Realism in FIFA? How social realism enabled platformed racism in a video game
First Monday

Realism in FIFA? How social realism enabled platformed racism in a video game by Sam Srauy and John Cheney-Lippold



Abstract
Platformed racism offers a unique lens through which to investigate technological structures that enable racism. Online video games, such as EA Sports’ FIFA series — which dominates the soccer video game market share through its touted realism — feature these structures. Like many platforms, FIFA enables representations of real bodies (i.e., professional soccer players). But, unlike many games, FIFA enables game players to directly affect the creation/modification of these representation in the form of player character cards. Analyzing a census of six years of player cards, this study found that platformed racism was enabled because the game’s realism invited racism when players tried to maintain that realism. The study concludes that the catalyst for racism to emerge in FIFA was the drive towards realism.

Contents

Introduction
Literature review
Methods
Results
Discussion
Strengths and weaknesses
Conclusion

 


 

Introduction

Within the video game literature, sports games have been the site of much productive inquiry. Specifically, scholars have pointed out numerous ways in which sports games racialize Othered bodies (Chan, 2005; Leonard, 2006, 2004, 2003; Voorhees, 2015). The representation of black males in digital games, for example, tend to be overwhelmingly in sports titles (Williams, et al., 2009). Media scholars and games scholars have pointed out that these representations of black bodies often rely on problematic discourses (Leonard, 2006, 2004, 2003; Williams, et al., 2009; Yang, et al., 2014; Shaw, 2012; Behm-Morawitz and Ta, 2014; Gray, 2018, 2014).

Indeed, racism within media texts, including video games, is well demonstrated. But, what if the developers attempted to avoid racism by encoding a way to quantify real world athletes in a game, while charging players to realistically encode athletes’ perceived performance? Would the mere absence of explicit racism be enough to mollify inequality? Or, would the reliance on code enable platformed racism to encroach (Matamoros-Fernández, 2018, 2017)? Platformed racism, defined as the way digital artifacts (i.e., “platforms” such as social networking sites and other online community spaces) reify systemic racism through its creators’ policies, choices made in the coding process, and end users who also bring their racial views to the artifact. In this light, platformed racism offers a powerful analytic lens to investigate sites where inequality take hold. What has not been examined is platformed racism in video game spaces. In doing so, we are centering the social factors that enable platformed racism to emerge. Our case study of EA Sports’ FIFA franchise, therefore, begins to fill that theoretical and empirical gap.

The FIFA Ultimate Team (FUT) mode’s focus on imagined athletes’ statistics (i.e., akin to Dungeons & Dragons and not baseball cards) is telling because it constitutes a purposeful attempt to code realism for each of these characters. Statistics are not political, so the assumption goes, but mere representation of the real world. Of course, scholarship from fields such as science and technology studies (see Gillespie, 2014b, 2014a, 2012, 2010) tells us that code can never be free of human biases. In this sense, EA avoids accusations of racism while knowingly or unknowingly reifying racism.

We found that white characters fit the dominant offline views of being smarter though less physical than blacks or Hispanic/Latinos. Hispanic/Latino characters fit the off-line discourse of flair and creativity. And, black characters fit the off-line beliefs of being stronger and more aggressive than Hispanic/Latinos or whites. We conclude the game’s touted realism perpetuates anti-black and anti-Latino racism through Matamoros-Fernández’s (2018, 2017) concept of platform racism. Extending her work, we conclude in our case study that FIFA’s purported realism enables video game players to import their society’s systemic racism into the game texts to make the game intelligible and realistic. This is because to be real requires a text to tap into the social narratives through which we come to recognize something as real (Galloway, 2004). Because the dominant racial discourse in the United States, in the case of our study, holds racist ideas as commonsensical, reading racism becomes the moment in which realism becomes knowable for players. A key insight of our study, therefore, is that realism — as a design strategy — can invite platform racism into seemingly neutral code.

 

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Literature review

FIFA’s dominant selling feature is the realism of the game. EA Sports’ FIFA 17 marketing materials widely publicized how realistic the game would be (EA Sports, 2016b). With 6.91 million copies sold in its first week, FIFA 17, and the FIFA franchise in general, enjoys a near-monopoly on the soccer video game market (Parkin, 2016). A popular game play mode introduced in recent editions of EA Sports’ FIFA series is the FIFA Ultimate Team (FUT) mode. This mode allows the player to purchase with real money, trade, and assign character cards of real world FIFA athletes to create custom squads. The idea behind this mode is similar to offline fantasy sports leagues whereby participants create teams. FUT goes beyond team building and tracking by allowing players to play their assembled squad against other players or in single player mode. Whenever athletes’ performances vary too much from those static statistics on player cards, new cards (and thus new entities) are issued by EA based off of the volunteer labor of select fans who are empowered by EA to re-encode those statistics.

Characters have either an actual, 3D scanned face or a virtual, artistic rendering, and their height and weight is based on official club data. Moreover, characters’ individual statistics are also made unique by a 1–99 scale of 29 different attributes: acceleration, sprint speed, positioning, finishing, show power, long shots, volleys, penalties, vision, crossing, free kick, short passing, long passing, curve, agility, balance, reactions, ball control, dribbling, interceptions, heading, marking, standing tackle, sliding tackle, jumping, stamina, strength, aggression, and composure. This type of quantitative attribute-based system is functionally similar to the Dungeons & Dragons (D&D) tabletop role-playing system, wherein characters’ ability scores (strength, constitution, dexterity, intelligence, wisdom, and charisma) set the quantitative foundation, and thus the ludic identity, of each character. This quantitative foundation allows D&D’s mechanics to run, and it serves as the ontological baseline by which many classic, text-based role-playing games, as well as newer, more graphically advanced games, operate.

EA deploys a coterie of video game players who voluntarily encode their perceptions of real athletes’ performances onto the in-game characters in an attempt to realistically capture these real athletes’ abilities. Following the popularity and profitability of this game mode in recent years, several amateur, unaffiliated websites began to build databases of these cards, including the 29 quantitative attributes that define each character’s in-game capacities. In other words, game players are tasked with coding realism into the game by watching actual soccer games and using the 1–99 scale on attributes in similar fashion to a D&D game. These volunteers are data reviewers for EA Sports as part of their World Football (Soccer) Web Editor (WWE). Reviewers are expected to watch certain teams’ matches in order to review the quality and accuracy of existing FIFA game data.

Racism

By racism we mean the social project (Omi and Winant, 2015) that systemically structures and orders people of different groups according to fiction taken to be common sense (Bonilla-Silva, 2010, 2007, 1997). In the United States, race is a social construct where social standing and privileges are distributed according to preconceived notions about groups, often demarcated by skin color and perceived cultural differences (Omi and Winant, 2015) — it serves as an analytic to explain how identity is racialized without explicit claims (Bonilla-Silva, 2007). Racism in the United States, therefore, is a systemic problem that orders life and is present in multitudinous ways. While we do not subscribe to essentialist notions of biological race difference, for this project we use the predominant view in society — biology (see Bonilla-Silva, 2010). In doing so we recognize that reality that race is a social construct which people tend to confuse as biological construct (Duster, 2003a).

Platformed racism and why games are a “platform”

The study of race and racism is replete with studies that demonstrate how systemic racism affects the perception of marginalized people’s performance in various jobs and settings (Bonilla-Silva, 2010, 1997). A relatively new concept, platformed racism is described by Matamoros-Fernández (2017) as the way that social media platforms enable racism on their sites through technical affordance, governance, capitalism, and a libertarian Silicon Valley idealism. For instance, Cirucci (2017) noted how Facebook’s user profile placed less emphasis on race and constructed an assumed whiteness. This subordination of non-whiteness, Cirucci notes, is the result of Facebook merely not having an option for users to describe their racial identities. Facebook, it seems, never needs to explicitly favor whiteness for systemic racism to write that understanding on the platform. Indeed, boyd (2012) noted that racial discourses surrounding MySpace profile decorations caused a “white flight” to Facebook, whereas the fleeing users assumed Facebook was more white due in part to the lack of profile page personalization. Matamoros-Fernández (2018) noted how emoji usage patterns changed and became part of an anti-Muslim hate campaign in Belgium because of how platform affordances enabled a platform specific hate practices. While Cirucci’s and boyd’s studies do not use platformed racism, per se, their findings and conclusions are congruent with Matamoros-Fernández’s concept.

We note that while platformed racism was intended by Matamoros-Fernández as an analytical lens to investigate social networking sites, video games with online components are often argued to be a form of social media (see Ang and Zaphiris, 2010; Cirucci, 2014, 2013). Platformed racism has a dual meaning of “tools for amplifying and manufacturing racist discourse” and community guidelines with “vague policies” and “arbitrary enforcement of rules” [1]. Online video games satisfy the term’s definition (see Busch, et al., 2015; Srauy, 2019). FIFA reviewers, in evaluating/redefining characters’ statistics, change the balance of character attributes according to their relative value among other characters as perceived by the reviewers.

We start with the assumption that the constellation of EA Sports’ FIFA (and specifically its FUT mode), www.futhead.com, and the attending infrastructure that enables social interaction and the trading among FIFA video game players meets the definition of a social network. Therefore, it is a site where platformed racism could be present. Following the literature, we assume that systemic racism exists and would be comprehensible in video game spaces.

Thus, we argue:

H1: Systemic racist discourses of biological differences will be used to enable platformed racism in EA Sports’ FIFA.

 

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Methods

Using Python, we scraped the site http://www.futhead.com to collect the pictorial and statistical information for every available athlete of a U.S. based team’s card. We did this because futhead.com, as one of the largest fansite, functions as a repository of archival data of EA Sports’ FIFA character statistics. We gathered a census of all the unique, playable cards from FIFA 12 through FIFA 17 as noted on the www.futhead.com forum. As changes to card statistics result in issuing updated cards, those new cards count as unique cases in our dataset. We statistically analyzed the characters’ quantitative attributes (where each character is assigned a trait of 1 through 99 according to his player-assessed real-world skill) and show how they reify dominant tropes around whiteness, blackness, and Latinidad.

Operationalizing attributes

We focused on four different attributes as algorithmic stand-ins for abilities: vision (or intelligence), aggression, strength, and agility. There were 29 total attributes in the game, each encoded 1–99. We focused on ones that directly reflect the structural racism of the United States (Bonilla-Silva, 2007; Omi and Winant, 2015). The other attributes are specific to soccer. In the United States, one dominant discourse on which racism hangs is biology (Bonilla-Silva, 2007; Duster, 2006, 2005, 2003b). Past studies of in-game representation note the ways in which biological differences are encoded as race (Braithwaite, 2014; Higgin, 2008; Monson, 2012; Nakamura, 2009; Pace, 2008). Furthermore, intelligence has been abused by racists as indicative of white racial superiority (see Croizet, 2012; Goodman and Leatherman, 1998). Our assumption is that by choosing attributes that have direct analogues to how race is articulated in the U.S., we could more readily argue that those statistics would have contextual fidelity. We understand that because race is socially constructed, we are likely to leave out other attributes that would also reveal inequality. Since our purpose is not to show that racism exists even when people are not intentionally racist but to investigate platformed racism and whether the mechanisms by which those racist ideas are rendered comprehensible for video game players, we opt to focus on biological statistics that are congruent with U.S. racial views.

The vision trait was developed in earlier versions of the game and has since become refined through the years as the game’s engine became more capable of representing realistic character actions. While there is no direct intelligence statistic, FIFA’s developer comments suggest that vision is an amalgamation of intelligence and knowledge of soccer. A character with poor (low) vision “doesn’t see all the opportunities that are presented in a place at a given moment” nor remembers what he saw (EA Sports FIFA, 2011). Therefore, vision is functionally the game’s version of an intelligence statistic.

The literature also suggests that black characters would be marked as more violent than white characters (see Stone, et al., 1997). The strength statistic captures a character’s performance of violence, according to EA Sports: “Your player’s Strength stat will decide how they cope with any physical battles, so a good score in this area is important for anyone with defensive responsibilities” (Electronic Arts, 2011).

Similarly, aggression “works in tandem with Strength; you’ll usually find that a [character] has high scores for both, rather than one or the other. Aggressive [characters] generally win more tackles” (Electronic Arts, 2011). As EA Sports explicitly describes how strength works with aggression, we see that aggression operates as a facet of a bellicose discourse. In this regard, aggression in FIFA is a character’s propensity for violence, and strength is the variable that determines how well those characters enact/cope with that violence.

Lastly, agility was defined by game developers to supplement other physical traits like strength. They write: “[characters] with high agility can perform acrobatic shots or clearances, and agility also affects dribbling ability. If you’re a player who likes to run with the ball, Agility is one of the stats to keep an eye on. The higher the better” (EA Sports, 2012). For individual characters, agility defines the variable metric for both physical ability as well as creative play.

Overall, these four traits allow us to see how FIFA’s gameplay engine accounts for the apparent skill of different professional soccer personalities, although each evaluation is indebted to the implicit biases of reviewers. We also note, that this study is not about soccer. Our case study is about a video game and its online component where racial discourses emerged, are reified, and deployed where soccer is a common fan interest.

Operationalizing race/ethnicity

Since the quantified ranking of each player is often regionally determined (where athletes in the U.S. are evaluated by players in the U.S.), we code racial (and ethnic) identity in the dominant vernacular of U.S. discourse: skin color is the primary demarcating quality of race and culture, while names serve as a secondary identifier. The cards for each player in FIFA all feature portraits and names (including surnames). Given dominant U.S. racial and ethnic discourses, we find this sufficient to infer how someone from the U.S. might identify a player’s racial identity. While no official taxonomy of racial categories exists in the U.S., the U.S. Census employs the category of race alongside the category of ethnicity. By using names and portraits as identifiers, we coded each player according to the U.S. Census’ 2010 categories. In the United States, the historical legacy of the “one drop rule” means that no one is truly white if she or he is also something else. Therefore, we define racial categories as someone whose skin color and name implies they meet a particular definition. Where someone meets the skin color marker of whiteness but fails the name marker, we opt to categorize them according to the character’s name and what it implied about the player.

Analytic strategy

FIFA’s main claim is its realism. Moreover, as FIFA’s characters are encoded by data reviewers (i.e., fans who are so invested in the game that they volunteer their labor to maintain that realism), any differences among racial groups congruent with the dominant discourses of racism are assumed to be an attempt to encode realism by deferring to racism. Of course, blatant racism would also account for any statistical differences. However, we follow Bonilla-Silva’s (2010) assertion that while blatant racism does still occur, racism is predominantly systemic and articulated as seemingly non-racist ideas.

The co-authors independently coded 2,494 (N = 2,494) FIFA characters for race. Krippendorff’s alpha was calculated at .8533 (α = .8533) (Hayes and Krippendorff, 2007). As Krippendorff’s alpha is a conservative method of computing intercoder reliability, we find the coefficient acceptable. A one-way MANOVA compared how a character’s race affected the character’s strength, aggression, agility, and vision scores. Descriptive statistics indicated few characters coded as Other (n = 2), American Indian/Alaskan Native (n = 15), Asian (n = 18), or Native Hawaiian/Other Pacific Islander (n = 11). We opted to drop those cases rather than risk errors. Additionally, glitches in the API resulted in entries with missing scores (n = 402), which we dropped. Our number of cases after dropping the Other, American Indian/Alaskan Native, Asian, Native Hawaiian/Other Pacific Islander and missing characters resulted in a total number of 2046 cases (N = 2,046 out of 2,494 cases originally).

 

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Results

Our hypothesis is that systemic racist discourses of biological differences would be used to enable platformed racism in EA Sports’ FIFA. Therefore, we expected that these differences would be seen in various character attribute scores. That is, data reviewers would encode athletes’ performances using a U.S. racial frame despite the game code’s lack of explicit racism. Our results support our hypothesis: race significantly affects characters’ attribute scores, [F(8, 4080) = 67.096, p = .001, η2 = .116]. Players’ race affects their strength score at the p < .001 level [F(2, 2043) = 50.605, p < .001, η2 = .050], aggression score at the p = 0.001 level [F(2, 2043) = 7.446, p = 0.001, η2 = .007], agility score at the p < .001 level [F(2, 2043) = 53.957, p < .001, η2 = .051], and intelligence (vision) score at the p < .001 level [F(2, 2043) = 28.782, p < .001, η2 = .021].

Post hoc analysis

We conducted a Tukey HSD post hoc analysis to examine how the mean scores for each race differed. As the table shows below, black athletes were scored by data reviewers as having significantly higher mean scores for aggression and strength than either white or Latino characters. This follows the dominant U.S. racial discourse. Vision acts as a proxy score for intelligence in the game. The mean vision score for blacks was significantly lower than either whites or Latinos. However, there was no statistically significant difference between the vision scores of whites and Latinos. This partially aligns with the hegemonic racial logic in the United States. However, that there was no significant difference between the mean scores for Latinos and whites runs contradictory to the predominant racist belief.

 

Tukey HSD
Tukey HSD
 

 

 

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Discussion

Media and journalism scholars have pointed out that media representation of minorities inform how the public sees Othered bodies (see Saha, 2018). The data reviewers, whether intentional or not, view their perceptions as reality and therefore encode bias such as the stereotypes of black athletic physicality and bellicosity that are often found in U.S. racial sport histories, science, popular culture, and the assumed white intellect (Stone, et al., 1997). On one hand, this is a case study of one game series. On the other hand, this is problematic for the larger video game community because black and Latino characters tend to be overly represented in sports related video games (Chan, 2005). Moreover, this overrepresentation tends to be avenues where white fantasy of supposedly extraordinary black physical ability is expressed and exploited for white enjoyment (King, et al., 2007; Leonard, 2004, 2003). Because blacks and Latinos are overrepresented in sports games, how those games construct them wields outsized weight. This imaginary of athletic blackness in the U.S. has continually been employed as a marketing tool to make black athletes legible to white mainstream consumer populations.

Our results indicated that biological views consistent with systemic racism is present in EA Sports’ FIFA video game’s FUT mode. We argued that games in general — and this game series in particular — is a platform. Thus, platformed racism can take the form of video games. Notably, because FIFA’s main selling point is its supposed realism and its attempt at neutral code, the presence of systemic racist discourses implies that realism itself was the key that made the game an example of platformed racism. To put it another way, the game’s design strategy of “realism” enabled racism to emerge. And, in doing so, enabled platformed racism.

Social realism in games

By realism we mean what Galloway (2004) calls social realism — the idea that what marks a video game as realistic is its fidelity to our social understanding of what is real in the world. This is distinct from photorealism or the fidelity of visual representation of objects to their material analogue. It stands to reason that players perceive the body of in-game athletes as predicated in part by an attempt to be realistic. After all, this is the main logic of games like FIFA, where ability statistics supposedly mirror physical bodies. Galloway (2004) argues that games are understood by the player as realistic insofar as they operate within the context of the social world that is understandable to the player. That is, fidelity in visual representation and fidelity in narrative representation from a game’s social realism, or fidelity of context. He argues, “[f]or instance, listening to music, ordering pizza and so on in The Sims is ... closer to the narratives of normal life than storming an enemy base in SOCOM, despite the fact that the actual visual imagery in SOCOM is more realistically rendered.” [2] SOCOM, the first-person shooter game where players use photorealistic guns to shoot at photorealistic enemies, is less real than ordering pizza on The Sims because we likely can recall the experience of ordering food but not the carnage of mass gun violence. This is similar to what narratologists have argued: Humans understand reality through narratives that contextualize information about the world (see Fisher, 1984). The difference is that Galloway’s (2004) fidelity of context relies on the porousness of game worlds where the real world intrudes and plays within the game space (see Consalvo, 2009).

The social aspect of racism

Bonilla-Silva’s (2010) seminal work implies this too when he finds that, while less common than their white counterparts, black interviewees also harbored anti-black views because those are the discourses that structure the social world. For audiences then, realistic is in part judged by who plays or design games (Machin and Suleiman, 2006) and audiences’ own personal identities. And, that judgement is rooted in audience perception of the genre and the story’s convergence with pre-existing view of what is real (Hall, 2009, 2003). Thus, even if we assume that all of FIFA’s external data reviewers are marginalized people of color (improbable, of course), research would suggest that reviewers would still harbor racially problematic ideas. They would be ineffective in curtailing racism while offering a cover from accusations of racism. We wish to note that we make no assumption of whether or not data reviewers are racist. Systemic racism appears in the larger cultural and social system. Questions about individuals are outside the scope of this paper and our theoretical lens.

Within a culture marked by systemic racism, realism is itself a discursive strategy that cede space for racism to encroach (Bonilla-Silva, 2010, 1997). This paper, therefore, accounts how attempts to be realistic can become the praxis through which racist ideas are activated. In our findings of U.S. player data in the FIFA video game series, social realism allows for data reviewers — players tasked with monitoring the performance of athletes and encoding perceived changes onto the athletes’ associated characters — to reify racial biases into the game while shielding the game developers and themselves from critiques of racism. To put it another way, the moment those racist tropes are articulated into the game by data reviewers is the moment in which the game becomes real. Again, these tropes were not imposed from game designers, nor planned by volunteers. As we argued, it is precisely this foregrounding of realism that leaves a contextual gap which data reviewers (players) can fill with problematic unconscious biases. Accuracy is not the nail on which realistic media hangs (Hall, 2009). This confirms Galloway’s (2004) assertion that realism in games depends on a fidelity of context. Race, after all, is socially constructed. Thus, as our study shows, to be mechanistic or non-narrativistic makes space for racialized discourses to fill in the gaps on the part of the player and results in a safe harbor for racism through realism. Even chess evokes narratives of status in its references to men/pieces/peons and kings/queens. Perhaps, beyond being narrative creatures, humans are creatures that cannot help but narrate.

Realism in platformed racism

Again, the FIFA series’ selling point is its supposed realism. What we see here is not explicit racism or unintentional racism because of a game narrative. What our results demonstrate is how realism is used to sell games while simultaneously acting as a vehicle for enabling platformed racism. By foregrounding realism, the FIFA series can profit off of racist discourse while remaining clean of racism’s stain. Galloway notes that a game’s realism is the product of the interaction of the text and the player, insofar as the player can understand the game in the context of his or her social world. In this way, FIFA enabled racism in their game through technical affordance, governance, capitalism, and a libertarian Silicon Valley idealism (Matamoros-Fernández, 2018, 2017). The accuracy of the characters’ ability scores is not aligned with any factual view, only what feels factual to the players. In this study, platformed racism depends on social realism as a marker of precision and authenticity (of the ability scores), which permits social biases.

In a slight departure from what Srauy (2019) noted, racism is not explicitly deployed here as a backstop against market uncertainty. Rather, FIFA’s attempt to deploy realism as their selling point allows for racism to elide into the game. It seems that realism in this case required racism to become legible. What is insidious is, as Gray (2012) noted, deviance is an anchoring factor that makes Otherness knowable. In this regard, we read the overrepresentation of black and Latino characters in physical ability and their underrepresentation in mental ability (and the inverse for whites) as the sacrificing of black and Latino bodies in an attempt at realism for white normativity.

 

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Strengths and weaknesses

This study further demonstrates platformed racism’s explanatory power. We extend and specify what is meant by the platform’s affordances to include the normative values — in our case, video game realism — that invite systemic racism in and expresses racism in this novel way. In this regard, platformed racism’s strength and this paper’s contribution is in further outlining the value of recognizing the role of users’ and producers’ sociality by lending empirical weight.

Our MANOVA indicated an unexpected result — namely, vision (intelligence) scores are not statistically different between white athletes and Latino athletes. Since the vision score — according to the developers — is a composite of intelligence and knowledge of the sport, we cannot disaggregate the two. This potentially explains the result. We leave this for further studies to examine. A primary weakness of our study is that we cannot tell why data reviewers re-encoded racism into the game. We do not know, for example, if they are encoding systemic racism or racism that is embedded in professional soccer. But, since this is a study of the game as a platform for racism, we believe the weakness is acceptable. For that explanation, we turn to past studies which suggest that this is the legacy of vilifying and marking deviant black and Latino bodies (Bonilla-Silva, 2010; Gray, 2014; Leonard, 2004, 2003). In our study, we see how striving for realism creates a space for racism. Systemic racism, after all, is endemic.

Our study’s strength lies in its explanation of how in the attempt at non-racism, racism finds a way back in. In our case study, the popular FUT mode’s reliance on decontextualized ability statistics and voluntary player labor (i.e., data reviewers) becomes the mechanics of how racism is recontextualized into the game, becoming a form of platformed racism.

 

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Conclusion

Beginning with the assumption that video games meet the definition of a platform, our study found that platformed racism was present in FIFA character statistics. While the developers did not specifically encode ratings of athletes’ physical abilities per se, by setting up a structure where those abilities can be noted by video game players (i.e., data reviewers), systemic racist discourses of race as biological differences were invited into the platform (i.e., the video game). We conclude this is likely due to the game’s noted “realism.” Because the game was marketed as realistic to players, data reviewers strove to maintain that realism through social cues in their society — the United States, in our case study. This implied that systemic racism was the lens that enabled to data reviewers to comprehend the game as realistic, and realism was the vehicle that invited platformed racism into the game.

How racism is recontextualized and that it is recontextualized at all, is troubling. If, as research suggests (Shaw, 2012, 2010), video games are popularly viewed as a predominantly white space that relegates minorities to sports games, then online sports games like FIFA’s FUT mode doubly harms minority game players. They are marked as deviant in their online presentation of self through online chat functions (Gray, 2012) while minority characters are marked as deviant through data reviewers whose intention is realism. This also suggests that for game developers to try to create a non-racist space for players, explicit anti-racism is needed. But, given this historical moment’s heightened anti-social justice tenor, explicit attempts are likely to incur market risks by developers and publishers, reifying video games as a white space. End of article

 

About the authors

Sam Srauy is Assistant Professor in the Department of Communication and Journalism at Oakland University in Rochester, Michigan.
Direct comments to: srauy [at] oakland [dot] edu

John Cheney-Lippold is Associate Professor in the Department of American Culture at the University of Michigan in Ann Arbor.
E-mail: jchl [at] umich [dot] edu

 

Notes

1. Matamoros-Fernández, 2017, p. 932.

2. Galloway, 2004, paragraph 7.

 

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Editorial history

Received 3 May 2019; accepted 26 May 2019.


Creative Commons License
This paper is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Realism in FIFA? How social realism enabled platformed racism in a video game
by Sam Srauy and John Cheney-Lippold.
First Monday, Volume 24, Number 6 - 3 June 2019
https://journals.uic.edu/ojs/index.php/fm/article/view/10091/8046
doi: http://dx.doi.org/10.5210/fm.v24i6.10091





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