On Video Game Balancing: Joining Player- and Data-Driven Analytics

Video game balancing is one of the most controversial topics of modern video games, especially in the context of (online) multiplayer games that undergo regular updates, both for competitive Player-versus-Player (PvP) as well as for collaborative Player-versus-Environment (PvE) games and modes. Besides the introduction of new content and bug fixes, balancing adjustments are among the driving factors of game update patches, as the often exploding complexity of choices, the diversity of player expectations and the hardly predictable impact of changes onto the actual adaption and reception of the player base render the problem of finding a well-balanced game state almost impossible. Games of all popular genres employ never-ending balance patch paradigms even years after the launch of a game. These can operate on various layers of in-game choices, such as the playable Champions¹¹1https://www.leagueoflegends.com/en-us/news/tags/patch-notes/ of the Multiplayer Online Battle Arena (MOBA) League of Legends (Games, 2009), equippable weapons²²2https://liquipedia.net/counterstrike/Patches of the First-Person Shooter (FPS) Counter-Strike: Global Offensive (Valve, 2012) or active and passive changes to classes, traits and skills³³3https://en-forum.guildwars2.com/forum/6-game-update-notes/ of the Massively multiplayer online role-playing game (MMORPG) Guild Wars 2 (ArenaNet, 2012).

In contrast to ordinary bug fixes that most of the time have a well-defined optimal solution, working on balancing issues is a steady and repetitive task suffering from the unpredictability and inertia of the player base accommodating to the new game configuration (“a lack of balance […] only becomes apparent after many months of play”)(Hullett et al., 2012), as well as from the diverging and controversial opinions and perceptions from both player base and developers (“after each patch, often the discussion begins again, factoring in new balancing or abilities for each class”)(Lewis and Wardrip-Fruin, 2010).

What makes this process even harder to solve is that there is no clear or accepted definition of what balancing means in the context of video games, or even what a well-balanced state or configuration of a game constitutes. Becker and Görlich recently stressed this incongruity, emphasized that this controversial but highly important topic is barely investigated by academia and contrasted various definitions from designers, developers and other practitioners (Becker and Görlich, 2020). They conclude that no two of these authors share identical understandings of game balancing and even if some concepts overlap, no undisputed fundamental concepts of game balancing protrude.

From an industrial perspective, a game might be balanced “if a reasonably large number of options available to the player are viable — especially, but not limited to, during high level play by expert players” according to Sirlin (Sirlin, 2001). This however necessitates a finer distinction on when reasonably large begins and how sharp viable can be defined. While the former is arguably highly game- and context-related, he refers to viable options as offering “meaningful decisions between promising alternatives”. A similar, yet slightly toned-down definition comes from Burgun, who asserts that game balancing is the craft of “keeping game elements relevant” - indicating that dominating strategies or choices (i.e., decisions that are by all means better than their alternatives) are the most harmful factors for the state of balance in a game (Burgun, 2011). Felder approves this take by claiming that these dominating choices express “broken gameplay, which consists of strategies or even singular actions rendering a lot of decisions meaningless”, which becomes detrimental for the overall player experience (Felder, 2015).

An intuitive implementation of viable options across the board would thus be symmetry, i.e. the identical power or expected performance of choices. As such, players are exposed to equal starting conditions, a game becomes fair by definition and only (or predominantly) individual skill matters. While this might be desired in some contexts (and design aspects as flair or variation still can enhance symmetrical game setups), a perfectly symmetrical game bears the risk that there are no interesting choices beyond proven strategies anymore and that the player’s decision actually does not matter (Brown, 2019b; Felder, 2015). This lack of impact on the own performance could again be harmful for a player’s intrinsic motivation. In that sense, even if a certain deviation from perfect symmetry creates a dominating strategy, this could be countered by implementing intransitivity between options in competitive situations, so that single choices display strengths and weaknesses when opposed to different other choices (“while a balanced game can easily lead to a stagnation of strategy discovery, […] slight differences in power between game elements encourage players to constantly search for new solutions against currently popular strategies”) (Becker and Görlich, 2020; Portnow, 2012). Provided that these can be approached with counter-strategies, Fender finds smaller power gaps as a “critical part of game balancing” (Felder, 2015).

From another viewpoint, the balance of options could be assessed by their probability to lead to victory in competitive play (Sylvester, 2013). Especially in these PvP scenarios, objective as well as subjective fairness can be a strong indicator for the perceived balance of a game (Adams, 2014). Industrial approaches of these do not always draw on parameter balancing for the underlying options, but especially in competitive games, matchmaking between players of similar skill is a promising strategy to lead to 50/50 win rates (DeCoster and Rubin, 2019). Yet, Claypool et al. discovered that even if winning chances can be closely approximated to 50%, such as in the highly populated matchmaking of League of Legends, players still subjectively perceive these as unbalanced (Claypool et al., 2015).

In contrast, ample scientific work highlights that difficulty can be the driving factor for balancing PvE scenarios and/or single-player games (Adams, 2014). The field of dynamic difficulty adjustment (DDA) – sometimes also referred to as dynamic difficulty balancing – mainly pushes the understanding of balancing as the adequate (automatic) regulation of difficulty (parameters) in order to keep players within the desirable flow state between mental under- and overload (Csikszentmihalyi, 1990; Hunicke, 2005), or ideally between “too hard” and “too boring” (Lomas et al., 2017). In this respect, if perfect matches are not attainable, mental overload is still seen as producing higher enjoyment than boredom (Klarkowski et al., 2016). Andrade et al. claim that “game balancing aims at providing a good level of challenge for the user” (Andrade et al., 2006), while Volz et al. keep it more general by defining the goal of the adjustment to make sure that “the resulting gameplay is as entertaining as possible” (Volz et al., 2016). While this “modification of parameters of the constitutive and operational rules of a game” (Schreiber, 2010) follows technical procedures similar to the adjustment of parameters for adjusting the viability, symmetry or fairness of in-game choices or strategies, the underlying agenda and purpose considerably differs.

Apart from these dimensions, other perspectives look into the balance between “skill and luck” (Schell, 2008), where skill is the main desired factor for outcome, but chance still makes up for an important mechanic in many games (Adams, 2014).

Conclusively, different fields, communities and purposes announce and use different definitions of balance, the act of balancing and what it means for a game to be (well-) balanced. With this amount of discordance, open issues and even conflicting definitions and understandings, polishing video games towards maximized player satisfaction becomes apparently difficult. Even more, Brown stresses that balance has to take part on every conceivable level of a game, for “all options a game offers, including singular actions and strategies” and maybe even more importantly, “the players’ perception of balance is just as important as the actual balance” (Brown, 2019a). This importance is elevated by Schell who claims that “to identify the right middle ground [of balancing], one has to take the audience into account” (Schell, 2008), Schreiber stating that “players have differences regarding their […] expectations” (Schreiber, 2010) and DeCoster and Rubin proclaiming that developers should be “open about balancing discussions to their players so they can expect solutions to existing problems” (Becker and Görlich, 2020; DeCoster and Rubin, 2019).

The divisiveness of defining balancing notions paired with the reliance on the satisfaction of the player base for the success of the title and the convinced mindset of experts regarding player requirements strongly calls for an integrated player-driven approach of elevating game balancing, which is largely under-investigated in academia. Even though many developers listen to professional players or communities and/or make use of recorded play data in some sense, player expectations are often not matched to balancing decisions and badly implemented update patches can lead to involuntary shifts of player behavior and/or eventual churn (Wang et al., 2020; Tyack et al., 2016; Hyeong et al., 2020). Prominent industrial examples of these can be found in the 1.05 patch of Uncharted 2: Among Thieves (Naughty Dog, 2009) that spoiled multiplayer balance for a major part of the player base as most weapons’ stats became too homogenuous (mismatching symmetry); Tribes: Ascend (Hi-Rez Studios, 2012) (patch 1.0.1103.1) that slowed down (and therefore eased) gameplay while the community was explicitly craving the high speed factor of the game (thus mismatching difficulty); or Street Fighter V (Capcom, 2016) significantly losing players after a balance update (3.5) that buffed already well-performing characters and even nerfed niche fighters (diverging from viability). This is only emphasized by the highly negative perceptions ($83\%$) of the Guild Wars 2 balance update in this work that raised global discontent among the community and led to a decrease of average daily playing time by $13.4\%$ when compared to the previous patch era.

In sum, balancing (online) video games aims at improving the viability of different playable elements (among other factors). This often backfires when balance perceptions mismatch between developers and players, which can happen due to conflicting requirements, unawareness about how players experience game dynamics or because of the many substantially different definitions of balancing. These disagreements can lead to dissatisfaction, impaired player experience and churn, rendering the proper handling and optimization of balance a problem for the industry, games user research and human-computer interaction in general. To counteract this and fortify the understanding between developers (or researchers) and players, we propose to push player-driven game balancing to tightly couple requirements and opinions of existing player communities into the balancing process of a game. While this player-driven approach aggregates the subjective view of a player base (with all of its advantages and drawbacks), we argue that joining it with the similarly under-investigated objective assessment of balance states in video games through data-driven techniques can overcome its limitations by grounding opinions in empirical foundations. This leads to the examination of the following research questions:

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  (RQ1): With so many conflicting theoretical definitions of balancing, how can a game understand and cater to the requirements of its players?

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  (RQ2): How can data-driven analytics help grounding the objectivity of this pool of opinions?

To answer these questions and assess the feasibility of this procedure, we conducted a case study with ($n=680$) novice up to professional players of the MMORPG Guild Wars 2, capture their mindset towards Becker and Görlich’s balance criteria of viability, symmetry, fairness and difficulty, and contrast this to the direction of actual balancing implementations. To validate the appropriateness of these opinions, we draw on data-driven analytics encompassing ($n_{a}=154,145$) unique player accounts and ($n_{l}=4,318,009$) atomic in-game combat logs of the game.

Eventually, by delivering a grounded, systematic approach of determining detailed balance requirements of players - exemplified through an ambitious community case study that is likely to generalize to other games within and without the genre - we contribute to the fields of player-centric design and development, games user research, game evaluation and strive to closer connect academia, industry and the very players.

For other application cases, player-driven approaches have already delivered promising solutions that exceeded the capabilities of complete in-house implementations. One example would be Da Silva et al.’s utilization of the collective power of a community to retrieve a widely nested narrative and story background merely from player input (Da Silva and Tomimatsu, 2013). Concerning procedural content generation, Shaker et al. highlighted the capabilities of player-centric approaches, including personalization of in-game maps or experiences (Shaker et al., 2012). Partlan et al. utilized participatory design in order to assess requirements and develop design-driven features for co-creative game AI design tools (Partlan et al., 2021). Even completely player-driven game development cycles have been shown to result in novel experiences, dynamic design procedures and central game features that are inherently tailored to the actual target audience (Lessel et al., 2019). Canossa and Drachen argue that increasing the players’ agency and influence on the development process can lead to enhanced experiences and immersion when introducing play-personas for customized gameplay (Canossa and Drachen, 2009) – which arguably extends similarly to continual balancing updates. Eventually, player-driven paradigms might even scale to the large magnitudes of communities that popular modern games accumulate, as Ma et al. indicate in their work on user innovation evaluation strategies, incorporating over 21,000 players that produced novel and sufficiently complex ideas and suggestions (Ma et al., 2019).

However, purely player-driven balancing decisions might still be warped by diverging opinions, missing empirical knowledge about the actual state of the game and the gap of experience (and requirements) between novice and expert players. The arguably most objective measures to counter lacks of knowledge and to condense how games actually play out are empirical data-driven methods (El-Nasr et al., 2013; Wallner, 2019). The majority of these data-driven approaches are stemming from and/or focusing on delivering insights for the game industry (e.g. data mining, classification or prediction) (Drachen and Canossa, 2009), targeting measures against churn (Hadiji et al., 2014), facilitating content generation (Risi and Togelius, 2019), or easing the burden of testing (Albaghajati and Ahmed, 2020) (among other areas). Most of the remaining approaches follow academic interests concerning similar topics or fundamental (psychological or technical) regularities, structures and concepts (Drachen et al., 2018; Yee, 2006), often employing visualizations to gather insights for researchers or analysts (Bowman et al., 2012). Prominent implementations target spatio-temporal movement (Moura et al., 2011; Wallner et al., 2019; Wallner and Kriglstein, 2012; Ahmad et al., 2019), decision making of individual or aggregate players (Loh et al., 2016; Nguyen et al., 2015) or higher-level metrics and statistics (Drachen et al., 2012). Effectively, certain academic approaches already addressed the balancing of viable game options, such as automatic symmetric and intransitive player modeling approaches from Pfau et al. (Pfau et al., 2020), asymmetric Monte-Carlo balancing from Beau and Bakkes (Beau and Bakkes, 2016), Jaffe et al.’s maximization of fair and useful card game cards (Jaffe et al., 2012) or Leigh et al.’s reduction of dominant strategies through coevolution (Leigh et al., 2008). Even if most of these draw on simulation or calculation towards well-balanced game states and (to the best of our knowledge) no academic work included the players’ perspective so far, it is reasonable to hypothesize that similar balancing solutions can follow or implement opinionative inputs.

Ultimately, we want to empower and harness player-driven balancing conceptions informed by data-driven methods. Making video game data transparent, explainable and applicable to its players is already one of the driving topics within the areas of game-related explainable AI and player modeling (Zhu and El-Nasr, 2021; Lucero et al., 2020; Wells and Bednarz, 2021), and comparably holds in the context of balancing. For this reason, we developed, published and populated the player- and data-driven Guild Wars 2 analytics platform Guild Wars 2: Wingman⁴⁴4https://gw2wingman.nevermindcreations.de/, constructed and refined over a 18-month participatory development cycle (Pfau and Seif El-Nasr, 2023b).

In the following sections, we briefly introduce the environment of Guild Wars 2, report on the acquisition and interpretation of the opinions and requirements of its community, ground these conceptions with empirical data, and extract quantifiable factors that led to the development of a democratic player-driven balancing instrument.

The game used for the subsequent case study (Guild Wars 2) is a prototypical MMORPG featuring single- and multiplayer content in storylines, open world events, various PvP modes and endgame encounters such as raid bosses, fractals or strike missions. The latter make for a large share of players’ time spent in game and as they are set in fixed scenarios with only few probabilistic factors and established group compositions, strategies and roles, they enable very comparable benchmarks. Based on these, large communities formed around discussions and optimizations to overcome these challenges from which balancing discrepancies can become apparent quickly.

As Guild Wars 2 is specifically designed to not feature power creep mechanics such as increasing level caps or item qualities over time, the vast majority of players of this endgame content participates on an identical or very similar character and equipment attribute level, and performance is mainly influenced by in-game proficiency, mastery of the classes, encounter knowledge, strategy and group composition, which further adds to the comparability of the data with regards to balancing. Still, when accepting certain degrees of noise or acknowledging these factors of variance by clustering players into equipment tiers or approximately subtracting out these confounding variables, the balancing assessment as presented here is likely to produce similarly powerful insights for instanced (group) PvE content in general, such as raids, dungeons, trials or ultimate encounters in World of Warcraft(Blizzard Entertainment, 2004), The Elder Scrolls Online(ZeniMax Online Studios, 2014) or Final Fantasy XIV(Square Enix, 2013).

Guild Wars 2 features a variety of playable class options (from now on referred to as professions), where each of the nine core professions can be expanded by particular specializations that can add further capabilities or open up new roles for this profession (e.g. the Ranger profession can be augmented with the Druid specialization to add a support dimension to the character or with the Soulbeast specialization to increase the damage potential). In theory, the professions of Guild Wars 2 allow abundant combinations of character constellations, such as individually distributed equipment attributes, chosen passive character traits and active weapon type and skill choices. In that way, players can represent and play out different roles within their party, such as dealing direct damage, damage over time, offering support or different degrees of mixtures of these factors. However, for the sake of optimization and role compression within the group, most of the time, these builds are min-maxed towards the roles of maximal damage per second (dps), full support (heal and buff application) or offensive support (dps and buff application). The majority of players uses builds and equipment that maximizes their functionality in one of these roles with only situational variation, following community guides and recommendations. Thus, the data-driven procedure in this paper automatically classifies recorded players into buckets of full support, offensive support, direct damage and damage over time. All professions are (in theory) capable of fulfilling all of these roles, yet their viability and efficiently greatly diverge (and differ with respect to the combated encounters), which constantly raises balancing gaps between builds.

For further terminology, the appendix lists explanations for all game-specific terms used across this work.

To sufficiently understand and represent the mindset of a player community regarding balancing, we distributed a mixed-methods survey among all major important communication channels of the affiliated game. These included the official Guild Wars 2 forums⁵⁵5https://en-forum.guildwars2.com/, the /r/GuildWars2 subreddit⁶⁶6https://www.reddit.com/r/Guildwars2/ and several Discords and community portals of beginner/training as well as speedrun groups, such as Snow Crows⁷⁷7https://snowcrows.com/, Lucky Noobs⁸⁸8https://lucky-noobs.com/, Discretize⁹⁹9https://discretize.eu/, Hardstuck¹⁰¹⁰10https://hardstuck.gg/, The Crossroads Inn and other interested communities. In order to capture the essence of players’ stances on balance and balancing discussions, the survey followed a major game update patch (June 28, 2022)¹¹¹¹11https://wiki.guildwars2.com/wiki/Game_updates/2022-06-28 that impacted the viability and performance of almost all available classes and builds. We specifically focused on the requirements to balance professions for the endgame PvE modes of the game (raids, fractals and strike missions), as these are highly comparable between players and groups, and we do not want to confuse potentially differing notions of balancing between PvP and PvE for this article. These instanced endgame modes are executed on the maximal level of the game, require comparable equipment and are designed on an either 5- or 10-player basis. To keep the questionnaire as understandable for the player base as possible, it frequently uses in-game terminology and game-specific notions that are explained in the appendix (A) of this work for comprehension.

The following section reveals quantitative outcomes of the balance survey and qualitative comments on the participant’s decisions and requirements. Subsequently, specific professions and builds are highlighted that deemed to be imbalanced by the community, before data-driven imbalance metrics are adduced for empirical comparison in the next section.

The former quantitative and qualitative analyses of the opinions of the player community revealed a series of insights that mostly went into a similar direction. While these could be utilized to inform balance decisions already, opinionative findings could be warped or biased by the reached sample, diverging experiences and preferences or the influence the recent game update patch might have had on their perceptions of balance. While we claim that a major shift in game balance does not necessarily change the players’ perceptions of balance itself, but rather point out and highlight one’s own requirements, beliefs and understandings of balance, we still declare that empirical foundations should be consulted to evaluate and ideally solidify the community’s views. To approach this endeavor, we adduce data and tools from the largest analytics platform for Guild Wars 2 endgame PvE (Pfau and Seif El-Nasr, 2023b). At the time of evaluation, it comprised ($n_{l}=4,318,009$) recorded atomic boss logs from ($n_{a}=154,145$) unique players and keeps track over the state of balancing and the game in general for the last five years. We deploy measures about the overall usage of different professions throughout the game modes, as well as empirical (dps) performances on actual boss encounters across all available builds.

Balancing video games can follow a multitude of different definitions, approaches and takes. To understand why players are satisfied or frustrated with current states of balance and balancing decisions, we collected notions and understandings of academia and industry, carried out a player-centric survey to assess the game-specific nuances and community-driven requirements based on the former categories, and deployed empirical assessments grounded on an abundance of atomic in-game data logs. Bringing these worlds together, the player base of Guild Wars 2 wants all of its nine professions to be viable, with at least some of their currently three choosable specializations, ideally being able to take the role of a (power or condition) damage dealer or support (questions V1-4, cf. Figure 1). This viability can partially be reflected in the popularity, or usage, these professions show in comparison to their alternatives (cf. Section 6.1). Seeing little to no usage of a profession suggests that their viability is threatened, which most commonly correlates with it being not efficient enough, implying a play style that is too complex or unrealistic to execute in actual boss scenarios, or being dominated by alternative choices that are superior in all or most respects. Some voices expressed that players often rather choose their class in endgame PvE on a preference, flair and style basis, but the significant shifts in profession popularity clearly indicate that balancing decisions and the resulting viability of builds are the driving force of what players bring into raids (and other content) how frequently. This can partly be explained by the optimal performance these professions can achieve under ideal circumstances, but balancing after only top players and performances neglects the vast majority of the player base which should be considered to retain satisfaction throughout the community. Thus, we deployed data-driven assessments of which classes are really lacking viability across the board, based on the performances of hundreds of thousands of players within the weeks of the study period (cf. Section 6.2). Admittedly, viability does not stop at afflicting as much damage as possible to the target encounter, but is highly influenced by the amount of utility a build can provide that potentially increases the offensive or defensive capabilities of other players and/or leads to increases in the success rate of the combat. Nevertheless, when striving for as fast and clean boss kills as possible (which is the most common take players seek to implement), this utility can be either theoretically calculated (by its contribution to the overall group efficiency/dps) or empirically measured (contrasting it to logs without this utility). Thus, the discussed viability assessment strategies (based on dps) do not differ systematically from viability based on dps plus the player’s contribution on group performance. This then reflects the community’s requirements on the equilibrium between “selfish” dps builds and those providing extra utility (questions V5-7).

While players have a high demand for viability across options, they clearly disapprove the idea of symmetry (all professions being equally efficient) (question S1), as this could lead to meaningless decisions, boring and stale gameplay, no room for optimization and the loss of identity. This holds for the damage potentials of the various builds, as they rather like to see spectra of difficulty demands, use cases and applications, but also for the utility builds can provide. Referring to the latter, having unique utility effects is a desirable way of adding identity to classes and diversity to group, as long as it does not limit or constrain the group formation (questions S2,3).

The perception of fairness within the surveyed community does not completely align with the understandings from literature. Summarized, players want to be able to choose builds and professions after personal preference and not necessarily after ideal or optimized performances of other players, even if the former is likely to be impacted by the latter. In a sense, the fair probability of succeeding in the game (Becker and Görlich, 2020) can be loosely transferred to having a just chance to be accepted in other player’s groups, and to being able to defeat a boss encounter with the option of one’s preference. However, this rather subjective topic presumably rests on the perception of viability within the community and for the case of Guild Wars 2, players rather find that the community allows non-optimal builds (questions F1,2) and that expectations on single players usually do not have to compete with high-end professional players (questions F3,4).

Judging from both quantitative as well as qualitative responses, difficulty should be one of the most important, if not the major impact factors for balancing. We note that the community’s understanding of this connection slightly differs from academic perspectives, as for most related work, difficulty is a parameter altered by (automatic) balancing, most often to maximize the player’s perception and duration of flow. In this context, difficulty emerges from the complexity of the play style of the profession or build, its (ideal) rotation, the hardness of maintaining damage uptime and similar factors. In that respect, the output to balance is rather the outgoing damage performance of a player, which preferably should be consonant with this difficulty to incentivize rewarding experiences. To a certain extent, both definitions still align if a game provides enough choosable options with different degrees of complexity and accordingly compensating damage performances, so that by choosing the most suitable option, players balance themselves into the proper sweet spot between boredom and frustration (flow). The community desires accessible gameplay for players throughout the entire proficiency spectrum (question D1), but easier builds should be outperformed by more complex ones (question D2) if players executing those are actually capable of fulfilling the higher demands of difficulty and realizability (questions D3,4). Detecting differences in this conception of difficulty of a class turned out to be suitable when quantifying the variance across performance distributions of single builds (cf. Section 6.2). This assessment is based on the observation and statements about inefficient players producing lower performances when playing more complex builds, compared to executing more forgiving and easy rotations.

Ultimately, the major balance patch released in June 2022 was primarily perceived as a deterioration of the state of balancing, judging from the majority (83%) of negative satisfaction responses to this survey as well as from the overall reception displayed in the previously mentioned communication channels. Interpreting the qualitative and quantitative answers from this community sample and contextualizing these with the introduced changes, the balance patch contradicted the requirements of the player base in multiple ways. This can be attributed to a shift in symmetry, as effects that made a number of classes unique were removed, leading to less diversity in group formation, which is not what players were looking forward to. The same change also impacted a series of power classes higher than condition builds, which significantly decreased their viability and performance outcome distributions, up to the point where (both damage and support builds) were completely dominated by other choices. On top of that, opinions on builds that should have been nerfed were either not fulfilled or even reversed, e.g. the unwelcome buff of the Power Mechanist or the Power Chronomancer nerf that went against their expectations (cf. Section 5.3).The biggest perception of unfairness in balancing was attributed to the mismatch of difficulty and outcome. This becomes apparent when observing the popularity across professions (cf. Figure 3) in which the Mechanist, Firebrand and Virtuoso alone make up the absolute majority of the used options – consistently these builds who are easy to play while afflicting decent damage with high uptime and/or providing massive group utility. This is not only reflected in their popularity, but also in the empirical performance assessment. In the meantime, more difficult professions lost usage as under realistic circumstances, they could no longer compete with performances of simplistic builds and rewarding playing experiences diminished.

Nevertheless, the abundance of qualitative and quantitative feedback from the player community motivated the developers to increase the viability of a series of neglected or negatively affected builds in promptly following balancing updates. This again emphasized the vital importance – but also their validity and appropriateness – of the opinions and requirements of a game’s community. Throughout this work, we compiled the advantages and possibilities of player-driven game balancing from related academic work and qualitative as well as quantitative responses of a player base, as long as they are backed up from empirical evidence data. In immediately succeeding work, we utilized the now extracted insights and measures for the construction of a tool that seeks to overcome occurrences of imbalance (Pfau and Seif El-Nasr, 2023a).

In the following, we will reiterate the methodology of connecting player-driven surveys, data-driven assessments and deriving an instrument towards balancing video game elements, while answering the priorly posed research questions with the help of a case study targeting balance in Guild Wars 2.

Balancing (online) video games adjusts different playable elements for equality, viability, popularity or other factors. In related scientific literature, myriads of (even conflicting) definitions and conceptions of balance and balancing exist (Becker and Görlich, 2020), every industrial game company decides for their own personal strategy (Scacchi, 2017) and above that, balance perceptions of the eventual player bases can deviate from these as well (Schreiber, 2010). This disagreement frequently backfires when balance perceptions of developers do not align with opinions and requirements of the players, which harms player experience, satisfaction, retention and critical as well as economical success of games. Thus, we approach the answering of (RQ1): “With so many conflicting theoretical definitions of balancing, how can a game understand and cater to the requirements of its players?” by a mixed-methods survey grounded in concepts of scientific literature. As the game elements, mechanics and dynamics essentially predetermine which balance concepts are important for a game, we first identified these crucial features with the help of a subset of experienced players (in the case of Guild Wars 2, this resulted in viability, symmetry, fairness and difficulty, cf. Section 4.1). The next step connected these higher-level concepts to in-game terms and ideas that players can understand (cf. Table 1). Together with qualitative assessments, surveys of these can give in-depth insights about how and why a target player base demands, rejects or is indifferent to specified balance concepts (cf. Sections 5.1, 5.2). Regarding our case study, a representative sample of the Guild Wars 2 community deemed multiple viability criteria as important, but strongly opposed that every playable class should produce symmetrical performance outputs or follow similar designs. This equally bears implications for recent scientific work that explicitly balanced towards symmetrical outcomes in the same or similar game genres (Pfau et al., 2022). Above that, in contrast to academic literature on difficulty balancing (Andrade et al., 2006; Tijs et al., 2008; Volz et al., 2016), we observed a clear trend in the community that sees difficulty not as the variable to adjust. Rather, they desire a variety of playable options that differ in difficulty – while the adjusted metric is rather the damage potential (and variance) it can offer, based on that difficulty. Details of these insights, paired with specific perceptions of imbalanced elements (cf. Section 5.3) thus reveal requirements that do not implicitly follow from literature (or even contradict those), which can help developers to understand the needs of their player base and researchers to extend existing notions of balance.

Nevertheless, one of the biggest drawbacks of subjective or opinionative assessments remains in the fact that player perceptions can easily deviate from actual circumstances in the game. This can happen due to unawareness of the big picture, inexperience of the game, effects of echo chambers when steadily playing with the same set of people and obviously because player-accessible higher- and lower-level analytics are not the standard, but rather uncommon for most games (Wallner, 2018). With this in mind, we want to answer (RQ2): “How can data-driven analytics help grounding the objectivity of this pool of opinions?” twofold. First, we present how (subjective) player-driven insights produced by the previous step can be consolidated by means of (objective) data-driven techniques. This can be seen in the changes within popularity of in-game elements (cf. Section 6.1) that go along with players’ perceptions of reduced viability. When locating dominant strategies moreover, relying on theoretical (or ideal) peak performances is a popular method that can give rough first insights, but yet does not always translate to realistic performances in actual combats. More importantly, empirical balance assessments should go even beyond that and incorporate distributions of performances which can reflect measures of difficulty and symmetry from the data (cf. Section 6.2). If these align with the former subjective outcomes, they arguably support prior insights with empirical evidence, fortifying the conclusions for suitable balancing decisions. Second, we aim to support answering this research question by reducing the gap between subjectivity and objectivity of players, so that requirements and opinions follow informed understandings instead of instinctive estimates. To assess how to educate players or entire communities, we introduce an empirical analytics tool for Guild Wars 2 that follows player-driven design and embed the balancing assessments of this work into it (Pfau and Seif El-Nasr, 2023b). This succeeds (position) papers that call for further research on approaches to player-centric analytics for the benefit of both players and science (Kleinman and El-Nasr, 2021; Wallner et al., 2021).

Having subjective as well as objective measures of in-game imbalances and well-balanced target states, we evaluate the integration of both into an interactive instrument in parallel work (Pfau and Seif El-Nasr, 2023a). While the final approach of assessing a player’s opinion of balance (based only on one visualization about performance distributions) is still shallow and an educated perception of balance arguably longs for experiencing the state of the game by playing it a fair amount of time, we still claim to support the assessment and regulation of balance, and strive to evaluate the impact of player-driven balance implementations in live patches. In order to showcase the applicability of this endeavor and to give a hands-on example that player communities are interested in and capable of being incorporated in balancing, we utilized Guild Wars 2 as a fitting, popular and contemporary use case. Yet, the proposed methodology would certainly also work for instanced (group) PvE content in general, such as raids, dungeons, trials or ultimate encounters in World of Warcraft(Blizzard Entertainment, 2004), The Elder Scrolls Online(ZeniMax Online Studios, 2014) or Final Fantasy XIV(Square Enix, 2013). The underlying balance concepts (not limited to viability, symmetry, difficulty and fairness) and the aggregation of a community’s performance requirements however are arguably generalizable and similarly applicable for single-player or competitive PvP settings such as in balancing champions of Multiplayer Online Battle Arena (MOBA) games (e.g. League of Legends (Games, 2009) or Dota 2 (Valve, 2013)) or class-based first-person shooters (such as Valorant (Riot Games, 2020) or Borderlands 3 (Gearbox Software, 2019)) – which yields great potential for player-driven balancing.

The endeavor of balancing, especially with the multitude of playable options, classes and builds of modern online games, is as complicated as finding a convincing definition of balance in the first place. Thus, the presented work undergoes a number of limitations, partly caused by the disparity of the conceptions and partly because of realistic restrictions within the methodology. Finding balanced configurations in a popular world-class video game that would suit requirements of hundreds of thousands to millions of active players without disappointing anyone is arguably impossible. To this respect, we could only reach a comparably minor part of the entire audience of players, even if the sample size is large enough to enable drawing conclusions. In order to accumulate this sample, we broadcasted this survey through the most popular communication channels (outside the game) and made sure to reach players on the full spectrum of game experience, but admit that those players interested in balancing (and in expressing their opinion) were more likely to respond to this survey and might have skewed the results. The topicality of the survey, as directly accompanying a major balance patch, might have activated more players that are unsatisfied with the changes and thus introduced a further bias. However, the gist of this work focuses on the underlying and basic understandings of balancing itself, which should not be systematically changed, but rather clarified within players by conceiving contemporary examples of what should or should not happen in proper balancing procedures. Findings related to the very patch are somewhat discussed, but placed back in favor for implications of (player-driven) balancing in general.

Developers are moreover responsible to push novelty, enjoyment and shifts out of rigidly stuck constellations, in order to keep their game innovative, interesting and economically competitive. We neglected factors of flair, intrinsic motivation of play styles and further variables not inherently related to performance for now, but acknowledge that player choices and preferences are not completely rational (with respect to efficiency and strategy optimization). The significant changes in profession popularity yet indicate that power and viability of choices do have a drastical impact on what players play in endgame PvE.

In their meta review on the definitions of balancing, Becker and Görlich list even further possible concepts appearing in related work, such as chance, (in)transitivity, positive/negative feedback, economies, costs, rewards or static versus dynamic balancing. While some of them turned out to be inapplicable to the domain of endgame PvE in Guild Wars 2, certain factors such as positive and negative feedback can be identified when attributed to the success of playing out an ideal rotation. Future work will look into the intricacies of single builds and rotations to pinpoint the impact of these points onto balancing perceptions instead of involving them simply inside of difficulty.

The biggest critique against utilizing player-driven balancing opinions came from some players themselves that proclaimed that “players do not know what is good for them anyway”. While this might hold to a certain extent and the driving mechanical, dynamical and design decisions should undoubtedly stem from the mindsets of developers, this work counted on the wisdom of crowds of a community, which (when validated with data-driven evidence) produces reasonable and thoughtful insights - often in accord with parallel scientific research. Eventually, balance decisions impact player experience, satisfaction and the critical and economical success of a game over longer terms, so tailoring it to the needs of the actual audience cannot be evaluated enough.

For future work, we mainly seek to extend and unravel the nuances of play styles, builds and implications for balancing. These will be incorporated in the lastly introduced player-driven balancing tool (Pfau and Seif El-Nasr, 2023a) to portray ideal perceptions of balance versus current empirical constellations down to the lowest possible detail. Even though we evaluated this tool in terms of balance perceptions regarding theoretical aggregated configurations, the implementation of such produced balancing decisions into actual gameplay and evaluation of the subsequent player experiences is an important open endeavor. In pursuing this path, we strive to tighten the connection between players and developers – as well as between industry and academia.

Balancing choosable or even customizable options is an interminable, controversial and considerable process for a game, its developers and players alike. Along with the introduction of new content and fixes for bugs, balancing changes are one of the major causes of update patches for online games, display never-ending experience optimization problems and highly impact how players play a game altogether. Scientific efforts to study balance are divided into several understandings of the term, even partly conflicting. When it comes to this definition of adjusting for equated or appropriate adjustments of in-game options, related work is largely under-investigated and mostly regards simulation- or computation-based approaches to even out viability across choices. The role, perception and requirements of the player or even the actual player community have not been considered in academia so far, despite bearing considerable implications for games user research, game design and human-computer interaction in general. For these reasons, we aggregated notions of balance from adjacent research and industrial perceptions, recruited ($n=680$) players of the MMORPG Guild Wars 2 (as a popular representative of online games undergoing constant rebalancing) and refined a game-specific understanding through quantitative as well as qualitative survey items. Analyzing and interpreting the players’ requirements, opinions and mindsets explained their reactions on recently implemented balance changes, enabled collateral data-driven assessments, paved the way for finding community agreements on balancing through an interactive democratic tool and entails (or approves) the following implications that likely hold for comparable games and larger concepts of balancing:

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  Players crave diversity of in-game choices and a high viability across these choices - Balancing should identify and address dominating choices that render alternatives irrelevant.

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  Perfect symmetry between the outcome of choices would implicitly entail balanced viability, but this risks leaving decisions meaningless - so different options should display different strengths, weaknesses, use cases and challenges.

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  Improper balance can evoke feelings of unfairness when common factors such as flair or preference influence players’ decisions - this might lead to decreasing satisfaction or potentially even churn.

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  While most academic approaches manipulate difficulty to balance a player’s flow state, players’ perceptions of difficult choices in online games strongly presuppose rewarding incentives - this does not have to be extrinsic, but should lead to an increased (perception of) efficiency and/or competence.

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  In order to optimize satisfaction and experience, players desire to be part of the balancing process - investigating and quantifying balance requirements in this player-driven process elevates the very player’s role and trailblazes novel approaches of engaging, binding and tailored games.

We thank all participants of the survey for their contribution on player-driven balancing analytics, as well as all users of our platform for sharing their extensive playing histories, constant feedback and ongoing discussions. We moreover are grateful for ArenaNet for developing Guild Wars 2. Guild Wars 2 and all associated logos, designs, and composite marks are trademarks or registered trademarks of NCSOFT Corporation or ArenaNet, LLC, respectively. ©2021 NCSOFT Corporation, ©2021 ArenaNet, LLC. All rights reserved.