=Paper=
{{Paper
|id=Vol-2486/paper-27
|storemode=property
|title=Game Balancing - A Semantical Analysis
|pdfUrl=https://ceur-ws.org/Vol-2486/icaiw_vgameedu_2.pdf
|volume=Vol-2486
|authors=Alexander Becker,Daniel Görlich
}}
==Game Balancing - A Semantical Analysis==
https://ceur-ws.org/Vol-2486/icaiw_vgameedu_2.pdf
Game Balancing – A Semantical Analysis
Alexander Becker1 and Daniel Görlich2
Wolfsgrubenweg 25, 67069 Ludwigshafen am Rhein, Germany
1
Alex@AOWBecker.de
2
SRH University Heidelberg, Ludwig-Guttmann-Str. 6, 69123 Heidelberg, Germany,
Daniel.Goerlich@SRH.de
Abstract. Although balancing a game is commonly considered critical
to its success, there is still no consistent definition of the term “game bal-
ancing.” This paper provides a review of eleven publications by renowned
authors, many of them experienced game designers. It shows that these
authors present different concepts of game balancing, formally analyzes
and discusses these authors’ concepts, definitions, and key aspects, carv-
ing out similarities and differences between them. The paper concludes
that these authors propose concepts suitable for games in general, but
that their concepts differ, that they focus on games made for fun and
entertainment, and that there is currently no definition of “game balanc-
ing” suitable for games focusing on other goals than fun, e.g. for serious
games.
Keywords: Game Balancing · Video Games · Semantics · Concepts
1 Introduction
Roughly speaking, game balancing is the activity of tuning a game’s rules, dif-
ficulty, algorithms and so on to achieve certain goals such as making a game
fair for all players, keeping a game challenging but winnable, etc. But although
game balancing is considered an essential key feature of any successful game [2],
surprisingly there is no consensus on what “game balancing” actually means.
In this paper, we review eleven publications by renowned authors, many of
them experienced game designers, based upon a formal concept analysis [19] as
described in [10], and modified by additional steps. More than 400 properties
were grouped into 48 concepts according to the authors’ descriptions. 22 concepts
that were largely described by more than one author are used as the bases
for a formal concept analysis. We consolidated and visualized the results with
the Online Lattice Editor by [7] using its “Build Concept Lattice (AddIntent)”
and “Min intersection layout (using Cenexp algorithm)” settings. The resulting
structure (see Fig. 1) is used as an orientation to start a discourse, referring back
to properties taken from the sources. The complete tables of objects, concepts,
and properties can be found in [3].
We show that the author’s definitions are diverse, focusing on different goals
and key aspects of game design. Although their concepts of game balancing often
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0)
2019 ICAI Workshops, pp. 344–359, 2019.
Game Balancing – A Semantical Analysis 345
overlap regarding central aspects, every author has a different view, a different
concept, and therefore a different understanding of game balancing.
2 State of the Art
To the best of our knowledge, no extensive semantical or ontological analysis
of the term “game balancing” has been published so far. There are scientific
publications focusing on game balancing and especially dynamic game balancing,
but they do not define the term; instead, they usually rely on definitions from
practitioners. We, therefore, present those before continuing with the state of the
art in scientific publications. We also could not find any publications addressing
game balancing for specific types of games focusing on other goals than fun, such
as, for example, serious games.
Ernest Adams has been a game designer since 1989, is a game design consul-
tant, author of several books on game design, and founder of the International
Game Developers’ Association (IGDA). In [1], he names the player’s skill as the
focus of balancing: Skill, especially in decision-making, should be the greatest
factor in determining a match’s outcome. This is achieved by ensuring fairness
and appropriate difficulty. Former primarily concerns player vs. player (PvP)
games, so every player has an equal chance of winning at the beginning of a
match; latter is crucial for player vs. environment (PvE) to provide constant
challenges without frustrating the player.
Keith Burgun is an independent game designer, author, composer, visual
artist, and author of two books on game design. In [4], he describes game bal-
ancing as the preservation of game elements from irrelevance. This is mainly
done to keep the player’s decisions impactful and prevent dominant strategies
that may ruin the game. Additionally, game elements must be treated within
their contexts and weighed against game elements they compete within those
contexts.
James Portnow is a game designer and game design consultant, known for his
theories on socially positive game design and as co-founder of the YouTube Chan-
nel “Extra Credits.” His channel’s episodes present, among others, the concept
of perfect imbalance: By incorporating subtle power differences between game
elements, players feel constantly encouraged to find slightly beneficial strategies,
instead of solely having to execute proven strategies [9].
Dan Felder is Senior Game Designer at Electronic Arts, having worked pre-
viously for Blizzard Entertainment as a Game Designer on “Hearthstone.” In [5],
Felder locates the main task of balance in avoiding broken gameplay. A game-
play or game design “breaks” when actions or strategies render a huge portion of
decisions meaningless and thereby prevent the positive user experiences games
are supposed to create. Since perfect equality would also render any player’s
decisions meaningless, one important part of game balancing is the creation of
small differences in power.
Jeannie Novak is lead author and series editor of the “Game Development
Essentials” series. In [8] she describes, as do Rollings & Adams in [11], the
346 A. Becker et al.
concept of static and dynamic game balancing. While both aspects still focus
on keeping the player’s skill as the most decisive factor for success, they involve
different parts of a game. Rules, numbers, relations and their interactions are
all part of the static game balance, while dynamic game balancing describes the
real-time balancing in a running game as dependent on the players’ interaction
and therefore does change over time.
Richard Rouse III has worked as a design and narrative lead for Ubisoft
and Microsoft Studios. Using the term “subsystem” to refer to all parts of the
gameplay that interact with each other to form the game, Rouse [12] calls the
dependencies within and between subsystems a major influencer of the overall
balance: Changes in one system almost always affect other parts of the game.
Jesse Schell is former IGDA chairman and currently professor for game de-
sign at Carnegie Mellon University. In his award-winning book, “The Art of
Game Design: A Book of Lenses” [13] he characterizes multiple concepts that
commonly appear in video games and partially contrast with each other, e.g.
challenge vs. success, or skill vs. luck. Balancing is concerned with hitting the
right benchmarks, dependent on the target group, by adjusting combinations of
and relations between game mechanics.
Ian Schreiber began programming and designing games in 2000, has writ-
ten two books on games, is co-founder of the Global Game Jam and assistant
professor for interactive games and media at Rochester Institute of Technology.
In [14], Schreiber investigates the mathematics behind game balancing: Every
game is quantifiable to a certain degree, but those numbers only have meaning
within their given context(s). These numbers and the relations between must
be adjusted in order to achieve a good balance. Additionally, balancing must
also consider players: Their access to information, their ability to process infor-
mation, their expectations and how their behavior might be influenced even by
factors outside of the game.
David Sirlin, president of Sirlin Games, is a game and graphics designer work-
ing mostly on competitive multiplayer games. Sirlin focuses on providing viable
options and fairness to players, especially in multiplayer games [15]. The former
refers to meaningful decisions between promising options; the latter means that
every player has an equal chance of winning at the start of a match.
Tynan Sylvester, founder of Ludeon Studios, has been designing games since
2000 and has written an instructional game design book [16]. He sees balancing
primarily as the act of adjusting the relative power differences of game elements.
The goal is to create multiple viable strategies, so they have equal chances of
success.
There are also a few scientific publications on game balancing which use
or extend the term, often adopting definitions from practitioners: [2], for ex-
ample, Raph Kosters references “A Theory of Fun” [6], concluding that “game
balancing aims at providing a good level of challenge for the user” and keeping
the player interested in playing the game. They evaluate dynamic game bal-
ancing approaches, stating that dynamic game balancing must satisfy at least
three basic requirements, i.e. adapting to the player’s initial level, tracking the
Game Balancing – A Semantical Analysis 347
evolutions (and regressions) of the player’s performance, and keeping the game
“believable.” Their evaluation indicates that adaptive approaches may be more
effective, i.e. result in better user satisfaction, than traditional, non-adaptive,
pre-defined game balancing with static difficulty levels.
Similarly, [17] state that dynamic game balancing is done by adjusting a
game’s difficulty level to a player’s skill level while playing: To be enjoyable,
parameters in the game should be changed to avoid undesired player emotions,
such as boredom and frustration. They argue that the player’s emotional (or
affective) state must be considered by dynamic game balancing so that the game
can become emotionally adaptive.
[18] suggest another approach: incongruity. They also define game balancing
as the adaptation of the game difficulty to a player’s skill or, more precisely, the
relationship between a game’s complexity and a player’s abilities: The player
should be challenged, but not frustrated, by the complexity of the game. They
apply the incongruity theory, trying to avoid letting the difference between the
complexity of a game and the complexity assumed by the player’s internal human
model becomes too large.
3 Semantical Analysis for Conceptual Structuring
Although the beforementioned authors may not seem to be far apart, their con-
cepts differ in many details. Most obvious are their different perspectives and
scopes: Some focus on game design, others already consider more technical per-
spectives. Many authors use terms such as “fairness” or “difficulty” that may also
be difficult to grasp. While all authors emphasize different aspects of game bal-
ancing, they rarely contradict each other. Furthermore, there are some concepts
they commonly agree on, despite sometimes using divergent names or descrip-
tions. Examples are “dominant / degenerative strategies” and “(meaningful)
decisions / (viable) options”. To analyze and compare the presented concepts
of game balancing, we, therefore, need to understand the authors’ basic ideas,
concepts, and assumptions that some of them take for granted, but others try
to define or describe explicitly in their respective publications.
Adams [ [1], p. 403] links balance essentially to the player’s skill: “In the most
general sense, a balanced game is fair to the player (or players), is neither too
easy nor too hard, and makes the skill of the player the most important factor in
determining her success.”Adams thereby adopts fairness, an inherently subjective
concept, as a general goal, and links fairness to the player’s “skill”—another
term that requires more consideration. To Adams, it is generally important that
chance must not be powerful enough to make skill irrelevant. To achieve that,
the game design should allow the player to make meaningful decisions, so that
the outcome of the game primarily depends on the player’s decisions [ [1], p. 404].
Game design must, therefore, avoid so-called dominant strategies, i.e. strategies
that do not need to be infallible but are so strong that they leave players no
reason to use any other strategy. Thereby, they make alternatives worthless and
render the player’s decision meaningless [ [1], p. 405f]. Even singular decisions
348 A. Becker et al.
or the mere avoidance of losing the game can be considered dominant strategies
[ [1], p. 405], as well as so-called “exploits”, which trivialize parts of a game [ [1],
p. 410f]. Sylvester calls dominant strategies “degenerative strategies” [ [16], p.
160] and warns that adding new game elements does not always create more
meaningful decisions; indeed, it might do the opposite [ [16], p. 159].
Depending on (in-)transitivity of involved game elements, Adams sees nu-
merous ways to avoid dominant strategies. “Transitivity” applied to relations
between game elements means there is a transitive order in power or useful-
ness: If one game element outclasses another, it also outclasses elements inferior
to the latter. In the opposite case of intransitivity, every game element can be
beaten by some other, which supports the avoidance of dominant strategies. To
avoid dominant strategies within a transitive relation, one can change costs or
use positive feedback. Costs might be outright stated prices, but also “shadow
costs” like hidden detrimental properties [ [1], pp. 406-407]. Positive feedback
describes giving the player rewards to accelerate future progress [ [1], p. 408]
without creating a sure-fire course [ [1], pp. 429-430].
Furthermore, Adams recommends assessing intransitivity in the elements’
properties, as is the case in rock-paper-scissor, instead of defining superiority.
This can be achieved by giving elements unique traits that cannot be solely
compared by their values. Adams calls this “orthogonal unit difference” [ [1], pp.
408-410].
Adams also delivers specifications about chance, which should only impact a
few actions that are relevant for the player’s victory. Many chances with little
risk are generally preferable to a small number with high stakes, so outcomes
tend to stay closer to expected values. Also, the player should receive crucial
information about the chances and be able to control how much of a risk they
take [ [1], pp. 411-412].
Besides general criteria, Adams distinguishes between priorities for PvP and
PvE games: Those are fairness and remaining able to win throughout the match
for PvP [ [1], p. 404] vs. difficulty for PvE games [ [1], p. 405]. While playing
a match in a PvP game, any player should have opportunities for a comeback,
if he or she falls behind early on. Stalemates, the inability to win or finish the
game properly, should be avoided [ [1], p. 404]. But most importantly, a PvP title
must be fair. Adams defines fairness as all players having a roughly equal chance
of winning at the start of every game. Fairness should always be granted [ [1], p.
404], e.g., by accordingly balancing starting options, protecting newer players, or
providing game updates [ [1], pp. 414-416]. In symmetrical games that provide
identical starting conditions to all players, fairness is already given. Most games,
however, come with varying prerequisites and are called asymmetrical, which
makes them more prone to developing dominant strategies [ [1], p. 413]. Sirlin also
adds a scale to the concept of (a)symmetrical games: While symmetry is a fixed
condition, a game can be more or less asymmetrical. The more asymmetrical a
game is, the more important maintaining fairness becomes [ [15], p. 1].
Difficulty in PvE games is strongly connected to the players’ expectations
and requires consistency [ [1], p. 405]: Sudden jumps should be avoided as well
Game Balancing – A Semantical Analysis 349
as stalemates and losses the player could never have prevented. Also, impor-
tant decisions should be marked as such and all necessary information to finish
the game should be accessible [ [1], pp. 416-417]. All this serves the purpose of
bringing the player into a state of flow. However, expectations of and require-
ments for this can vary immensely between audiences [ [1], pp. 418-419]. Adams
subclassifies “difficulty” into three parts:
1. Absolute difficulty. The combination of required skill and time restrictions.
It highly correlates with the game’s numbers, such as enemies’ strengths and
maximum health points [ [1], p. 420].
2. Relative difficulty. What is left when the player’s power is subtracted from
the absolute difficulty [ [1], pp. 420-421].
3. Perceived difficulty. Also, takes the player’s experience into account [ [1], p.
422].
Ideally, the perceived difficulty stagnates or increases throughout the game ac-
cording to the target group’s preference. The relative difficulty has to grow faster,
since the player’s experience also increases. The absolute difficulty has to rise
even faster, while the player gains more power [ [1], pp. 423-424]. Also, the player
should be able to adjust difficulty somehow, so the game covers a wider audience
[ [1], pp. 425-426].
While Burgun [ [4], p. 2] primarily addresses multiplayer games, he includes
single-player games in most of his statements, especially if they are supposed to
have replay value. Generally, a well-balanced game stays interesting for longer.
His definition focuses on choices [ [4], p. 1]: “Gameplay is all about making choices
and in a poorly-balanced game, many of the choices available to the player are
essentially rendered useless.” He argues, as does Adams, that dominant strategies
can render other strategies useless and game elements irrelevant. Whether, a
strategy is dominant or not, however, can depend on the player’s skill, especially
in more complex asymmetrical games. Therefore, the target group should be
taken into account when setting a balancing goal. While tailoring to all audiences
would be ideal, this is too intricate. The effort rather should focus on one group,
e.g. competitive players [ [4], p. 2].
Furthermore, game elements must be balanced within all contexts they oper-
ate in. This includes, for example, costs compared to other elements in the same
production line, their usefulness when competing with opposing elements, but
also their power about others that prohibit or limit each other’s use [ [4], p. 1].
This contest on multiple layers takes place even in symmetrical games, although
they typically include fewer contexts since all players use the same selection of
elements [ [4], p. 2].
James Portnow of Extra Credits [ [9], 0m34s] summarizes his concept of per-
fect imbalance as follows: “Fundamentally, it is the idea in game design that you
don’t always want things to be perfectly balanced. In fact, in most games, you
actually wanna make sure that there are some imbalances in your systems. (. . . )
many games are actually made far more engaging by just a little bit of imbalance,
multiplayer games especially.” Portnow highlights that those imbalances refer to
350 A. Becker et al.
subtle differences, not huge gaps in power [ [9], 0m30s-1m00s]. The distinction
between “out of balance” and “broken” is crucial: No strategy or game element
should be much stronger than the rest, but only slightly. These subtle variations
in power can be measured and adjusted with the help of a “power curve”, a rela-
tion from cost to power for game elements [ [5], 3m35s-4m20s]. In the metagame,
which is basically the situation or context in which the game is played, such an
imbalance allows for discussions, discovery and therefore fun, while players try
to find slightly advantageous strategies. They can even find new solutions for
problems of their current state of play without having to know all established
strategies. The resulting metagame allows players to grow into the game and
prevents any playstyle from becoming the best [ [9], 2m45s-3m35s].
In contrast to a perfect imbalance, in (almost) perfectly balanced games like
chess, the best strategies are discovered sooner or later. At that point, most
players are left with nothing but executing those instead of creating their own
strategies. Only the best players could still find new strategies that are not
already established. This removes part of the fun for a huge portion of the
audience [ [9], 1m00s-2m45s].
Felder [5] bases his view of balancing on the avoidance of imbalance: “I’ve
found that the most useful definitions of balance are based on what we’re trying
to avoid: Broken Gameplay. (. . . ) When you’re designing a game you naturally
want to create a positive experience for your players. When your gameplay isn’t
providing that experience, your game is broken. It’s that simple.” An example
of something broken would be a strategy that makes all others obsolete, and
therefore a lot of decisions, if not all of them, broken. However, the exact oppo-
site would also render decisions useless: If every option was equally good, there
would be no reason to prefer one. Instead, subtle differences in power allow for
strategic decision making. Using a power curve also benefits the balancing of
game elements that are introduced later [5].
Novak [ [8], p. 202] relates balancing to the player’s skill: “The ease of winning
the game also increases as the players’ skills increase. Random events (e.g. a
meteor hitting the area, destroying a player’s resources) can still occur in the
game that might decrease a skilled player’s chance of winning. However, a better
player should be more successful in general at the game than a less-skilled-player,
unless the game is based purely on luck instead of skill.” Considering the desired
results of balancing, Novak concludes: “A game is balanced if players perceive
that it is consistent, fair, and fun,” implying that perceived quality of game
balance may be subjective.
Without using potentially subjective terms, Rollings and Adams [ [11], p.
240] similarly state that “A balanced game is one where the main determining
factor for the success of the player is the skill level of that player. That does not
mean that random events cannot occur, but a better player should ordinarily
be more successful than a poor one unless he has an unusually long run of bad
luck.” While not identical, [8] and [11] have a similar focus. They name criteria
found in well-balanced games:
Game Balancing – A Semantical Analysis 351
– The game becomes consistently more challenging [ [8], p. 202ff] until the
climax [ [11], p. 272].
– The player perceives fairness by always being able to win, even after early
mistakes [ [8], p. 202ff]. This perception extends to offering the player infor-
mation, control, training, and beginner protection. Unnecessary repetition
of tasks should be avoided [ [11], p. 272-276].
– No unsolvable situations that lead to the player being stuck [ [8], p. 202ff]
or lacking the information to continue [ [11], p. 276f].
– No trivial decisions. These are decisions that have no impact, or one alter-
native is clearly the best [ [8], p. 202ff]. Additionally, micromanagement –
the act of administering a high number of small elements – should never be
mandatory, only optional [ [11], p. 277-279].
– Adjustable difficulty [ [8], p. 202ff] [ [11], p. 279-281].
Beyond general criteria, they continue their investigations of static and dynamic
balancing. Static balancing is concerned with the game’s rules and how they
interact. Its main goals are to avoid dominant strategies [ [11], p. 243] and
provide fairness [ [11], p. 267]. Rollings and Adams contribute two new aspects
to dominant strategies: A strongly dominant strategy always wins the game,
while a weakly dominant strategy prevents a loss. Other than the former, the
latter can be beneficial to the game. Furthermore, an “almost dominant strategy”
does not always win the game but is still the best option available under any
circumstances [ [11], p. 244ff]. Novak describes another strategy-related concept
a game should include, so-called “obvious strategies”. These are strategies that
are generally the best, but explicitly not under any circumstances [ [8], p. 203].
Game elements with transitive relationships to each other are useful as rewards
for progress [ [8], p. 204] [ [11], p. 252ff], while those with intransitive relationships
profit from having orthogonal unit differences [ [11], pp. 258-261]. The latter
should not contradict the narration of the game and its world, Novak adds [ [8],
p. 205].
Dynamic balance covers how the game changes over time and with player
interaction [ [8], p. 207]. It can be done passively or actively to prevent unfair
advantage [ [11], p. 267]. Players interact with the dynamic balance in three ways
[ [8], p. 207]:
1. Restore balance. The player restores a disturbed balance. De-balancing forces
are weaker than the player or can be removed [ [11], p. 269].
2. Preserve balance. The player repels de-balancing forces. Those are at least
equally as strong as the player. There is no win condition and the player
loses when doing nothing [ [11], p. 269ff].
3. Destroy balance. The player alternates the state of balance or creates chaos
[ [11], p. 270ff].
Rollings and Adams continue with “emergence”, the creation of complex results
using simple rules. A world can be simulated by reduction to basic properties
and still deliver the targeted experience. This reduces complexity and preserves
352 A. Becker et al.
control for the player but might favor the formation of dominant strategies [ [11],
pp. 262-265]. There is also a reverse version of positive feedback called negative
feedback, which limits progress or leadership, e.g. by adding further costs [ [8],
p. 206] [ [11], pp. 265-267].
Rouse [ [12], p. 493] describes games as systems composed of subsystems: “In
order for the game to be balanced, all of these [sub-]systems must be in place,
since changing one system impacts how the other systems must be set up in
order to achieve the overall balance you are seeking.“ He distinguishes between
provisional and true balancing. While the former creates a balanced foundation,
the latter uses this basis mainly to adjust numbers to deliver a quality game.
Playtester feedback is crucial for this iterative approach [ [12] , pp. 493-494]. It
is also necessary to understand the relations and influences within and between
one’s own systems to avoid unintended consequences, while being able to quickly
iterate values within the game [ [12], p. 495].
Schell [ [13], p. 202] states that “Balancing a game (. . . ) is all about under-
standing subtle nuances in the relationships between the elements of your game
and knowing which ones to alter, how much to alter them, and which ones to
leave alone.” He continues with various patterns that frequently appear and are
partially opposed to each other. Some of them are:
– Challenge vs. success. A game should neither be too easy nor too difficult.
The goal is to keep the player in a state of continuous flow. However, learning
rules and controls are already challenges in themselves [ [13], pp. 207-209].
– Skill vs. chance. It is commonly good to have both in a game to a certain
degree, dependent on the audience [ [13], p. 214f].
– Strategy vs. dexterity. The best ratio depends on the audience [ [13], p.
215ff].
– Competition vs. cooperation. Although many games contain just one, they
can appear combined [ [13], pp. 216-218].
– Short vs. long. Via changing win conditions, players should have enough time
to strategize, but never get bored [ [13], p. 219].
– Rewards vs. punishment. Rewards are a human desire. The rewards must
increase over the course of a game to keep the player interested [ [13], pp.
219-222]. Although rewards should generally be preferred, punishment can
also enhance the experience, e.g. by increasing the challenge [ [13], pp. 222-
225].
– Simple vs. complex. It is generally better to create complex results using
simple rules, but small case-specific additions might still be beneficial. The
former makes a game “elegant” and can be referred to as “natural balanc-
ing”, while the latter is called “artificial balancing”. Games should neither
be unnecessarily complex nor simple to the point of being trivial [ [13], pp.
226-230].
Despite all details being important, Schell emphasizes the big picture: The game
should feel right. If it does not, one should ask and search for the causes [ [13],
p. 237].
Game Balancing – A Semantical Analysis 353
Schreiber [ [14], p. 1] follows a mathematical approach: “While perhaps an
oversimplification, we can say that game balance is mostly figuring out what
numbers to use in a game.” It is important to understand that every game
contains numbers, even if these are not stated outright [ [14], p. 1], and that
numbers only have a meaning within a context [ [14], p. 2]. These numbers are
connected within greater systems that are divided into subsystems, like combat
or economy [ [14], p. 2].
He differentiates between “deterministic” and “non-deterministic” games.
Former always produces the same outcome dependent on the action in a certain
state; the latter does not, due to chance or other players’ actions. “Solvability”,
which means that in every situation, there is a recognizable best action, is gen-
erally undesirable to have in a game since it renders decision-making obsolete.
There are different levels of solvability, starting with trivial, which can be solved
in real time. Others are theoretically solvable but require too much calculation
to be solved within an acceptable time frame. However, even non-deterministic
games are solvable. While every game that provides perfect information about
its state is theoretically solvable, one can limit the players’ access to information.
This might be affected by the metagame [ [14], p. 1].
Another dimension to balancing is costs. Costs are everything that limits
access to advantages or interferes with them. The advantage is basically every-
thing that benefits the player. We can view costs as negative advantages and
vice versa. They can be calculated as such to create a cost curve [ [14], p. 3].
Schreiber adds that shadow costs can be divided into two concepts: Sunken costs
and opportunity costs. The former describes prerequisite costs that are indirectly
related to the stated costs, while the latter limits the player’s future possibilities
once s/he has spent the stated costs [ [14], p. 6].
Schreiber also adds to the concept of rewards. Regularly giving out smaller
rewards should be preferred to fewer larger ones. Players prefer randomization,
as long as it still feels like the result of their actions. Rewards and progress
should support each other, and popular rewards should not be held back [ [14],
p. 7].
“Economic systems” are another topic Schreiber addresses. These comprise
any resource of a game and typically involve the following mechanics for re-
sources: Generation, destruction, trading and limited zero-sum. In-game economies
can exhibit traits and interactions similar to real economies and marketplaces.
Open economies allow outside intervention, such as buying resources with real
money, while closed economies do not. Each should be designed differently [ [14],
p. 10].
Sirlin [ [15], p. 1] focuses on balancing multiplayer games: “A multiplayer
game is 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 play-
ers.” In addition to fairness, “viable options” must be provided. This refers to
meaningful decisions between promising options and excludes the existence of
dominant strategies. Meaningless decisions unnecessarily increase complexity;
only meaningful ones benefit a game [ [15], p. 1]. However, despite the need for
354 A. Becker et al.
fair starting conditions, a game does not have to be completely balanced within
every state of the game. On the contrary, imbalanced states can be situationally
desired, e.g. by giving rewards for playing well. He continues that “checkmate
situations”, in which one player is clearly going to lose, should generally not
arise. Although manifold games are generally desired and provide many bene-
fits such as counter elements and actions, no game element should be worthless.
Worthless elements never provide meaningful decisions [ [15], p. 2].
Sirlin further discusses the concept of fairness: Comeback mechanics are help-
ful to prevent unforeseen balancing issues. Also, new game elements should be
introduced after a balanced basis is created, and banning certain elements or
combinations subsequently, e.g. for tournaments, is highly undesirable. When a
power curve is used, it should be noted that the exact ratios between power val-
ues are not necessarily provided. Also, decisions, that are made at the beginning
of a match or game should not determine the outcome right away [ [15], p. 3].
Sylvester [ [16], p. 155] extends the importance of power to strategies: Balanc-
ing “means adjusting game mechanics to change the relative power of different
tools, units, strategies, teams, or characters.” In addition to being fair, games
need to be deep which refers to meaningful play even at higher skill levels: Even
experts must be uncertain as to the best option in a given situation. To achieve
this, strategies should be balanced. A strategy is a specific combination of ac-
tions a player can choose from to achieve a certain goal [ [16], pp. 157-158].
Multiple viable strategies must be offered; even two can be enough though, since
adding more decisions, even meaningful ones, can increase complexity without
making the game deeper [ [16], pp. 161-162]. A difficulty in balancing strategies
comes from having to change game elements which are typically part of multiple
strategies, to affect a strategy [ [16], p. 166].
4 Discussion
Having analyzed the semantics behind the abovementioned authors’ concepts
of “game balancing”, we will now look for similarities and differences in their
concepts and will then move on to a discussion of these. The complete formal
concept analysis including all tables of concepts, properties, and formal objects
(see example in Table 1) is available in [ [3], pp. 163-202]; its results are visualized
in Fig. 1.
This diagram shows which author covers which concepts, and which concept
is covered by which author. Also, coupled occurrences can be identified. The
Table 1. Exemplary extract from the table of formal properties from [ [3], pp. 163-202]
Authors Formal Formal Objects: Game Balancing according to
Concepts Properties Ad No RA Ro SII Sy Bu Po Fe Sr Si
Asy- Asymetrical games
metrical give players different No SII Bu Si
games starting conditions
Game Balancing – A Semantical Analysis 355
Fig. 1. Conceptualization of “game balancing” as a lattice form diagram created with
[7]
356 A. Becker et al.
higher on top a node appears in the diagram, the more authors and fewer con-
cepts it contains, and vice versa. Only the green nodes are labelled since they
mark the fundamental level on which an author or concept occurs. The line “Au-
thor(s):” is only listed above “Concept(s):” if the node contains all concepts of
at least one of its authors, it shows his or her first appearance. Smaller nodes
indicate a combined appearance and can be used to follow connecting lines.
The diagram reveals countless implications, among them: No concept is cov-
ered by every author, which means that there is not even a consensus about one
concept being the singular essential core of the term “game balancing”. No author
covers all concepts; instead, Schreiber, Novak, Schell, Rollings and Adams, Sir-
lin, and Burgun each introduce combinations of concepts no other author covers.
These implications corroborate our original impression that there is no compre-
hensive definition of the term “game balancing.” There is not even a common
foundation or central core concept for the term, although often several authors
employ the same or similar concepts.
Surprisingly, concepts such as fairness, flow, or user satisfaction appeared
to be important, but there were no central or fundamental concepts for the
definition of game balancing. However, there is a basis of only four concepts
that are not exclusively covered together with specific other concepts, but which
are shared by many authors and connected with many other concepts: Difficulty,
balancing (as a purposive act or process), symmetry, and characteristics of well-
balanced games. Therefore, we will now continue discussing these qualitatively.
Characteristics of a well-balanced game: While various characteristics meet
explicit approval, such as avoiding stagnation (3/6) and allowing the user to
make meaningful decisions (3/6), some aspects are still vague. One such aspect
is when something becomes “stagnant”: Even though the player should not have
to unnecessarily repeat tasks, no boundaries are given when repetition becomes
a problem; after all, games do feature tasks that can or must be repeated in order
to progress or improve something. While examples are given such as having to
repeat easy parts, no rule or definition applies generally. Additionally, there is no
comprehensive definition of the commonly used term “skill”: Though there is an
implicit distinction between skill as “decision-making” and skill as “dexterity” in
executing actions, skill is rather the presumed entirety of influence a player has
on the course of a game rather than a well-defined term. This leads to further
problems within the concept of “difficulty.”
Concerning meaningful decisions, all authors (3/3) underline their impor-
tance and describe meaningless decision-making as useless or even harmful to a
game. However, there is no exhaustive definition of what a “meaningful” decision
exactly is; instead, it is circularly defined as not being meaningless. The type
of meaningless decisions that only provide weak options plus one option that
is clearly the best, can also lead to dominant strategies. If these are obviously
dominant, Sylvester even calls them “degenerative strategies.” Those authors
who talk about any sorts of strategies agree that dominant strategies should
generally be avoided (7/7).
Game Balancing – A Semantical Analysis 357
Difficulty: Which difficulty level may be right is assumed to depend on the
players’ perception, the players’ skills and how quickly their skills improve (5/5).
Although skill and the individual perception of skill are somewhat subjective
quantities, they must be mapped onto in-game numbers that can be calculated
and manipulated. Several authors (2/5) explicitly name on the goal of keeping
the player in a state of flow. To achieve this, the perceived difficulty must be
right, by staying the same or steadily growing.
Symmetry: Most authors (5/8) state that symmetrical games are automat-
ically fair. Many modern games, however, are asymmetrical, which leads to a
higher balancing effort. Sirlin appears to be the only author to explicitly state
that a game can be more or less asymmetrical. Fairness is an important con-
cept, most authors agree. However, Adams and Sirlin especially emphasize the
importance of fairness for multiplayer games and also state that fairness alone
does not provide a well-balanced game.
Balancing: The high number of methods and means for balancing games may
be an indicator of the lack of agreement on the actual goal of balancing, i.e. the
pursued state of game balance: While no author denies that huge imbalances
are bad, smaller ones can be accepted. Not only that: Portnow and Felder even
state that a slight imbalance might be more beneficial than perfect balance.
They primarily base their view on a perfectly balanced game offering little to no
reason to try something other than proven strategies, or all options being equally
good; therefore, the decision between those options does not matter anymore.
However, it is unclear if this is the only solution, or if players can have other
reasons to use or try different strategies. This might be connected back to the
concept of meaningful decisions not being fully grasped yet.
5 Conclusion
Our analysis of eleven renowned authors’ concepts of game balancing revealed
that their concepts are clearly different. Although the authors usually agree
on certain aspects, for example, that games should provide meaningful decision
options to the players, there is no central aspect, no central goal of balancing that
all eleven authors focused on in their respective books, texts, or videos. Often,
the authors are not far apart, though: For example, while Novak, assuming the
players’ perspective, concludes that a “game is balanced if players perceive that
it is consistent, fair, and fun”, Schell advises keeping the player in a state of
continuous flow, and Koster concludes that “game balancing aims at providing
a good level of challenge for the user.”
Going into detail, it becomes obvious that some authors focus on certain
types of games (e.g. Sirlin and Burgun on multiplayer games), while others try to
address games in general (Adams, Schell, etc.). All of them, however, talk about
games made for fun and entertainment, but not about games made for other
purposes: serious games, health games, exergames and others that might need
to be balanced towards achieving goals other than fun. Still, the authors’ different
perspectives already lead them to differing concepts about game balancing.
358 A. Becker et al.
Our analysis, however, also revealed that never all, but at least most authors
focus on four aspects of their respective game balancing concepts: the charac-
teristics of well-balanced games, difficulty, symmetry, and the balancing process
itself. Combining these authors’ opinions on the characteristics of well-balanced
games, meaningful decision options, player skill, and the prevention of dominant
strategies seem to be pivotal. Combing their opinions on difficulty and sym-
metry, most authors seem to agree that finding the right level of difficulty is
essential; that the difficulty should stay the same or grow steadily, according to
the player’s increasing skill; that fairness is inherent to symmetrical games but
must be ensured in asymmetrical games alike; and that fairness alone does not
make a game well-balanced.
However, concerning the balancing process and the available means to bal-
ance games, the authors’ opinions and concepts differ. While many authors seem
to strive for some sort of “perfect” game balance that must be fixed before a
game is released and played, others argue for intentional imbalances and dynamic
balancing. Though it is obvious that the balancing process is of utmost interest
to renowned game designers wanting to share their knowledge and experience,
their concepts about the balancing process itself are diffuse: They present many
aspects and ideas, ranging from feedback loops and the transitivity of game ele-
ments to chance and metagame—but no author presented a practical, clear, and
concise abstraction of an actual game balancing process.
We, therefore, conclude that further research is required to develop a com-
monly agreeable definition of “game balancing” and a suitable abstraction of a
practical game balancing process.
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