Everyone Needs to Pitch In”: an Ethnographic Study Of

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The Pennsylvania State University

The Graduate School

“EVERYONE NEEDS TO PITCH IN”: AN ETHNOGRAPHIC STUDY OF

COLLEGIATE ESPORTS

A Dissertation in

Learning, Design, and Technology

Robert Hein

Submitted in Partial Fulfillment

of the Requirements

for the Degree of

Doctor of Philosophy

December 2020

The dissertation of Robert Hein was reviewed and approved by the following:

Ty Hollett Assistant Professor of Learning, Design, and Technology Dissertation Advisor Chair of Committee

Simon R. Hooper Professor of Learning, Design, and Technology

Stuart A. Selber Associate Professor of English Director of Digital Education

Priya Sharma Associate Professor of Learning, Design, and Technology

Susan M. Land Associate Professor of Learning, Design, and Technology Director of Graduate Studies

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ABSTRACT

Although researchers have shown interest in videogaming since the early 2000s, the hyper- competitive world of “esports” has received less attention. However, multi-million dollar gaming tournaments—such as the 2019 Fortnite World Cup—now make headlines and spark national discussion. Similarly, colleges and universities have begun offering athletic scholarships to students who excel at games like League of Legends and Overwatch.

Consequently, this present study aims to shine a light on the values, beliefs, and practices of gaming’s most “hardcore” players and communities. To better understand how these competitors improve their in-game skills, the author adopted a “connective ethnographic” approach and immersed himself in the day-to-day activities of a collegiate esports club. This process involved attending club meetings, interviewing members, and participating alongside players as they competed with and against one another in the game of Overwatch. As the investigation unfolded, the study narrowed its focus to explore how club members leveraged technology—like the livestreaming platform of Twitch and social network of Discord—to engage in collaborative observation, analysis, and self-critique. By drawing and iterating upon

Gee’s “affinity spaces” and Rogoff’s theories of “learning by observing and pitching in,” this study suggests that competitive gamers naturally create and seek out their own learning ecologies. More specifically, these gamers come together to form “observational and analytical gaming ecologies” (OAGEs) wherein members find the cultural tools necessary to experience and re-experience gameplay from multiple perspectives. By harnessing virtual worlds and emerging technologies in compelling new ways, these gamers are thus reimagining how people learn from their peers and from their own failures.

TABLE OF CONTENTS

LIST OF FIGURES ...... vi LIST OF TABLES ...... viii ACKNOWLEDGEMENTS ...... ix

CHAPTER 1: INTRODUCTION………………………………………………………….. 1 Background………………………………………………………………………… 2 Why Esports, Why Now?………………………………………………………….. 5 Research Questions………………………………………………………………… 7 Significance…………………………………………………………………………8 Chapter Outline…………………………………………………………………….. 9

CHAPTER 2: LITERATURE REVIEW AND THEORETICAL FRAMEWORK……….. 11 Affinity Spaces……………………………………………………………………...11 Esports and Livestreaming…………………………………………………………. 15 Learning by Observing and Pitching In……………………………………………. 31 Towards a Theory of Observational and Analytical Gaming Ecologies…………... 38

CHAPTER 3: METHODS…………………………………………………………………. 41 A “Connective” Ethnography……………………………………………………… 43 Primary Research Sites…………………………………………………………….. 45 Overwatch………………………………………………………………….. 47 Twitch……………………………………………………………………… 51 Discord……………………………………………………………………... 53 Willard 371………………………………………………………………… 55 Overview of Participants……………………………………………………………57 Profiles of Select Participants……………………………………………………… 58 Researcher Identity………………………………………………………………… 63 Procedure and Data Collection…………………………………………………….. 65 The Weekly Meeting………………………………………………………..65 Match Day………………………………………………………………….. 69 Informal and Impromptu Sessions…………………………………………. 74 Interaction and Data Analysis……………………………………………………… 77 Summary…………………………………………………………………………… 82

CHAPTER 4: FINDINGS…………………………………………………………………. 84 Preparation…………………………………………………………………………. 84 Scouting……………………………………………………………………. 84 Storytelling…………………………………………………………………. 91 Gameplay…………………………………………………………………………... 99 Callouts…………………………………………………………………….. 99 Emotional Calibration……………………………………………………… 107 Review……………………………………………………………………………... 120 Self-Reflection……………………………………………………………... 120 Looking to the Pros………………………………………………………… 126 v

A Culture of Leveraging Perspectives……………………………………………... 132

CHAPTER 5: DISCUSSION AND IMPLICATIONS…………………………………….. 140 Summary and Discussion of Findings……………………………………………... 141 How Club Members Participated with One Another………………………. 141 How Club Members Organized Themselves………………………………. 145 How Club Members Interfaced with a Wider Community………………… 149 Contributions………………………………………………………………………. 153 Contributions to Theory……………………………………………………. 153 Methodological Considerations and Recommendations for Future Work… 155 Towards an OAGE-Infused Classroom……………………………………………. 158 Closing……………………………………………………………………………... 160

REFERENCES…………………………………………………………………………….. 163

LIST OF FIGURES

1.1: The anatomy of a Twitch stream………………………………………………………. 3

1.2: The anatomy of a Discord server……………………………………………………... 5

2.1: Competition in early arcades………………………………………………………….. 18

2.2: The Shanghai Dragons win their first match…………………………………………. 29

2.3: The LOPI Prism……………………………………………………………………….. 36

3.1: A “Victory Screen” in Overwatch…………………………………………………….. 41

3.2: A “Field of Relations”………………………………………………………………… 46

3.3: Tracer’s abilities in Overwatch………………………………………………………...48

3.4: The “Battle of LA”……………………………………………………………………. 49

3.5: In-game spectating…………………………………………………………………….. 51

3.6: Club members streaming……………………………………………………………… 53

3.7: The club Discord server………………………………………………………………. 55

3.8: The weekly meeting……………………………………………………………………56

3.9: An in-person VoD-review…………………………………………………………….. 69

3.10: An Overwatch “lobby”………………………………………………………………. 72

3.11: Sending a Discord “ping”……………………………………………………………. 75

3.12: A text-based VoD-review……………………………………………………………. 79

3.13: Conducting analysis………………………………………………………………….. 81

4.1: Oak’s scouting report…………………………………………………………………..85

4.2: Junkertown……………………………………………………………………………..93

4.3: Storytelling at the weekly meeting……………………………………………………. 98

4.4: Comic panels showcasing “callouts”………………………………………………….. 100-4 vii

4.5: Comic panels showcasing “emotional calibration” …………………………………... 109-13

4.6: More comic panels showcasing “emotional calibration”……………………………... 115-8

4.7: Coaching through Discord………………………………………………...…………...121

4.8: Dealing with Mei……………………………………………………………………… 123

4.9: The Open Division stream…………………………………………………………….. 124

4.10: The Dallas Fuel “comp”……………………………………………………………...129

5.1: Cross-contextual participation………………………………………………………… 145

5.2: The “Academy Team”………………………………………………………………… 148

5.3: The Esports Club during Covid……………………………………………………….. 161

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LIST OF TABLES

3-1: List of Participants……………………………………………………………………. 58

3-2: Types of Data…………………………………………………………………………. 77

ACKNOWLEDGEMENTS

Research and writing are not individual endeavors. This dissertation was only made possible by amazing ensemble cast that worked tirelessly behind the scenes. I would now like to recognize those colleagues, friends, and family members that supported me on this journey.

To my committee, thank you for your patience, trust, and open-mindedness. I will always remember Dr. Priya Sharma as one of the first professors to welcome me to the department. By legitimizing the study of videogaming and action-sports in her own classroom, she gave me the confidence to pursue the “new and strange” types of research that I describe throughout this dissertation. Dr. Stuart Selber offered me a safe haven at a time when I was feeling lost in my graduate studies. In particular, he encouraged me to learn and experiment with multimodal tools to better bring my research and writing to life. Similarly, Dr. Simon Hooper constantly challenged me to answer the question “so what?” He thus showed me how to take the theories and philosophies of our discipline and to turn them into something more tangible and practical. Dr. Ty Hollett tied it all together while providing a steady voice of encouragement throughout the process. I could not have completed this dissertation without him. He always knew what to say and how much space to give me. I will always treasure our conversations at

Rothrock Coffee, where he taught me how to become a better researcher, writer, teacher, and person.

To my friends and family, thank you for keeping me sane during these last six years. Dr.

Jason Engerman mentored me in qualitative research methods and exemplified how to be a hardworking graduate student. Dr. Nate Turcotte helped me to break out of my shell and to be more sociable at academic conferences. My parents, Jim and Georgienne Hein, not only x were my number one fans, but they also became my go-to editors and therapists. My godmother,

Dr. Roberta Zolkoski, represented a spiritual rock to help anchor myself during uncertain times.

And to the members of the Penn State Esports Club, thank you for the excitement and interest you showed in my work. Thank you for spending your time and energy to teach a thirty- year-old “boomer” about your culture’s practices, values, and beliefs. “GG.”

CHAPTER 1: INTRODUCTION

When I was growing up, my best friend, Evan, owned a Sega Genesis. While I had a hand-me-down Nintendo, it simply was not the pinnacle of cool that the 16-bit Genesis was in

1992. Mario was dull and boring; Sonic was intense and flashy. Not surprisingly, I would always leap at the opportunity to visit Evan and spend as much time as possible zipping around

Green Hill Zone as everyone’s favorite blue hedgehog. There was only one problem; we had to take turns. Looking back on it, we were actually pretty good at the whole sharing thing—Mr.

Rogers had taught us well. However, that did not stop the waiting, the watching, from being agony.

The irony is that, 25 years later, many gamers—including the participants of my study— are just as happy (if not more so) to tune into a gaming event on Twitch.tv as they are to boot up the Xbox and play for themselves. What changed, and why does it matter? My dissertation aims to explore these and other questions related to the burgeoning world of “esports,” video game spectatorship, and their increasingly intertwined cultures. By both examining and participating in the games themselves, as well as their online community hubs like Twitch and Discord, I hope to give readers a more holistic understanding of the values, beliefs, practices, and rhetoric of esports competitors. More specifically, I want to arm teachers with new ways to think about and connect with their Fortnite-obsessed students—to help them leverage how learning occurs in esports communities in order to build a better classroom.

This dissertation isn’t about the games today’s students play. It doesn’t attempt to claim that those same games have some latent educational value trapped inside of them. Those papers have been written, discussed, and revisited many times over (Gee, 2003; Prensky, 2006; Squire,

2006). This study, instead, is about learning through observation, interaction, and authentic 2 participation. It is about how affinity spaces have and will continue to evolve to accommodate their members. It is about how a community of “hardcore,” competitive gamers leverages livestreaming technology to transform both gameplay and culture.

Background

As I alluded to in my introduction, I’ve been a “gamer” my entire life. I grew up with the likes of Donkey Kong and Mario, and I have continued to play a variety of games—across all platforms and genres—into my early thirties. And although I’ve been keenly aware of the industry’s growth and development over the years, sometimes even I forget how culturally relevant and economically powerful gaming has become. In November of 2018, Red Dead

Redemption 2—a wild west adventure game—sold $725 million worth of copies in just three days (Business Wire, 2018). For context, the film The Avengers: Infinity War, which had one of the biggest box office openings in history, made $630 million worldwide over the same span

(Mendelson, 2018). While I don’t care to make the argument that games have somehow eclipsed or replaced more traditional forms of media, I do want to emphasize that—broadly speaking— gaming can no longer be viewed as a niche hobby. As educators, it is important to remember that many of our students are gamers—and those that don’t identify as such are nevertheless influenced by modern games and their various communities. We have a responsibility to our students to understand where, how, and why they consume and transform culture. This dissertation therefore will take readers to those locations and expose them to those aims and methods. Specifically, it examines how the most competitive of these gamers collaboratively create, watch, and learn through Twitch—a popular video game livestreaming platform and one of the fifty most-visited websites in the world (see Figure 1.1).

Figure 1.1: Popular Twitch personality, Summit1G, broadcasts his gameplay live to thousands of viewers who can “chat” together during the show. This simultaneous performance and interaction distinguishes the platform from similar sites like YouTube.

However, as Engerman (2016) reminds us, “gaming” is so broad, and its players are diverse in their goals and interests. Under the umbrella of gaming, players often feel it’s necessary to break themselves into many different subcommunities, factions, and cliques. For researchers, it becomes easy to misrepresent or conflate these groups’ values and beliefs (Becker,

2008) and, consequently, to make sweeping claims about how all gamers must therefore leverage technology, approach challenges, and teach one another. After all, to the untrained eye, the visuals and gameplay of titles like Call of Duty and PlayerUnknown’s Battlegrounds look identical; the way their communities interact on Twitch appears similar. I have always been particularly sensitive to this confusion. During my teenage years, my parents would regularly ask me if I could “pause Mario” when, in reality, I was playing World of Warcraft—a drastically different game—online with my friends. As researchers, we owe it to these communities to understand what makes them unique; not only will we be treating them with care and respect, but we will also be able to bring the best, targeted theoretical and analytical tools to bear on their 4 study (Creswell, 2013). My dissertation makes both a concerted effort to address these concerns and to provide a model for future research to follow and build upon.

As such, it is important to remember that data I present, describe, and discuss herein is unique to a very particular subset of gamers—esports competitors. They have been chosen precisely because their unwavering pursuit of mastery drives them to the cutting edge, to innovation (Hein & Engerman, 2016). They are the gamers that have historically experimented with and pioneered the technology that ultimately becomes commonplace in the broader community. Through a focus on esports competitors, we can better understand how and why certain tools—like Twitch and Discord—become either adopted or discarded, updated or

“modded” (see Figure 1.2). We can better see their affordances and constraints in practice, and, consequently, make informed predictions and recommendations regarding their use in other educational settings. While my own study doesn’t necessarily aim to provide blueprints for using either Twitch or Discord in the classroom, it nevertheless recognizes teachers’ efforts to channel such technology to engage learners (Alvermann et al. 2018, Caldwell et al., 2017;

Engerman et al. 2015). Moreover, it describes and discusses how esports culture understands and foregrounds learning while simultaneously advancing our field’s own theories related to participation in digital communities.

Figure 1.2: Discord (shown here) is one of the emerging tools that competitive gamers are using to connect, mobilize, and communicate online. It blends the features of traditional message- boards, instant messaging, and voice chat to help its users find and build likeminded communities.

Why Esports, Why Now?

Although academia has shown interest in gaming since the early 2000s (Anderson &

Bushman, 2001; Gee, 2003; Jenkins, 2006), it has been somewhat slower to respond to and study esports cultures and communities—which, as Taylor (2012) reminds us, have existed since the

1970s. I really can’t blame researchers for overlooking this particular gaming niche until recently. Throughout the 1990s and 2000s, esports communities (in the United States) were far more clandestine, and their tournaments and events were generally unsponsored, unsanctioned, and underground (Hein & Engerman, 2016; Kane, 2008; Taylor, 2012). However, thanks to its increased visibility on Twitch.tv, showcases on major television networks, and multi-million dollar investments from the likes of Comcast and Robert Kraft, esports and their communities have become more accessible and less opaque. Perhaps most notably, however, colleges and universities have begun offering athletic scholarships to students who exhibit tremendous skill or potential in esports titles like League of Legends and Overwatch (Melcher, 2014; Perez, 2018;

Robinson, 2016). These developments at once raise questions about the relationship between 6 traditional sports and digital hobbies (Holden & Kaburakis, 2017; Jenny et al., 2017; Wagner,

2006), while also simultaneously serving to legitimize esports as a meaningful, worthwhile endeavor for young people to pursue (Richard et al., 2018). As educational researchers, it feels like we have some catching up to do—we have to equip ourselves to study, interact with, and teach a new generation of student-athletes. Moreover, with esports bursting so publicly onto the university stage, many administrators, policy makers, and benefactors will soon find themselves navigating blindly and on uncharted waters.

I have a bit of a personal stake in all of this as well. In many ways, this dissertation represents the culmination of an adventure started back in 2006, when I attended and participated in my first esports event—a small, 16-person Super Smash Brothers: Melee tournament held at a now defunct gaming café. I lost and lost badly, but that experience opened my eyes to a wider world. It led me to discover a tight-knit community of high school and college gamers that were fixated on improvement. At the time, their digital home was a place called Smashboards, a text- based discussion forum in the tradition of websites like AoM Heaven, which Gee (2005) explicitly references and champions as a quintessential “affinity space.” While archaic by today’s standards, Smashboards nevertheless served as both a hub and a gateway for novice gamers like myself. By making visiting, exploring, and writing on Smashboards part of my daily routine, I “got good,” really good. It wasn’t long before I was placing highly in tournaments and making a name for myself in the wider community. To this day, I’m still amazed by how quickly and seamlessly I made that transition from novice to expert, and I still want to know more about exactly why and how it happened. However, as much as I might want to go back in time to study those moments, esports communities are always moving forward and looking to adopt new tools and technologies to help their members improve. Although Smashboards itself 7 might now be a relic of a bygone era, the heart and soul of its community has migrated to new platforms like Twitch and Discord, each of which boast their own unique affordances that I hope to unpack and analyze through my study of collegiate esports.

As the platforms where these esports communities interact and participate evolve, so to must our theories and methods to study them. There has been a wealth of literature written about games and learning through affinity spaces, but the constant transformation and reproduction of both culture and gameplay on Twitch—in particular—challenges our understanding. Here, the lines between novice and expert, between spectator and participant, between past and present blur in strange and surprising ways. To help untangle this web, I turn to equally surprising places—most notably to studies on indigenous Central American communities and their childrearing practices and spiritual ceremonies (Rogoff et al., 2014). For Rogoff (2014), these communities thrive when members—both novice and expert alike—can make meaningful contributions to shared endeavors. As I explore, Rogoff’s ideas provide us with a framework for understanding the cultural practices and values we see in collegiate esports competitors. In turn,

I hope that my work—through its focus on digital communities—is able to give back and make meaningful advancements in theories of “learning by observing and pitching in” as described by

Rogoff (2014).

Research Questions

However, like Smashboards before them, Twitch and Discord will exist only so long as gamers find them productive and entertaining. I, therefore, feel pressure to conduct a study that will survive the rise and fall of the specific technologies it describes. Thus, I have engineered my research questions in the hopes of ultimately painting a cultural portrait (Creswell, 2013). I 8 want to tell the story of how collegiate esports works, informed by the shared values, experiences, practices, and words of the people who live it.

1. How do club members participate with one another in shared, community endeavors? a. How do they leverage technology to transform that participation? 2. How do club members organize themselves (in-game, online, and in-person)? a. How do they negotiate their differences and provide feedback to one another? 3. How do local club members interface with and relate to players and fans of the larger, global esports community?

Significance

While interest in collegiate esports is at an all-time-high, researchers are not necessarily equipped to conduct immersive studies on its culture. For example, although Taylor’s (2012) study led her to observe, interview, and interact with community members, she stresses that her work is not an ethnography. She remarks that she—as a [relatively] older woman and noncompetitor—never felt like a “natural inhabitant of the e-sports community” (p. 29). Not surprisingly, she laments that “things that were obvious for the insiders generally weren’t for me” (p. 29). This is to take nothing away from Taylor’s contribution, her Raising the Stakes is undoubtedly the seminal text on esports’ formalization. However, her struggles are nevertheless representative of those facing researchers across the nation. The world of gaming—especially that of esports—moves faster than most of us can keep pace. Fortunately, as someone who has remained “jacked in” to the esports community for over a decade, I am uniquely positioned to translate jargon, uncover themes, and make connections that outsiders might overlook or misinterpret1. The following study thus serves to fill gaps in our understanding of esports culture by taking a decidedly ethnographic approach; likewise, it provides a gateway for fellow teacher-

1 I realize that, in many ways, my identity as a former competitive gamer is a double-edge sword—as I will have to negotiate and reckon with my biases throughout this study. I will explore this researcher identity in greater detail in chapter three. 9 researchers to enter and thereby contribute to ongoing discussions about competitive gamers and the tools that help them learn.

Chapter Outline

Over the course of this dissertation, I draw on theories of informal, community-driven learning in order to make sense of how esports competitors transform and share their practices.

- Chapter Two will begin this effort by synthesizing literature on “affinity spaces”

(Gee, 2005) and theories of “learning by observing and pitching in” (Rogoff, 2014). I

continue by detailing the history of competitive gaming and exploring its complicated

relationship with livestreaming technology. By supplementing these theories and

stories with related, games-based research, I conclude this chapter by introducing the

concept of observational and analytical gaming ecologies (OAGEs), a lens through

which researchers can better examine and understand the motivations and experiences

of modern esports-competitors.

- Chapter Three will describe my participants and methods. I guide readers through a

connective ethnographic approach that involves both online and face-to-face data

collection (Leander, 2008). I also provide an overview of Twitch, Discord, and

Overwatch—the three digital loci of club activity. Finally, I describe how interaction

analysis enables me to parse data from across these various settings (Jordan and

Henderson, 1995).

- Chapter Four details my findings. Specifically, I describe my participants’

observational and analytical practices as they watch, play, and discuss the game of

Overwatch. Likewise, I both summarize and provide excerpts from participant-

interviews that further contextualize my data. 10

- Chapter Five returns to and expands on the theoretical and methodological

frameworks outlined in previous chapters; specifically, I continue to develop and

define my own understanding of OAGEs. In so doing, I also discuss my work’s

implications for future games-based research, learning design, and classroom

application. I then conclude by reframing our wider, societal conversations about

video games to focus on what players actually do in and beyond their favorite virtual

worlds.

CHAPTER 2: LITERATURE REVIEW AND THEORETICAL FRAMEWORK

In this chapter, I bring together literature that examines how learning occurs in “affinity spaces” (Gee, 2005) and through “intent participation” (Rogoff & Paradise, 2003; Rogoff, 2014);

I make an effort to place that literature in the context of emerging esports and livestreaming communities so I can advance and describe a theory of observational and analytical gaming ecologies (OAGEs). While studies on affinity spaces have been central to games-based research for over a decade (Curwood et al., 2013; Hayes & Duncan, 2012; Gee & Hayes, 2012; Lammers,

2011), many of these interest-driven communities are migrating to—and even pioneering— strange, new platforms like Twitch. As Squire (2011) reminds us, gaming culture has always been a “participatory” one; the affordances of modern livestreaming technologies embrace and extend that tradition in complicated ways. Consequently, to fully understand how today’s esports competitors are changing the game, researchers need to arm themselves with specially tailored theories that can adequately account for the values, beliefs, and practices of these most

“hardcore” gamers. Thus my goal, in advancing a theory of OAGEs, is twofold: (1) to respond to recent calls to examine the “psychological, social, and performance-regulatory techniques” of esports competitors (Richard et al., 2018) and (2) to establish the rhetoric and tools I need to describe and analyze the unique cultural practices of this study’s participants.

Affinity Spaces

When Gee (2005) originally forwarded and conceptualized affinity spaces, he did so as a reaction to Lave and Wenger’s (1991) notion of a “community of practice.” Gee desired to focus on the “space” in which people interact rather than on their “membership” in a community. For

Gee, the true danger with thinking in terms of communities of practice is found in labeling—and 12 mislabeling—people. In many ways, this dissertation is born out of similar fears. As I alluded to in my introduction, our society is still quick to stereotype “gamers” as white, heterosexual, antisocial males (Becker, 2008; Chess et al. 2017; Kane, 2008; Paaßen et al., 2017). When journalists and researchers produce work that actively combats those stereotypes, they often fail to highlight—or even acknowledge—the deep-seated philosophical and cultural differences between the various gaming sub-communities. It’s easy to understand how readers might come away from such pieces mistakenly thinking that all gamers develop similar skills and respond to certain stimuli in certain ways. As such, by starting with the space-first thinking outlined by Gee

(2005), I hope to avoid similar traps as I report, describe, and analyze how learning occurs through Twitch and Discord.

I don’t think it’s an accident that Gee, in his effort to define affinity spaces, turns to the game Age of Mythology and—more specifically—one of its online portals, AoM Heaven, as examples. As described by Gee (2005), Age of Mythology is a “real-time strategy” game in the tradition of Warcraft and StarCraft. It involves building and managing a mini-civilization while simultaneously commanding an ever-growing army against similarly outfitted computer or human opponents. It can be a creatively, intellectually, and mechanically taxing experience—so much so that I’ve shied away from playing such titles myself. Not surprisingly, and as Gee

(2005) explains, “[real-time strategy] games offer up a characteristic set of multimodal signs to which people can give specific sorts of meanings and with which they can interact in various ways” (p. 218). In other words, Age of Mythology features a complex rhetoric that newcomers must decode and internalize if they are to survive and, ultimately, to achieve victory in the game.

This often leads players to seek out “portals” like AoM Heaven to supplement, focus, and accelerate that process (p. 220). 13

Gee then goes on to list and describe the eleven definitive features of a paradigmatic affinity space and that are exhibited by the AoM Heaven website. Although I will not detail them all here, I nevertheless highlight those features that are of particular interest for my study and for advancing a theory of OAGEs. After all, it is the permutation and reimagination of these classic features that lend Twitch and Discord their allure and power today. For one, Gee explains that, on message boards like AoM Heaven, “newbies” and “masters” share a common space (p. 225).

These interactions often involve what Gee calls “mingling,” where visitors can freely choose when and how to learn from one another. Even the least experienced or confident members stand to benefit from “lurking” in the discussion threads of more advanced players. Lammers

(2011; 2012) provides a more specific example when she describes the critiquing process that occurs on fanfiction forums like The Sims Writers’ Hangout. In this particular case, users share their writing with one another in ways that resemble the peer review session of a traditional

English classroom. However, unlike the classroom, which Gee points out is quick to segregate students based on grade level and aptitude, critiques on The Sims Writers’ Hangout actively bring novices and experts together. Lammers adds that, by providing one another with a combination of “praise, evaluation, and suggestions,” these users practice pedagogical discourse while simultaneously sliding in and out of mentoring roles. Twitch and Discord, as I will later explore, bring added dimensions of connectivity and immediacy to the novice-expert paradigm that unfolds on more traditional online affinity spaces. These new wrinkles will pave the way for us to think in terms of OAGEs.

Gee (2005) also provides us with useful rhetoric for describing the different types of information that affinity space users learn and share. He argues that affinity spaces privilege both “intensive” and “extensive” forms of knowledge. On the one hand, intensive knowledge is 14 highly specialized. It is concerned with fine, minute details about a topic or activity; in gaming, precise information about character statistics, ability cool-downs, or weapon ranges constitutes intensive knowledge. Conversely, extensive knowledge refers to broader, macro-level concepts and ideas—i.e. understanding the importance of “high ground” in first-person-shooting (FPS) games. There is plenty of information to spread, and everyone—regardless of experience level—“has something special to offer” (Gee, 2005, p. 226). Steinkuehler and Duncan’s (2008) empirical study of conversation on World of Warcraft message boards supports this notion. For one, they found that 86% of talk on these forums involved “social knowledge construction[, or] the collective development of understanding, often through joint problems solving and argumentation” (p. 5). Moreover, they describe how “solutions developed by one person [were] referenced, debated, and built upon by masses of other participants, not merely a handful of designated experts” (p. 12, emphasis mine). For the likes of Gee, Steinkuehler, and Duncan, affinity spaces thus expose the inherent flaws of traditional classrooms; specifically, that our classrooms rarely encourage and enable students to gain intensive knowledge. When classrooms do, it is often a luxury afforded to only the most advanced students—and even they aren’t necessarily given the opportunity to share that newfound knowledge with the teacher and their classmates (Gee, 2005, p. 230). In affinity spaces, however, each user is seen and treated as a potentially valuable resource.

The final feature of affinity spaces that I want to touch on here relates to user participation. Specifically, and as Gee explains (2005), a good affinity space will carve out multiple “routes” to participation. That participation can be either “central” or “peripheral,” and its “patterns” might change over time (p. 228). Although Gee himself doesn’t describe this feature in great detail, Curwood et al. (2013) build on his outline to describe the “multifaceted, 15 self-directed, and dynamic” nature of participation on a Hunger Games fanfiction website (p.

680). On this particular affinity space, participation can involve creative writing, directing and producing videos, or designing roleplaying games. The authors add that, as users “gain social and cultural capital within the affinity space,” even more routes open to them; for instance, they might decide to become website moderators or to contribute to weekly podcasts (p. 680). For

Curwood et al. (2013), affinity spaces thereby become bastions for young people to engage in authentic, 21st-century reading and writing practices. Not only does this encourage us—as researchers—to bring multimodal theories of composition to bear on the study of affinity spaces, but it also challenges us—as teachers—to channel such spaces to bridge the ever-widening digital divide in our classrooms.

Unfortunately, even Curwood et al.’s (2013) revision and amendments cannot fully account for and describe the type of participation that now occurs on livestreaming platforms like

Twitch, where creation and publication occur simultaneously. On these new affinity spaces, the boundaries between writer and reader, producer and consumer, participant and spectator similarly blur and, on occasion, completely dissolve (Hein & Engerman, 2016; van Ditmarsch,

2013). In fact, Twitch brands itself as “a global community [that comes] together each day to create [its] own entertainment: unique, live, unpredictable, never-to-be repeated experiences created by the magical interactions of the many. You don’t just watch […], you’re a part of the show” (Twitch, 2018). Our understanding of authorship thus becomes complicated, and we need to dig deeper into the existing literature on esports and on video-game livestreaming to help us make sense of those “magical interactions.”

Esports and Livestreaming

In this section, I trace the history of competitive gaming as its communities migrated from the local arcade to the online and global platform of Twitch.tv. Along the way, I explore how certain deep-seated values and practices of esports culture evolved and intensified as its competitors gained access to increasingly powerful digital tools. Specifically, I use the personalities and events depicted in the 2007 documentary The King of Kong: A Fistful of

Quarters as a frame to help better understand what—in the esports community—has changed and what has remained the same.

In gaming culture, there has always been a split between the “casual” and the “hardcore”

(Fritsch et al., 2006; Poels et al., 2012; Taylor, 2012). According to Fristch et al. (2006), hardcore gamers exhibit a “stubborn resistance in playing the same game [and] with way more than average interest” (p. 2). Conversely, casual gamers tend to play a wider range of titles, but each with only a passing interest. As the popularity and “seriousness” of esports competitions has grown, so too has the contrast—behaviorally and ideologically—between hardcore and casual gamers. The goal of this section, therefore, is to explore the relationship between that

“stubborn resistance” of the hardcore gamers and the “magical interactions” that take place on video-game livestreams. To do so, first, it will be important to consider how games, their cultures, and their affinity spaces have evolved over time. By tracing competitive (hardcore) gaming’s trajectory, researchers thus can better understand the values, beliefs, and practices of its players today. We can better appreciate the unique affordances that Twitch—and through it, livestreaming—now provides.

When I was a young boy, I loved playing the original Super Mario Brothers for the NES.

I reveled in the accomplishment of completing particularly difficult jumps; I enjoyed the thrill of discovering secret power-ups or hidden levels. What I did not understand about the game, 17 however, was its seemingly arbitrary and meaningless scoring system. One hundred points for kicking a Goomba, five hundred points for grabbing a Fire Flower. They all added up and ultimately rewarded the player with nothing of significance. But of course I didn’t understand.

After all, I was a seven-year old kid playing alone in his parents’ basement. I was a “casual.” I had no knowledge of the wider, competitively-minded communities that Taylor (2012) describes in her account of esports’ formalization. For this hardcore audience, game mechanics like Super

Mario Brothers’ points become transformative vessels. They allow players to turn a leisure activity into a “deeply instrumental and serious endeavor” (Taylor, 2012, p. 3). As Taylor explains, “high score lists,” complete with players’ personalized initials, have promoted asynchronous competition since games like Asteroids (1979) filled arcades. Moreover, in these public arenas, practice and performance could become intertwined (Burrill, 2008; Harper, 2013).

For example, arcade-goers would often “alter their in-game and out-of-game behaviors to please or work the crowd” (Harper, 2013, p. 69). Successful player-performers could thus garner fame, notoriety, and respect from their peers.

The social and competitive dynamics of these arcade-goers is perhaps best captured by the award-winning documentary The King of Kong: A Fistful of Quarters (2007). The film follows an aspiring Donkey Kong player, Steve Wiebe, and his attempt to break the legendary game’s all-time scoring record (see Figure 2.1). On the surface, this documentary serves as an interesting time capsule and character study. However, for researchers, it does so much more—

King of Kong brings competitive gaming’s unwavering obsession with both recognition and legitimization into relief (Atencio & Beal, 2011). The film’s subjects repeatedly describe how motivated they are to prove and (im)prove their skills. One respondent even recalls his early memories of practicing arcade games saying, “I wanted to be a hero. I wanted to be the center of 18 attention. I wanted the glory, I wanted the fame, I wanted the pretty girls coming at me and saying ‘hi, I see that you’re good at Centipede’” (Walter Day, King of Kong, 2007). Setting a high score on a local arcade cabinet was only the beginning though. As the documentary explores, official organizations such as Twin Galaxies emerged in the 1980s to record, validate, and publish in-game achievements. Taylor (2012) adds that gaming magazines similarly began to print high-score lists “so players could compare their performance with those outside their immediate networks” (p. 6). To this day, that intense desire to become recognized—through legitimate channels—continues to drive the competition and innovation evident in modern esports culture. I will explore these emerging avenues in greater detail when I discuss the rise of

Twitch and livestreaming platforms.

Figure 2.1: Steve Wiebe plays Donkey Kong as onlookers crowd around him (Gordon, 2007).

As showcased in King of Kong, recognition and legitimization are central to competitive gaming’s story. Throughout the documentary, Wiebe is under tremendous pressure not only to 19 break the Donkey Kong scoring record, but also to do so in the “right” way—live, on a vetted machine, and in the presence of an official referee. Exhibiting that familiar “stubborn resistance” that characterizes so many hardcore gamers, Wiebe travels across the nation, from his home in

Washington to Funspot Arcade in New Hampshire, to test his mettle in a tournament setting.

After several arduous days of competition, Wiebe eventually succeeds in setting a new high score of 985,600 points and reaches the Donkey Kong’s famed “kill-screen,” the point at which the game runs out of memory and shuts down. Unfortunately for Wiebe, his reign as the new world record-holder is short-lived. Rival and self-proclaimed “gamer of the century,” Billy

Mitchell, quickly produces a low-quality VHS-tape depicting himself achieving an incredible

1,047,200-point score. As the audience, the film leaves us in an uncomfortable position and with an extreme lack of closure: just who is the true king of Kong? Is it Wiebe, who recorded his score through the proper channels and under intense scrutiny? Or is it Mitchell, whose higher score comes from a suspicious tape and was achieved on his personal cabinet? The questions and controversy are useful for us to consider because they put esports’ evolution—and that of its peripheral technologies like Twitch and Discord—into context. Players have long been motivated by the promise of fame; likewise, they have always been wary of cheaters. It is those desires and fears that shape how modern esports competitors approach, utilize, and modify affinity spaces. In particular, today’s most hardcore gamers—including the participants of this study—flock to Twitch because of its uncanny ability to expose; it serves to simultaneously vet and showcase top performers.

While King of Kong (2007) serves as an excellent entry point into this discussion, there are more academic works that describe and analyze the themes of recognition and legitimization as well (Boluk & LeMieux, 2017; Consalvo, 2005, 2009; Irwin & Naweed, 2018). As Taylor 20

(2012) reminds us, for many gamers, head-to-head multiplayer games like Doom and Quake began to replace the asynchronous competition of classic arcade games during the mid-1990s.

With this transition came new ways for players to gain exposure and new ways for them to abuse or cheat the system. For instance, Thiborg and Carlsson (2010) explore the nature of law and morality in Counterstrike, a popular FPS game that has remained a cornerstone of esports culture for well over a decade. The game pits teams of five terrorists and counter-terrorists against one another in a mad dash to either trigger or defuse explosives. Individual players are tasked with controlling their virtual avatars through war-torn streets and dark alleys as they attempt to sniff out and gun down their opponents. According to Thiborg and Carlsson (2010), successful players not only need to have lightning-fast reflexes, refined hand-eye coordination, and hyper- awareness, but they also need to accurately predict their opponents’ movements and strategies.

On the one hand, these factors make Counterstrike a compelling spectator sport. On the other hand, however, they have simultaneously made the game “a prime target for manipulation and exploitation by cheaters” (Thiborg & Carlsson, 2010, paragraph 43). In-game cheating, commonly referred to as “hacking,” can give users the ability to see through walls, ignore smoke or explosions, move at faster speeds, or even reduce weapon recoil. As Thiborg and Carlsson

(2010) explain, the specter of hacking looms so large over games like Counterstrike that many companies have developed sophisticated anti-cheat software to help detect offenders.

Furthermore, although Counterstrike can be played online, the most prestigious events are held in-person and over local area networks (LAN) in part to reduce the likelihood that players will be able to hack during competition (paragraph 23). Referees and tournament officials are not only able to inspect player equipment, but they are also able to observe gameplay from a variety of angles and perspectives. 21

Consalvo (2009) seizes on the complex relationship between cheating, fair play, and one’s ability to gain status within gaming circles. Based on her own series of interviews with players, designers, and anti-cheat developers alike, she notes that:

Players who are considered elite by other players are thought to possess large amounts (as well as particular types) of gaming capital. Such players may excel at playing particular types of games, or be quite knowledgeable about gaming hardware or the latest releases. They are aware of multiple options available in games, and can probably provide help or advice to other players. Such is the ideal gamer. Having such gaming capital confers a certain degree of power within gaming circles. (p. 123)

Consalvo’s (2009) use of “elite” and “power” echoes the feelings and desires of many players featured in the King of Kong (2007) documentary. She goes on to explain that being “looked to as an expert” is—for many gamers—the ultimate validation of one’s intense research and practice (p. 123). However, those same players seem to realize that being caught using certain hacks could “destroy gaming capital for them.” (p. 123). These claims are supported by

Engerman’s (2016) phenomenological study of high school boys and their gameplay practices in

Call of Duty. While the participants of his study were more “casual” than “hardcore,” they nevertheless were driven to “[gain] social capital through explicit demonstration of skills (p.

129).2 Likewise, Engerman (2016) stresses that “social capital [gains] were greatest in [Call of

Duty] when competition was at its highest” (p. 129). This recalls the prestigious nature of the

LAN tournaments that Thiborg and Carlsson (2010) describe as well as the crucial role that

Funspot arcade plays throughout King of Kong (2007).

With the relationship between fair play, competition, and prestige in mind, we can begin to understand how and why Twitch’s “magical interactions” serve the hardcore and esports

2 Although Engerman (2016) uses the phrase “social capital,” he is actually describing the same concept that Consalvo (2009) calls “gaming capital.” For Engerman (2016), social or gaming capital often comes in the form of “cool points” or bragging rights. 22 gaming communities. Johnson and Woodcock (2019), in their study of aspiring live-streamers, describe Twitch as a tangled web of “digital intimacy, celebrity, community, content creation, media production[,] and consumption” (p. 1). However, unlike other researchers, who have traditionally focused on “consumption”—particularly “why viewers watch”—Johnson and

Woodcock (2019) instead attempt to unpack the motivations and strategies of the would-be

“celebrities.” As the authors note, many of these streamers transitioned from careers as either professional players or “shoutcasters,” leaning on their years of experience and insider knowledge to carve niche fanbases for themselves (p. 10). Still other content creators, dissatisfied with the impersonal and delayed interactions on platforms like YouTube, migrated to

Twitch for its ability to provide “instant” feedback (p. 10). For Johnson and Woodcock (2019),

Twitch provides streamers and viewers alike with a new level of “immediacy” and “intimacy” that older, more traditional affinity spaces cannot replicate (p. 12). In further describing Twitch’s affordances, the authors draw on Short et al.’s (1976) notion of “social presence” to describe the

“degree to which a medium conveys the actual presence of those who are communicating”

(Johnson & Woodcock, 2019, p. 12). Not only can players stream their gameplay, but many choose to set up “facecams” to better capture their range of emotions during competition

(Hamilton et al., 2014; John & Woodcock, 2019; Recktenwald, 2017). As Hamilton et al. (2014) explain, clever use of webcams can increase streamer-viewer “engagement” and, in turn, actively facilitate many of the “magical interactions” that elevate Twitch above other platforms.

One of these emerging “clever usages” is known as the handcam. This recent phenomenon is a direct response to cheating allegations, affectionately known as “hackusations,” leveled against professional Counterstrike and Overwatch players. After all, Kücklich (2007) reminds readers that the “aimbot” is one of the most notorious and widespread cheating 23 devices—it has the power to automatically “snap” a user’s weapon to an opponent’s head, resulting in a “pixel-perfect” shot. However, since the muscle memory and control of top players is often so refined (Witkowski, 2012), it can be challenging for novice players to tell the difference between a skillful shot and one guided by an aimbot. Consequently, in addition to showing their faces on stream, many competitors have elected to set up separate webcams to simultaneously record their hand and mouse movements. The goal is to legitimize their gameplay, to showcase their “haptic engagement” (Witkowski, 2012). As Witkowski (2012) explains, haptic engagement refers to how, in esports, “gameplay practices that are a result of

‘more than the game’ [… and are] touched by all the networked bodies and technologies that make up the gaming moment, regardless of their complexity […] or simplicity (such as tables[,

…] chairs[, or mice])” (p. 366). In the case of handcams, the streamer is thus able to prove that his or her mouse movements mirror the actions that are occurring in the game. Perhaps the most high-profile example of a handcam vindicating and validating a player is the case of Kim

"Geguri" Se-yeon. In 2016, this Korean, female Overwatch player came under intense scrutiny after recording a series of suspiciously high win-rates and kill-to-death ratios on the competitive ladder (Alexandra, 2016; Chalk, 2016; Kimes, 2017). Even other professional players on

Korea’s Overwatch circuit assumed she was cheating until she streamed a showcase of herself playing with a handcam; she was subsequently signed to a professional team herself. Geguri’s case is a compelling reminder of Twitch’s ability to expose. In one fell swoop, she—through livestreaming—was able simultaneously to clear and make her name. Players, fans, scouts, and coaches alike were given a behind-the-scenes look at her haptic practices and could observe that her skills were as authentic as they were spectacular. 24

On the one hand, the “behind-the-scenes”—or “backstage-pass”—nature of such a broadcast helps to cultivate a sense of “intimacy” (Johnson & Woodcock, 2019). Viewers feel more connected to—and thus become more likely to subscribe to or donate to—streamers that fully utilize Twitch’s audiovisual elements and communicative environment. Similiarly, “the virtual stage created by the microphone and webcam overlay afford a high level of visibility for the behaviours and knowledge of the streamer” (Sjöblom et al., 2018, p. 23). Since so many spectators—including many of the participants in my study—are interested in improving at the esports themselves, they are attracted to streams where they can both see and hear expert perspectives. After all, and as Taylor (2012) explains, “learning by watching” has been an integral part of esports culture for decades. “Videos on demand,” (VoD) in particular, have been

“key training tools, providing the opportunity to review opponents’ playstyles in advance of competitions. Much like the use of prior game film in traditional sports, VoD and other archived games form a core component of a practice regimen for players” (Taylor, 2012, p. 199). A

Twitch stream’s intimacy, however, fundamentally transforms the classic VoD into something more. Where a VoD merely allows a spectator to see through the eyes of a professional player

(Taylor, 2012), Twitch streams include that critical, additional layer of narration and in-the- moment analysis. On Twitch, play and conversation are concurrent. It is the streamers’ constant,

“metacognitive self-talk that demystifies their problem-solving processes” and enables the learner-spectator to internalize an esports’ best practices (Hein & Engerman, 2016).

Consequently, many esports-focused Twitch streamers actively build and facilitate “cognitive apprenticeships” (Brown et al., 1989) with their viewers (Hein & Engerman, 2016; Richard et al., 2018). Overwatch streamers like Emre “Kabaji” Dincer and Jeff “Emongg” Anderson, keenly aware of their roles as tutors and mentors, will even title their broadcasts to reflect those 25 educational values. They thus invite viewers to tune in for an “Educational Stream” or to watch as they are “Reviewing Viewer-Submitted Matches.”

Streamers like Kabaji and Emongg also seamlessly weave question-and-answer sessions into their broadcasts, tailoring their activities to the ever-changing needs and desires of their viewers. Cheung and Huang (2011), who surveyed fans of competitive Starcraft, describe these particular viewers as the “pupils.” According to Cheung and Huang (2011), the pupil’s question

“is not merely ‘how did [the player-streamer] do that?’ it is also, ‘how does this information change how I play?’” (p. 5). Viewers thus seek out the self-proclaimed “educational streamers” to help “translate knowledge into practice” (p. 5). Smith, Obrist, and Wright (2013) add that

Twitch’s built-in text-chat enhances a viewer’s ability to receive that just-in-time information. In turn, the streamer’s metacognitive self-talk becomes informed by an active and invested viewer- base. As Squire (2011) insists, “to understand how games operate, we need to look beyond the game itself toward the broader cultural contexts in which it is situated. In many game communities, players themselves become the content, making them emblematic of participatory media culture” (p. 12). My hope is that this dissertation can respond to Squire’s (2011) call to look beyond the games. Twitch—where viewers become “part of the show”—is now at the forefront of that participatory culture. Moreover, livestream viewers actively “co-labor in play”

(Smith, Obrist, & Wright, 2013, p. 137) and thus can make meaningful contributions to shared endeavors. I will return to this notion of “co-laboring” when I introduce the second component of my theoretical framework—intent participation—later in this chapter. For now, by highlighting how interactivity can transform both a streamer’s broadcast and, indirectly, a viewer’s future gameplay, I simply want to emphasize that (1) the streamer-viewer relationship is 26 a symbiotic one, and that (2) both parties benefit the most when they are able to occupy the same temporal space.

In fact, Twitch—when compared to text-based forums or video-sharing sites—has a unique relationship with time. By default, Twitch broadcasts are only saved as VoDs for several months; the content is fleeting, ephemeral. This isn’t to say that the captured VoDs or “clips” are useless or unimportant, quite the contrary. Many of these are ultimately recycled, repurposed, edited or uploaded to external repositories where they can be meaningfully re- experienced at later times. However, Twitch’s focus on the present is nevertheless telling. As I have already described, live interactions shape broadcasts in compelling and often “magical” ways. As Smith, Obrist, and Wright (2013) argue, “without interaction a video game is benign”

(p. 131). Twitch’s affordances thus have the power to transform the traditionally passive role of the spectator into both something far more active and more congruent with the values of gamer culture. Perhaps more importantly, especially where the “pupil” is concerned, Twitch’s recency bias ensures that spectators only have access to the most up-to-date information. After all, the majority of esports are not static, immutable things. Developers and players alike frequently update, change, and “mod” the games themselves; esports leagues often institute new rules to ensure fair play and to maintain high levels of competition. Overwatch, in particular, is

“patched” or updated roughly four to five times a year; these updates include new maps, characters, and abilities that can fundamentally change how the game is played and which strategies will become the most effective. Esports competitors refer to this ever-shifting balance of power as the “metagame” (Carter, Gibbs, & Harrop, 2012). Aaron “Bischu” Kim, a professional Overwatch player for the Los Angles Gladiators, defines the buzzword in his own terms, calling it “the flavor the month. All of the pros think this [strategy] is the best. This is 27 what the norm is, the standard” (Overwatch League, 2019). He also adds that, “as a gamer, these kind of gamer terms kinda slip out—whenever something is in fad, I will accidently say, ‘oh yeah, these shoes are in the meta right now” (Overwatch League, 2019). Bischu’s understanding of the “metagame” is revealing. Although on the surface his use of the phrase “flavor of the month” might seem like a hollow cliché, it becomes far more serious—and literal—when we understand how quickly and substantially the game of Overwatch can evolve. When I began working on this dissertation in the summer of 2018, many of my participants were obsessed with learning how to perfect the “Genji-Tracer, Dive” meta. By the winter of 2019, Overwatch had changed, and my participants were struggling to adapt to curiously named “GOATs” meta. I’ll describe those experiences in greater detail in chapter four; for now, I simply want to highlight why watching current or live content is so valuable for esports competitors. Quite simply, in the world of competitive gaming, the half-life of knowledge is short. Twitch’s emphasis on the present not only reinforces what really matters in esports culture, but it also does so in ways that traditional affinity spaces never could.

While watching to learn is a common motivation, it isn’t the only reason why esports enthusiasts tune into matches on Twitch. As Taylor (2012) explains:

People generally do not come into the [esports] scene expecting to be fans or spectators but typically first think of themselves as players and then, after some exposure to videos on demand, websites, or podcasts come to transform their own object of leisure into one that is simultaneously about fandom. This is potentially a distinctive feature of e- sports. Unlike traditional sports where fans may have never actually played the game themselves, in computer gaming the path to pro gaming fandom is often born directly out of their own experience with the title. (p. 188)

For Taylor (2012), “shared moments of spectatorship” can also “build ties between players” that

“[become] another layer of engagement” unto itself (p. 189). Recently, I witnessed and participated in one of those “shared moments of spectatorship” myself while watching an 28

Overwatch League match on Twitch. On February 22nd, 2019, the beleaguered Shanghai

Dragons, carrying the weight of a historically dreadful 0-40 season, were on the verge of finally winning their first professional match. Even with over 250 thousand unique viewers watching the event unfold online, there was one unifying refrain being “spammed” in Twitch’s text-based chat widow, “I WAS HERE!” (see Figure 2.2). When the match clock hit zero, and the

Shanghai Dragons had indeed secured the victory, so many users were now typing messages that

Twitch’s servers began to buckle under the pressure; the livestream itself started to glitch and lag.

Of course, this only prompted users to spam all the harder, “WE BROKE TWITCH!” So when

Twitch boasts about its ability to foster “never-to-be repeated experiences created by the magical interactions of the many,” I believe these are the kinds of moments it is referencing. Similarly, the esports community’s reaction to Shanghai’s first win is also representative of Taylor’s (2012) feelings regarding “shared moments of spectatorship.” That inaudible chant, “I WAS HERE!” is quite literally about experiencing Short et al.’s (1976) social presence; it is about building “ties between players” who may never physically meet (Taylor, 2012). It is also reflective of the spectator persona that Cheung and Huang (2011) call the “crowd,” viewers who believe that the pleasure of experiencing esports is derived from “the strong communal aspects of spectating” (p.

6). Taylor’s (2012) description and analysis of esports fandom, along with recent examples of that fandom in action, are compelling reminders that the roles that esports enthusiasts adopt are

“malleable” (Smith, Obrist, & Wright, 2013). As they interact both in the games themselves and on Twitch, they slide into and out of the roles of competitors, fanatics, mentors, and pupils. That

“malleability,” and perhaps unpredictability, is what compels me to, with this chapter, advance a theory of observational and analytical gaming ecologies—to better describe how esports 29 competitors come to understand the relationships between themselves, their games, and their peers.

Figure 2.2: Fans celebrate the Shanghai’s first win both at the Blizzard Arena and on Twitch. 30

Although Twitch certainly changes the game, it is important to remember that spectatorship has played a key role in esports culture since the earliest days of the arcades— where “standing alongside and watching others [compete] formed a key part of the experience”

(Taylor, 2012, p 183). The ideas I have discussed in this particular section are representative of the values, concerns, and practices that have defined the competitive gaming scene for a generation. Twitch, bolstered by its modern affordances, now shines the spotlight on them. I want to end this section where I began—with the story of Steve Wiebe, Billy Mitchell, and their lifelong quests to become the King of Kong. Following the release of their documentary, the always controversial Mitchell became a rather disgraced figure in the gaming community

(Kotaku, 2018; Sports Illustrated, 2018; Variety, 2018). After months of investigation, Twin

Galaxies determined that Mitchell’s infamous 1,047,200-point Donkey Kong score had indeed been falsified. His records were stripped from the Twin Galaxies database, and, as of this writing, he has been banned from participating in future competitions (Twin Galaxies, 2018).

However, the story doesn’t quite end there. Recalling Fristch et al. (2006), hardcore gamers are characterized by their “stubborn resistance in playing the same game [and] with way more than average interest” (p. 2). Mitchell, as it turned out, would continue to display that “stubborn resistance” even in exile. At 52-years old and mere months after having his records stripped,

Mitchell “embraced the internet age” and began streaming his Donkey Kong gameplay on Twitch

(McCumbers, 2018). On November 24th, 2018, he achieved a 1,050,100-point score in front of hundreds of live viewers. Impressive as that score is, Mitchell’s recent endeavors on Twitch will do little to reverse his lifetime ban from Twin Galaxies. Nevertheless, Mitchell successfully leveraged Twitch to legitimize his skills. Gamers might have not forgiven him for past offensives, but they can at least feel a bit more comfortable celebrating Mitchell for his now 31 unquestionable talent. And in the end, that’s what competitive gamers crave the most— acknowledgement and recognition from their peers. As I have illustrated in this literature review—and as I will showcase through my data in forthcoming chapters—Twitch is uncanny in its ability to provide gamers with a multi-faceted social platform. Through its screen-sharing technology, it has the power to simultaneously legitimize and expose. Similarly, its heightened levels of intimacy and immediacy can usher viewers into the fold and can provide access to the eyes and minds of expert players. Finally, the constant interaction between viewers and streamers not only strengthens the bonds between users, but it carves out opportunities for them to adopt a multiplicity of roles. Gee’s (2005) understanding of affinity spaces has been invaluable for describing and analyzing how gamers—in particular—learn from one another in online environments. However, that cannot account for all the ways that esports competitors are innovating on emerging platforms like Twitch. These hardcore gamers are truly trailblazers, and we—as researchers—need to lean on additional theories if we are to keep up and to make sense of their experiences.

Learning by Observing and Pitching In

I now move from my account of esports’ history and its relationship with livestreaming technology to introduce and describe those related learning theories. In this section, I leverage

Rogoff’s (1997, 1998, 2014) work on learning in indigenous communities to help scaffold and inform my ongoing discussion of how esports competitors improve their skills by watching and participating on Twitch.

Rogoff et al. (2003) describe “intent participation” as a practice whereby “learners engage collaboratively with others in the social world” (p. 16). It involves “keenly observing and listening in anticipation of or in the process of engaging in an endeavor” (p. 13). While 32 intent participation is traditionally associated with learning in indigenous communities and through volunteering organizations, I believe that it can also help to demystify many of those

“magical interactions” that unfold on Twitch. For one, intent participation is especially useful for describing how learning occurs when authority is decentralized; Rogoff et al. (2003) showcase this by contrasting intent participation with “assembly-line instruction,” a classic learning model predicated on fixed expert-novice relationships and knowledge “transmission.” As I have explained, Twitch is a social platform where users’ roles are “malleable” (Smith, Obrist, &

Wright, 2013), which in of and itself complicates how users establish, perceive, and relate to authority. Secondly, the theory aims to describe learning in communities where “collaborative participation is expected when [members] are ready to help in shared endeavors” (Rogoff et al.,

2003, p. 11). Specifically, Rogoff et al.’s (2003) account of “collaborative participation” in

“shared endeavors” recalls the magical interactions that can both create and spawn from “shared moments of [esports] spectatorship” on Twitch (Taylor, 2012). Quite simply, there are deep, striking similarities between the communities that Rogoff et al. (1993, 2003, 2014) once studied and the ones that now gather on Twitch.

However, that alignment—while strong—is not always perfect. Intent participation, as a learning tradition, has changed and evolved over time. Most notably, Rogoff and Paradise

(2009) have revised their early understanding of intent participation to emphasize a more

“natural” sense of “belonging.” In particular, they draw on Lave and Wenger’s (1991) notion of

“legitimate peripheral participation” to highlight how one’s “active agency and initiative [while] contributing to the consequential activities [of a community]” fuel learning (Rogoff & Paradise,

2009, p. 104). Rogoff and Paradise (2009) thus rebrand intent participation more accurately as

“learning by observing and pitching in” (LOPI), a designation that I now both lean on and amend 33 as I construct this study’s theoretical foundation. While esports competitors certainly display

“active agency” and contribute to “consequential activities” on Twitch, their networked and technologically-charged practices demand that we—as researchers—extend our present understanding of LOPI further. Therefore, in this section, I not only describe and explore

LOPI’s features as they relate to esports competitors and their communities, but I also make moves to advance the approach itself. By considering Twitch’s unique affordances, LOPI can thus be bolstered to account for and analyze the learning that occurs in OAGEs.

Today, Rogoff (2014) characterizes LOPI in terms of seven “interrelated facets” that bridge the topics of “motivation, social interaction, goals of learning, attention, and communication of language” (p. 73). Those facets are outlined and exemplified as follows:

1. Learners are “incorporated” into “community endeavors.” Experts and novices

alike are treated as “regular participants” and are expected to “contribute”—in

whatever ways they can—to group activities. For instance, Coppens et al. (2014)

found that children from indigenous-heritage communities of Guadalajara were quick

to engage in “a wide range of complex family household work activities and sibling

care” (p. 118). These children also reported that their contributions were primarily

motivated by a sense of collaborative “responsibility,” a concept that leads Rogoff

(2014) to introduce LOPI’s second facet:

2. A learner’s “eagerness” to “belong” drives their contributions. In turn, more

experienced members guide and support these learners as, together, they work to

accomplish tasks. Paradise & de Haan (2009) note that children in the indigenous

Mazahua community seemingly “need no coaxing, no incentive that is unrelated or 34

extrinsic to the activity itself [, …] children want to be involved in these activities like

any other bona fide member of their community” (p. 199).

3. The community itself is organized as a “collaborative, flexible ensemble with

flexible leadership” (Rogoff, 2014, p. 74). Members coordinate and interact with

“fluidity,” and anyone may take initiative. During their study of the annual día de los

muertos celebrations in Puebla, Mexico, Gutiérrez et al. (2015) reported that children

“play a major role in sustaining the tradition” through their active participation in

both the event’s preparation and celebration (p. 230). As part of their community’s

“flexible ensemble,” these children could contribute by decorating graves, dancing to

music, listening to elders’ stories, and helping to cook meals.

4. The goal of learning is to “transform participation.” Rogoff (2014) contrasts this

philosophy with those of more formal, “assembly-line” models, where learning is

thought as the “acquisition of knowledge and skills” (p. 74; Rogoff, 1997, 1998). In

the case of the día de los muertos celebrations, for instance, Gutiérrez et al. (2015)

argue that the children not only learn the “value of the tradition,” but they also learn

“how to be adults in their culture” (p. 238). Thus, with each passing year, the learners

become “more and more adept” and can contribute in increasingly complex ways (p.

248).

5. Learning itself involves “wide, keen attention, in anticipation of or during

contribution to the endeavor at hand” (Rogoff, 2014, p. 74). Correa-Chávez and

Rogoff (2009), who compared and contrasted toy-making practices between

traditional Mayan families and those involved with Western schooling, found that this

“attending to ongoing events and beginning to pitch in when ready seemed to be 35

[natural, cultural, and key] feature” of learning in more indigenous populations (p.

630). Consequently, the children in Mayan families generally needed less help

making toys themselves and, ultimately, learned more about the construction process

than their European counterparts.

6. Communication utilizes “shared references.” Explanations are “nested with the

shared endeavors (Rogoff, 2014, p. 74); learning thus runs parallel to—and becomes

inseparable from—the task at hand. For indigenous populations, this facet often

manifests itself during moments of collaborative talk and storytelling wherein

communities will explain “the rules” to their children through dramatization and

“instructional teasing” (Coppens et al., 2014).

7. Like explanations, assessment occurs during an endeavor. Its purpose is not only

to “aid” learners’ contributions, but also to provide an ongoing “appraisal” of

learners’ support. Conversely, in assembly-line instruction—where assessment is

“external” to the activity, “feedback comes from extrinsic rewards, praise or threats,

and ranking against other learners” (Rogoff et al., 2016).

Furthermore, Rogoff (2014) suggests that these facets interface with one another in

“multidimensional” ways. She thus characterizes LOPI as a “prism,” capable of reflecting and refracting light to illuminate new or hidden details (see Figure 2.3). When held up to modern esports communities, that prism represents a uniquely powerful analytical lens. For example, through LOPI, researchers can come to a more holistic understanding of Twitch’s magical interactions; in fact, we gain access to the rhetoric and theory necessary to describe an entire

“constellation” of cultural practices (Rogoff, 2014). 36

Figure 2.3: The LOPI “prism” as described and presented by Rogoff (2014).

Consider, in particular, the role that “cross-modal communication” plays on Twitch

(Reckenwald, 2017). During broadcasts, streamers and viewers converse with one another through a variety of voice and text channels. Recall that streamers often rely on prompts, questions, and feedback from their viewers to help guide and direct content (Johnson &

Woodcock, 2019), a practice that Smith et al. (2013) describe as “co-laboring” in play. But what is the real work that Twitch users hope to accomplish in their co-labor? Smith et al. (2013), who frame their argument in terms of “interactive television,” suggest that these users co-labor “for the purposes of entertainment; the viewer is heightening their enjoyment, and hopefully others’ enjoyment, by interacting with the performer” (p. 136). However, I think this assessment only tells a small part of the story. For one, LOPI challenges the notion that users would co-labor for 37 entertainment purposes, instead championing their “eagerness to contribute and belong” (Rogoff,

2014). This later interpretation also seems to align more closely with the values and beliefs of esports culture, where enthusiasts “first think of themselves as players” and seek recognition for their knowledge and skills (Taylor, 2012, p. 188). Even as a spectator, one can leverage “Twitch chat” to these ends. As Hamilton et al. (2014) explain, “viewers who regularly show up, eventually become recognized community members” and can even become “moderators” (p. 2).

These trusted, privileged users often answer questions and welcome newcomers when the streamer is otherwise preoccupied (Hamilton et al., 2014), a fluid role that necessarily expands our understanding of what it means to “co-labor” on Twitch. LOPI thus reveals such cross- modal communication to simultaneously become process and performance. It represents both a way for learners to become “incorporated” into the community and a “shared endeavor” in and of itself. While I cannot unpack and connect every facet of LOPI to Twitch chat in this section, I wanted to briefly showcase how this framework can help describe and analyze the data I present.

That said, Rogoff and Paradise (2009) note that LOPI is an informal and “natural” sociocultural practice that has evolved over thousands of years. I see part of my task as guiding

LOPI through its next iteration. While it may be “comfortable for and well-suited for

[describing] human learning of all kinds,” I move to consider the approach in a very different context. Traditionally, intent participation—and by extension, LOPI—has been used to describe how toddlers collaborate with their caregivers in indigenous communities such as Guatemalan towns, Indian villages, and Turkish neighbors (Rogoff et al., 1993). The “shared endeavors” at the epicenter of those studies involve activities such as cooking, cleaning, dressing, fetching firewood, and operating tools (Alacá et al., 2014; Coppens et al., 2014; Rogoff et al., 1993).

However, esports communities are stitched together by computer-mediated, Web 2.0 and 3.0 38 technologies (O’Reilly, 2007; Hendler, 2009). Consequently, LOPI lacks a means to account for and describe the cross-pollination and networking that so often occurs in online gaming. On

Twitch, in addition to the video live-stream itself, a channel will often feature numerous hyperlinks to and advertisements for related, external content. This supplemental material might connect users with a streamer’s social media, a more in-depth strategy guide, a community

Discord server, or an affiliated vendor. Recalling Gee’s (2005) features of affinity spaces,

Twitch thus “encourages dispersed knowledge” (p. 227). The website and its channels do not represent monolithic authorities, but rather they become the “portals” through which today’s esports competitors and enthusiasts prefer to travel. Furthermore, as Magnusson, Stöckel, and

Berglund (2015) note, Twitch streamers regularly “host” or “raid” other channels at the conclusion of their broadcasts. On the one hand, these practices, which involve an active transferring of viewers between channels, are symbiotic forms of “guerilla” and “buzz” marketing (Dennisdotter et al., 2008; Magnusson, Stöckel, & Berglund, 2015). Perhaps more importantly though, hosting and raiding can also be seen as distinctly 21st-century attempts to bridge disparate communities and to expose members to new ideas. Consequently, as I present and describe data in later chapters, I will consider how the unique cultural and community practices of esports competitors can shape our understanding of LOPI now and into the future.

Towards a Theory of Observational and Analytical Gaming Ecologies (OAGEs)

As I described in my introductory chapter, this dissertation isn’t about any one video game. Nor is it bound by the just the latest and most popular livestreaming platforms. Rather, this dissertation is about the “constellation of cultural practices” that esports competitors employ as they work and interact with one another across both digital and physical spaces (Rogoff,

2014). To these ends, I build on and extend Richard et al.’s (2018) description of how esports 39 competitors form and participate in “learning ecologies.” Likewise, I draw on Barron’s (2004;

2006) foundational understanding of “learning ecologies” to help account for and describe the totality of “activities, material resources, and relationships” that now help competitive gamers improve their skills. For Barron (2006), a learning ecology framework perspective “foregrounds the fact that adolescents are simultaneously involved in many settings and that they are active in creating activity contexts for themselves within and across settings” (p. 199). As I have explored throughout this chapter, that active creation of new contexts is an integral component of esports culture. From curated “high-score” databases to interactive VoD reviews, esports competitors have long appropriated technology to both implicitly and explicitly “raise the stakes” (Taylor,

2012). Likewise, they have “dispersed”—to use Gee’s (2005) term—community knowledge across a vast network of Twitch channels, YouTube videos, podcasts, text-based message boards, and hybrid platforms. In this dissertation, I argue that the unique ways in which “hardcore” gamers connect to and interface with these “portals”—bolstered by meaningful, transformative interactions with teammates and competitors alike—give birth to observational and analytical gaming ecologies (OAGEs).

I describe this framework as “observational and analytical” for several key reasons. As

Caldwell (2004) muses, “[video] games might share some basic purpose—to entertain—but each new game that appeared on my screen could well have been in a different medium, or a different language, altogether” (p. 42). Apperley (2006) echoes this sentiment, arguing that video games

“cannot be regarded as a consistent medium” (p. 6). Unfortunately, vendors and researchers alike have historically prioritized “aesthetics” over “interactivity” when categorizing games

(Apperley, 2006). Titles are thus organized into genres based on shared iconography and largely independent of gameplay mechanics, the media-specific and participatory properties that 40 distinguish games from television, books, and movies. Not surprisingly, the player communities themselves have similarly been subject to lazy and misguided generalizations (Becker, 2008).

My decision to frame their ecologies in terms of observational and analytical practices represents—above all—my desire to be specific and precise. After all, the participants in my study are not “casual” gamers. Rather, they have far more in common with Cheung and Huang’s

(2011) “pupils” and “assistants”—esports enthusiasts that are deeply invested in transforming the gameplay of both themselves and others. As I will explore through my data, that excitement and willingness to engage in Taylor’s (2012) “shared spectatorship,” combined with individual moments of self-reflection and study, leads me to see observation and analysis as the ecology’s unique, defining features. These are gamers that have not only recognized how to learn from the metaphoric sidelines, but that have also harnessed technology in ways to simultaneously access, widen, and re-experience multiple perspectives. Furthermore, by highlighting the word

“observation,” I hope to establish a thematic link with Rogoff’s understanding of LOPI that will carry through the collection, analysis, and interpretation of my data. As such, the following chapter will describe the methodological approach that is best suited to tracing the emergence and evolution of OAGEs.

CHAPTER 3: METHODS

Figure 3.1: A “victory” screen in Overwatch, showing the winning team’s gamertags and avatars.

“Let’s fucking go boys!” I yell into my microphone as the match timer hits zero and the word “Victory!” flashes across the computer screen. My exclamation jumbles together with those of my equally excited teammates. We did it. The university’s club Overwatch team had just pulled off an impressive comeback against a rival school, and I—a thirty-year-old graduate student and aspiring researcher—was an active participant through it all.

“GGs,” I type out in the in-game chat window as my teammates’ outbursts continue to echo through my headset. I lean back in my chair and think for a moment. “This can’t be right,”

I chuckle to myself, “this isn’t what real research is supposed to look like… is it?”

Our team captain tries to calm everyone down so he can deliver his traditional post-game speech. I instinctively glance to the side, but he’s not there. Nobody is there. I’m alone in my apartment. It’s a surreal moment; I just did battle on the virtual streets of the fictional King’s 42

Row, competed with and against students a decade younger than me, and shared in a collective celebration mediated by computer technology.

“So, are you guys ready to watch the D1 team play now?” another teammate asks, “I think they’re about to start streaming.”

---

What is research supposed to look like? This is one of the questions I have grappled with throughout my graduate school experience and, increasingly, over the course of my work on this dissertation. This chapter, in part, represents my attempt to answer that question—to come to terms with the affordances and limitations of more traditional research methodologies when applied to the study of niche and predominately online communities. And, on a more practical level, this chapter describes how and why I collected different types of data in immersive and often participatory ways. As I noted in chapter one, not only have I maintained a life-long interest in gaming, but I have also regularly attended and competed in esports events over the last

15 years. As recently as 2015, I placed 2nd in a 50-person, multi-university Super Smash

Brothers: Melee tournament (which also happened to be streamed on Twitch). This statement is not meant to be—as the participants in my study might say—a “humble brag” or a “weird flex” but rather as a reminder to my readers that I am uniquely positioned to study such gaming communities from the inside out. Consequently, this chapter explores how I go about that research; it describes how I understand my work as a “connective ethnography” that aims to trace my participants’ interactions, relationships, and activities across the virtual settings of

Twitch, Discord, and Overwatch, as well as through their everyday campus lives (Hine, 2000,

2008; Leander, 2008). Furthermore, I hope that the methodological blueprint I provide herein 43 can help inform, inspire, and improve future research on topics related to competitive gaming, livestreaming, and student clubs.

A “Connective” Ethnography

From its inception, this dissertation’s rhetorical goal has always been to tell the story of collegiate esports—specifically, that of the culture-sharing Overwatch club at the Pennsylvania

State University. To accomplish this task, I posed the following set of research questions to serve as a guide and as a touchstone throughout my ethnographic process:

Ideally, these questions would help capture the “essence of how [the club] functions,” while simultaneously providing readers with a widow into “the group’s way of life” (Creswell, 2013, p.

92; Wolcott, 2010). More specifically, and as Wolcott (2010) suggests, these questions were designed to discover, understand, and explain what club members need “to know and do [in order to] make [their] system work” (p. 74). As I have alluded to, I consider my process to be

“ethnographic” in nature. The questions I asked, the data I collected, and the relationships I built were all conducted in such ways as to better “describe and interpret the shared and learned patterns of values, behaviors, beliefs, and language” of competitive Overwatch players

(Creswell, 2013, p. 90). As such, my research involved extensive fieldwork—including immersive and participatory observation—that integrated me into the group’s day-to-day activities (Creswell, 2013). However, the more I took in, the more I realized that the success of my own ethnography would depend on my ability to gather diverse sources of data from 44 increasingly “new and strange” places (Wolcott, 2008, p. 45). I would have to challenge my preconceived notions of what research itself can and should look like.

After all, as Hammersley and Atkinson (1983) explain, “the ethnographer participates, overtly or covertly, in people’s daily lives for an extended period of time, watching what happens, listening to what is said, asking questions; in fact collecting whatever data are available to throw light on the issues with which he or she is concerned” (p. 2, emphasis mine). In many ways, I see my research as an exploration of just how “new and strange” that “whatever” can be in 2020. My work thus follows in the tradition of “virtual” ethnographies (Hine, 2000, 2008), wherein researchers have transferred and adapted familiar methodological tools for use in online social spaces (Leander, 2008). Most notably, virtual ethnographies have been employed to study the player communities of Multi-User Dungeons (MUDs) and Massively Multiplayer Online

Roleplaying Games (MMORPGs). For example, Hunsinger and Krotoski (2013)—much like

Steinkuehler (2004, 2005) before them—were interested in how Lineage players used their virtual avatars to interact and communicate within and beyond the game space. In order to better understand how players engaged in “collaborative problem-solving” in Lineage’s digital environments, Hunsinger and Krotoski (2013) decided to create in-game characters for themselves and to play alongside their participants for a period of 18 months (p. 83). To immerse themselves even more thoroughly, the authors also became members of a “clan,” a highly structured and intimate group of players that share specific in-game goals. Over the course of their virtual ethnography, Hunsinger and Krotoski (2013) were thus able to collect a wealth of screenshots, videos, and chat logs that combined to paint a detailed and authentic cultural portrait. However, it was their willingness and confidence to meet participants “in the 45 wild” that—for me—stood apart and would come to serve as the primary inspiration for my own ethnographic approach that I will soon detail.

As I move to describe that process, I do want to be as precise as possible with my language. As Leander (2008) notes, on a practical level, the terms virtual ethnography, social spatial ethnography, traveling ethnography, and connective ethnography are largely interchangeable (p. 37). For Leander (2008), a “connective” ethnography—in particular— acknowledges and embraces how “notions of the research ‘site’ are being disrupted and [how] relationships are being traced among sociocultural practices and agents” (p. 37). It challenges researchers to “reimagine and study the event, the text, the classroom, the school and global relations as a nexus […] rather than a container” (Leander, 2008, p. 60). When one looks at the unique “sites” that my participants frequent, many of them—Twitch, Discord, and Overwatch— are seemingly defined by their “virtual-ness.” However, the more time that I spent with these tools, environments, and their users, the more I came to understand how they are powered by their “connective-ness.” What happens in Overwatch is simultaneously broadcast on Twitch and is later shared through Discord. Conversely, strategies that are first “theorycrafted” on Discord invariably circulate on Twitch before ultimately manifesting themselves in competitive matches of Overwatch. Each “site” has its cultural tentacles in the other as well as in the daily lives of their users. For these reasons, I choose to characterize my work as a “connective ethnography,” as it is the term that best describes and emphasizes the ways in which modern competitive gamers participate in “event complexes” around the computer (Jones, 2005).

Primary Research Sites

I conducted research at four primary sites: in the game-space of Overwatch, on the livestreaming platform of Twitch, in the group-discussion channels of Discord, and in the 46 physical classroom of Willard 371. Each site provided my participants with its own unique affordances that they felt were valuable for their continued progression and improvement as competitive gamers. Likewise, as a researcher, those same affordances gave me the opportunity to collect and analyze many different types of “new and strange” data. In the following section, I describe these sites on an individual basis for the sake of readability and clarity. That said, it is important to note that my participants would rarely visit or use any one of these sites in insolation. Rather, my participants would often inhabit two or more of these sites simultaneously, deploying their unique affordances in concert and for maximum benefit. To borrow the phrase from Olwig and Hastrup (1997), the sites, their users, and the activities that transpire between them thus form a “field of relations.” Although I now move to outline the research sites in a linear fashion, my study ultimately seeks to uncover their connections and interplay (see Figure 3.2).

Figure 3.2: The “field of relations” that participants form and navigate as they interact with one another online.

Overwatch

Overwatch (2016) is a critically and commercially successful team-based, first-person- shooter (FPS) video game. Developed and published by Blizzard Entertainment—the same studio that created the likes of StarCraft and World of Warcraft—Overwatch has, as of 2018, sold 40-million copies across various platforms (PlayOverwatch, 2018). Conceived of as a “love letter” to the FPS games of the 1990s (O’Dwyer, 2016), Overwatch allows its players to adopt the roles of various different “heroes”—each with clearly defined strengths, weaknesses, and abilities—as they attempt to attack and defend various objectives in the game’s virtual world.

Since players compete with and against one another in two teams of six, selecting heroes that can synergize together is an essential part of Overwatch’s strategy. For example, one player might choose to be the time-traveling adventurer, Tracer, who is a quick but fragile hero capable of dishing out large amounts of damage with surgical precision. A separate teammate might instead choose to play as the genetically engineered and super-intelligent gorilla, Winston, who is a mobile and well-armored frontline presence that aims to sow discord in the opposing team’s ranks. When working together on the battlefield, Tracer can take advantage of the space

Winston creates and the distraction he provides, thus allowing her to more safely isolate and eliminate key targets. Consequently, the game—especially at higher levels of competition— demands that its players not only understand how character-abilities interact with one another, but also it encourages those same players to constantly engage in voice-conversation to successfully plan and execute strategies. 48

Figure 3.3: An in-game description of Tracer’s role and abilities (PlayOverwatch, 2018).

While Overwatch—with its vibrant worlds, diverse cast of characters, and fast-paced action—certainly has broad appeal, it was also designed from the ground up with competitive esports in mind. Even during the game’s prerelease and “beta-testing” periods, hardcore players and community insiders alike would regularly gather together online to host and participate in grassroots tournaments. Shortly after the game had officially launched in May of 2016, Blizzard

Entertainment announced its intentions to fully support and regulate the game’s professional play through the Overwatch League (OWL). Modeling itself after the governing bodies of traditional sports leagues—such as the NBA or the NFL—the OWL would support its players with guaranteed contracts, signing bonuses, and incentives for placing well in intraleague events. As I alluded to in my introductory chapter, spots in the OWL sold to investors for as much as 20- million dollars during its inaugural season. Likewise, a 3.5-million-dollar prize pool was available for competitors to collect on top of their regular salary (Overwatch League, 2019). As far as esports goes, the OWL is as serious as it gets. Although none of the student-participants in 49 this study are—at the time of this writing—players for OWL-caliber teams, many of them are nevertheless passionate fans of both the league and its personalities. A handful of my participants have, on occasion, played with and against OWL players both in smaller tournament settings and through the game’s online “ladder” system. This particular system ranks players based on their in-game performance and uses complex algorithms to match them up with other similarly skilled players, thereby ensuring the fairest games possible. Whether they are novices or experts, Overwatch players can thus always find an appropriate way to test, practice, and improve their skills.

Figure 3.4: A look inside the “Blizzard Arena” during an Overwatch League match between the Los Angeles Valiant and the Los Angeles Gladiators. When these two intracity rivals face off, fans refer to the match as “The Battle of LA” (Overwatch League, 2019).

As a research site, the game-space of Overwatch possesses many of the qualities that researchers have come to associate with “virtual worlds” (Merchant, 2010; Pearce, 2009;

Steinkuehler & Duncan, 2008; Taylor, 2002). At its core, Overwatch is a game about spatial, 3-

D navigation and avatar-to-avatar interaction. While its environments are certainly more 50 constrained and fixed than those found in either World of Warcraft or Minecraft, Overwatch’s

“maps” nevertheless afford players with ample opportunities to simultaneously explore, socialize, and compete in shared, virtual spaces. Although there were some challenges in adapting the data collection methods used in the ethnographic studies of more traditional virtual worlds (Fields & Kafai, 2009; Hollett, 2015; Hunsinger & Krotoski, 2013) to those of

Overwatch, video screen-captures of participant gameplay remained a natural fit for my own study. By recording my participants’ screens while they strategized, competed, and “hung out” in Overwatch, I could come to a better understanding of how their in-game roles, positions, responsibilities, and avatars shaped their experiences and relationships. Furthermore, as

Engerman (2016) suggests, the screen-capture of particularly frantic moments could help researchers and players alike better identify what particular in-game actions and reactions have become learned, internalized practices. As I conducted interviews with participants later in my study, I would constantly return to these instances to discover more about their moment-by- moment decision-making processes. Finally, in addition to simply capturing the first-person perspectives of individual participants, I occasionally utilized Overwatch’s built-in “spectator” feature. As a “spectator,” I was able to control an invisible, drone-like camera within the game- space of Overwatch and could thereby record an aerial view of the action (see Figure 3.5). I could more accurately track player-movement in relationship to their teammates, their opponents, and their environments. I will detail my struggles and successes using this “new and strange” tool later in this chapter. For now, I simply mention it to illustrate how screen- capturing—as a data collection method—can and should continue to evolve as researchers become more comfortable inhabiting virtual worlds.

Figure 3.5: An overhead view of an Overwatch match captured using the game’s built-in spectator cameras.

Twitch

I provided a cursory overview of Twitch.tv in my chapter one, and I tied its features to existing literature on affinity spaces, livestreaming culture, and competitive gaming throughout my chapter two. I revisit Twitch in this present chapter to describe its affordances and constraints as a research site for my particular study. As a reminder, Twitch is a popular video game livestreaming platform and is one of the fifty most-visited websites in the world. The primary activity on the platform involves content creators—commonly referred to as streamers— broadcasting their individual video-game play and “metacognitive self-talk” to remote viewers

(Hein & Engerman, 2016). As Sjöblom et al. (2018) note, “the infrastructure of Twitch has been designed to foster high engagement between the audience and the streamer” (p. 20). Twitch thus invites its viewers to become “part of the show” through their co-participation in real-time, text- based “chat” (Twitch, 2019). Many of the participants in my study have made both watching and chatting on Twitch part of their daily routines. Some of them—who I will profile later in this 52 chapter—regularly stream their own gameplay for fellow students to observe. While the live broadcasts themselves are undoubtedly the platform’s main attraction, Twitch streamers also have the option to temporarily save a broadcast and its corresponding chat-log for up to two weeks. On the surface, these VoDs represented an excellent way to supplement my ongoing and more active data collection process. However, through their natural collaboration and interaction on platforms like Twitch, modern esports competitors show themselves to be increasingly

“tethered,” with many of their unique practices bringing “always-on culture” to new relief

(Turkle, 2006). Although I stayed in constant communication with my participants over the course of this two-year study, I could never know exactly when one of them would go live on

Twitch. Access to these public, historical VoDs allowed me—as a researcher—to retroactively capture fleeting moments and “never-to-be-repeated experiences” that might have otherwise gone unnoticed (Twitch, 2019).

As Fields and Kafai (2009) argue, “in-game identities and socializing is not as ‘within game’ as many perceive it to be” (p. 50). Since Twitch can preserve time-stamped chat-logs of viewers’ communications with one another and with the streamer, its VoDs become useful tools for charting how “relationships and talk traverse well beyond” the game-space of Overwatch

(Fields & Kafai, 2009, p. 50). While a purely in-game chat-log—such as those collected by

Nardi et al. (2007)—might provide insight into how players develop content-specific strategies or tactics, those found on Twitch VoDs seem uniquely equipped to help researchers “move from

‘roots to routes,’ [… to] trace and map the texts and contexts articulated in the space-times of literacy practice” (Leander, 2008, p. 60). After all, on Twitch, users do not simply interact with one another as player-to-player; depending on the circumstances surrounding a given “event complex,” they might instead find themselves conversing as mentor-to-mentee, celebrity-to-fan, 53 producer-to-consumer, student-to-student, or friend-to-friend. As a researcher, the Twitch VoD thus became another “new and strange” source of data that I could leverage in order to make sense of my participants’ evolving relationships both with one another and with the wider esports community.

Figure 3.6: A club member uses Twitch to share his gameplay and to interact with fellow players. A time-stamped chat-log of his viewers’ conversations appears on the right.

Discord

Discord is a multi-purpose social-platform that has been designed to accommodate the unique cultural values and needs of modern gaming communities. More specifically, it has risen to become the preferred voice-over-internet-protocol (VoIP) service for the majority of PC gamers, replacing older communication systems like Ventrilo, TeamSpeak, and Skype. As

Williams et al. (2007) remind readers, the challenge and complexity of online multiplayer games increased dramatically throughout the 2000s, and many players struggled to “facilitate communication between large numbers of people within hierarchies[; consequently,] they […] adapted communication modalities to support themselves. Most notably, [hardcore players began] to use out-of-game voice systems to supplement the text-based systems built into the 54 game” (p. 430). To this day, esports competitors—like the participants in my study—still prefer to use “out-of-game voice systems” to organize and conduct in-game activities. In addition to sporting VoIP capabilities, Discord also borrows a number of social features from platforms like

Twitter and Slack to help its users connect and play with other likeminded gamers. For instance,

Discord enables users to: build contact lists, send direct text-messages, initiate private voice- calls, join public voice and text channels, create custom servers, share hyperlinks, broadcast group alerts, and receive news about their favorite games. When combined together, these affordances—which can be accessed and leveraged during gameplay—make Discord the ideal, online home-base for many esports competitors.

The participants in my study mobilize on Discord in several ways, including—most notably—through the official “PSU Esports” server. This particular server (see Figure 3.7) acts as a nexus for club activity, connecting members to one another across space and time. It also serves as a living database, where members can hear the latest announcements and find out information about the club’s hierarchy, rules, and mission statement. Finally, the server features additional, separate voice and text channels according to esport; members are thus always able to find and participate in the most relevant sub-conversations based on their personal interests, experiences, and gameplay goals. The bulk of data that I gathered from Discord ultimately came from the server’s “#overwatch” text-channel and its associated voice channels, where users would post highlights, ask questions, and discuss strategies specific to Overwatch. Text-based conversations were captured through screenshots and voice-based conversations were audio- recorded. Several of my study’s semi-structured interviews were conducted through Discord as well. As James and Busher (2016) argue, the tool and location used for interviews “depends on the purposes of the research project and the characteristics and circumstances of the participants’ 55 lives” (p. 251). Since communication on Discord is a regular and authentic practice for those in my population, it proved to be a natural and convenient platform for interviews—especially over the summer months and for staying in touch with recent alumni. Furthermore, Discord allows users to share live-feeds of their computer screens with one another. This feature allowed participants to provide more visual answers, examples, and explanations for my questions that would not have been possible in traditional, face-to-face interviews.

Figure 3.7: A screen-shot of the “PSU Esports” Discord server. This image showcases the latest club announcements. A list of currently online users is featured on the righthand side.

Willard 371

Willard 371 is a traditional classroom on the university’s campus, and it served as the primary location for offline data collection (see Figures 3.8). Once a week during the fall and spring semesters, members of the esports club’s “Overwatch Division” would meet in Willard

371 to hang out, review gameplay footage, plan future events, and engage in light-hearted competition. The students typically sat at tables in clusters of three to six that were scattered 56 throughout the room. Two projector screens were positioned on opposite walls; the division head utilized these screens to display a variety of information, notes, diagrams, and videos to help initiate and frame group discussions. I was struck by how “school-like” both this setting and its meetings could be, and, to an unaware passersby, the student-run gatherings must have resembled formal lectures. After approximately an hour of more structured activity, the meetings would break, and students could disperse to go their separate ways, often not before planning to reconvene online later that same evening.

Figure 3.8: Club members gather in Willard 371 to discuss the latest esports news.

As a teacher-researcher, Willard 371 was ironically the site where I felt most out-of-place and uncomfortable. Despite being the one setting that was neither “new nor strange,” its offline, face-to-face nature served to accentuate the differences between myself and my participants. In

Overwatch and on Discord, I was just another player. In Willard 371, I was a camera-toting outsider that clearly had a few years on everyone else in the room. For these reasons, I struggled to participate actively during meetings and, instead, preferred to collect data more passively. I’ll 57 detail this dynamic when I describe more about my researcher identity later in this chapter.

Nevertheless, my weekly observations in Willard 371 represented a crucial step in my connective, ethnographic process. As Jones (2005) reveals, to simply:

[look] at what [young people are] doing online […] would completely miss the point of studying online behavior. Because it would set up this kind of idea that what they do online is somehow separate from what they do offline, that there’s this kind of “cyberspace,” where they go and do all sorts of these special things, and there’s a clear boundary that’s drawn, and, that’s not what’s happening at all. What they’re doing online has a lot to do with what they’re doing in the real world.

The metaphoric door, in other words, swings both ways. In order to understand “how school assignments, online gaming, life happenings, friendships, romances, and other areas of youth life are […] bounded at particular moments,” I—as a researcher—had to be willing to trace connections no matter where they led (Leander, 2008, p.52). Consequently, my data collection process had a tendency to get messy, and, as I will describe throughout this dissertation, the interactions, activities, and relationships on display in Willard 371 truly tested my abilities to untangle the knots and follow the threads that bound its users.

Overview of Participants

Although the esports club at Penn State boasts over 600 members and recent alumni, my study focused on one particular “division” that was comprised of nearly 50 Overwatch fans and competitors. From that population, I narrowed and centered my investigation around two

“teams” of the most “hardcore” players and their closest associates. While these fourteen club members would go on to become my “featured” participants, the fluidity and unpredictability of esports life necessitated that I also collect data on as many as twenty additional, “supporting” participants—students who would occasionally “stumble into” the group’s online activities

(Jones, 2005). For example, these supporting participants were often called on to be “substitute” 58 players for matches when the “starters” had scheduling conflicts. I provide general background information on all the featured participants in following table (see Figure 3.9) before describing several of them in greater detail in the subsequent section.

Name Gender Team Additional Club In-Game Role Affiliations Role Brock Male D1 Division Head (2018- Support 2019) D1 Manager Ash Male D2 Division Head (2019- Tank 2020) Oak Male D2 D2 Coach Support Red Male D2 Tank D1 Substitute Blaine Male D2 Damage Erika Female D2 Substitute D2 Manager Tank Koga Male D1 D1 Coach N/A Kevin Male D2 Damage Scott Male D1 Division Head (2020- Tank 2021) Roger Male D1 Tank Leon Male D1 Damage Lance Male D2 Damage D1 Substitute Sarah Female D2 Support Ming Male D1 Support Table 3-1: General demographic information on my featured participants.

Profiles of Select Participants

While all my participants where interesting people and important team members in their own ways, I wanted to highlight several students who—by virtue of their values, practices, and relationships—stood apart from their peers.

Brock was one of the most vocal and skilled Overwatch players in the club, and he regularly competed at the “grandmaster” level during online play. Overwatch, much like chess, uses an “Elo” rating-system to separate its players into competitive tiers. An Overwatch 59

“grandmaster,” like Brock, thus finds themselves ranked amongst the top 1% of players worldwide. As such, Brock would occasionally be matched with and against OWL-caliber players and popular Twitch streamers while playing online. Brock leaned on these unique experiences as he captained Penn State’s “D1” team—the group of club members that would travel to represent Penn State in more serious LAN tournaments. Brock also acted as this team’s in-game “shot-caller,” the player responsible for verbally directing teammates during skirmishes.

Out-of-game, he took on various leadership roles within the club, including—most notably— acting as the “division head” for a semester and a half. As the division head, Brock would moderate group discussions in Willard 371, host more casual events online, and serve as the club’s ambassador at university functions. In many ways, Brock was the heart and soul of Penn

State Overwatch.

Ash was perhaps the club’s most out-going member and largest personality. Famous amongst his peers for both his outlandish catchphrases and his reckless gameplay, Ash was as popular as he was skilled. I got to know Ash more personally during the Fall 2018 semester when we competed together on one of the club’s more casual teams. During that time, I had many private conversations with Ash and thus learned a great deal about how he thought about the game of Overwatch, his role on the team, and his growth as a player. Although he was initially known for his use of Reinhardt, a burly “tank” of a character, Ash went to great lengths to diversify his “hero pool” and to become a more flexible player. He regularly leveraged

Overwatch’s “custom games” function to create personalized, targeted drills for himself to practice. His favorite of these custom game-types was the “Widow Headshot Lobby,” a mode designed to simulate the intense sniper duels that would so often take place in regular matches.

He relied on these modes both to improve his aim and to serve as a warmup. By integrating 60 these drills into his daily routine, he quickly became one of the club’s most consistent and versatile players.

Oak was an analytically-minded and data-driven thinker. If Brock was the club’s heart and soul, Oak was certainly its brain. As such, he sought out many managerial and coaching roles in the club, and he relished opportunities to help fellow club members improve their in- game decision-making. Similarly, he networked with other university teams to coordinate friendly “scrims,” wherein players could test strategies in relatively consequence-free environments. However, what really distinguished Oak was his eagerness to perform rigorous pre-game scouting. While “profile-checking” (Turcotte, Hein, & Engerman, 2017) has been a common practice in gaming circles for decades, Oak took that research to new extremes. He would meticulously scout opponents—sometimes weeks in advance—and would create predictive models based on their in-game statistics. He would then share those findings with his team in the hopes of developing counterstrategies.

Red, like Brock, was another grandmaster-level player. Since so few of the local players were experienced enough to help him improve, Red often relied on the wider esports community to help him identify weaknesses in his game and to learn from mistakes. He thus became an active member in the Twitch communities of several high-profile Overwatch personalities.

Recalling Twitch’s (2019) tagline, “you don’t just watch […], you’re part of the show,” Red would occasionally submit his personal game-tape for these streamers to review and critique during live-broadcasts. By channeling Twitch in this way, Red was able to receive individualized coaching from some of the world’s best Overwatch players—including former professionals like Jeff “Emongg” Anderson. However, due to some scheduling conflicts, Red was not always able to compete alongside of Penn State’s other top-ranking players. 61

Consequently, he spent much of the Spring 2018 semester acting as a player-coach for some of the club’s more casual teams. This allowed Red to step into mentoring roles and lead-by- example in-game.

Blaine was what many Overwatch players refer to as a “one-trick.” As the phrase implies, a one-trick specializes in the use of a single hero and dedicates their time to mastering its intricacies. In a game like Overwatch, which features 30 different heroes, “one-tricking” is an inherently risky practice. Specifically, a one-trick severely limits the number of viable compositions and strategies that a given team can employ. Not surprisingly, Blaine would often find himself at odds with teammates who grew increasingly frustrated with his lack of flexibility.

I highlight Blaine here because he inadvertently created drama where it otherwise might not have existed. Through Blaine’s identity as a one-trick, I was thus able to collect meaningful data on how club members negotiated their differences, resolved conflicts, and worked creativity to find solutions. To emphasize, Blaine was by no means a villain, but his unique approach to

Overwatch certainly tested relationships in unexpected ways.

Erika, contrasted against Blaine, was the ultimate team-player. Not only was she happy to play as any of the game’s characters, but she also acted as a manager and substitute for a variety of the Penn State affiliated teams. When teams would scramble to find a last-second replacement for one of their matches, Erika was always quick to answer the call. As such, her flexibility—both in and out of game—was invaluable to the club’s success. In addition to Erika would regularly “duo-queue” with her boyfriend, and fellow club member, Oak. Together, they would attempt to “climb” the game’s online ladder and improve their ranks. When I began my research, I didn’t realize that my efforts to “trace relationships” (Leander 2008) would end up being—at times—quite literal. 62

Koga was a late addition to my study, but his perspectives and experiences were especially interesting because he worked as a translator for the Los Angeles Valiant. While his time was certainly limited, Koga was eager to mentor individual players or to coach teams when his schedule allowed it. Specifically, he would host “VoD reviews” on both Twitch and Discord to breakdown and analyze members’ gameplay. Through their conversations, Koga could come to a better understanding of how and why the players made certain in-game strategic and positioning decisions; consequently, he could more accurately diagnose issues while offering workable solutions. Furthermore, since Koga was a well-connected member of the wider

Overwatch community, he was able to quickly schedule impromptu scrims. Koga was thus responsible for exposing club members to a variety of new ideas and for helping them network with likeminded players beyond the university.

To reiterate, all the club members—regardless of whether they became “featured” or

“supporting” participants in my study—had something significant to reveal about esports culture.

They were all deeply invested in their personal development as players and their collective improvement as teams and as a club. The highlighted participants described above simply were able to transform those shared values into some of the more unique and noteworthy practices. In addition, these participants exhibited an uncommon interest in my own research and were thus happy to act as my translators and guides as I explored their culture. As such, the findings I will present in chapter four are overwhelmingly mediated by their perspectives and experiences.

Finally, as I now move to describe my role and identity as a researcher, I wanted to introduce readers to the participants who made the more immersive and participatory aspects of my study possible. I wouldn’t have felt confident employing many of the ethnographic methods I describe herein without their insight and support. 63

Researcher Identity

For those conducting connective ethnographies in the tradition of Jones (2005), “it is essential to disrupt the binary and power relationship of researcher/research subject in order to get at the more native ways of understanding the meaning of digital practices (Leander, 2008, p.

50). Therefore, prior to describing my own data collection process, I wanted to clarify how I constructed and presented my identity—as researcher—in ways that could simultaneously

“disrupt [that] binary” and “get at the more native.” I have already spoken at length about my time as a competitive gamer in the mid-to-late 2000s. While those experiences were certainly formative and—in many ways—acted as the catalysts for my present study, they were no longer representative of how today’s esports enthusiasts interface with their chosen games and communities. In fact, while conducting a separate study with Engerman (2016), I mentioned to our participants—high school boys—that I still played a variety of GameCube-era video games.

Their response? “Oh… so you’re a retro gamer?” The comment stung, and it made me feel like an out-of-touch old man; however, it also served as an acute reminder that, in order to seamlessly and successfully “get at the more native” in my own studies, I would have to be willing to reinvent myself.

By the time Overwatch released in the summer of 2016, it was already clear that a vibrant, local community would spring up around the game. While I wasn’t completely sure if or how Overwatch might ultimately factor into my dissertation, I nevertheless decided to dedicate myself to playing and learning the game. At the very least, I figured that the process of immersing myself in its world might prepare me to have more productive conversations with a younger generation of hyper-competitive gamers. As it turned out, I became rather obsessed with Overwatch and sunk nearly 500 hours into the game in advance of this present study. I 64 even attempted to climb the game’s online ladder, slowly rising through the lower ranks to eventually settle in its second highest division, “masters,” by the fall of 2017. On the surface, my independent foray into competitive Overwatch might seem like overkill. However, it— combined with the knowledge and skills I gained along the way—allowed me to interact with club members as player-to-player instead of simply as researcher-to-subject. Furthermore, since

I could play the game at the same level as my participants, a host of “new and strange” data collection opportunities presented themselves to me. Most notably, I could naturally integrate into the club’s existing team rosters and actually compete alongside participants during interuniversity play. From the very start of my study, I was able to conduct both unstructured interviews and analysis in situ; I thus allowed the culture’s most immediate and pertinent activities to guide my research.

Hammersley and Atkinson (1983) urge ethnographic researchers to become “acceptable incompetents” in the domains they wish to study. By “grinding” Overwatch for over a year, I took that suggestion to heart. Unfortunately, that personal journey to “git gud” also led me to develop certain biases about esports, its players, and its communities that other, more “distant” researchers might not have come to harbor (Kendell, 2008). Likewise, I constantly ran the risk of conflating my individual experiences learning Overwatch in 2016 and 2017 with my participants’ ongoing and collaborative efforts to improve throughout 2018, 2019, and into 2020.

As a writer, I also fear that I may underexplain or gloss over certain aspects of esports culture that I have long since internalized and now mistakenly assume are common knowledge. I share these concerns now because, although I draw on the frameworks of Hine (2000; 2008), Jones

(2005), and Leander (2008), my own ethnography deviates in ways that some readers may find jarring. Know that I felt a similar discomfort throughout my investigation, and, as such, I tried to 65 never lose sight of both the benefits and the dangers that these “new and strange” methods could pose. However, in the end, I believe that the more immersive and participatory methods that I now move to describe are precisely what will set my work apart and will make it a valuable resource for future researchers. In particular, by gaining my participants’ trust and respect as a competitor first and as researcher second, I was able to “disrupt the binary” and “get at the more native” in meaningful and striking ways.

Procedure and Data Collection

This study’s overarching challenge was to trace participants’ activities and relationships across ‘‘multiple, simultaneous space-time contexts’’ (Leander & McKim, 2003). I thus followed the blueprints of Fields and Kafai (2010) by gathering and analyzing “numerous types of data” aimed at tracking the “youth in the club over multiple spaces (physically in the

[classroom] as well as virtually over multiple spaces on[line])” (p. 96). I now describe that

“gathering” process through a series of vignettes that I feel are most representative of my regular ethnographic work.

The weekly meeting

As I alluded to in a previous section, Willard 371 tested my abilities as a researcher in a variety of complicated and unpredictable ways. However, before I could even think about recording, capturing, and logging the actual meetings, I first had to navigate the building’s chaotic hallways. Specifically, these liminal spaces tended to become the noisy staging areas for a variety of student-run organizations as their members milled around and waited for their designated classrooms to empty out. As Jordan and Henderson (1995) explain:

Events always have a structure. Minimally, they have beginnings and endings. […] [Researchers should] always want to observe the starting up and winding down process 66

because significant interactions tend to happen at these junctures. Beginnings and endings are often marked by rearrangements of artifacts. Tracking what is turned on, brought in, taken out, or rearranged prior to the official start reveals what sorts of props and technologies are thought to be necessary for carrying off the event. (pp. 57-8)

For club members, the “starting up” processes that took place in Willard’s hallways served to bridge their virtual and campus lives. Conversation was equally likely to revolve around recent, professional Overwatch matches as it was to recount the weekend’s college football game.

Likewise, these students would seamlessly transition from complaining about their classes to describing their hopes for Overwatch’s upcoming “patches.” Consequently, these moments provided great insight into how campus and esports culture collided together at Penn State to create a unique, one-of-a-kind community. Unfortunately, due to the mercurial, borderline lawless nature of these interactions, it was not always possible to video-record them for later analysis. Instead, I relied heavily on my own “wide-angle lens” as a participant observer as I joined in conversations, asked questions, and took field notes (Spradley, 1980).

When Willard 371 finally became available, the students would filter into the classroom and take seats at one of its eight tables. Based on what transpired in the hallway, I would position my video cameras and microphones to follow those initial student-interactions as they came to occupy a new space-time (Leander & McKim, 2003). Since the attending members and their conversations would vary on a week-to-week basis, I was always setting up my equipment in new ways for each meeting. For example, if I was having a discussion with Oak, Blaine, and

Ash in the hallway, I might then leave a wireless microphone at their table and position a corresponding camera nearby. I would also place a second camera in the back of the room and angle it as to capture the wider totality of interactions between and amongst tables of students.

This second camera would also record the podium and projector screen—from which the division head would deliver and display the meeting agenda. However, since it was so 67 challenging to anticipate how “interactional ‘hot spots’” (Jordan & Henderson, 1995) might spring up, shift, evolve, and disappear, I would frequently have to reposition or temporarily man the camera equipment. Spradley (1980) explains that—during data collection—the participant observer will “experience being both insider and outsider simultaneously” (p. 57, emphasis mine). At no other point in my study was I more self-conscious of that dual identity than in these moments—when students would suddenly rearrange themselves and I would be forced to break away to reorient and temporarily operate the cameras.

The meetings themselves would cover a variety of topics ranging from the logistics of club life to the finer strategies of competitive Overwatch. For instance, on some nights, students were invited to submit and share video highlights of their own gameplay. These clips, many of which originated from the prior weekend’s tournament matches, would be displayed on the projector to be critiqued and analyzed by fellow members. On the one hand, these hyper- abbreviated VoD review-sessions functioned to bring, quite literally, the participants’ virtual identities into the classroom. Furthermore, they provided an open forum wherein ideas could be exchanged across teams and experience levels (see Figure 3.10). I will revisit the concept of the

“VoD review” throughout chapters four and five. However, I mention it now because these VoD reviews—as foundational practices of OAGEs—posed a variety of unique methodological challenges and questions. After all, Overwatch is hard enough to follow and understand even when one has the proper context and game-knowledge. The VoD reviews that occurred during these meetings would often feature and revolve around a brief, 30-second snippet of action taken from the middle of a match. Especially at the onset of my study, when I still struggled to keep students’ names and gamertags straight, these VoD reviews represented intricate knots of both real-world and virtual threads. In order to untangle them, I employed a version of what Hollett 68

(2015) calls “temporal circling.” This strategy, which involves gong “back in time to focal points of high energy, productivity, activity” became a means for me to “re-experience” chaotic interactions on my own terms (Hollett, 2015, p. 87). Specifically, I would ask club members to send me the entire VoDs—not just the featured highlights—on Discord so I might slow down, rewind, and pause the action that I found so difficult to decipher during the actual meetings. I thus supplemented and informed my face-to-face data collection in useful, culturally significant ways. In addition, with access to the original VoDs in their native resolutions, I was free to video-record these weekly meetings without dedicating a camera to the projector-screen alone.

Figure 3.10: Brock leads the club in a VoD review of the D1 team’s weekend game.

Match day

Club members—according to their skill-level, in-game role, and availability—played on a variety of different university-affiliated teams that would regularly compete in official matches, 69 scrims, and “pick-up-games” (PUGs). As a researcher, each team and activity provided something interesting to capture and analyze, and so I collected data across these contexts when and where I could. However, in this section, I am going to describe my observation of and participation with the “D2” team as they competed in the semester-long “Tespa” tournament during the spring of 2018. According to its website, “Tespa is a network of college clubs founded to promote gaming culture and [to] host the best college esports events” (Tespa, 2019).

This organization thus supports and runs multiple online tournaments each semester and even offers prizes and scholarships for its top-performing players. Not surprisingly, Tespa matches feature a rigid set of rules, and its competitors tend to play more seriously and ruthlessly. Penn

State’s D2 team was no exception, and, therefore, my continual efforts to trace its players’ interactions and relationships took many fascinating and challenging turns.

Tespa matches took place online at 3:00pm and 6:00pm on Sunday afternoons. However, much like with the weekly meetings, players would begin congregating on Discord and warming-up in Overwatch as early as an hour beforehand. While I had no issues participating in and audio-recording their pre-match conversations, the players’ concurrent warm-up rituals were frequently too personal or nebulous to capture. For example, participants might join private lobbies with custom settings to practice niche skills, loosen muscles, or reacclimate to their mice- and-keyboards. Although I couldn’t always follow and observe participants during these moments, I nevertheless highlight them here because they served as important reminders of the

“central yet discreet staging of physicality that is required in high-performance [esports] play”

(Witkowski, 2012, p. 369). My participants were more than simply disembodied voices and virtual avatars; they were people whose physical “composure, breathing, and […] steadiness […] direct[ed] the actions, as well as the outcome, of every game session” (Witkowski, 2012, p. 369). 70

As the players, myself included, would engage in these individual warm-ups, Oak—who managed and unofficially coached the D2 team—would typically brief us on our opponents and delegate in-game responsibilities.

In an earlier section, I mentioned that participants would regularly inhabit two or more

“sites” at a given time. Match day represented one of those such instances, when players could simultaneously converse in Discord, play Overwatch, stream on Twitch, and, intermittently, browse the internet. The totality of their actions and interactions was thus impossible to untangle, and I was forced to tug on what threads I could. At a minimum, one of my participants would screen-capture and live-stream their individual perspective each week. Likewise, I utilized a special software program, XSplit: Gamecaster, to video and audio-record our online interactions from my end. Unfortunately, due to the limited processing capabilities of my PC, I occasionally had to deactivate XSplit during match-play. Running XSplit and Overwatch simultaneously could—at seemingly random intervals—cripple my in-game framerate and prevent me from playing as effectively as possible. It wasn’t fair to my teammates that I continue recording during these moments, and, consequently, I often came away from an evening of matches with fewer data-points than I anticipated. And while these technological glitches could be frustrating, I never felt like I really lost anything when they occurred. On the contrary, without the manufactured responsibility of operating a tool like XSplit, I could more fully and authentically immerse myself in “being there” with participants (Boellstorff et al., 2012). So whatever might have been “lost” in data was gained in experience and perspective.

However, that “experience” would always vary on a week-to-week basis. Our D2 team could never be completely sure which of its six “starters” and three “substitutes” would actually show up for the start of a match, and we were often forced to field different, makeshift lineups— 71 each of which featured novel relationships and thus cultivated unique interactions. At 3:00pm,

Oak would send an in-game text-message to the opposing team’s captain, and, together, they would create a lobby for the two teams to join (see Figure 3.11). These “lobbies” were to

Overwatch what the hallways of Willard were to the weekly meetings. Players from both teams would filter in and begin casual, text-based conversations with one another. Generally, players exchanged pleasantries or engaged in a bit of friendly banter and pre-game trash-talk. Since these messages all appeared in a communal chat-window, they were easily captured and recorded with XSplit. Interestingly, as these inter-team, text-based conversations took place within

Overwatch, very different voice-conversations would transpire in our team’s private Discord channel. Specifically, our players would frantically “profile-check” opponents to learn their strengths and weaknesses before blurting out these discoveries for teammates to hear (Turcotte,

Hein, & Engerman, 2017); likewise, based on this new information, Oak would make last-second adjustments to our team’s roster and strategy. The pre-match lobby thus represented a compelling, multi-context “interactional hot spot” wherein deep-seated cultural values regularly bubbled to the surface and manifested themselves in surprising new ways (Jordan & Henderson,

1995). 72

Figure 3.11: Players gather in an Overwatch lobby for their weekly Tespa matches.

Matches would ultimately begin when both captains confirmed that their teams were ready. During the games themselves, I simply played to the best of my abilities and communicated with teammates in a natural, culturally appropriate manner. Typically, I was expected to play as either Ana or Mercy—two characters that have historically filled the “main- support” role. Methodologically, this is not an insignificant detail. Since I was often screen- capturing my own first-person perspective, the relational positioning of my virtual avatar within

Overwatch mattered; it affected what my data looked like. Ana and Mercy are characters that— to make a comparison to basketball—act as point guards. They “assist” teammates during combat through their use of various healing and amplification abilities. An effective Ana or

Mercy player will thus position themselves in the “backline,” where they can simultaneously avoid danger and maintain visibility on their teammates. As Jordan and Henderson (1995) explain, researchers—when filming—should “make every effort to have all participants in the

[frame] and to have their whole bodies visible. […] Interaction Analysis, which is based on the 73 premise that what the speaker says or does[,] is fundamentally a social phenomenon, orchestrated with, and responsive to, other individuals in the scene” (p. 89). Playing “main-support” not only afforded me the requisite “visibility,” but—as I will describe in chapters four and five—it also led me to develop a greater appreciation of just how explicit and visceral that “orchestration” and

“responsiveness” can be in today’s virtual worlds.

Matches would end much as they began, with players reconvening in the lobby to say their goodbyes. I kept my screen-capturing and audio-recording software running during these moments as our team, in Discord, would privately reflect on the match. Emotions were often at their highest following particularly narrow victories or tough losses, and conversations were thus prone to taking unpredictable turns. More commonly though, participants would verbally recall their mistakes and successes while simultaneously musing about how a match might have played out differently. Other times, they might simply be eager to “go agane” and to play Overwatch long into the night. For Jordan and Henderson (1995), these types of “endings, although often perceived as externally imposed, [were] in fact collaboratively achieved by participants” (p. 58).

Their “winding down process” thus produced its own unique set of interactions, and, whenever possible, I tried to make sure that my recording software was “the last agent on the scene”

(Jordan & Henderson, 1995, p. 58).

Informal and Impromptu Sessions

In earlier sections, I have described esports culture—and specifically its community at

Penn State—as “always-on” (Turkle, 2006). Just because an official meeting or Tespa match wasn’t on the calendar, didn’t mean that students weren’t mobilizing online in a variety of ways.

I now move to provide a brief overview of what these more miscellaneous, unscheduled activities involved and how I—as a player-researcher—adjusted both my methods and daily 74 routine to remain tethered. However, I first want to consider Hollett and Hein’s (2018) understanding of “affective atmospheres,” interactional hot spots that “continuously [form] and

[feed] off of numerous intensities” (p. 6). For Hollett and Hein (2018), who studied the cultural practices of action-sports athletes, these atmospheres “emerged at the confluence of material and immaterial bodies” and were frequently signaled by a “palpable energy” (p. 6). More specifically, called by “pumping music,” “slamming skateboards,” and general “chatter” athletes would naturally navigate to and congregate in such “affectively-charged places” which, in turn, proved ripe for the researchers’ investigation and analysis (Hollett & Hein, 2018). As I took my own ethnography to “new and strange” places, I thus had to learn what “palpable energy” looked, sounded, and felt like online.

Throughout the semester, participants would frequently leverage the baked-in affordances of Overwatch, Twitch, and Discord to broadcast their availability to one another. The most common of these practices involved “pinging” individuals or groups of players on Discord.

Much like a classified ad in the newspaper, a “ping” served as an open and public invitation to participate in a given activity—such as a VoD review, a scrim, or a watch-party. Any members online at the time of a ping would receive an audio-visual alert on their desktops; those with the

Discord app downloaded on their phones would get similar notifications. While the “pumping music” and “slamming skateboards” of Hollett and Hein’s (2018) “affective atmospheres” would passively draw action-sports athletes together, my own participants needed a more active means to signal one another across time, space, and context. The Discord ping thus became their digital flare-gun of choice (see Figure 3.12). Not surprisingly, as my study progressed, I found myself becoming a compulsive Discord-checker. Each ping represented a new opportunity to immerse 75 myself in esports culture and to collect data, and, as such, I responded to and participated in as many of these impromptu events as possible.

Figure 3.12: Oak “pings” club members in the Overwatch division to let them know that a new map is available to play in-game.

Since these sessions typically involved grouping up in Overwatch, I could employ many of the same collection methods that I relied on during match days. However, due to the more casual and unstructured nature of these activities, I was also free to be more experimental in my approach. For example, without the obligation to play myself, I could take advantage of

Overwatch’s built-in “spectator” feature to screen-capture the action in new ways. As I noted in an earlier section, as a “spectator,” I could pilot an invisible, drone-like camera through the three-dimensional game-space of Overwatch. Furthermore, like an omniscient narrator in fiction writing, I also could—on command—access each player’s first-person perspective. With such powerful tools at my disposable, I was thus able to zero-in and focus on particular interactions that I might otherwise miss during regular gameplay. Of course, collecting data in this manner was not without its challenges. I mistakenly assumed that—as a veteran of the game itself— learning the “keybinds” and controls for Overwatch’s spectator cameras would come naturally for me. Unfortunately, that was not the case, and I spent my initial sessions flying aimlessly into walls and switching perspectives to the wrong players at the wrong times. While I eventually 76 improved, I should have taken the time to practice with the feature prior to data collection. And as if I wasn’t already self-conscious about these struggles, my participants would occasionally request copies of my spectator-data so that they could conduct their own VoD-reviews at later dates. On the one hand, I welcomed these exchanges; recalling Jones (2005), they certainly served as a means “to disrupt the binary and power relationship of researcher/research subject”

(Leander, 2008, p. 50). At the same time, I nevertheless worried that the clumsiness of my spectating could prevent footage from being as useful to participants as it was to me.

When I described my attitude, role, and practices during match day, I mentioned that I tried my best to keep my communication relevant to the game; I never wanted to unnecessarily distract participants from the goals at hand. However, during these more informal sessions— where conversation was generally unfocused and lighthearted—I felt comfortable asking open- ended questions, encouraging “think alouds,” and, when appropriate, even transitioning into semi-structured interviews. Kendall (2008) explains the importance of such techniques, arguing that “more than any other method, qualitative interviews allow for the exploration of meaning, especially as meaning is constructed by the research participants regarding a topic or setting of interest” (p. 133-4). She also emphasizes that interviewers should “compensate for the distance between [themselves] and [participants]” through their “immersion in interviewee’s world” (p.

137). For Kendall (2008), this “immersion” involves “active listening” during the interview and through “research or preparation” prior to the interview (p. 137). I took her call for immersion more literally, going as far as to create custom Overwatch lobbies for myself and participants to virtually inhabit as our interviews in Discord unfolded (Merchant, 2010). Together, we would thus re-trace our in-game movements from match days, and participants could “physically” direct my attention to the finer details of their Overwatch experiences. 77

Event Location(s) Data Collected Tools Used Weekly Willard 371 - Video and audio - Two video cameras Meeting Discord (occasionally) recordings - Multiple wireless - Field notes microphones

Match Day Overwatch - Video and audio - Twitch livestreaming Discord recordings - Xsplit screen-capture Twitch

Impromptu Overwatch - Video and audio - Twitch livestreaming Sessions Discord recordings - Xsplit screen-capture Twitch - Digital artifacts - Discord file-sharing

Table 3-2: An overview of where and how data were collected.

Interaction and Data Analysis

As I have alluded to, I drew on Jordan and Henderson’s (1995) understanding of

“Interaction Analysis” to inform and guide my collection process, especially where video- recordings or screen-captures were involved. I now describe how their framework also allowed me to parse, analyze, and interpret that data in helpful and illuminating ways. After all—and in alignment with my connective ethnographic approach—“the goal of Interaction Analysis […] is to identify regularities in the ways in which participants utilize the resources of the complex social and material world of actors and objects within which they operate” (Jordan & Henderson,

1995, p. 41). Specifically, in this section, I explain how I revisited my video-data to “identify regularities” and to fill gaps in my cultural portrait of collegiate esports competitors.

While analysis always began in the field and during gameplay, it focused and intensified at the library, where I would first re-view video-data and create corresponding “content logs”

(Jordan & Henderson, 1995). These content logs would include a rough, timestamped summary of events as they occurred on the tapes. Methodologically, these thus proved “useful for providing a quick overview of the data corpus, for locating particular sequences and issues, and 78 as a basis for [eventually] doing full transcripts of particularly interesting segments” (Jordan &

Henderson, 1995, p. 43). Tangentially, content logging represented yet another way that—over the course of my study—my practices as a researcher came to mirror the cultural practices of my participants. I have already spoken at length about how, historically, both online and face-to- face “VoD reviews” have led esports competitors to re-experience and, ultimately, transform their gameplay. In addition, my participants would regularly conduct asynchronous, text-based critiques for one another. In these instances, players would timestamp a VoD’s key moments while providing descriptive summaries and prescriptive recommendations (see Figure 3.14).

Although the resulting cultural artifacts could be helpful in their own rights, players often leveraged them to guide and frame the discussion during more traditional and collaborative

VoD-review sessions.

Figure 3.14: A screenshot of an asynchronous, text-based critique that Brock provided for Oak.

I used my own content logs in a similar manner. Throughout the semester, I would occasionally review video-data with fellow graduate students and faculty from Penn State’s

“Learning, Design, and Technology” department. Informed by my content logs, I would start, stop, fast-forward, and rewind footage so colleagues could “propose [their own] observations and hypotheses” about “particularly interesting segments.” Jordan and Henderson (1995) also argue that “collaborative viewing is particularly powerful for neutralizing preconceived notions on the part of researchers and discourages the tendency to see in the interaction what one is conditioned to see or even wants to see” (p. 44). As I described in a previous section, my experiences and identity as a competitive gamer have unquestionably “conditioned” me to fixate on certain aspects of my participants’ interactions. However, by integrating multidisciplinary, collaborative group-work into my analytical process, I was able to limit such “ungrounded speculations” while simultaneously interrogating many of my “prior interpretations” (Jordan & Henderson, 1995, p.

45). Consequently, analytical “categories emerge[d] from [the research group’s] deepening understanding of the orderliness of the interaction as participants on the tape ma[de] this orderliness visible to each other” (Jordan & Henderson, 1995, p. 43). My analysis thus not only remained grounded in what actually happened, but it also came to echo the aims and methods of my participants’ own VoD reviews.

Interaction Analysis also “attempts to include material [and nonmaterial] objects as special kinds of participants in its analytic endeavors” (Jordan & Henderson, 1995, p. 75). More specifically, “artifacts and documents [… can] provide resources for [community members] to monitor whether they are in agreement or not[, …] serve as territory markers[, … perform] special functions[, …or afford] symbolic significance” (Jordan & Henderson, 1995, p. 76-7).

Just as I attempted to trace my participants’ interactions and relationships across time, space, and 80 context, I made similar efforts to analyze how they would create, edit, share, and display their own cultural artifacts. For example, I became particularly interested in how a digital meme, spreadsheet, or VoD could “provide a crucial focal point for marshaling a group's attention” on either Twitch or Discord (Jordan & Henderson, 1995, p. 78). As I revisited and re-viewed video data, I simultaneously re-examined the artifacts behind those captured conversations and interactions. I use the word “behind” because of its double meaning—to describe both the artifacts’ “physical” locations and their abilities to facilitate or support. Although participants regularly inhabited multiple online contexts at the same time, the technical limitations of my screen-capturing tools prevented me from seamlessly recording the totality of what Jordan and

Henderson (1995) call the “social field.” As my participants played Overwatch, they would often have other websites, programs, and artifacts “open” in separate “tabs” (located behind their games) or on separate monitors. However, since tools like XSplit can only record the “top layer,” I had to separately screenshot these objects either before or after gameplay sessions. I mention this issue because it represented a unique challenge of capturing and analyzing my participants’ online habits. Therefore, in order to successfully engage in Interaction Analysis, I frequently had to stitch video-data and artifacts together (see Figure 3.15); only then could I begin to “understand what kinds of activities and interactions particular material objects engender and support” (Jordan & Henderson, 1995, p. 75). 81

Figure 3.15: When conducting data analysis, I would often re-watch gameplay on my main monitor while digital artifacts were open on my laptop.

As I conducted my analysis—and in alignment with my research questions, literature review, and theoretical framework—I looked and listened for moments when participants would engage in their own types of observation and analysis. I became particularly interested in how these moments could spring up during actual gameplay. Despite the frantic and chaotic nature of most Overwatch matches, participants would still regularly critique themselves and one another as they competed. The simultaneity of analysis, debate, and gameplay captured during these moments drew my attention and ultimately provided some of the richest, most revealing data.

For example, because of the time pressure that Overwatch competitors are under, my participants would frequently utilize “shared references” to hasten their conversation, activity, and learning

(Rogoff, 2014). These shared references could be prior VoD reviews, one of Oak’s spreadsheets, a famous professional match, or a clip from a popular Twitch streamer’s recent broadcast. As such, I paid close attention to how team leaders like Brock, Oak, and Ash would quickly “check 82 for understanding” before requesting that teammates engage in a wholesale strategy change.

These were especially compelling moments because even quieter team members would be required to “pitch in” to the ongoing discussion and planning. For my part, these moments came to represent important flashpoints in my analytical work; not only were they rich in their own right, but they would also help direct me to still other moments, events, and personalities in the club’s history that—only then—would coalesce to tell the entire story of an interaction.

Summary

I began this chapter with an overarching thought: “what is research supposed to look like?” After embarking on and struggling through my own version of a connective ethnography,

I think I finally have my answer—“whatever it needs to look like.” Throughout this chapter, I have described the immersive and participatory methods of my data collection and analysis.

This two-year-long process involved tracing my participants’ interactions, relationships, and activities across a variety of “new and strange” settings. Along the way, I learned how to use their cultural tools; I integrated their community language into my speech; I competed with and against them in Overwatch; I tuned in and “chatted” during their Twitch streams; I contributed to their discussions and debates on Discord. And perhaps most importantly—as a researcher—I adopted many of their observational and analytical strategies as my own. I thus found an approach that could at once “disrupt the binary and power relationship of researcher/research subject [and get] at the more native ways of understanding the meaning of digital practices”

(Leander, 2008, p. 50). In fact, only by pushing the boundaries of Hammersley and Atkinson’s

(1983) “whatever” did I feel I was truly able to “throw light on” the values, behaviors, and beliefs of collegiate esports competitors. At times, this journey was uncomfortable and scary.

Especially as a novice researcher attempting to cut one’s teeth, I felt pressure to do things “the 83 right way.” However, as it would turn out, those “uncomfortable” moments actually produced some of my study’s most compelling findings. I now move to report and describe those observations in the following chapter.

CHAPTER 4: FINDINGS

Where chapter three described what I did as a researcher, chapter four refocuses attention on my participants. After all, this dissertation is—at its core—about the values and practices of collegiate esports players. It is about how and why they observe, interact, and participate across multiple settings; furthermore, it is about how they leverage technology to connect with local and global esports communities in their ongoing efforts to improve at the game of Overwatch. In this chapter, I now present and describe the most representative and striking of their interactions through a series of ethnographic snapshots.

The rhetorical challenge I face in sharing these multimodal findings, however, is ordering them in a way that will make thematic and narrative sense for my readers. As I described throughout chapter three, my data is comprised of a tangled web of online screen-captures, in- person videos, audio interviews, text-based chat logs, and participant-directed livestream- broadcasts. What follows is my attempt to bring some order to that chaos—to take over two- and-a-half years of disparate data and to weave them together to tell the story of a collegiate esports club. I thus frame my data in terms of a typical week of Overwatch competition, highlighting how club members participated with one another leading up to, during, and after high-stakes tournament matches. Semester in and semester out, I watched as this rhythmic cycle—of prepare, perform, reflect—repeated itself many times over. And while the players came and went over the years, the defining features and practices of their community remained largely the same. This is what I found.

Preparation

Scouting 85

It’s 3:02 on a Friday afternoon—72 hours before the first of our two weekly tournament matches—and I get a text-message notification. It’s Oak, the captain of the club’s D2

Overwatch team. It contains no words, just a link to a “Google Sheet” titled “Weekly Scouting

Report.”

Figure 4.1: Oak shares scouting information on the D2 team’s upcoming opponents. Details include individual players’ estimated “skill-rating” and their preferred roles/characters. As time went on, Oak would provide increasingly in-depth statistics and eventually even tried his hand at developing predictive models.

Blaine reacts with a “thumbs up” emote, confirming that he received the file. Sarah and Surge quickly follow suit.

Kevin writes, “We’re going to clap these fools!”

I chuckle to myself. I really appreciate and admire his confidence, but, as I look over the sheet, I can’t help but notice that two of our opponents are “Grandmasters.” It’s going to be a very tough match for our D2 team. But on the bright side, thanks to Oak’s diligent scouting, at least we know what we’re in for.

--- 86

In this anecdote, Oak’s “Weekly Scouting Report” takes traditional “profile-checking” practices to new extremes. As Turcotte, Hein, and Engerman (2017) remind us, in the world of online gaming, profile-checking refers to the practice of leveraging particular in-game tools to research opponents’ strengths and weaknesses prior to competition. For the more “casual,” high- school-aged players of Turcotte, Hein, and Engerman’s (2017) study, the practice revealed itself in relatively shallow ways. It typically involved a last-minute, cursory evaluation of opponents’ performance-statistics. Participants would then focus on metrics such as “kill-to-death ratio” and

“weapon accuracy” to determine how threatening an individual opponent might be on the digital battlefield. While these younger participants felt that having access to this information helped them to mentally prepare for matches, profile-checking rarely led their teams to rethink their more macro-level strategies. However, for Oak and the rest of the club’s D2 team, their aims and methods turned out to be significantly more complicated. I now lean on my theoretical framework of “Learning by Observing and Pitching-In” (LOPI) to help describe how the Oak-led

D2 team employed various scouting practices to “transform [its] participation” and succeed in tournament play (Rogoff, 2014).

Most notably, rather than simply engage in profile-checking as an isolated, last-minute activity, Oak—and by proxy, his team—adopted a holistic and ongoing approach to “scouting” opponents and preparing for matches. The process involved tracking down and analyzing opponents’ in-game profiles and match-histories as early as an entire week in advance. And due to certain constraints of Overwatch’s in-game database, Oak frequently had to seek out and navigate various third-party websites—such as the now defunct MasterOverwatch.com—to complete his initial research. He would then compile those findings and share them with his teammates and other respected club members in the hopes of collaboratively developing game- 87 plans and counterstrategies for the upcoming match (see Figure 4.1). I was struck by how seriously team members would take Oak’s weekly “homework assignment.” Recalling Rogoff

(2003, 2014), they read and studied the scouting reports with “keen, wide attention” in anticipation of ultimately making their own unique contribution to the team’s strategic game- plan. When match-day eventually arrived, players proved eager to reference the reports, workshop possible solutions, and offer practical advice.

As the following transcript—taken from a pre-match, online voice-discussion— demonstrates, the D2 team relied heavily on scouting to simultaneously transform gameplay, manage expectations, and build confidence:

Oak: [Their “Grandmaster” player] is their DPS, so—

Brock: (suddenly joining the call) —are you guys playin’ yet?

Multiple People: No.

Oak: We haven’t started yet.

Brock: OK. I’m going to watch you for a little bit [on Twitch], then I have to start driving back to [campus]. Good luck guys.

Oak: Yay!

Blaine: Thanks.

Brock: (leaves the call)

Sarah: OK, remember guys, just try your hardest to kill TrueBizzaro.

Multiple People: (nervous laughter)

Kevin: Hey man, if I’m playing D.Va… and he’s a Pharah? That’s—that’s reasonable—

Blaine: —well the problem is [that] he also plays—

Oak: —a lot of other DPS.

Blaine: —fucking everything but Genji, Junkrat, [and] Widow.

Surge: If we have a Zen[yatta], just always have “discord [orb]” on him…

Oak: OK.

Surge: …unless called out otherwise. But we just want to eliminate him from the fight as much as possible. I think he can probably beat anyone of us “one on one” if we don’t team-up against him.

Sarah: Yeah, we gotta gangbang him.

Kevin: We gotta do what every [Overwatch League] team does against Jjonak, where everyone just—

Surge: —targets him.

Kevin: —gets in on him. Yeah.

Oak: Yeah.

Surge: That’s how Boston beat [New York].

Kevin: That’s how Houston almost beat them, [too]. Like, they just got on Jjonak.

(Captured April 15th, 2018)

Oak opens the conversation by drawing attention to the rank and role of the opposing team’s strongest player—as identified in a scouting report. However, before the team can formulate its plan of attack, they are briefly interrupted by a fellow club member, Brock. This type of interruption was common and not entirely unwelcomed. At the time of this recording, Brock was a senior club member who loved lending his experience, expertise, and support to novice players. When he was not playing or coaching for his own team, Brock would watch and analyze the D2 team’s matches as they were livestreamed on Twitch. And while Brock’s interruption does not directly inform my present discussion on scouting, I include and mention it 89 here because it is representative of the observing and pitching-in that would so often occur across teams and skill-levels within the club.

When Brock exits, Sarah quickly refocuses attention on the matter at hand—preparing a strategy to combat “TrueBizzaro.” The team’s nervous laughter is a telling concession that, as

Surge later elucidates, TrueBizzaro “can probably beat anyone of us ‘one on one.’” Kevin, sensing that his team’s confidence is shaken, attempts to offer some solace, noting that “if I’m playing D.Va… and [TrueBizzaro]’s a Pharah,” the team should have a rather favorable matchup on paper. However, in turn, Blaine references more information on the scouting report, noting that TrueBizzaro actually plays a variety of different heroes at a high level; so the team won’t necessarily be able to take advantage of that particular character matchup. Surge offers up another possible solution, suggesting that, “if we have a Zen[yatta], just always have ‘discord

[orb]’ on [TrueBizzaro].” It is a “blink and you’ll miss it” moment, but Surge’s statement here is the critical piece missing from the team’s strategic puzzle. Unlike Kevin’s conditional solution,

Surge instead provides one that is entirely within his team’s control—so long as someone on the team agrees to use the hero, Zenyatta. Oak, the most likely candidate for the job, immediately says “OK” in support and acknowledgement of Surge’s plan. Oak’s stamp of approval thus sets off a chain reaction of excited chatter from teammates who further build on the idea, from

Sarah’s crude but hilarious “we gotta gangbang him” to Kevin’s allusion to similar strategies employed by professional Overwatch teams. Not only did the D2 team now have a concrete plan, but they also seemingly found the confidence to execute it.

As time went on, Oak became increasingly creative and detail-oriented in his scouting practices. In a follow-up interview, he explained to me how—in addition to profile-checking opponents—he would regularly search Twitch and YouTube for the opposing team’s VoDs. This 90 process not only provided context to data uncovered through profile-checking, but it also allowed

Oak to observe precisely how teams would utilize certain strategies during competition. He recalls his process saying:

As I scrubbed through their videos, I would watch for changes in their [team] compositions. And I would record it in [a spreadsheet] as a “hero swap.” And as you would go through the entire match […], you’d actually be creating a weighted average. So you can actually pull together what compositions teams liked to run any given week. And you can pull that together and not only look now at an overall “what do they like to run,” but you could also […] filter by map, filter by hero, […] and correlate that to their win-rate. (Individual Interview, Oak, March 30th, 2020)

For Oak, scouting his opponents this thoroughly was important become it helped him make decisions about how his own team should prepare leading up to matchday. He lamented the fact that his D2 team did not get many opportunities to meet online and practice during the week; so when those practices did occur, Oak wanted to make the best use of everyone’s limited time.

Most weekends, the D2 team was scheduled to play two tournament matches. Unfortunately, preparing equally for both matches was not always a realistic scenario. However, thanks to

Oak’s meticulous scouting, the D2 team was able to dedicate its time, energy, and resources to more competitive matchups while ignoring the potentially lopsided ones. While this strategy did not necessarily help Oak’s team beat the highest rated of opponents, it did gave his team comparatively better odds against opponents of equal skill-level.

Although Oak certainly led the club with his scouting prowess, other members were also keenly aware of the benefits that researching one’s opponents could provide. Most interestingly,

Koga—the serious and demanding manager of the 2019-20 D1 team—was quick to reprimand his players for sharing and posting publicly-available VoDs on Twitch and YouTube. Koga recognized that other teams could easily have a cunning coach or player like Oak on their rosters as well, and, in turn, he wanted to deny such teams the corresponding advantages. In this 91 manner, the club willingly and enthusiastically engaged in “Spy vs. Spy” tactics reminiscent of

“sign stealing” in Major League Baseball. Through their attitudes and practices, Oak and Koga thus demonstrated that collegiate Overwatch—as a competitive endeavor—was not something that could easily be bound by the time or space of its gameplay. Rather, Overwatch represented an ongoing journey that constantly tested its players’ wit and mettle in surprising ways. And as researchers, it once again reminds us that we must continually expand our arsenal of data- collection tools and methods if we are to truly understand the gaming cultures we claim to study.

Storytelling

In the previous section, I showcased a lengthy transcript that was laden with esoteric historical and cultural references. I tried my best to unpack its contents, but I still recognize that it would be a challenging read for any community outsider. However, its arcane nature is precisely why I want to briefly refer back to it now as a way to introduce my next key finding.

In the D2 team’s discussion about TrueBizzaro, Kevin closed with an allusion to professional

Overwatch. Specifically, he remarked that “that’s how Houston almost beat them.” On the surface, this seems like a rather trivial extension of Surge’s previous statement that “that’s how

Boston beat [New York].” What is important to note here is Kevin’s emphasis on the word

“Houston.” In 2018, the Houston Outlaws were not just any professional Overwatch League team; they were a comedically average team that struggled even against weaker competition.

They were the antithesis of powerhouse teams like the Boston Uprising and the New York

Excelsior—which were successful, well-oiled machines by comparison. Kevin’s teammates—as fellow fans and players—would be intimately familiar with these facts. By calling attention to the colossal skill-gap between Houston and New York, Kevin thus utilized a shared reference to help hype up his teammates. After all, if Houston could have success employing a specific 92 strategy against a superior New York, then surely the D2 team would be able to leverage similar tactics against TrueBizzaro’s team, right? As it turned out, these types of shared references represented one of the central ways in which club members related to and participated with one another. However, for as in sync as their community typically was, communication breakdowns were still a common occurrence. And when members sensed that an important reference was not shared between them, they instinctively turned to classic and “dramatic” storytelling approaches in attempts to eliminate any confusion and to bring everyone into the discussion (Rogoff, 2003,

2014).

Since so many of the club members were hardworking, involved students, they could not always attend meetings, practices, or matches. In these cases, it fell to their friends and teammates to fill the absentees in on what they missed. During one particular mid-week “scrim,” the D2 team attempted to integrate a fairly new club member—Lance—into their competitive roster. However, due to Lance’s unfamiliarity with his new teammates, their strategies, their strengths, and their weaknesses, Blaine took it upon himself to catch Lance up to speed on the

D2 team’s recent “Junkertown” woes:

Figure 4.2: Junkertown is a notoriously unforgiving map in Overwatch. Its unique design often forces players to experiment with and implement unconventional strategies. As such, the D2 team struggled to find success on the map throughout its 2018 spring season.

Kevin: I’d like to play the “Junkertown” map again. Just so we’re—

Oak: —Work on it.

Kevin: —we can try a comp that is built around it.

Oak: Yeah.

Lance: Oh, Junkertown would be fun! It’s usually a toss-up.

Kevin: I hate Junkertown. But we need to get good at Junkertown, you know?

Blaine: I hate that map so much.

Lance: (laughs) I mean, we could always “meme-strat” it… with Bastion.

Blaine: That’s what we did.

Kevin: (sheepishly) That’s what we did last night.

Blaine: Did you watch any of it… or did anyone tell you how things went?

Lance: No, I didn’t actually see it. But I inferred that we lost? (laughs)

Oak: Yeah.

Blaine: Yeah, so first map, they pulled “Pharmacy,” and we could just not counter. I tried going Pharah at first, and it was, like, effective at killing their ground stuff—but their Pharah was just killing fucking everything. So I went to “hitscan,” and, even with two hitscans, we couldn’t kill her fast enough and move on to everything else. So we lost Ilios real fast. We switched to…

Kevin: …Temple of Anubis, baby!

Blaine: Temple of Anubis. We lost the first point rather, but we held the second point for basically forever. We didn’t lose it; they didn’t get a single tick on it.

Lance: That’s good!

Blaine: [Then we] got to Junkertown, we attacked first—Bastion to the first point— and I don’t think we stopped moving. Because their D.Va, if I’m right, was really out of position right at the beginning; so we picked her instantly and then just pushed through all the way to the first bend inside. [We] got stalled for a little bit. I swapped off Bastion and went to Junkrat. We had Kevin on… Widow, I think?

Kevin: —Widow at first, and then I went Reinhardt for the last twenty seconds.

Blaine: Yeah. So we got it eventually inside on the second point, got it to the first curve [on the third point], got stalled, and then—in “overtime”—we pushed it all the way from that curve to point. So that put it there. [On their attack,] they started pushing, [and] they took the first point extremely easily. Then we held them inside for about two minutes, then they pushed again. We held them again for about two minutes, but then they finally got through with two minutes—a minute-thirty, I think? So we had a minute, and they had two-and-a-half minutes [for our final attacks]. We pushed it to the bridge, and they basically went “cheese-comp” and—and they did defense-Bastion against us when we did attack-Bastion, and they were just more set- up. And whenever they attacked, they just kinda had to win one fight. And that’s what happened. Umm… so yeah.

Lance: (laughs) Oh well. Well...

Oak: —Yeah. I, personally, am really proud of what we did. I think it was a massive improvement.

(Captured April 16th, 2018)

The excerpt begins with the D2 team choosing a map to play for their scrim. As I explained in chapter three, scrims were low-stakes, “friendly” matches that placed an emphasis on experimentation and practice. Not surprisingly, teams regularly chose to dedicate scrim-time to working on their perceived weaknesses. The D2 team was no exception, and, in the first few lines of their dialogue, they describe their general feelings about “Junkertown” while simultaneously expressing their desire to improve at playing on it (see Figure 4.2). This sets the stage for Lance—the team’s newest player—to learn more about his teammates’ troubled past with the map. Blaine inquires, “did you watch any of [our match from last night]… or did anyone tell you how things went?” Lance admits that he did not, signaling that the team—prior to this point—had been communicating via an unshared reference. When considering this moment through the lens of LOPI, we begin to get a better understanding of why Lance’s ignorance is so potentially threatening. After all, he is not some uninvested bystander; Lance is an up-and-coming player that is hoping to become actively involved in his local Overwatch community. Moreover, he is mere minutes away from directly participating in a scrim that will be taking place on “Junkertown.” Therefore, he needs to be aware of how his teammates have played on the map in the past if he is to effectively “transform” his own practices and best

“contribute” to the team-based endeavor at hand (Rogoff, 2003, 2014).

What then follows is Blaine’s dramatic account of the previous night’s match. Due to the excerpt’s impressive length, I will forgo “geeking out” over all the little allusions and references that are contained within its lines. However, I nevertheless want to take the time to highlight several of its overarching themes and ideas. Most notably, for this community, the depth and details truly matter. Blaine walks through the match moment-by-moment, actively inviting others to contribute when his memory proves hazy. He needs to get it right. He is not just 96 recalling a disconnected history—he is also preparing his listeners for imagined and possible futures. After all, the D2 team will play on Junkertown again. Blaine’s narrative, while entertaining, implicitly challenges the team to learn from its past failures. More specifically, his story invites newcomers like Lance to take initiative and to help brainstorm solutions to the community’s ongoing problems: such as how the team might go about developing counter strategies to “Pharmacy” or “defense-Bastion”?

While storytelling was an undeniably popular and powerful instructional tool for the club members, it also served more mundane—but equally important—social functions as well. In particular, players would regale one another with stories of their various in-game accomplishes at their weekly, in-person meetings. However, in these cases, rather than serving as just-in-time exposition to help prepare for impending challenges, it became a means to for club members to build and strengthen personal connections. Specifically, given the almost exclusively online nature of Overwatch competition, these collaborative and in-person storytelling practices allowed people to put real faces to the voices, screennames, and avatars of their fellow players.

In one such example, Oak explained to the entire club how his D2 team fared over the weekend:

Oak: For those of you that don’t know me, my name’s Oak (waves hand and turns to face audience), and I’m the captain for the D2 team. [And…] we had a really, really great day yesterday. We played our “second” match first because the other team couldn’t do the regular timeslot; so just as a courtesy to them, we schedule earlier. That was [against] Schreiner University, I believe, out of Texas. And, uhh… we smoked ‘em.

Multiple People: (laughs)

Oak: (laughing) We ran all over them—easy “2-0.” It was Ilios and then Horizon. And we more or less dominated them. [But...] even so, they were really good sports. And since we beat them in thirty minutes, we actually scrimmed them on Dorado—which would have been the next map—and we rolled them there. We held them just shy of first point.

Unidentified Club Member: (sarcastically) Could you be a little more humble, please? 97

Multiple People: (laughs and inaudible murmurs)

Oak: (laughing) No, watch the YouTube video—we rolled over them. [So…] the second game was versus the University of Calgary—so Canadians? (looks to his teammates)

Erika: Alberta, Canada.

Oak: So [anyhow,] we lost Oasis. We lost the two [points]… I know we didn’t get “University”? (looks to his teammates)

Blaine: We didn’t get [to play on] “University”—we lost the other two.

Surge: We got to 99% on both.

Oak: Yeah, we got to 99%, and they swept it from zero to a hundred both times. So it was not a good time. And then we went to Hanamura. And we just rolled through on that map as well. We finished with, like… I think it was four minutes to go? (looks to his teammates with a confused expression)

Erika: There was four minutes to [their] 1:27 or something.

Oak: Yeah, and they finished it with 1:29, and, uhh… uhh… (motions to Erika)

Erika: We got a first point hold and then [took] one “tick” to win.

Unidentified Club Member: Is she the captain? (points towards Erika)

Oak: No. I’m the actual captain, but she’s listed as [the manager]. And she was playing yesterday… so yeah. [This…] was actually the team right here (turns and motions to a group of club members). And [the researcher]… don’t forget [the researcher] in the back (motions back to the researcher). (laughing) So this was actually the team that played yesterday (motions to club members again)—so really good day.

Multiple Club Members: (clap)

(Captured October, 2018)

Figure 4.3: After telling his story at the weekly meeting, Oak (left) motions to where a particular group of club members (out of frame, right) are sitting, saying, “So this was actually the team that played yesterday” (emphasis mine).

Although this excerpt certainly bears numerous similarities to Blaine’s online account, there are some key distinctions and differences that warrant further examination. On the surface, Oak’s story is—by virtue of the in-person setting and the makeup of his audience—more performative in nature. He stands and gestures wildly as he chronicles his team’s exploits. However, rather than fixating on the minute details that were emblematic of Blaine’s story, Oak instead choses to employ hyperbolic slang to describe his team’s performance. He emphasizes that “we smoked

‘em, […] ran all over them, […] rolled over them, […and] dominated them.” Through these types of embellishments and exaggerations, Oak thus taps into competitive gaming’s long history of showmanship and machismo (Atencio & Beal, 2011; Burrill, 2008; Harper, 2013; Taylor,

2012). Interestingly, one woman in the audience even playfully calls him out on this, asking,

“could you be a little more humble, please?” For Oak and his team though, this brand of storytelling was a culturally acceptable way to establish themselves within the club’s hierarchy. 99

While not quite as skilled—on average—as the D1 roster, Oak’s D2 team nevertheless wanted to prove themselves to the rest of their peers. Sharing their stories so publicly not only allowed them to gain recognition for their online accomplishments, but it also caused their successes to feel more lasting and real. Oak’s hand gestures towards his teammates, combined with his audience’s subsequent applause, only serves to underscore these themes.

Gameplay

Callouts

Whereas moments of preparation were marked by measured speech and deep, analytical thinking, gameplay itself was rife with exclamatory outbursts and impromptu reactions.

However, buried in that shouting chaos and flurry of activity, familiar themes could be heard echoing in dramatic and emotional new ways. Specifically, during the heat of competition, players demonstrated their abilities both to communicate through and act on shared references.

Furthermore, they heavily relied on the perspectives and “callouts” of their teammates to paint an accurate, dynamic picture of their surrounding digital-battlefield (Castillo, 2019; Freeman &

Wohn, 2019; Tang et al., 2012). Recalling theories of LOPI, these tournament matches thus came to represent the ultimate “community endeavor” in which the “collaborative and flexible ensemble” came together to prove its worth (Rogoff, 2003, 2014). The following data illustrates the back and forth of a typical “team-fight” in an online match of competitive Overwatch. The

D2 team, fresh off a last-minute discussion related to their pre-game scouting, now marches their respective avatars across “Ilios” to meet their opponents. They communicate with one another verbally in Discord as the in-game action begins:

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Figure 4.4: The comic panels showcase the communications and maneuvers of the D2 team as they engage in a typical “team-fight.” The players need to listen closely for their teammates’ verbal “callouts” if they are to react fast enough to avoid danger.

The opening panels of the comic focus on the positioning battle between the two sides. Here— and throughout the entire team-fight—gaining and sharing information is key. After all, if a team understands what and where the enemy’s threats are, they will be able to adjust and counterpunch more effectively. Consequently, both Kevin and Blaine use their avatars’ abilities to propel themselves into the air and to seek out higher vantage points [2]. In turn, the grounded

Oak asks, “what do we see?” Blaine relays the bad news—the opposing team is using the devastating “Pharah-Mercy” character-combination, more affectionately known as “Pharmacy”

[4 and 5]. Lance urges his teammates to continue moving to the right, where they can temporarily regroup and barricade themselves in an abandoned shop [6]. However, despite the clever, on-the-fly adjustment, Lance recognizes that his team cannot stay holed up forever, and— as the pressure mounts—he remarks, “we’re going to have to ‘dive’ the point soon. They’re 105 gettin’ a lot of real estate” [8]. What follows is a particularly revealing sequence that showcases both a communication breakdown and its subsequent repair. Kevin announces that he is “going on their Widow,” but he fails to specify where his target is until after he has already leapt into the fray. To compound matters, he only provides the vague callout of “topside,” which could refer to as many as four different locations on the map. Erika cannot orientate herself fast enough to support his engage, saying, “I lost you” [9 and 10]. Simultaneously, the researcher—still unsure of the enemy Widowmaker’s exact position—wanders directly into her line-of-fire and is promptly eliminated [11 and 12]. And within two seconds of Kevin’s botched callout, the D2 team’s attack is completely compromised. Fortunately, Oak eventually notices the bullet-trail from Widowmaker’s sniper rifle and specifies that “[she’s] on top of the lighthouse.” With the original “callout” now corrected, the team is finally able to pinpoint Widowmaker’s position and neutralize her [13 and 14].

Win, lose, or draw, the D2 team’s intense gameplay provides compelling insights into why and how the “collaborative and flexible ensemble” of collegiate esports works. In the span of just thirty-two seconds, every team member—from the novice substitute, Erika, to the hardened veteran, Lance—made multiple, meaningful contributions to their endeavor. I tried my best to illustrate those interactions, conversations, and movements through the above comic panels (Figure 4.4); however, I realize that competitive Overwatch—even for the most experienced of players—can be frustratingly difficult to follow. If any readers felt confused or disoriented when attempting to parse my data, know that you are not alone. In fact, the participants themselves often reported feeling those very same emotions. In a separate interview with one of the club’s most elite players, Roger explains his personal struggles with listening to, shouting out, and properly responding to in-game “calls:” 106

[You have to prioritize] the biggest threat—whatever is gonna kill you faster probably. So, for example, if there’s a “Pharmacy” in the sky, right? She’s “pocketed.” Do we want to focus her? Or do we want to focus the Reaper that’s clearly going to teleport behind us and “[Death] Blossom” in a second here. It’s kinda hard.

This is actually when my roommate gets really mad at me because I used to be really loud [during gameplay]. Like, I’m really loud. When I’m “calling,” I’m yelling… because there’s six [teammates], and they’re all calling different stuff. So everyone’s saying “there’s Pharmacy in the sky,” right? And if I see the Reaper’s going to teleport behind us—and I know he has “Blossom”—I’m going to have to be super loud [to be heard]. That’s the difficulty.

To an untrained ear, I know [our communication] sounds weird—like, [it seems like we’re] just “comm-ing” all over the place. But if you actually listen to pro “comms,” that’s literally what they do as well.

[…And] the difference in learning “what actually matters” comes with experience, I think. Cause if you walk into a “team-fight,” and you want to “combo” [abilities with a teammate]? [For example,] take me and Scott. Obviously, it’s still a work-in-progress, but I have a feel for his playstyle. So I kinda feel when he’s going to get aggressive, when he’s going to pull back, when he’s going to try to do a “Bomb-Shatter” combo. And that sometimes even goes without comms, if you know what I mean? He might just say, “I’m going to ‘Bomb’ now,” and I’m like, “alright.” Then I’ll just wait [to see] the bomb explode, and then I’ll “Shatter.” But if I was playing with a new off-tank? I would need him to give me a more [clear] idea of what he’s doing. But because [Scott and I] have played with each other for a good amount of time now, a lot of comms go without saying. (Individual Interview, Roger, April 10th, 2020)

Throughout his monologue, Roger reiterates that in-game communication is “hard”—so much so that his struggles have transcended the online game-space and have even caused friction between him and his college roommate. And while there are obvious, tactical benefits in every teammate contributing to “comms,” Roger also implies there is still a limit to how much information the brain can reasonably process. On the surface, this challenge simply led Roger to yell into his microphone more loudly than either he or his roommate would have liked. More interestingly though, Roger theorizes how—with enough “experience”—a general “feeling” between teammates might work to reduce verbal clutter. In particular, he describes the near-telepathic bond he that he started to form with his teammate, Scott. Since the two played together so 107 frequently, Roger claims that they were able to develop their own shorthand, which ultimately enabled them to coordinate and combo abilities more efficiently (Castillo, 2019). With these lines, Roger thus ties together “shared references” and the “nonverbal” to express how the communication of competitive Overwatch teams is equal parts spoken, heard, observed, and felt

(Rogoff, 2003, 2014).

In this discussion of how participation occurs during online gameplay, I focused on communication as it relates to Overwatch’s fundamental mechanics. In other words, I tried to illustrate precisely how players went about completing match-specific tasks, such as assaulting the “point,” combating an enemy Widowmaker, or “combo-ing” their powerful abilities together.

However, Roger’s speech points towards something more natal and nebulous—the camaraderie that develops amongst players and the subsequent ways in which it works to transform their practice (Castillo, 2019; Engerman, 2016; Macedo & Falcão, 2020; Taylor, 2012). And although

I initially scoffed at the idea of retreading such old ground in my own dissertation, the club members’ unique trust-building practices—especially when contrasted against the well- documented toxicity of a more global gaming culture—could not be ignored. In the following section, I will extend my present discussion to highlight the ways in which participants supplied one another positive feedback and collectively worked to foster a sense of belonging.

Emotional Calibration

In the wider esports community, jaded players use a rather tongue-in-cheek adage to warn bright-eyed newcomers about the Overwatch experience: “although the game is advertised as

6v6, prepare yourself to compete 1v11” (paraphrased). The implication is, of course, that players will spend equal time and energy dealing with their teammates’ egos as they will fighting virtual gun-battles with their opponents. While the Overwatch community at Penn State was not 108 without its flaws, the club was overwhelmingly more helpful, welcoming, and accommodating than it was antagonistic. Its players expressed genuine excitement when their teammates succeeded, and they tried to offer sincere sympathy and advice when witness to failure.

Moreover, they allowed the natural ebb and flow of gameplay to transform their interactions in powerful and dynamic ways. As such, players constantly found themselves calibrating and re- calibrating their own excitement and energy levels to match those of their teammates. Like the skateboarding sessions at the center of Hollett and Hein’s (2019) study, Overwatch matches had a similar capacity to “create felt-intensities, collective experiences that accrue and congeal over time for those participating, both actively and passively” (p. 12). And at no point was that energy more palpable and infectious than in the closing seconds of competition.

What follows are two related excerpts from one of the D1 team’s very first matches together. While I listened in on their Discord conversation and followed the action using

Overwatch’s in-game spectatorship tools, the match was simultaneously livestreamed on Twitch by “Boise State Esports.” This is an important detail because the freshly-assembled D1 team was eager to prove itself to the wider Overwatch community; they were also interested in seeing how Twitch “casters” might respond to and critique their gameplay. We now pick up the action as the in-game clock ticks down to zero and enters “overtime”:

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Figure 4.5: The comic panels illustrates how the D1 team frantically and emotionally supports one another in the closing seconds of a match.

Compared to more tactical—callout-oriented—approaches to gameplay, the D1 players lean into the moment and allow themselves to be swept up in the “hype” of their teammates. Callouts still 114 occur, but they are now buttressed by positive reinforcement and feedback that manifests in the form of excited cheers, compliments, and expletives. Daewon uses a timely ability to great effect, and Brock immediately recognizes that contribution by shouting, “Good! Nice ‘Beat’!”

[3]. Likewise, Adam unleashes a devastating “EMP,” eliciting shouts of “big, big, big!” and

“huge, huge, huge!” from approving teammates [9 and 10]. As the tide of battle slowly starts to turn in their team’s favor, Stan motivates the others with assertions of “we can do this, we can do this!” [10]. And when the game concludes, there is a final release of energy culminating in

Daewon’s exhausted, but satisfied, “holy fucking shit” [15].

Upon entering the downtime between matches, the D1 team exhibited an uncanny ability to channel and re-experience those “felt-intensities,” transforming and repurposing them in an ongoing effort to keep morale high. To these ends, the players would often unite in celebration around one another’s in-game exploits. In one such example—illustrated by the following panels—the team tries to reassure an uncharacteristically sullen Adam that his individual contributions were instrumental to the group’s success. The players’ interactions are thus shown to extend and evolve in the moments following their victory:

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Figure 4.6: The victorious D1 team re-watches the end of their match together. Now with access to new perspectives of the action, they come to a better understanding of why and how they were able to secure the win.

Beginning with the team’s collective viewing of Brock’s “Play of the Game,” the participants are quick to shower one another with praises [1]. Stan and Joe even go as far as to suggest that

Brock’s “tracking” is so good that it resembles an “aimbot” [6]. However, the key moment occurs when Adam—despite the victory—suggests that his gameplay did not quite live up to the groups’ standards. Brock immediately intercedes, pushing back against Adam’s claims and arguing that, “your hacking was sooo good though” [9]. Stan and Daewon build on this idea, stressing that Adam’s play was “perfect” [9]. And their excitement only intensifies as they re- watch their game-winning fight on the “Boise State Esports” livestream. Brock and Stan—now with access to their opponents’ perspective of the action—realize just how “perfect” Adam’s

“EMP” truly was. Stan can hardly believe his eyes, exclaiming “you hacked the Moira ult?!

Holy shit!” in adulation [12]. 119

As I alluded to at the start of this section, the club members—on the whole—were naturally supportive and protective of their teammates. That said, many players also felt that there was a strong correlation between their team’s mental state and its in-game performance. So while the majority of their positive energy was indeed genuine, players nevertheless had a competitive interest in maintaining everyone’s happiness. In a separate interview, Scott—a member of the 2019-20 iteration of the D1 team—explains how and why he took it upon himself to act as a mediator during gameplay:

For me, I honestly think of myself as—I don’t know—the positivity ambassador on the team. I try to be the least “mentally boom-able” person on the team. If we lose a fight or lose a map or whatever, I try to be the one who’s like, “don’t worry about it, let’s move on.” Cause—I don’t know—some people on the team can get frustrated. And when people are frustrated, certain people will just check out and stop communicating as much as they would normally. And like I said, communication is everything; so once you’re missing that communication, [it’s over].

Like, if our support player is frustrated because someone said he made a mistake in the last fight… in this [current] fight he [might] not call that he needs help in the back. But I need him to call that out so I know to go help him, you know? And that can be the most frustrating part of being on a team… people can get “boomed” like that. So rather than blaming them for being frustrated, I try to be a good example for positivity. (Individual Interview, Scott, April 10th, 2020)

In these lines, Scott deftly traces the relationship between effective communication, a positive attitude, and a team’s in-game success. More specifically, he identifies “frustration” as the leading threat to undermine the “felt-intensities” of collaborative gameplay. As Scott succinctly explains, “if people are frustrated, [they] will just check out. [And] once you’re missing that communication, [it’s over].” His teammate—Leon—later echoed these sentiments, confessing how:

[In the past,] I kinda “flamed” a lot—not going to lie. I would just “educate” my team, if you know what I mean? But I’ve stopped flaming teammates during games—or [rather] I just stopped flaming in general because you don’t want to “tilt” your own teammates. 120

You don’t want to make them mad, because then they’ll just want to lose to spite you. (Individual Interview, Leon, April 11th, 2020)

With his closing statement, Leon brings us full circle—back to the cautionary adage that introduced this section. These club members universally dreaded the prospect of their friends and teammates suddenly turning against them when it mattered most—during the gameplay of high-stakes Overwatch matches. Consequently, they took a variety of preventative measures to ensure that none of their teammates would ever become so “mentally boomed.” Whether they were complimenting a good play, consoling a dejected teammate, or acting as the unofficial

“positivity ambassadors,” club members thus calibrated their emotions to meet the needs and match the intensities of their fellow players.

Review

Self-Reflection

Although club members tried to avoid engaging in critiques during gameplay, they became far more receptive to constructive criticism after the “felt-intensities” of matchday had subsided. And since the club’s gameplay was regularly livestreamed and recorded on Twitch, its players almost always had the ability to re-watch and re-experience the chaos of matchday in the coming week. Specifically, through both individual and communal “VoD review” practices, club members turned analytical eyes towards their gameplay in an ongoing effort to recognize mistakes and identify weaknesses (Gerber, 2017). The most common of these practices involved sharing VoDs through the community Discord channel and providing corresponding, text-based feedback. While designated “coaches” typically took the lead, all players were invited to “take initiative” and “pitch-in” during the weekly review-process (Rogoff, 2003, 2014). As the 121 following Discord screenshot illustrates, some players even felt comfortable giving one another mini “homework” assignments to reinforce key concepts:

Figure 4.7: A club member uses the community Discord’s dedicated “Feedback” channel to record and share his thoughts.

Here, part-time coach, Ewing, requests that his players individually review gameplay of the previous night’s match. He directs them to focus on the particular maps where the team struggled, and he cites “positioning” and “coordination” as the biggest culprits. Although Ewing recognizes that his players are all capable of reviewing the VoDs on their own, he nevertheless offers to “go over a specific POV for you […since] an outside perspective [can] always help.”

Ewing thus taps into the tradition of apprenticeship-learning that has been emblematic of esports culture for over a decade (Hein & Engerman, 2016; Gerber, 2017; Richard et al., 2018).

Furthermore, in his second paragraph, he even ties his current criticisms back to Scott’s understanding of the relationship between “positivity” and effective “communication.”

Channeling Scott, Ewing explains that when “you try to talk through [mistakes] aloud [during gameplay…,] it causes confusion.” Finally, Ewing concludes by putting a positive spin on the entire situation, remarking that “even if you didn’t win, it’s a learning experience. If you 122 constantly roll them, you get complacent.” This attitude was echoed by various other club members over the course of my investigation: so long as the review process was taken seriously, players often felt that there was more to learn in defeat than in victory.

Although many of the club members would habitually reflect on their own gameplay throughout the week, they would also occasionally schedule and participate in more formal, collaborative review-sessions. During these meetings, players would engage in the synchronous observation of their pre-recorded gameplay. As they collectively watched and analyzed the footage, they regularly asked one another questions, pointed out key moments, and workshopped long-term solutions. The following Discord conversation thus reveals how club members would come together to reflect on their past gameplay-experiences in the hopes of transforming future participation:

Roger: I’m going to try to use “Shatter” more passively, because—something I noticed—I basically use it on “cooldown.” Once I get it, I’m instantly looking for a “Shatter.”

Koga: —Especially when they have a “Mei,” you have to be really careful! Like, what kind of space can you take without being punished?

Roger: Yeah. That’s what I was trying to work on. Like, I’m [now] starting to wait until for Rein’s shield to break—or waiting to see Mei’s cooldowns are used.

Leon: Usually you can just “charge.” Out of all the VoDs we’ve watched—and even in “ranked”—Reins literally just charge out of Mei ult.

Roger: That’s what I’ve been tryin’ to do, yeah.

Koga: Yeah, you want to try to charge out of it. But [know that] the Mei is still planning on freezing [you]. You know how the “freeze system” works, right?

Captured February 19th, 2020

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Figure 4.8: The character “Mei” uses her ultimate ability to freeze nearby opponents. During the spring of 2020, Mei wreaked havoc in Overwatch tournaments and forced many teams to completely change their playstyles to counter her.

In these lines, Roger confides in his team that he has been dissatisfied with his “Shatter” usage during their matches. He comments that it is “something [he has] noticed” about his own gameplay and is something that he is “trying to work on.” Leon and Koga then pitch in suggestions about possibly using the “charge” ability to retreat and reposition, at once referencing past VoD-reviews and aligning with Roger’s desire to play “more passively.”

Unfortunately, with Overwatch, nothing is ever quite that simple. Koga cautions that—even with those suggestions—an enemy “Mei” can still pose problems. And by concluding this exchange with a check-for-understanding, Koga takes an additional step to ensure that his teammates know how to respond to such threats in the future (see Figure 4.8).

While self and group-reflections proved to be effective, rigorous ways for club members to hold themselves accountable and gradually improve their skills, these practices could also serve to motivate, inspire, and reminisce. Many players reported experiencing “hype” or excitement upon re-watching past highlights of their gameplay. Interestingly though, these feelings were most acute when the replays were viewed from new or different perspectives— such as from an overhead angle or through the eyes of an opponent. This notion recalls how 124 skateboarders and action-sports photographers would rekindle the “felt-intensities” of a session by capturing and “transducing” its energy into another medium (Hollett & Hein, 2019). We saw a glimpse of this phenomena in the previous section, with Brock and Stan excitedly “tabbing out” of their match to check-in on its corresponding Twitch broadcast. However, an even more compelling example emerged as the D2 team participated in Open Division. Unlike the more insular, collegiate events that the club was typically involved with, this prestigious tournament also featured competition from the wider esports community. Consequently, many of its matches were professionally livestreamed through official Overwatch channels on Twitch, which could easily garner several thousand online viewers. The D2 team was lucky enough to have one of its Open Division matches featured and “casted” by the popular esports personalities Jen

“LemonKiwi” Pichette and Christian “Heurix” Thomasser (see Figure 4.9). In a follow-up interview, Kevin recalls the thrill of participating in the event, of re-watching his in-game exploits, and even of connecting with his father in surprising new ways:

Figure 4.9: LemonKiwi and Huerix cast the D2 team’s Open Division match on Twitch. Hundreds of fans “chat” in the sidebar, interacting with the casters and cheering on their favorite players. Several members of Penn State’s esports club can be seen posting “WE ARE!” chants. 125

I’ve watched [the match] three times back… just because I think there’s a certain “vibe” that you get from hearing your own name in an excited way—which is a neat thing. My dad even watched that match. Like, I gave him the link to that.

The one summer when I worked in the Philly area, my dad and I went to a couple of the [Overwatch League] “watch-parties.” […So] we would go to those, and he was, like, learning the game. Like, he doesn’t know all the things, but he was able to get it to a point where he would know what’s going on—and was able to follow who was winning and losing.

[…So] I was like, “look [dad]. We’re playing this one game [that’s going to be livestreamed on Twitch.]” So I’m sitting there playing—and my phone usually sits on my desk underneath my keyboard—and I’d get texts from him while I’m playing. And he’d be like, “oh my god, that was great!” or “oh, that was so dope!” So that’s why I really wanted to go back and watch it a couple of times. Plus I knew [the casters] were being really nice about us. (Individual Interview, Kevin, March 30th, 2020)

Kevin’s account highlights how, even upon multiple re-watches, he was still able to feel the

“vibe” of a match. In particular, he draws attention to how his gameplay’s intensity was amplified and transferred by the “excited” voices of casters. Finally, his ability—through

Twitch—to share that experience with his father once again speaks to the powerfully felt-nature of esports competition. After all, although he was still “learning” the game, Kevin’s father nevertheless found himself swept up in moment and eager to participate in his own way.

Players on the 2019-2020 D1 team expressed similar sentiments. Specifically, they relished their opportunities to play with and against professional players and other high-profile

Twitch streamers during semi-randomized “matchmaking.” Like Brock, Stan and Kevin, they were especially interested in watching these professionals’ VoDs “back” after gameplay. As

Scott explains, although it was a bit of a guilty pleasure:

It’s kind of irresistible [to watch those VoDs back]. Because you want to see if anyone in “[Twitch] chat” compliments you. Like, if you hit a “Shatter” as Rein and Emongg3 is

3 Jeff “Emongg” Anderson is a former professional Overwatch player and a popular Twitch personality that is known for his positivity and his educational approach to livestreaming. Several of the club members reported looking up to him as their esports role-model. 126

playing D.Va? You want to see if anyone in his chat is like: “Ohhh! PogChamp!” or “Big shatter!” you know? Or if Emongg [himself] says, “big slam!” or something like that. Because that’s happened before—like, I’ve hit a shatter with Emongg on my team and his chat spams “big slam!”

And then I’m there like, (whispering) “holy shit, that’s awesome!” you know? Cause, I feel like a lot of people dream of being a YouTuber or a Twitch streamer… and [watching a highlight of yourself] is kind of like being that for five seconds. Like, a thousand people just saw me “carry”? That’s so cool.

But then other times I’ll see myself make mistakes, and I’m like, “please nobody in the chat say: ‘what the fuck is this guy doing?’” (Individual Interview, Scott, April 10th, 2020)

For Scott, this type of re-viewing process was about seeking positive reinforcement and recognition from unconventional sources. Whereas Kevin emphasized the important role of the casters in propagating and perpetuating the “felt-intensities” of gameplay, Scott instead fixates on the unheard roar of “Twitch chat,” even looking to it for short-term validation and support.

And given the anonymous nature of “chatting,” Scott certainly plays a dangerous game here.

However, in engaging with chat in this manner, he also necessarily challenges our understanding of how participatory online-spectatorship works (Cheung & Huang, 2011; Taylor, 2012).

Finally, embedded in Scott’s response is a profound reverence and deep appreciation of professional Overwatch. While not all the club members were skilled enough to play with and against the likes of Emongg in their own online matches, nearly everyone reported watching and learning from professionals or popular streamers in some capacity. In the next section, I will turn from a discussion of how club members looked inward to describe how they sought out and accessed expert perspectives.

Looking to the Pros

As an English teacher, I am sometimes expected to be a steward of the “literary canon,” the body of influential texts that—as Matthew Arnold might say—represent the “the best which 127 has been thought and said in the world.” And while there is rightfully great debate and anxiety amongst academics regarding just which works and authors should be considered “best”

(Applebee, 1992; Medina, 2014; Guillory, 2013), there was considerably less disagreement between the club members at Penn State. Of course, I am now no longer talking about a literary canon, but rather about the collection of “pros” and streamers that were championed as the creators of the most entertaining and useful Overwatch “content.” In this section, I thus lean on my participants’ experiences with Twitch and the Overwatch League to share their “canon of esports” and to describe the instructional value that it provided.

Just as the club teams would rely on scouting and profile-checking to help formulate their pre-game strategies, they would also regularly allude to the players, tactics, and moments from professional Overwatch League matches to further transform their participation. The following excerpt thus showcases this “canon of esports” at work. Specifically, the D2 team coordinates through the Overwatch League—as a shared reference—in their “collective endeavor” of gameplay (Rogoff, 2003, 2014). As the match prepares to start, the players discuss if they should make any last-minute adjustments to their hero “composition”:

Kevin: Do you want to do “Reaper-Mei” for Village?

Oak: We’re on Sanctum.

Lance: Oh… should we do the Dallas Fuel comp?

Kevin: Yeah, on Village.

Researcher: I don’t know that we should do anything that involves the Dallas Fuel.

Kevin (laughing): Hey, the one thing the Dallas Fuel does well is “Reaper-Mei” on Village… the one thing!

Lance (laughing): They’re good at one comp, and that’s all. 128

Kevin: That’s the one square kilometer that they’re good at.... not even a square kilometer really.

Lance: Yeah, but they also have Seagull to play Hanzo—

Kevin: There was that one game on “King’s Row” that Carpe played Hanzo.

Oak: Yeah.

Surge: Yeah, actually a lot of [Overwatch League] teams have been going “Hanzo-Widow” for the first map, just to force all [of their opponents] into a corner.

Lance: I also saw that TviQ used Mei to—

Blaine: —when he used the wall to climb on the point?

Surge: —yeah, right on the point.

Lance: Yeah.

Captured April 23rd, 2018

In this exchange, the D2 team deploys community language and shorthand to an effort to convey complex ideas in more efficient ways. Kevin initiates by asking his teammates if they would like to use the character-combination of “Reaper” and “Mei” when the map transitions to “Village.”

Lance immediately acknowledges Kevin’s suggestion, identifying it even more narrowly as “the

Dallas Fuel comp” (see Figure 4.10). With this line, Lance signals that he is “in the know”— that he has been keeping up with the Overwatch League and, consequently, has acquired an intimate familiarity with the current “meta.” He is not alone. All five of his fellow teammates, including the researcher, build on Kevin’s suggestion in the subsequent lines. Some even choose to chime in by “name-dropping” other Overwatch League players like Seagull, Carpe, and TviQ

(Lebherz, 2006). And as the conversation wraps up, Lance cannot even properly finish telling a 129 story because Blaine and Surge—also having watched the professional matches over the weekend—already know what happened.

Figure 4.10: Word of the Dallas Fuel’s clever use of Reaper and Mei spreads online. Within days of the strategy’s debut, most club members were already aware of how to utilize the “comp” during gameplay.

While many of my participants casually followed the latest Overwatch League news and storylines, the club’s most competitive players watched its matches with especially critical and analytical eyes. Some even payed for a premium viewing-service known as the “Command

Center.” This tool—which was available on Twitch during the 2019 Overwatch League season—gave its users the ability to toggle between the various first-person perspectives of all twelve competing players. As such, users could customize their viewing-experiences to focus on the tiny details and interactions that interested them on more personal levels. In particular, club members frequently reported observing the matches from the point-of-views of pros that shared their in-game roles and responsibilities. Kevin, who had recently dedicated himself to learning and practicing “Widowmaker,” describes how he would use the “Command Center” when watching the Philadelphia Fusion:

I actually bought the [Commander Center] for myself, Surge, and Henry. So when [the Philadelphia Fusion] plays? I watch Carpe. I watch Carpe quite a bit, and I’ll also watch Poko… but just because he’s just fun to watch.

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But when you watch the pro players play… and seeing all the little things that they do? [Like] jumping every time you go to “scope” as Widowmaker. I don’t know if you know about that trick. If you’re in cover, and you want to “peak” somebody? Usually you want to hop a little bit before you’re visible to them; so that way your head’s not horizontal while you’re [simultaneously] powering your shot. So usually by the time you land, you’ll have a fully-powered shot.

You’ll see the pros do that a lot. And just watching and picking up those little things [is important]. Taking notes helps, too. (Individual Interview, Kevin, March 30th, 2020)

For Kevin, the affordances of the Commander Center allowed him to see through the professional eyes of Carpe—one of the Overwatch League’s most prolific Widowmaker players.

With access to this new perspective, he felt he was able to “pick up those little things” that—in practice—add up to have a big impact on one’s gameplay. And in this case, he describes

“picking up” on the most efficient way to “peak” opponents as Widowmaker.

Kevin closes with an allusion to his note-taking practices, a concept that Roger would seize and elaborate on a related interview. However, where Kevin leveraged Carpe’s individual perspective to learn more about the intricacies of playing Widowmaker, Roger adopted a far more holistic approach. Specifically, he described how he watched and listened along as former

Dallas Fuel and Team Canada coach—Jayne—analyzed one of the most famous Overwatch matches ever played:

I first found Jayne—and I don’t remember how “big” he was when I found him—but I found his YouTube channel. And he had all these VoD reviews [on his channel]… but the one that really struck me the most was the one—like, I heard the [Kongdoo Panthera vs. Runaway] game was really good. And it’s an eight-hour VoD review going through the whole thing.

And I was like, “if this doesn’t make me good, I don’t know what will.” I made sure— instead of writing it down in, like, a “Google Doc” or something like that—I actually had a notebook. And I was writing notes; I had a little sharpie, and I was highlighting stuff about “rotations” and what not. Like, “Lijiang Tower” took me the longest time—cause I was pausing the video, and I was highlighting stuff, and I was writing stuff down. So it was probably more than eight hours.

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That was—that was the start of the “GOATS” meta. I think that was the biggest tournament? Because the North American Contenders team, GOATS, created [and named the strategy]. And they kind of slapped people around with it. And I think Overwatch League teams couldn’t really pick it up, but the Korean players who were still in Contenders could. So that’s when Kongdoo Panthera and Runaway picked it up, and they were really good with it. […] So honestly, just watching them play and understanding the “main tank” role—like, I would say, watching [Runaway’s] Bumper play? I was like, “I understand this.”

I started exploding up the “ladder” after that. […] That VoD review really helped me understand the game. (Individual Interview, Roger, April 10th, 2020)

Roger begins by explaining how he originally discovered Jayne’s content on YouTube, hinting that the coach has since become a “big” name in esports circles. He continues, mentioning that he chose to watch this particular VoD-review because he “heard the [Kongdoo Panthera vs.

Runaway] game was really good.” Here, Roger demonstrates his awareness of the “esports canon” and implicitly laments his perceived gap in knowledge. And despite the review’s eight- hour length, he was determined to become informed.

In chapter three, I described how “school-like” the club’s in-person weekly-meetings could be. Roger taps into that tradition as he moves to describe his note-taking practices. He also shows tremendous faith in the reviewing process, recalling his feeling that “if this doesn’t make me good, I don’t know what will.” This notion ties to club’s successes with similar reflective practices and to esports culture’s deep-seated obsession with “watching to learn”

(Taylor, 2012). However, Roger pushes the envelope even further, describing how he used a physical notebook, sharpie, and highlighter to help reinforce and internalize key concepts.

Finally, he concludes with a second allusion to the “esports canon” by recounting the convoluted history of the “GOATS” meta. This is an interesting moment because it hints at the dual benefits of following the professional Overwatch scene. On the surface, and as players like Kevin and

Roger repeatedly claimed, watching the pros “really helped [them] understand the game.” On a 132 more affective level though, studying the game’s history and central figures allowed club members to develop a powerful connection—across space and time—with the wider Overwatch community. After all, Emongg, Carpe, Jayne, and Bumper were not simply esports celebrities; they became distance educators who—whether they knew it or not—apprenticed club members as they made their own transitions from novices to experts.

While Kevin and Roger described some of the more unique approaches to engaging with professional Overwatch, the rest of the club was not so easily outdone. During the 2018-2019 school year, Brock—the club’s acting division-head—concluded many of his in-person meetings by featuring a “Streamer of the Week.” Specifically, he would display Twitch clips and YouTube videos on the classroom projector-screen to help the uninitiated familiarize themselves with professional Overwatch’s biggest personalities and most talented players. In this manner, he worked to transform the nebulous idea of an “esports canon” into a more tangible curriculum.

Thus, recalling how important shared-references are to communication before and during gameplay, Brock laid a foundation so that even the most casual of club members could meaningfully pitch-in and respond to discussion. With that in mind, I now turn from a fine-grain examination of how club members prepared, played, and reflected to consider the overarching themes that defined their participation. In the following section, I pull back the lens to explore precisely what it means to be a member of an “observational and analytical gaming ecology.”

A Culture of Leveraging Perspectives: An Observational and Analytical Gaming Ecology

Koga: Alright, let me just ask you… what do you think the biggest issue with the team is right now?

Scott: Who—who’s he asking?

Leon: Everyone. 133

Koga: Like, everyone.

Roger: Communication.

Leon: Yeah, communication.

Roger: Like, general, like… not everyone’s on the same page.

Leon: Yeah, yeah…

Scott: Yeah, I would just say like trust slash listening to each other slash communication.

Monte: Everyone needs to pitch in.

Captured February 19th, 2020

In this section, I trace the major themes that run through my data and tie them to the literature in my ongoing effort to describe and advance a theory of observational and analytical gaming ecologies (OAGEs). Specifically, I continue to build on research that examines how collaborative learning occurs amongst players during high-stakes competition (Richard,

McKinley, & Ashley, 2018). By considering a wider range of collegiate-esports experiences, I emphasize the “always on” nature of their communities while simultaneously showcasing the multitude of ways in which club members could legitimately contribute to collective endeavors.

Theirs was a culture of leveraging perspectives: to observe, to analyze, and, ultimately, to transform their own participation. I now move to explore how they lived and embodied its ideals.

In this section’s introductory excerpt, Koga leads the D1 team in an online Discord meeting. The players had recently participated in a high-stakes LAN-tournament hosted by 134

Harrisburg University,4 and they were eager to analyze the weekends’ matches while also taking stock of their team’s overall progress. Koga begins by asking the open-ended question, “what do you think the biggest issue with the team is right now?” The “collaborative, flexible ensemble” quickly springs into action with Roger, Leon, Scott, and Monte all “fluidly blending” their ideas together (Rogoff, 2003, 2014). In turn, the teammates unanimously identify “communication” as their biggest issue. Monte even takes the critique an additional step, insisting that “everyone needs to pitch in” (emphasis mine). And on the surface, this seems like sound advice that also aligns with the present chapter’s findings on colligate esports-culture. Unfortunately, it simultaneously posed the group with a massive and potentially uncomfortable challenge. Their

Overwatch team has six players, but—for the first twenty minutes of the meeting—only five of them have contributed to the discussion. For as skilled as he was at the game’s mechanics, Ming was that notoriously quiet remaining teammate whose silence indirectly led to various communication breakdowns over the team’s weeks of competition together. Nevertheless,

Ming’s fellow players all seemed to recognize that—if they could just figure out how to effectively leverage his perspective—they might finally unlock their collective, full potential.

Just as Ming was the key to solving the D1 team’s communication issues, he similarly became the key for my own understanding of what it means to be part of an OAGE. As their

Discord meeting continued, the team members made a concerted effort to understand Ming’s plight, and they exhibited a selfless willingness to transform their own participation so to support his. What follows is a compelling and rather heartwarming look into how the D1 team attempted to carve out space for Ming to contribute and belong. Koga initiates the discussion by explaining

4 Harrisburg University boasts one of the leading collegiate esports programs in the country and offers athletic scholarships to many of its players. Harrisburg defeated the D1 team by a score of 3-0 in the finals of this particular LAN-tournament. 135 how “ult-checking” should work on a cohesive team; however, the conversation quickly turns to

Ming’s difficulties with communication:

Koga: So, the whole process of “ult-checking”: what to use next fight, what to react to next fight. This should be kicking-in in 20-seconds. Then the whole “ult-check” should take 10- seconds maximum.

Roger: Uh, huh.

Leon: Yeah, true.

Koga: The problem with that is that Ming’s not… as vocal as you want from a “main support.” So… that’s something I wanted to go over on how to address it.

(silence for 10 seconds)

Leon: Yeah. Ming, are you just shy or do you just not know English very well? Or you’re not comfortable speaking it?

Ming (timidly): What?

Leon: Are you just shy? Or do you not know English that well? Or are you not comfortable speaking it? Or…

Ming (barely audible): You mean, like, communication?

Leon: Yeah. Like talking right now.

Ming: It’s just… so much.

Koga: So he gets overwhelmed?

Ming: Yeah. There’s too much.

Koga: So your brain’s still trying to process what we’re saying—

Leon: I mean, even I am [overwhelmed] when there’s six people talking. It gets kinda crazy.

Ming: Yeah. When six people [are] talking…

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Koga: How fast do you think can check on ults? Like, start an ult-check?

Ming: I mean, I can do it.

Scott: I mean, I know it’s a “meme,” but actually we could all just shut the fuck up. Like, after a fight ends, we all just shut the fuck up and say “Ming check,” and then Ming’s the only one who’s allowed to talk.

Multiple People: (laughs)

Leon: Dude, pog.5

Ming (laughing): True!

Leon: Trueee, trueee!

Koga: Yeah, we could do that (types “ming check” in the Discord channel). […] So we’ll try it for a few “blocks.” And if it’s not working out, we’ll see if we can work around it.

Captured February 19th, 2020

Koga begins by building on Monte’s previous assertion that “everyone needs to pitch in.”

Specifically, he stresses the importance of “ult-checking” between team-fights, and he implies that its responsibility traditionally falls to the “main support.” As I described in an earlier chapter, Overwatch’s “main support” role is comparable to that of a “point guard” from basketball. “Main support” players position themselves so they have greater vision of the battlefield and, consequently, are expected to make useful “callouts” to help direct their more nearsighted teammates. Unfortunately, as Koga is quick to note, “Ming’s not… as vocal as you want from [the role]” and thereby creates complications that the team will have to figure out

“how to address.”

5 “Pog” is Twitch-speak for conveying general “hype” or excitement. Participants would frequently inject this kind of culture-specific rhetoric into their conversations. 137

The extended silence following Koga’s observation is especially telling. Ming is clearly expected to contribute at this point, but—for whatever reason—he seems uncomfortable to do so.

Leon, recognizing this, attempts to relieve the pressure by directly and sincerely asking Ming,

“are you just shy or do you just not know English very well? Or you’re not comfortable speaking it?” Here, the genuine empathy in Leon’s voice represents a striking departure from his more characteristically brash and sarcastic tone. Likewise, he scaffolds Ming by offering him multiple—equally acceptable—prompts from which to construct a response. And, after a bit of nudging, Ming finally reveals that the chaos of in-game communication is just “too much.”

Once again, Leon steps up and sympathizes with Ming’s situation, admitting that “even I am

[overwhelmed] when there’s six people talking.” He continues, noting that “it gets kinda crazy,” further absolving Ming of blame. Scott—now with a better understanding of Ming’s struggles— takes the opportunity to offer a practical solution, suggesting that “we [could] all just shut the fuck up and say ‘Ming-check,’ and then Ming’s the only one who’s allowed to talk.” His matter- of-fact approach draws some laughs and even an excited “true!” from Ming himself. With everyone finally in agreement, Koga concludes by metaphorically signing the “Ming-check” into law through a public, text-based reminder in their Discord channel.

However, as I now argue, the “Ming-check” was far more than one team’s clever wordplay on phrases like “ult-check” and “mic-check.” It was representative of how the esports club at Penn State internalized and embodied the seven facets of LOPI through their collaborative preparation, play, and reflection. Moreover, it showcased what made their culture’s observational and analytical practices so powerful. After all, the “Ming-check” was an implicit and self-aware confession that the D1 team—in its inability to leverage everyone’s unique perspective—was only a shadow of what it could be. The teammates instinctively 138 recognized that Ming’s perspective was an invaluable resource, and—through Scott’s suggestion of instituting the “Ming-check”—they revealed the depths to which they were willing to go to access it. Thus five players chose to transform their participation so that one felt comfortable enough to evolve his own.

I wanted to highlight and describe the “Ming-check” here because it neatly encapsulates so many of the major themes that run through my data. It also serves a final way to help contextualize my findings while simultaneously doubling as an entry point to theorize about the unique properties of OAGEs. Beginning with their scouting habits, club members scoured the corners of the internet for insight on their opponents’ strengths and weaknesses. They engaged in dramatic storytelling practices to establish shared-references and to gain recognition for their in-game accomplishments. During competition, club members communicated with precise language and often relied on fellow teammates to become their eyes and ears. They kept morale high by offering supportive feedback and by perpetuating “felt-intensities” through excited outbursts and praise. Upon reflection, they brought observational and analytical lenses to bear on the intricacies of both their individual gameplay and their collective teamwork. When in doubt, they turned to the “esports canon” to watch quality models at work and to listen to the wisdom of seasoned coaches. And the “Ming-check” provides a final, poignant illustration of how important leveraging peripheral perspectives were to the club’s overall growth and development. To these ends, tools like Twitch, YouTube, and Discord became the glue that simultaneously held the ecology together and connected it to the wider Overwatch community.

What is an OAGE? It is an oasis settlement in the vast, networked landscape of competitive gaming. It is a “set of contexts” in which players of shared interests and shared goals come together to share perspectives (Barron, 2004, 2006). Those perspectives—once 139 assembled—are then utilized to observe, analyze, and, ultimately transform the group’s participation. Through the club’s Overwatch division, I studied just one of the many OAGEs that called “Penn State Esports” its home. I hope that—through the presentation of my data—I was able to showcase their unique, informal learning-practices in clear and compelling ways. I hope that I did their story justice.

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CHAPTER 5: DISCUSSION AND IMPLICATIONS

In this dissertation, I adopted a “connective, ethnographic” approach to help tell the story of a collegiate esports club. (Hine, 2000, 2008; Leander, 2008). More specifically, I traced my participants’ interactions and relationships across a variety of in-person and virtual contexts to better understand how they came together to contribute to shared endeavors. I even took opportunities to participate alongside select club members as they prepared for, played in, and reflected upon their weekly tournament matches. Informed and guided by Jordan and

Henderson’s (1995) understanding of “Interaction Analysis,” I thus collected and parsed “new and strange” types of data—including Overwatch gameplay, Twitch livestreams, and Discord conversations. I then leaned on theories of LOPI as I unpacked and presented that data to best illustrate why and how club members leveraged perspectives to “transform their participation”

(Rogoff, 2003, 2014). In this chapter, I continue to pull back the lens. First, I aim to summarize and contextualize this study’s findings by returning to answer its guiding research questions.

Second, I discuss how those findings might extend theories of LOPI while simultaneously contributing to the growing body of literature on esports games, cultures, and communities.

Similarly, I will consider how my own methodological successes and failures might provide blueprints for researchers to follow as they embark on their own studies in the world of competitive gaming. Finally, I conclude by surveying the current landscape of esports culture and looking to its horizon. I wonder what participation in OAGEs reveals about the collaborative-learning that takes place in more formal, educational settings; I consider what practices such as the “Ming-check” might look like in our classrooms. And to these ends, I give the final word back to my participants, allowing their experiences to lead parents, teachers, and researchers into the future. 141

Summary and Discussion of Findings

In this section, I attend to the study’s research questions, allowing them to frame the present discussion of its findings. I further contextualize the club members’ values, practices, and relationships by situating them within the literature and by contrasting them against prevailing mainstream-stereotypes about competitive gamers. As a reminder, the guiding questions were as follows:

How Club Members Participated with One Another

As I illustrated throughout chapter four, club members participated with other another in a variety of ways and across a variety of face-to-face and online contexts. I thus draw on Ito’s

(2013) characterizations of how young people “hang out” on “friendship” and “interest-driven networks” to help highlight what made my participants’ own interactions so compelling and unique. Similarly, I lean on Turkle’s (2006) understanding of “always on, always-on-us” communication devices to describe how—through a combination of synchronous and asynchronous participation—club members were able to strengthen their connections to one another while simultaneously honing their crafts. In this manner, I now move to synthesize and interpret their participation so to make larger claims about the “shared and learned patterns of values” inherent to their culture (Creswell, 2013, p. 90). 142

After completing this dissertation’s literature review, I anticipated that club members would be considerably more ruthless and single-minded in their efforts to improve at Overwatch.

I thought that their participation would paint the portrait of a “git gud” culture that prioritized winning above all else. And while I certainly heard echoes of King of Kong (2007) in the club’s own practices and interactions, members balanced their individual competitive-drives with concerted and collected efforts to support one another in shared community-endeavors. This distinction aligns with the findings of Freeman and Wohn (2017), who similarly suggest that the

“context of eSports facilitated frequent acts of helping through both tangible and intangible means within the game […and] also ‘bled’ out into in-person interactions and relationships” (p.

435). This is a significant revelation because, as Freeman and Wohn (2017) note, researchers have long overlooked the world of esports—in favor of MMORPG games and communities— when investigating how “social support is exchanged between players” (p. 444). Consequently, the unique ways in which collegiate esports competitors participated provide new entry-points for us to examine how relationships form and strengthen online, in-game, and “in-room”

(Stevens, 2008). Through practices like the “Ming-check,” club members were observed to adopt decidedly empathetic approaches as they simultaneously bolstered their “collaborative, flexible ensemble” and transformed their gameplay (Rogoff, 2003, 2014). As such, their participation was overwhelmingly motivated by desires to “belong” and to “contribute” (Rogoff,

2003, 2014).

These themes were most explicit during tournament competition, when teammates enthusiastically cheered one another on and frantically communicated through “callouts.”

However, their collaborative gameplay represented just a tiny—albeit very intense—fraction of their weekly participation. Club members, especially those on the D1 and D2 teams, lived and 143 breathed Overwatch. In addition to playing the game, they constantly “hung out, messed around, and geeked out” in their “always on” Discord channels and Twitch streams (boyd, 2007; Ito,

2013; Turkle, 2006). They thus formed a “full-time intimate community” where their activities could begin in one context before moving seamlessly across media (Ellison & boyd, 2013; Ito &

Okabe, 2005; Leander & McKim, 2003). The club members at Penn State took things one step further; their participation did not just move across media, it also unfolded on and connected between multiple platforms at once. This simultaneity was a hallmark of their community and cultural practices; it was emblematic of how participation occurred in their modern OAGE.

Perhaps no member exemplified these practices better than Brock, who constantly sought ways to participate with fellow members across both time and space. In chapter four, I referenced one such moment in which he interrupted the D2 team’s private Discord call to wish them luck on their upcoming tournament match. I now highlight a related instance to showcase how their “full-time intimate community” interacted on and across different contexts. In the following exchange captured during an interuniversity scrim, the D2 team verbally strategizes in

Discord while Brock watches and “chats” along via Twitch:

Blaine: Yeah, I think the biggest problem is that a lot of our “healers” are “main-healers.” And I’m the only one that plays any of the “off-healers.”

Oak: Yeah.

Surge: I can play off-healer as well, but—

Oak: I’m really not that great at Zen[yatta].

Red: I can Lucio, but—

Oak (reading his “Twitch chat” and suddenly starting to laugh): Brock’s calling us out.

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Blaine: What’s he calling us out for?

Oak (still laughing): He’s saying we’re scared to play [the D1 team].

Blaine (now also laughing): I mean, he’s not entirely wrong.

(Captured April 16th, 2018)

In these lines, Brock once again interrupts the D2 team’s discussion. However, this time, he does so more indirectly. Rather than intrude on the voice-call itself, Brock instead sends a text- based message (not captured) to Oak through Twitch. He asks Oak why the D2 team is

“scrimming” with another university instead of against Penn State’s own D1 team—playfully suggesting that it must be because the D2 team is “scared.” Recalling how Twitch’s unique affordances foster a sense of “immediacy” and “intimacy,” Brock makes his presence felt despite watching from metaphoric sidelines (Johnson & Woodcock, 2019). His participation, while mediated by Twitch and Oak, is no less significant than that of those actively speaking in

Discord (see Figure 5.1). In fact, Brock’s “calling out” of Oak’s team here eventually prompted the D1 and D2 players to scrim with and against one another in the coming weeks. Participation thus had the capacity to reverberate through and across the various contexts of their OAGE, twisting and morphing in surprising ways to foster unique, new forms of engagement.

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Figure 5.1: Club members frequently interacted with one another despite inhabiting multiple different contexts. In this particular case, Brock challenges the entire D2 team to a scrim by leveraging Twitch and Oak as intermediaries.

To summarize, the participation that I observed was multifaceted, omnidirectional, and

“always on.” It was at once about belonging and contributing, about building stronger friendships and becoming stronger competitors. Along the way, these club members prepared, played, and reflected together, leaning on digital tools like Twitch and Discord to enhance, transform, and perpetuate those cultural practices. As such, their own “full-time intimate community” existed at the nexus of various contexts, and—by layering and mixing each platform’s unique affordances—the club members created entirely new ways for themselves to participate. And for researchers, the distinct cultural practices of OAGEs—such as VoD- reviewing or scouting—necessarily challenge us to develop new methods to capture and trace simultaneous, cross-contextual participation.

How Club Members Organized Themselves

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Throughout chapter four, I described how the club’s “collaborative, flexible ensemble” came together to observe and pitch-in to shared endeavors (Rogoff, 2003, 2014). Specifically, I zoomed in on the fine-grain practices of the club’s D1 and D2 teams as they prepared for, played in, and reflected on their weekly tournament matches. However, in so doing, I glossed over explanations of the ways in which players would arrange and re-arrange themselves over the course of the school year. In this subsection, I will now explore why and how the D1 and D2 teams came to be. To these ends, I lean on and extend Gee’s (2005) understanding of “affinity spaces” to describe how the esports club willingly fractured only to cross-pollenate, re-align, and re-congeal at later times and in new ways.

As Gee (2005) argues, in affinity spaces, “newbies and masters and everyone else share common [areas]” where members can “mingle with others as they wish, learning from them when and where they choose” (p. 225). That said, he also notes that—within those spaces— there might still be “portals” where novices and experts are “segregated” from one another. Gee

(2005) does not speculate on why this segregation occurs beyond acknowledging the obvious limitations of most multiplayer games. For example, in Overwatch, the game can only accommodate two teams of six at any given time; likewise, large skill-imbalances tend to produce lopsided matches and frustrated players. When combined with tournament rules regarding roster sizes, there were certainly logistical reasons motivating the club’s self- stratification. However, my findings also suggest that having such “portals” in the D1 and D2 teams allowed club members to contribute, belong, support, and take responsibility in culturally significant and authentic ways. After all, considering how frequently these players would take cues from the professional leagues, it is not surprising that they wanted to experience similar team-based environments and endeavors through their own OAGE. The D1 and D2 teams thus 147 provided long-term, intimate contexts in which players could simultaneously develop as friends and teammates. Their participation necessarily transformed as they became increasingly familiar with one another’s personalities and playstyles to the point where—as Roger reminds us—“a lot of comm[unication could] go without saying.”

Of course, for however well-intentioned the creation and curation of the D1 and D2 teams might have been, their mere existence implicitly raises concerns about “gatekeeping” and

“elitism.” Gaming culture—and by extension, the world of esports—is often rightfully criticized for perpetuating a “toxic meritocracy” that is “self-insulating and self-replicating” (Paul, 2018).

This dissertation makes no attempt to refute those broader claims. However, the particular

OAGE that I observed demonstrated a surprising self-awareness and actively looked for empathetic ways to include and support its novices. As I explored throughout chapters three and four, the club boasted a variety of “common spaces” where the “whole continua of [its members] from new to experienced, from unskilled to highly skilled, [and] from minorly interested to addicted” could contribute and belong (Gee, 2005, p. 225). In addition, it frequently generated specialized “portals” as demand for more structured, team-based experiences increased.

Beginning with the formation of D1 and D2 rosters in late 2017, the OAGE quickly expanded to feature over six such teams—each of varying skill and dedication-levels—that club members were encouraged to join (see Figure 5.2). And by late 2018, everyone that wanted to compete as part of a team could easily do so. The most interesting of these additional rosters, however, was known as the “Academy Team.” Its unique organizational structure and goals at once embodied the facets of LOPI while simultaneously combating that omnipresent specter of “toxic meritocracy” that hangs over gaming culture.

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Figure 5.2: The above diagram illustrates the relationships between the various club teams. Many of the more casual teams (D2, W, X, Y, and Z) frequently shared and traded players amongst one another. During the 2018-2019 season, they even competed together as part of an intraclub league. The D1 team remained more isolated, but it still worked closely with fellow club members through its participation in the “Academy Team.”

As I alluded to in chapter one, collegiate esports has become increasingly “serious” in recent years, with many tournaments now awarding large cash prizes and scholarships to their top competitors. Predictably, the D1 team—as the university’s representative in the most prestigious and exclusive of these events—was the most selective when it came to building and maintaining its roster. In fact, it was the only club team that required potential players to first participate in a formal “try-out” process. However, this did not mean that the D1 team was completely insular in its practices. For example, its members regularly participated with and against the other club teams during inhouse scrims and as part of more casual, impromptu play.

More notably though, its members also served as coaches and managers for the “Academy

Team”—a collection of aspirational players that desired to compete as part of D1 team in future semesters. Conceived of by then division-head Brock, the “Academy Team” was intended to 149 serve as a liminal space where novices could enter more intimate, “cognitive apprenticeships” with the club’s most experienced players (Brown et al., 1989). As such, it addressed a number of the OAGE’s needs. The “Academy Team” thus provided opportunities for experts to step into mentoring roles, for novices to experience increasingly higher-stakes competition, and for the D1 team to scout and groom talent in order to replenish its own roster. After all, students frequently graduated and moved on; portals like the “Academy Team” allowed the club to enculturate new members quickly and seamlessly into its way of life.

When taken together, my findings suggest that club members constantly struggled to balance their competitive ambitions against their better impulses to create and organize a welcoming community. In the increasingly cutthroat world of competitive, collegiate esports, this was no easy task. Fortunately, they devised a variety of creative solutions—including the formation of the “Academy Team”—to carve out new, hybrid spaces where novices and experts could collide in culturally significant ways. And as educators, their grouping strategies challenge us to re-think how informal, collaborative learning can and should occur in our classrooms.

How Club Members Interfaced with a Wider Community

Previously, I claimed that many of the club members “lived and breathed” Overwatch. In this subsection, I now want to return to and expand on that notion as I describe how they interfaced with the wider esports community. Specifically, through their daily participation— both active and peripheral—on the “always-on networked publics” of Twitch, Twitter, Discord,

YouTube, and Reddit, club members were able to connect with and relate to peers from across the globe (boyd, 2007, 2013; Ito, 2013; Turkle, 2006). As I detailed through an analysis of their reflective practices, club members were thus able to access and leverage the ever-evolving 150

“esports canon” as they watched and learned from professional players and coaches. However, as Jones (2005) is quick to remind us, “what [young people are] doing online has a lot to do with what they’re doing in the real world.” In addition to their daily web-browsing, many club members also reported attending in-person watch-parties, conventions, and LAN tournaments where they interacted with fellow fans and esports celebrities alike. Consequently, I consider literature on “boundary crossing” to discuss the various ways in which club members pushed and pulled on the fabric of esports culture (Akkerman & Bakker, 2011; Engeström et al., 1995;

Suchman, 1994).

At a glance, “boundary crossing” refers to how people enter unfamiliar territory and “face the challenge of negotiating and combining ingredients from different contexts to achieve hybrid situations” (Engeström et al., 1995, p. 319). Drawing on the Bakhtinian notion of

“dialogicality,” it similarly recognizes “learning as a process that involves multiple perspectives and multiple parties” (Akkerman & Bakker, 2011, p. 135). As my findings illustrate, so many of the OAGE’s weekly activities and interactions could thus be thought of as exercises in boundary crossing. Even in the most mundane of their practices, club members were constantly layering and mixing contexts to better leverage their teammates’ perspectives. However, it is equally important to look beyond their more routine, online participation to consider how they entered face-to-face dialogues and relationships with members of the wider esports community. As I will now explore, their OAGE was neither a closed system nor a one-way street. Its metaphoric doors swung both ways, and, in turn, its members were both influenced by and influences on the culture they “lived and breathed.”

Recalling pervious discussions about the “esports canon,” club members generally looked up to and “followed” the same core of popular streamers and skilled professionals. However, as 151 evidenced by Scott’s in-game interactions with personalities like Emongg, these “e-celebrities” were not impossibly distant, mythical figures (Armelin, 2012). Not only did the two parties occasionally cross paths and share spaces together online, but they also had the potential to meet in-person at various Overwatch-related events. When asked about his relationship with these content creators, Ash shared the details and significance of one such encounter:

[The YouTube channel] “YourOverwatch” presents things in a much more educational way, which I think is better—especially for someone like me, who’s looking to improve when I can. I like Samito a lot because I met him; I met KarQ once, too. And I think they’re really cool guys.

Interestingly enough, right when the Overwatch League [started], me and my friends went to this convention in [southeast] Pennsylvania. The year we went, the Philadelphia Fusion ran a “showcase” tournament there. And I had been watching the Overwatch League since it came out, so I was pretty excited to finally see a live LAN- event.

And it actually turned out that the [then] D1 Penn State team was also there, and they played a game—that I watched—against this team of insanely “stacked” pro players. KarQ was there, Kephrii was there, and Samito was there. And after that match, they all went to the Wendy’s down the street—and I just happened to be there. So I got a minute to talk to them, and they were really nice.

I definitely go [out of my way] to watch their content now. That’s also how I sort of fell into “YourOverwatch,” because Samito works with them a bit. And one day, I was watching his [Twitch] stream, and I “commented” about the time I met him, and I just said “thank you” because that was really nice of him to take the time to talk to me. And he remembered me and [mentioned] what we had been talking about [at Wendy’s]. And I just really appreciated that. (Individual Interview, Ash, April 10th, 2020)

He begins by echoing the sentiments of Kevin and Roger—who similarly reported “looking to the pros” as they attempted to learn and improve at the game of Overwatch. Here though, Ash extends our understanding of how and why the “esports canon” acts on its “readers.”

Specifically, he mentions that he “liked Samito a lot because he met him” (emphasis mine). Ash elaborates, citing how that one positive, face-to-face interaction actively led him to seek out more of the streamer’s content. By meeting Samito at such a “boundary,” Ash thus experienced 152 a “transformation” that produced a “profound change in [his own] practices” (Akkerman &

Bakker, 2011). Furthermore, he casts their conversation at Wendy’s not as an isolated event but, rather, as the start of a relationship. After all, their interaction reverberated across space and time as the two later resumed their dialogue on Twitch. And as such, Ash felt as if he contributed to and belonged in the wider esports community.

Just as his conversation with Samito inspired changes in how Ash himself approached the esports canon, club members were able to exert their own influences on fellow Overwatch fans as well. Roger recalls an interesting such moment from a separate tournament hosted at

Harrisburg University’s campus:

I remember that we were coming off of the stage after beating Temple [University] 3-1. And I think this kid was in high school—maybe he was a sophomore or a junior? And he [started] talking to me. And he was like, “are you guys Penn State?” And I’m like, “yeah, we’re Penn State.” And he was like, “whoa!”

That was the first time that someone had looked up to me. And I was like, “wow, this is kind of cool to have someone look up to you like that.” And he was like, “I really want to get good at this game.”

He had actually been playing in the high school match. I remember seeing him up on the stage, and you could tell he was getting frustrated [with his performance]. So he actually cared about what was going on. And maybe he was only “plat” or “gold” or whatever, but he was competitive about it. [Anyhow,] it feels good to have someone look up to you and think you’re super cool. I want that feeling more when I go to LANs. I don’t want to necessarily win; I just want to be there. I like the atmosphere of it. (Individual Interview, Roger, April 10th, 2020)

While it is difficult to trace how the high schooler’s practice might have transformed in the wake of watching and chatting with Roger, their unexpected meeting nevertheless reveals how

“boundary crossings” can lead people to rethink and reimagine their own “identities” (Akkerman

& Bakker, 2011). As Roger reiterates again and again, this was “the first time that someone looked up to [him] like that.” Likewise, he seemed to recognize a piece of himself in the bright- 153 eyed and determined high schooler. Through his face-to-face encounter with this fan, Roger thus came to a new understanding and appreciation of his personal growth and development as an

Overwatch player. The high schooler’s admiration was proof that Roger’s hard work and training was paying off; it was evidence that his role and identity in the wider esports community were starting to change.

In this subsection, I have showcased some of the more unique ways in which club members would interface with players and fans outside of their immediate OAGE. While their daily participation through “always-on networked publics” remained an excellent way for them to connect with and relate to distant peers, the fact that so many of the club members desired to attend and compete in LAN events cannot be ignored. After all, there has been a wealth of literature written about the relationship between anonymity and increased toxic behavior in online-gaming environments (Kwak et al., 2015). The members of this OAGE, however, were not interested in participating in such anonymous, clandestine ways. Instead, much like the major characters of King of Kong (2007), they wanted public recognition for their skills and contributions. Club members thus constructed their practices and identities in anticipation of ultimately encountering their idols, opponents, and fans in the field.

Contributions

Contributions to Theory

This dissertation has been motivated by a desire to describe the values, practices, and tools of a very particular subset of competitive gamers. By immersing myself in the day-to-day life of a collegiate esports club, I observed a unique learning ecology that melded various affinity spaces together to create new, hybrid contexts for itself. In turn, those contexts—amplified by the combined affordances of platforms like Twitch and Discord—allowed club members to 154 participate with one another in powerfully transformative ways. They improved at their favorite games quickly, and they did so together. They thus formed what I now understand as an

“observational and analytical gaming ecology” (OAGE)—a dynamic system of contexts that draws players of shared interests and shared goals together to share perspectives. As my study’s major contribution, OAGEs also provide researchers with a more precise way to think about and describe the modern, tightknit esports communities that are increasingly springing up around college and university settings.

While today’s OAGEs certainly share some common features with the arcade-cultures of gaming’s past, they differ in several notable ways. For one, OAGEs are increasingly networked.

Not only do they facilitate interactions between their local members, but they also serve as nexus points on the global esports landscape. As such, OAGEs are not self-contained systems; rather, they take cues from an evolving “esports canon” as they constantly refine their community practices, rhetoric, and contexts. Secondly, an OAGE coalesces under the assumption that its members will eventually collaborate in shared endeavors. Rather than coming to view one another as direct competition—as they might in more traditional gaming circles—OAGE members come to recognize and depend on their immediate peers as resources. As such, they are willing to pioneer new, empathetic ways to share their perspectives with one another. Through practices such as the “Ming check” and the through the creation of portals such the “Academy

Team,” OAGEs thus carve out pathways whereby peripheral and novice members can contribute and belong.

Through critical examinations of OAGEs—like those formed by collegiate esports clubs—our theories of LOPI also necessarily extend. LOPI has become a useful framework for understanding how children learn from watching and participating in community endeavors 155

(Rogoff, 2014). However, in the wake of the Covid-19 pandemic, we—as a society—are now challenged to consider what happens when such complex, collaborative, and community endeavors move online. Enter OAGEs. For over a decade, these gaming communities have pushed the boundaries of how LOPI can and should occur on more networked contexts; their members have invented creative new ways to participate with and support one another in their shared endeavors. And as our school systems now struggle to engage students in distance- learning programs, OAGEs hold up mirrors—perhaps unfairly—to measure our progress. After all, when compared to the esports competitors that call OAGEs their homes, we are the novices.

We would do well to watch and learn from practices, tools, and solutions. Thus, by forwarding the concept of OAGEs, I hope my dissertation has responded to Squire’s (2011) call “to look beyond the game[s themselves] toward the broader cultural contexts in which [they are] situated”

(p. 12). I hope I have provided some insight on how the world of collegiate esports works, and, more specifically, on how its players form and participate in learning ecologies. In the following subsection, I move to reflect on my own methods while offering suggestions, recommendations, and directions for future research.

Methodological Considerations and Future Work

Throughout my dissertation, I have demonstrated how—by adopting an immersive,

“connective ethnographic” approach—I was able to “disrupt the binary and power relationship of researcher/research subject in order to get at the more native ways of understanding the meaning of digital practices” (Leander, 2008, p. 50). Specifically, I went to great lengths to become an

“acceptable incompetent” at Overwatch, investing nearly 500 hours into learning and practicing the game prior to conducting this study (Hammersley & Atkinson, 1983). And while this degree of preparation was certainly overkill, it nevertheless allowed me to interact with club members as 156

“player-to-player” instead of simply “researcher-to-subject.” As such, it became relatively easily to build and maintain rapport with participants throughout my investigation. Interviews, in particular, flowed more seamlessly as result. With participants unburdened by a need to translate community-language or to define Overwatch-specific concepts, their culture exposed itself in raw, unfiltered ways. Participants were thus able to focus on and share—with authenticity—the finer-grain details of their experiences and practices. When they spoke, they knew that I understood them. In turn, I was able to ask more pointed follow-up questions and to steer our conversations in increasingly productive directions.

That said, simply playing the games that we study is not a particularly new or novel idea

(Aarseth, 2003), nor should it be viewed as some type of methodological magic-bullet for conducting games-based research. Recalling Squire (2011), it is equally important to consider

“the broader cultural contexts in which [the games] are situated” (p. 12). As I started to observe and play alongside club members, I quickly became aware of just how central their “reading” of the “esports canon” was to their own participation. As I have already argued, their OAGE was not a closed system. It was constantly influenced by and an influence on the global esports community. Consequently, I made a concerted effort to keep with that wider community’s latest news, events, and drama. More specifically, I adopted my participants’ practices as my own by creating and crafting esports-focused social-media profiles on Twitch, Twitter, and YouTube.

Like my participants, I thus made following and watching the likes of Emongg, Carpe, Samito, and Jayne part of my daily routine. This approach helped me to recognize and appreciate the richness, depth, and significance of so many of the club’s shared references. Interactions and moments that I might have otherwise overlooked instead drew me in and—ultimately—led me to some of my project’s most compelling findings. For researchers looking to work with esports 157 competitors and their communities, I recommend that they adopt similar approaches. While they should not feel as if they need to study and play the games as intensely as I did, they would still do well to become “acceptable incompetents” and to become avid “readers” of the “esports canon.”

In this dissertation, I examined one very particular niche of the gaming world. I observed and participated alongside a collegiate esports club as it prepared for, played in, and reflected on high-stakes tournament matches. I looked on as its members shared their unique perspectives as part of an OAGE. And by tracing their interactions, relationships, and activities across a variety of “new and strange” hybrid-contexts, I came to a better understanding how modern esports- competitors leverage technology to transform their participation. However, in so doing, I still only scratched the surface of what this evolving subculture has to offer researchers and educators. As esports grows in popularity and legitimacy, its OAGEs will continue to emerge in new places and in new ways. While colleges and universities have proven to be fertile grounds for studying such communities, esports are also starting to find homes in high schools as well

(Juhasz, 2020). How do these younger students—under the guidance of classroom teachers and coaches—come together to form their own OAGEs? How do schools go about creating more equitable gaming-commons where historically marginalized groups can contribute and belong?

What happens if and when schools attempt to sanitize or curate the “esports canon”? Recalling

Roger’s chance encounter with a high-school-aged player and fan, future work could also examine the role that esports programs and clubs play in the college admissions and recruitment processes. There has been a lot of literature written about how traditional student-athletes select colleges (Letawsky et al., 2003; Popp et al., 2011), but we know comparatively little about what budding esports competitors look for in those same institutions. And as more colleges add their 158 own varsity esports-programs, the competition to recruit the most outstanding of these high- school players will only intensify. By seeking to understand their unique experiences at the high-school level, we might better learn how to smooth their transition into university life.

Towards an OAGE-Infused Classroom

For over two-and-a-half years, I had the privilege of working with and learning from the dozens of intelligent and passionate players that comprised “Penn State Esports.” And I was also fortunate enough—through the club’s various Discord channels—to stay in touch with many of these individuals as they graduated from the university and entered the workforce. One of these players was Erika, who would go on to leverage her collegiate-esports experiences as she began her own career as a high school teacher. In a follow-up interview, she explained how she volunteered to become the faculty advisor and coach for her district’s newly formed esports team. Erika not only described how she interacted with students during meetings, practices, and games, but she also reflected on what they gained through the process:

[High-school esports] builds all of those character attributes that parents [and teachers] want their kids to have. Whether it’s joining another club or playing sports, you get that camaraderie, you get that teamwork, you get friends. But [esports] also removes many of the barriers that normally exist in traditional, team sports. You don’t really have to have athletic ability in order to play. You could be in a wheelchair, and you could still compete in esports.

Some parents might have problems with the content of these games, but if you really look at what [the kids] are learning and what they’re gaining from it? A lot of my kids are now really good friends. They talk all the time in our team Discord, and they’re so much more connected with the school. And for the kids that were on the outer-fringe— that didn’t normally fit in? They found a place where they could meet other kids that were like them.

I’ve had kids that have worked really, really hard to get their grades up so that they could compete. And I’ve had kids that have thanked me for coaching because—without [high-school esports]—they wouldn’t have anything to do after school. They would just 159

go home and be bored. So it really gives the kids a lot. (Individual Interview, Erika, April 10th, 2020)

If—as Erika suggests—esports are already doing such important work in extracurricular capacities, then it is worth considering what their cultural values, practices, and tools might have to offer our pedagogy. Using Erika’s monologue as a springboard, I now turn to imagine what an OAGE-infused classroom might look like and feel like.

Central to Erika’s speech is an emphasis on “connectedness.” As I have explored throughout my dissertation, esports competitors have long sought ways to connect both with their local peers and with more prominent, expert members of the wider community. An OAGE- infused classroom would provide similar services and opportunities to its students. By leveraging the “always-on, networked” platforms of OAGEs, teachers could take practical steps towards reimagining their classrooms as “nexuses” rather than “containers.” For example, through participation on a “classroom Discord server,” students might streamline, extend, and enhance their peer-to-peer collaboration in new ways. And educational researchers are already recognizing the benefits of using Discord in this manner (Lacher & Biehl, 2019; Wulanjani,

2018). However, my findings suggest that—by inviting and recruiting additional, outside experts to participate alongside students—a classroom Discord server could become even more powerful. Where Red once leveraged such contexts to have his Overwatch gameplay reviewed by Emongg, our students might use a classroom Discord server to share their writing with local authors or their designs with industry professionals. OAGEs thus challenge us to break down classroom “walls” and to install “portals” in their places. They force us to reconsider where, when, and how we give our students access to expert-perspectives—and to acknowledge that without connections there can be no relationships. 160

As Leander & Lovvorn (2006) remind us, traditional classrooms “are not dull and unmotivating merely because they are filled with unmotivated persons. They are unmotivating because they are immobile” (p. 336). I argue that an OAGE-infused classroom is not a place but a vehicle. It takes students where they want to go and when they want to get there. It does so by providing students with a rich set of hybrid-contexts that are inhabited by peers and professionals alike. Perhaps it starts with the creation and maintenance of a classroom Discord server— complete with dedicated channels for homework discussion, writing workshops, and media sharing. Maybe it expands to include a classroom Twitch channel, through which students could model best practices and engage in live performances. As an English teacher, in particular, I wonder what it might mean for students to “stream” the writing process? What might their impromptu, metacognitive self-talk reveal about their writing processes that finals products cannot? Likewise, what occurs when traditional “peer-reviews” are infused with the practices and values of collaborative, esports “VoD-reviews”? Whatever shape or form it ultimately takes, an OAGE-infused classroom will assuredly be founded on connectedness; it will aim to bring new people together in new ways to transform everyone’s participation.

Closing

Throughout this dissertation, I have tried to look “beyond the games” and instead focus on how their players engage in observation, analysis, and authentic participation. Consequently, in this final chapter, I discussed how members of a collegiate esports club created a “full-time intimate community” for themselves that existed at the intersection of multiple online contexts.

Likewise, I described how they leveraged these new, hybrid spaces both to arrange themselves into smaller teams and to connect with members of the wider esports community. I then pulled the lens back further to consider what their unique aims and methods—as an OAGE—might 161 mean for educational researchers and practitioners. Specifically, I argued that these esports competitors have been pioneering and “beta-testing” distance-learning strategies for over a decade. And where Covid-19 has disrupted work, learning, and leisure for so many, the daily life of the “Penn State Esports Club” has remained largely unaffected. In fact, as a more

“socially distanced” semester begins this fall, club members are still organizing, gathering, and participating together much as they have for the last three years (see Figure 5.3). We would do well to take cues from their culture as we strive to the build our own, more connected classrooms.

Figure 5.3: The club activities for the new semester kick off on Discord. Players for the various D2 teams use voice-chat (left sidebar) while players for the D1 team text-message one another (right).

That said, the games—and the technologies that bind them—are always changing. Since embarking on this dissertation project in late 2017, the esports community has witnessed the rise 162 of Fortnite and the fall of Mixer. While Overwatch has remained relatively popular, enthusiasm around the game has certainly waned in recent months. Many of its players—casual and professional alike—have started to make the transition to newer games like Valorant. Surprise titles like Fall Guys and Among Us also frequently burst onto the scene to completely change the esports and Twitch-ecosystems for months at a time. As such, it can be difficult for researchers and educators to keep up with the “metagame.” However, as esports continues to solidify its place as a legitimate scholastic activity in our high schools and colleges, we need to figure out ways to stay connected to what its players are doing and saying. I believe a continued study of

OAGEs can provide that understanding. After all, their members are not just the most hardcore of players… they are also the designers of powerfully transformative contexts and the stewards of the esports canon. By following and learning from these trailblazers and trendsetters, we are afforded an unfiltered view of how collaborative technology gets deployed and iterated upon in the wild.

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VITA

Robert James Hein [email protected] ______Education

The Pennsylvania State University, College of Education, University Park, PA Ph.D. Candidate in Learning, Design, & Technology (2014 – present); A.B.D. (expected Winter 2020)

Duquesne University, McAnulty College and Graduate School of Liberal Arts, Pittsburgh, PA MA English Literature, 2014 BS Secondary Education – English, magna cum laude, 2010

______Professional Appointments

The Pennsylvania State University, Instructional Designer 2014-2019 Duquesne University, Graduate Assistant 2012-2014 Bishop Canevin High School, English Teacher 2010-2011

______Select Publications and Conference Presentations

Hollett, T., & Hein, R. J. (2019). Affective atmospheres and skatepark sessions: The spatiotemporal contours of interest. Learning, Culture and Social Interaction, 23, [100265]. https://doi.org/10.1016/j.lcsi.2018.12.001

Hollett, T., & Hein, R. J. (2018). Spot-hunting and street riding: Reading, "riding," and making place on the move. A paper presentation at the American Education Research Association Annual Meeting. New York, NY.

Turcotte, N., Hein, R. J., & Engerman, J. A. (2018). Strategies for Adopting Games-Based Lessons in the K-12 Classroom. PAECT Technology Education Research Journal, 1(1), 324-341.

Hein, R. J., Engerman, J. A., Turcotte, N., Macaluso, A., & Giri, S. (2016). Thinking like writers and critics: How adolescent boys experience narrative-driven games. A paper presentation at the Games, Learning, and Society Conference 12, Madison, WI.

Hein, R. J., and Engerman, J. A. (2016). Knowledge production in e-sports culture: Learning with and from the masters. In K. D. Valentine & L. J. Jensen (Eds.), Examining the evolution of gaming and its impact on social, cultural, and political perspectives. IGI Global.