 2020; Taks et al., 1995). They also find that individuals from higher social class groups are not only more likely to directly engage in sports activities but also tend to attend sporting events more frequently (Coakley, 1994; Eitzen and Sage, 1991; Gruneau, 1999; Kahma, 2012; Moens and Scheerder, 2004; Thrane, 2001; White and Wilson, 1999; Wilson, 2002; Hartmann-Tews, 2006). However, the bulk of scholarly literature on social class and sports has historically concentrated on direct sports participation, receiving substantially more academic attention than other forms of sports engagement (Thrane, 2001).

These findings have generally held true for more recent scholarly work in this field, which has continued to be primarily focused on direct sports participation rather than other forms of sports engagement, such as viewership, following, or fandom, which all arguably better represent an individual’s cultural or taste profiles (Kahma, 2012; Warde, 2006; Gemar, 2019a, b). Theoretically, spectator sports represent a significant aspect of cultural consumption, as highlighted by Bourdieu’s (1978, 1984) work on sport and cultural capital. Spectator sports serve as a key site where cultural distinctions and social stratifications are produced and reproduced. While active participation in sports can also reflect these dynamics, following and engaging with spectator sports is more common in contemporary society (Elgaddal et al., 2022) and arguably more indicative of cultural capital and social status. By examining sports following, we gain insight into the broader sociocultural dynamics that shape cultural consumption patterns, social hierarchies, and sociocultural interactions and connections between diverse groups.

Studies in spectator sport

In the study of social class and sports engagement, Wilson’s (2002) foundational study of the United States identified a “paradox” in the relationship between social class and sports involvement, as both a participant and spectator. Wilson observed that while individuals higher in both economic and cultural capital were generally more engaged in sports, those with elevated cultural capital were less inclined to participate in “prole” sports, which were typically associated with lower and working classes [1]. Wilson’s findings suggest that class-based economic differences enable upper-class participation in more expensive sports, relegating sports associated with those of lower socioeconomic groups as distinctive of those groups.

Class distinctions in spectator sports consumption have been observed in different contexts, with studies in Australia and the United Kingdom identifying class differences in the following and fandom of various sports (Collins, 2009; Holt, 1992; Pope, 2015; Ward, 2009). Pope (2015), for instance, highlighted a rivalry between rugby union and soccer fans in the UK, underlining the class-based distinctions in sports fandom between fans of these two sports in that context, and having social implications for sport-based sociocultural segregation based on socioeconomic position.

Thrane’s (2001) study on sports spectatorship in Scandinavian countries likewise found that income had a positive, though not linear, relationship with sports spectatorship. This study also revealed varying effects of education on sports spectatorship across different countries, adding complexity to the understanding of economic capital (operationalized as income) and cultural capital’s (operationalized as education) influence on sports consumption (Thrane, 2001). Indeed, Mehus (2005) found that higher education was associated with less frequent spectatorship of sports, both on television and in person for the Norwegian context, while Kahma (2012) found that demographic factors like age and gender play a more significant role in explaining sports spectatorship than income or education in Finland.

White and Wilson (1999) conducted a foundational study analyzing the relationship between socioeconomic position and attendance at sporting events in the North American context of Canadian sports. Their findings revealed socioeconomic associations with sports spectatorship, with higher socioeconomic status facilitating attendance at these events and lower social position as a constraint to attendance (White and Wilson, 1999). With regards to some of the leagues that are prominent on the American landscape assessed in this paper, specifically following the National Hockey League (NHL) in Canada, Gemar (2019b) echoes Mehus in finding that those with the highest levels of education were less likely to follow than those with lower levels of former education. This was true even as higher income levels likewise predicted higher levels of following the NHL in Canada (Gemar, 2019b). Conversely, following the NBA and Major League Soccer (MLS) in the Canadian context was predicted by elevated levels of education, while following the NFL and Canadian Football League (CFL) were predicted by elevated levels of income (Gemar, 2019b). Both voracious and omnivorous consumption of these prominent spectator sports in Canada was also found to be associated with elevated levels of income and education, although not linearly so (Gemar and Vanzella-Yang, 2022).

Studies of the socioeconomic makeup of in-person attendance at sporting events thus form a substantial proportion of the work that has been done on socioeconomic position and its relationship to consuming spectator sports. However, empirical studies examining these dynamics present some mixed findings, especially if they also consider alternative methods of engaging spectator sport (e.g. watching on television or “favorite” sports). For instance, Kahma (2012) analyzed people’s “favorite” spectator sports and whether these were patterned by distributions of Bourdieusian forms of capital. This study found that while many sports were associated with elevated levels of both economic and cultural capital, some were less so, and some represented sports where lower levels of capital were associated with elevated levels of favoritism (Kahma, 2012).

Many of these studies were interpreted by their authors through a Bourdieusian lens, offering different levels of direct support for Bourdieu’s originally articulated theories of the relationship between social class and sporting taste or behavior, but all finding clear empirical connections between socioeconomic position and engagement with spectator sports. With these core theories and empirical understandings of the relationship between social class and sports engagement, we focus on key measures of socioeconomic position and seek to understand first, what are the relationships between sports following in the United States and the socioeconomic variables of income and education. Second, do these relationships differ between different sports or socioeconomic variables? And finally, what do these findings tell us about the relationship between socioeconomic position and sports following in the US today?

Data and methods

The scarcity of academic research on socioeconomic status and sports spectatorship in the United States can be significantly attributed to a shortage of accessible data for researchers. This study leverages a novel and contemporary dataset that captures sports following for a broad list of professional sports leagues, both domestic and foreign, along with college athletics and large spectator sporting events such as the FIFA World Cups and Olympic Games. The dataset for this study comes from a national survey designed by academics and commissioned to the prominent survey research firm Momentive/SurveyMonkey, distributed to a large online survey-taking population in December of 2023 who were recruited and compensated by the survey research firm. The survey process involved initial random distribution within this survey-taking population, followed by algorithmic adjustments during collection to ensure final representativeness in terms of gender and age, as determined against the latest US Census data figures. Therefore, the survey methodology of the research firm ultimately employed stratified random sampling approaches to representativeness for the commissioned number of survey respondents. Most survey takers did so on mobile devices, and there were 2032 total responses. Online surveys, especially those able to be delivered to mobile devices, are increasingly necessary in a cordless world and are increasingly accurate and utilized in contemporary survey research (Kennedy and Deane, 2019). The survey research firm conducted quality control and reliability testing of survey respondents, such as systematic testing for straight-lining or speeding. This study adopts an available case analysis approach to handle the missing response data. This approach is appropriate given the minimal impact that the small number of missing responses is likely to have on the overall analysis.

In Table 1, we provide the demographic and socioeconomic composition of the survey participants. While certain variations in racial and educational representation are typical of surveys in general, they pose some limitations for certain analyses and conclusions of this study, especially as they may relate to the relative frequencies of sports following in the US. However, the overall alignment with census data across most socio-demographic categories, combined with sample sizes that surpass statistical robustness thresholds for the US population, lends credibility to the dataset for the specific research conducted in this paper.

The specific survey question asked respondents, “How closely do you follow … ?” in relation to various sports leagues and competitions. Respondents who selected “very closely” or “fairly closely” were categorized as following these sports for the purpose of our analysis. Conversely, those who selected “not that closely” or “not closely at all” were categorized as not following these leagues or competitions. This kind of question, response options, and the language of “following” aligns with the established and validated measures and methodology for capturing North American sports following developed by Professor Reginald Bibby in the long-running Project Canada Survey program (e.g. Bibby, 2005). The relative frequencies for these survey results appear in Table 2.

In this paper, the concept of the “follower” encompasses both the activity of following and the cultural taste involved in choosing particular sports. Unlike specific activities, such as in-person attendance or watching TV, “following” covers all methods by which one can follow sports. This term is dynamic and thus can apply to both past and future methods of sports engagement, regardless of technological change. It also better represents taste in cultural engagement than traditional survey questions, as watching TV or attending an event involves specific cultural activities, whereas the sport followed is the cultural preference. Thus, “following” is both an action and a taste within broader cultural contexts. However, this classification thus cannot differentiate between the methods of following or appreciation schemes, limiting the study to identifying which sports are consumed without capturing the social class distinctions in modes of consumption.

The methods of analysis that we employ in this paper are two-fold. First, we employed Cramer’s V analyses to investigate the relationship between variables related to sports following and the operationalization of economic and cultural capital variables, namely income and education (see Table 3). This approach was chosen for its efficacy in quantifying the strength and nature of associations between categorical variables, which is crucial for understanding the interplay between variables, in our case, socioeconomic variables and sports following. Cramer’s V is particularly advantageous to this kind of analysis due to its compatibility with variables encompassing a diverse range of categories, such as income and education levels. In understanding socioeconomic position, occupational status is an oft-used and useful additional category for fully comprehending income and education’s intersecting and compounding effects. However, the dataset used in this paper did not include information about respondents' occupations. Rather, we utilize household income to measure respondents’ economic capital and formal educational attainment to measure respondents’ cultural capital. Both measures are established measures to capture these forms of capital, with education representing institutionalized manifestations of cultural capital (Bourdieu, 1986; Gemar, 2023)

The second method of analysis used in the analysis of this paper was multiple logistic regression analysis (see Table 4). This method was chosen for its ability to predict the probability of an individual following a specific sport based on varying income and education levels. Using both income and education in the same regression model, these models are used here to analyze the influence of each predictor variable while simultaneously controlling for the other variable in the model. This allowed for a nuanced understanding of the individual and combined effects of economic and cultural capital on sports consumption and to understand the relationship of one while controlling for the other. Race and gender categories are used as control variables in these regression models of each spectator sport and sporting event to isolate the socioeconomic variables representing economic and cultural capital.

Results

Table 3 presents Cramer’s V measures for income and education across these various sports leagues and competitions. This helps us to answer our first question regarding the relationship between sports and the key measures of socioeconomic standing used in this study. They illustrate the strength of association between the variables, with higher values indicating stronger relationships. Regarding household income, MLS followers exhibited a strong association (Cramer’s V = 0.266, p < 0.001), suggesting a notable association between following MLS and higher income levels. This was closely followed by the NBA and the English Premier League (EPL), with Cramer’s V scores of 0.231 and 0.263, respectively, both highly significant (p < 0.001). Sports like the Summer and Winter Olympics showed weak associations with income (Cramer’s V = 0.074 and 0.068 respectively), indicating a weak link between income levels and following these sporting events.

Similar patterns emerged for the variable of educational attainment. MLS again showed a high correlation (Cramer’s V = 0.295, p < 0.001), as did the NBA and EPL, with Cramer’s V scores of 0.252 and 0.285, respectively, both highly significant (p < 0.001). Other sports, such as the NCAA Basketball (both Women’s and Men’s), Liga MX (Mexican professional men’s soccer), Professional Golf Association tour (PGA), and Ladies Professional Golf Association tour (LPGA) demonstrated moderate to weak associations with education (Cramer’s V = <0.100, both statistically significant and not).

Many other sports, such as Formula One (F1), Men’s and Women’s World Cup, Women’s Tennis Association (WTA) and Association of Tennis Professionals tour (ATP-men’s professional tennis), and the Women’s National Basketball Association (WNBA), among others, showed moderate associations with both income and education. Overall, Cramer’s V results across different sports indicate varying degrees of association between sports following and socioeconomic status, with certain sports like MLS, NBA, and EPL showing strong associations with higher income and education levels, while others like the Olympics and NCAA Women’s Basketball demonstrating weak associations. It is notable that only one of these sports, the LPGA, showed non-statistically significant relationships for both household income and educational attainment, although this may also be a statistical function of this being the smallest subgroup of the following. We now move on to the results from the regression analyses of household income and education for each of these sports competitions.

The results from our regression models, as displayed in Table 4, provide a detailed analysis of the relationship between the following of various sports leagues and competitions in the sample and our two socioeconomic factors of household income and education level when they are controlled for each other, along with controlling for race and gender. This analysis helps answer the second research question for this analysis of whether the nature and strength of relationships differ between socioeconomic variables or sports categories. Each specific socioeconomic variable is revealed through the coefficient values in Table 4 and primarily discussed in this section. The model fit and overall predictive relationship of all included variables is summarized through the Nagelkerke R² values presented in Table 4.

The results show generally consistent patterns for the six largest and most mainstream American sports leagues and competitions. For the NFL, College Football, MLB, NBA, MLB, and NHL, there are clear and strong predictive parameters between sports following and both income and education. Those with higher income and education levels are most likely to follow all six of these leagues. While patterns for income are relatively similar among these leagues, the MLS seems to show the most stratification of following by (higher) income. For education, the differences are slightly greater, with (higher) education seeming to again predict MLS following the most and NFL and MLB following the least. However, all six of these most followed leagues show consistent and strong patterns linking elevated education levels, especially graduate level education, to much higher following than lower levels of education.

The next most followed sporting events, the summer and winter Olympic Games, show significantly lower levels of predictive power for these two variables. Indeed, there are no statistically significant or particularly strong results linking income to the following of these events when controlling for education, as done in this table. At the same time, there are few predictive educational parameters; those with graduate degrees are more likely to follow these events than those with a high school diploma or less, and slightly more so for the summer than winter iteration. Some other sports in the data show similar dynamics, with little predictive power of income, while some educational stratification between the highest and lower education levels remained. This pattern is seen in the following of NCAA Women’s basketball, the National Women’s Soccer League (NWSL), and the PGA tour.

The sports that show the strongest stratification by income and education are the two European soccer leagues included in the data, the English Premier League and Spain’s La Liga. Those with higher income, especially income over $100,000, are much more likely to follow these leagues than those with lower income levels. Similarly, those with graduate degrees are much more likely to follow these two foreign soccer leagues than those with all other levels of education, especially lower levels. These two leagues thus mirror the relationship to these socioeconomic variables seen in the following of Major League Soccer, although presenting as even more pronounced.

Therefore, with only a few exceptions, elevated income levels are predictive of following these different sports leagues and competitions. The regression analyses reveal that when controlling for each other, education level is generally a more pronounced predictor of following for these sports. The strength of the stratifying effects of these variables also varies among these sports, with education showing the strongest stratification for the sample’s men’s, women’s, foreign, and domestic soccer leagues. While some other sports show lower levels of stratification, or perhaps do not have large enough subsamples to statistically reveal them, it is notable that the six most prominent and most followed sports all show strong and relatively consistent stratification of following for both household income and personal education.

Discussion and conclusion

In answering the first and second research questions of this paper regarding the empirical and relative relationship between economic and cultural capital in following different sports of contemporary American society, our analysis reveals some key findings. The results of this study first reveal that higher income groups and individuals with elevated levels of education exhibit an increased likelihood to follow a wide array of sports. Indeed, according to our initial analysis, there were only four sports for which there was no statistically significant relationship to income and only two where there was no similar relationship to education. For income, these sports were the Olympic Games, both summer and winter, NCAA women’s basketball, and the LPGA tour. For education, the two sports without statistically significant associative relationships to following were again the LPGA tour and NCAA men’s basketball.

Conversely, the general trend of strong positive association and likelihood between (elevated) income and education for following these different sports is particularly pronounced in the context of major sports leagues such as the NFL, NBA, MLS, and NHL, among others. However, regressions reveal that international soccer leagues, specifically the English Premier League and La Liga, represent the most capitally possessed following base, indicating that following these sports may be cultural markers of distinction and social status par excellence on the American sporting landscape. Therefore, the analysis shows that socioeconomic factors, namely income and education, are significantly associated with these American sports consumption patterns. However, these patterns are particularly strong for some of these sports, while not for others, and vary between income and education variables for some sports. These results also suggest arguments in answer to our third research question about what these results may tell us more broadly about the relationship between socioeconomic position and sports following in the US today.

For instance, it is notable that the Olympic Games represent one-off megaevents and thus do not take the same type of time or material commitments to engage in regularly. Because free time for consuming culture and sport is linked to economic capital (Gemar, 2024), the Olympic Games may represent the type of spectator sporting event that requires less economic capital, both in material terms and in terms of free time facilitated by such capital. NCAA basketball, both men’s and women’s, may represent a similar dynamic, as respondents may consider following the end of the year tournaments or “March Madness” as “following” the sport, even as this is unable to be parsed from the data. Finally, it is notable that women’s sports, and events with prominent women’s sports are included in this list of less capitally stratified sports, as it may reflect the influence of other demographic variables, such as gender, on spectator sport engagement over traditional socioeconomic variables (Kahma, 2012).

While the six most prominent sports in the US may be the most television-available sports, they are also generally the most expensive to attend due to higher demand. Therefore, elevated levels of economic capital may be needed to fully access the following experience if attending in person is essential to someone’s following. It is also the case that these leagues are increasingly taking their broadcast rights outside of free-to-view network television and onto streaming platforms (Darcy, 2023), and as the most followed sports, they can command higher prices than others on these platforms. Indeed, MLS primarily broadcasts on the Apple + streaming platform after signing a 10-year deal with the tech giant (Reedy, 2023). The increased fragmentation of broadcast rights may stratify the amount of economic capital needed to follow these leagues to the extent that people may currently follow. Regarding the connection of cultural capital to following these major spectator sports, Bonnie Erickson (1991, 1996) highlights how sports can operate as a lingua franca in workplaces, leading to social and professional connections that facilitate workplace success and promotion. The potency of this kind of cultural capital may be more salient with more socially and culturally salient sports leagues in the US, such as the six most followed leagues in the data for this paper.

The observation of the elevated socioeconomic position of soccer following, especially foreign soccer following, aligns with Bethany Bryson’s arguments that openness to diverse cultural forms outside of one’s immediate culture might differentiate high-status groups from others (Bryson, 1996). In this case, following these foreign leagues may signal an openness to these cultural products because of their foreign, and perhaps specifically their European, origins. Scholars like Johnston and Baumann (2007), and Ollivier (2008) similarly propose that other cultural mechanisms like “authenticity,” “exoticism,” and “openness” play a role in creating distinctions within broader consumption styles. This phenomenon is explained through the application of Bourdieu’s aesthetic disposition (Friedman, 2011; Lizardo and Skiles, 2012) and other cultural markers like “cosmopolitanism” (Cappeliez and Johnston, 2013; Emontspool and Georgi, 2017) for its creation of distinctive taste profiles and connection with social class position.

These elements are also seen in many global contexts, and in non-Western contexts, openness and cosmopolitan consumption of Western cultural goods are associated with socioeconomic distinctions (Bekesas et al., 2016; Rankin et al., 2014; Schwedler, 2010). Indeed, Prieur and Savage (2013) argue for a “cosmopolitan cultural capital,” suggesting that social shifts to broader and less exclusionary cultural consumption patterns, such as those that have a focus on openness and diversity, can reconfigure and reinforce lines of class divisions in cultural consumption. These dynamics of cosmopolitanism have also been found and argued for in the realm of sports consumption (Lozada, 2008; Rowe and Gilmour, 2009, 2010).

The distinctive following of these foreign soccer leagues by those of elevated socioeconomic position also echoes the concept of “emerging cultural capital” (Prieur and Savage, 2013). Emerging forms of culture, such as yoga, meditation, and vegetarianism, present as new cultural engagements that bridge the gap between highbrow and lowbrow (Gemar, 2020) and are often preferred by middle and upper-middle-class, educated youths (Savage et al., 2015). Just as yoga and meditation represent old and traditional forms of culture in many culturally Eastern contexts but come with specific elevated social cache in culturally Western contexts, so too may the traditional and often working-class coded (Pope, 2015), European soccer leagues for the American context. This emphasis on cultural capital for these more foreign or internationally coded sports likely also explains the relative emphasis on education over income for these and other more niche, culturally “cool,” or similarly coded sports (e.g. F1, NBA), rather than the more widely popular leagues such as the NFL where economic capital may be more important than cultural capital for access and “legitimate” participation. For this reason, there may be disparities in results between the highest income and highest education levels for following, especially when controlled for each other, an empirical finding and argument also going back to Bourdieu (1984).

Reflecting on Wilson’s (2002) foundational study of the US, which identified a “paradox” in the relationship between social class and sports involvement, the research of this paper underscores that individuals higher in economic and cultural capital are generally more engaged in sports but does not find such a paradox. While this study focuses on a slightly different element of sport, that of “following”, it does not agree with studies such as Wilson (2002), Mehus (2005), Kahma (2012), or Gemar (2019b), which find specific sports that are indeed predicted by lower levels of capital possession. In not finding sports predictive of distinctively lower socioeconomic position, we also contradict some of the assertions of socioeconomic relationships to sport set forth by Bourdieu (e.g. 1978, 1984), especially as they relate to spectator sports. This is to say that we do not find any evidence of mass spectacle sports in the US as characteristic of low social status or characteristic of lower social class groups, even as the mass spectacle event of the Olympic Games showed less social class connection than other sports. Rather, the more mass spectacle sports may convey more readily applicable forms of cultural capital for everyday use and instrumental utility (e.g. Erickson, 1996; Gemar and Pope, 2022). Indeed, the results of this study show cultural capital, as operationalized here by education, as a relatively more potent variable than income in patterning the following of sports in the United States.

Practically, the consumption of spectator sports engages a wider demographic than active sports participation, including individuals who may not have the time, resources, or physical ability to participate in sports themselves. Spectator sports can also provide a common cultural reference point and a shared experience that can bridge different social groups. Indeed, studies have shown that sports spectatorship can foster community identity and social cohesion, particularly in settings where sports events are communal experiences (Inoue et al., 2015). Research has also demonstrated sports spectatorship’s positive social and psychological benefits, such as enhanced social connections, a sense of belonging, and improved mental health and well-being (Wann, 2006; Heere and James, 2007).

Understanding the socioeconomic factors influencing sports can help identify barriers to cultural participation and inform strategies to make sports more inclusive and accessible. From a policy perspective, promoting inclusivity in sports engagement as spectators can have significant societal benefits. Policies to reduce financial barriers to attending live sports events or accessing sports broadcasts can help democratize cultural consumption, such as subsidized tickets, transportation, or public access points to broadcasts occurring behind paywalls (Collins and Kay, 2014). Additionally, supporting diverse sports programming and ensuring equitable access to sports media can foster social cohesion, bridging and other forms of social capital, and enhance community well-being (Gemar, 2021b; Misener and Mason, 2006; Widdop et al., 2016). Focusing further research on spectator sports may allow policymakers to address the cultural and social dimensions of sports engagement, which may help promote similar types of positive community engagement and connection, or similar mental and physical health outcomes as those associated with active participation (Spaaij, 2012; Wann, 2006).

Some limitations of this work also entail calls for future research into the intersection of social class and sport, along with the relevant practical and policy interventions to increase equitable access to spectator sports and engagement with this prominent cultural domain. First, more comprehensive conceptualizations of the intricacies of social class and social status are necessary to understand the complexity of ways socioeconomic position may interact with marginalized racial, gender, or sexual identities to further inform status judgments in spectator sports engagement. Second, while recognizing the limitations inherent in online survey methodologies, such approaches are increasingly considered necessary, accurate, and effective (Kennedy and Deane, 2019). Similar methodologies have been effectively used in significant works of research exploring social classes, cultural consumption, and sports (Savage et al., 2013, 2015; Sutton and Knoester, 2022). Recognizing the limitations of cross-sectional data, further studies into the social place of spectator sport within American or other societies worldwide may benefit from longitudinal understandings of social change in these dynamics and more compellingly establish causality.

In conclusion, this research provides a contemporary and comprehensive empirical update to work on core elements of socioeconomic position and spectator sports in the prominent sporting context of the United States. It updates Wilson’s (2002) work on socioeconomic position and sport in the US and expands our understanding of the evolving landscape of sports consumption and its socioeconomic connections and implications. Highlighting the persistent connection of socioeconomic factors to sports consumption, the results emphasize the importance of considering sports following as a crucial part of cultural engagement, able to reflect and reproduce broader socioeconomic stratification. In the case of this paper’s results, this divide appears mainly between those who follow sports and those who do not. Secondarily, the most widely followed and foreign-coded sports, especially foreign soccer leagues, show increased stratification along these measures. In these ways, this study reaffirms assertions of the role that socioeconomic position may play in the American sporting landscape today, even for spectator sports.

Table 1

Demographic characteristics of the survey sample of this paper

Variable		% In sample (n = 2032)
Household income
	Less than $25,000	12.4%
	$25,000–49,999	18.4%
	$50,000–74,999	18.8%
	$75,000–99,999	14.8%
	$100,000–149,999	21.4%
	More than $150,000	14.3%
Education
	H.S. diploma or less	19.3%
	Some college	18.3%
	Associate’s degree	11.4%
	4-year college degree	25.1%
	Graduate degree	25.9%
Age group
	18–29	21.4%
	30–44	28.7%
	45–59	26.5%
	60+	23.3%
Gender
	Non-binary	0.6%
	Men	46.4%
	Women	53.0%
Race/ethnicity
	Asian	10.6%
	Black/African American	7.4%
	Hispanic/Latinx	9.2%
	Indigenous	2.3%
	Other	2.4%
	White	68.2%
Region
	East North Central	14.1%
	East South Central	5.3%
	Middle Atlantic	22.3%
	Mountain	5.2%
	New England	4.1%
	Pacific	15.8%
	West North Central	4.8%
	West South Central	9.3%
	South Atlantic	19.1%

Source(s): Table created by author

Table 2

Relative frequencies for sports following variables

	% of sample which follow “fairly closely” or “very closely”	% of sample which follow “not at all” or “not that closely”
Sports/leagues
NFL	53.9%	46.1%
College Football	43.2%	56.8%
MLB	42.1%	57.9%
NBA	41.1%	58.9%
MLS	33.9%	66.1%
NHL	33.2%	66.8%
Summer Olympics	30.5%	69.5%
Winter Olympics	29.7%	70.3%
Formula One	20.7%	79.3%
NASCAR	19.4%	80.6%
Men’s World Cup	17.5%	82.5%
English Premier League	16.2%	83.8%
WNBA	14.8%	85.2%
NCAA Men’s basketball	14.2%	85.8%
Women’s World Cup	12.1%	87.9%
Minor League Baseball	12.1%	87.9%
Spanish La Liga	12.0%	88.0%
WTA Tennis	11.4%	88.6%
IndyCar	10.9%	89.1%
ATP Tennis	10.3%	89.7%
PGA Tour	9.4%	90.6%
NCAA Women’s basketball	8.3%	91.7%
Mexican Liga MX	6.4%	93.6%
NWSL	6.3%	93.7%
LPGA	4.7%	95.3%

Note(s): ^*p < 0.05; ^**p < 0.01; ^***p < 0.001

Source(s): Table created by author

Table 3

Cramer’s V scores of income and education for sports following variables

	Household income	Education
Sports/leagues
NFL	0.198***	0.179***
College Football	0.166***	0.189***
MLB	0.163***	0.157***
NBA	0.231***	0.252***
MLS	0.266***	0.295***
NHL	0.198***	0.215***
Summer Olympics	0.074	0.142***
Winter Olympics	0.068	0.104***
Formula One	0.183***	0.178***
NASCAR	0.088**	0.100***
Men’s World Cup	0.166***	0.174***
English Premier League	0.263***	0.285***
WNBA	0.137***	0.148***
NCAA Men’s basketball	0.075*	0.063
Women’s World Cup	0.147***	0.141***
Minor League Baseball	0.124***	0.119***
Spanish La Liga	0.241***	0.260***
WTA Tennis	0.156***	0.162***
IndyCar	0.115***	0.094**
ATP Tennis	0.150***	0.164***
PGA Tour	0.080*	0.087**
NCAA Women’s basketball	0.025	0.069*
Mexican Liga MX	0.099**	0.082*
NWSL	0.116***	0.130***
LPGA	0.067	0.061

Note(s): ^*p < 0.05; ^**p < 0.01; ^***p < 0.001

Source(s): Table created by author

Table 4

Log odds ratios from each sport’s regression models considering education and income

	NFL	College FB	MLB	NBA
Household income
Less than $25,000	−0.537**	−0.553**	−0.671***	−0.698**
$25,000–49,999	−0.437*	−0.386*	−0.567**	−0.427*
$50,000–74,999	−0.421*	−0.303	−0.243	−0.284
$75,000–99,999	−0.431*	−0.375*	−0.290	−0.380*
$100,000–149,999	0.135	−0.118	−0.184	0.325*
$150,000 or more	–	–	–	–
Education
HS diplomas or less	−0.528**	−0.726***	−0.452**	−0.845***
Some college	−0.582***	−0.717***	−0.600***	−1.208***
Associate degree	−0.319	−0.506**	−0.446*	−0.934***
4-year college degree	−0.412**	−0.503***	−0.298*	−0.744***
Graduate degree	–	–	–	–
Gender
Non-binary	−0.543	0.245	−0.244	−1.224
Men	0.818***	0.532***	0.581***	0.843***
Women	–	–	–	–
Race/ethnicity
Indigenous	1.199***	0.911**	0.984**	1.925***
Asian	0.123	0.040	0.284	1.031***
Black	0.408*	0.379*	0.179	1.418***
Latinx	−0.011	0.019	0.501**	1.045***
Other	−0.932**	−0.118	−0.807	0.137
White	–	–	–	–
Nagelkerke R2	0.129	0.085	0.089	0.227

	MLS	NHL	Summer Ol	Winter Ol
Household income
Less than $25,000	−0.921***	−0.735***	−0.070	−0.199
$25,000–49,999	−0.700***	−0.581**	0.095	0.116
$50,000–74,999	−0.537**	−0.403*	0.292	0.212
$75,000–99,999	−0.602**	−0.353	0.095	0.101
$100,000–149,999	0.166	−0.014	−0.035	−0.019
$150,000 or more	–	–	–	–
Education
HS diplomas or less	−0.976***	−0.610***	−0.813***	−0.515**
Some college	−1.439***	−0.874***	−0.419*	−0.243
Associate degree	−1.270***	−0.876***	0.019	0.154
4-year college degree	−0.799***	−0.588***	0.032	0.012
Graduate degree	–	–	–	–
Gender
Non-binary	0.069	0.589	−0.583	0.315
Men	0.557	0.642***	−0.113	−0.247*
Women	–	–	–	–
Race/ethnicity
Indigenous	1.853***	1.521***	−0.087	−0.089
Asian	0.818***	0.414**	−0.171	−0.106
Black	0.807***	0.455*	−0.001	−0.313
Latinx	1.095***	0.415*	−0.402*	−0.567**
Other	−0.238	−1.128*	−0.512	−0.482
White	–	–	–	–
Nagelkerke R2	0.216	0.135	0.040	0.033

	F1	NASCAR	Men’s WC	EPL
Household income
Less than $25,000	−0.336	−0.480	−0.635*	−0.967**
$25,000–49,999	−0.083	−0.215	−0.402	−0.904***
$50,000–74,999	0.051	−0.239	−0.262	−0.369
$75,000–99,999	0.372	−0.374	−0.267	−0.248
$100,000–149,999	0.783***	−0.084	0.220	0.431*
$150,000 or more	–	–	–	–
Education
HS diplomas or less	−0.248	−0.190	−0.659**	−1.106***
Some college	−0.770***	−0.324	−0.716***	−1.513***
Associate degree	−1.214***	−0.248	−0.964***	−1.413***
4-year college degree	−0.488**	−0.489**	−0.176	−0.672***
Graduate degree	–	–	–	–
Gender
Non-binary	0.511	0.512	−0.345	−19.445
Men	0.672***	0.368**	0.889***	0.899***
Women	–	–	–	–
Race/ethnicity
Indigenous	0.870*	0.895**	0.208	0.470
Asian	0.852***	−0.105	0.625***	0.494*
Black	0.634**	0.205	0.442	0.732**
Latinx	0.376	−0.262	1.063***	0.594*
Other	−0.125	−1.207*	0.405	0.156
White	–	–	–	–
Nagelkerke R2	0.128	0.043	0.130	0.215

	WNBA	NCAA(M)	Women’s WC	MinorLB
Household income
Less than $25,000	−0.519	−0.266	−0.914**	−0.420
$25,000–49,999	−0.588*	−0.138	−0.634*	−0.585*
$50,000–74,999	−0.429	0.280	−0.585*	−0.338
$75,000–99,999	−0.568*	0.000	−0.242	−0.517*
$100,000–149,999	0.102	−0.189	0.069	0.089
$150,000 or more	–	–	–	–
Education
HS diplomas or less	−1.101***	−0.149	−0.577*	−0.629*
Some college	−0.945***	0.024	−0.847**	−0.768**
Associate degree	−0.634**	0.326	−0.560*	−0.560*
4-year college degree	−0.510**	0.234	−0.164	−0.195
Graduate degree	–	–	–	–
Gender
Non-binary	1.038	−18.627	−0.016	1.048
Men	−0.048	0.869***	0.278	0.172
Women	–	–	–	–
Race/ethnicity
Indigenous	0.506	−0.178	−0.209	0.760
Asian	0.875***	−0.180	0.738***	0.411
Black	1.775***	0.275	0.663**	0.696**
Latinx	0.637**	−0.532	0.661**	0.471
Other	−0.314	0.062	−0.523	−0.597
White	–	–	–	–
Nagelkerke R2	0.117	0.059	0.078	0.056

	La Liga	WTA	IndyCar	ATP
Household income
Less than $25,000	−0.713	−0.829*	−1.198***	−0.640
$25,000–49,999	−0.614*	−0.500*	−0.541*	−0.476
$50,000–74,999	−0.792**	−0.925***	−0.205	−0.675*
$75,000–99,999	−0.157	−0.853**	−0.589*	−0.174
$100,000–149,999	0.578**	−0.245	−0.275	0.122
$150,000 or more	–	–	–	–
Education
HS diplomas or less	−1.269***	−1.094***	−0.301	−0.644*
Some college	−1.368***	−0.912***	−0.070	−1.114***
Associate degree	−1.573***	−0.952**	−0.567	−0.744*
4-year college degree	−1.059***	−0.427*	−0.361	−0.451*
Graduate degree	–	–	–	–
Gender
Non-binary	−18.172	−0.079	0.861	−18.529
Men	1.113***	−0.097	0.466**	0.504**
Women	–	–	–	–
Race/ethnicity
Indigenous	0.451	1.098*	0.364	0.227
Asian	0.193	0.755***	−0.037	0.686**
Black	0.874**	0.877***	0.005	0.493
Latinx	1.568***	0.009	0.070	−0.145
Other	−0.277	−0.903	−0.584	−0.356
White	–	–	–	–
Nagelkerke R2	0.239	0.091	0.047	0.092

	PGA	NCAA(W)	LigaMX	NWSL	LPGA
Household income
Less than $25,000	−0.081	0.164	−0.059	−0.709	0.335
$25,000–49,999	0.518	0.013	−0.348	−0.285	0.577
$50,000–74,999	0.535	−0.074	0.131	−0.587	0.688
$75,000–99,999	0.437	−0.051	−0.256	−0.662	−0.088
$100,000–149,999	0.565*	−0.059	0.643*	0.167	0.707
$150,000 or more	–	–	–	–	–
Education
HS diplomas or less	−0.580*	−0.762*	−0.558	−0.829**	−0.748*
Some college	−0.278	−0.596*	−0.998**	−1.184***	−0.337
Associate degree	0.057	0.038	−0.379	−1.020**	0.083
4-year college degree	−0.403	−0.116	−0.485	−0.574*	−0.478
Graduate degree	–	–	–	–
Gender
Non-binary	−18.306	−18.746	−18.529	−18.699	−17.612
Men	0.728***	0.322	0.512**	0.102	0.403
Women	–	–	–	–	–
Race/ethnicity
Indigenous	−0.224	0.223	0.275	0.699	0.994
Asian	0.193	0.594*	0.710*	0.916***	0.323
Black	0.059	1.305***	1.067***	1.139***	0.500
Latinx	−0.672	0.412	1.944***	0.635	0.359
Other	−0.732	−0.005	0.166	0.395	−17.709
White	–	–	–	–	–
Nagelkerke R2	0.055	0.050	0.119	0.081	0.045

Note(s): ^*p < 0.05; ^**p < 0.01; ^***p < 0.001

Source(s): Table created by author

Notes

1. The term “prole” dates from the late 19th Century as a derogatory colloquial British term for people or things associated with lower social class groups – a shortened version of “proletarian” (Merriam-Webster, 2024).