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开发者谈量化分析游戏深度和上手性的方法(一)

发布时间:2019-10-18 09:15:47 Tags:,

开发者谈量化分析游戏深度和上手性的方法(一)

原作者: Tobias Karlsson 译者:Vivian Xue

这是一篇由三部分组成的系列文章的第一部分,本系列旨在介绍一种审视、分析和比较游戏深度及上手性的方法。第一部分概述了此方法的内容,第二部分详细介绍了该方法,第三部分将运用该方法分析具体实例。

一、为什么需要这项工具?

你的新游戏加了绿光计划,一款休闲战术性射击游戏,并且具备吸引硬核玩家的深度。尽管目前每个人都对这款游戏很有信心,但大家都清楚这个游戏对工作室来说是一个很大的赌注,无法交付该游戏将造成严重的后果。随着项目开发的进行,问题出现了:你一年后正在进行的项目、或者两年后准备交付的项目还能符合最初计划的深度和复杂性吗?它足够休闲,不至于吓跑新玩家吗?它具备你所承诺的深度吗?如果你增加了功能X,它会使游戏过于复杂吗?如果会,你能否通过删除其它功能使游戏恢复休闲水平?更不用说,你的游戏和其它竞争产品相比怎么样?

这些是困难但关键的问题,你必须在把游戏交付给玩家之前回答它们。你可以使用经验和直觉,但当你投入到开发过程中时,你很难准确评估自己的游戏,你需要一个更精准客观的方式分析游戏。本系列文章介绍了这样一种方式,它能帮助你分析和比较游戏,以及评估你的功能将如何影响游戏的上手性和深度。

Warhammer Age of Sigmar: Realm War(from pocketgamer.biz)

Warhammer Age of Sigmar: Realm War(from pocketgamer.biz)

二、概念的定义

首先,我将更准确地定义本文使用的术语,在游戏设计中,许多概念都很模糊、主观,以及/或缺乏对严格定义的一致认同。本系列文章将涉及游戏的复杂性、上手性、深度,以及“掌握游戏”这个概念。所谓复杂性,我指的是游戏规则以及在此规则下玩家可能采取的行动共同产生的复杂性。请注意,游戏规则产生的复杂性和玩家行为产生的复杂性并非相互依赖。围棋的规则很简单,但玩家可采取的行动不计其数,因此围棋作为一款游戏,具有高度复杂性。游戏的深度和其复杂性紧密相关,但它不是以游戏规则的复杂性来衡量的,而是玩法的复杂性。若玩家在游戏过程中只能使用一种解决方案,则此游戏缺乏深度。高深度的游戏允许并要求玩家运用大量策略和筹码,玩法千变万化。复杂性和深度不是一回事,不过缺乏复杂性的游戏往往也缺乏深度。“掌握游戏”指理解游戏的复杂性和深度,包括理解任何情况下相关的规则,明白针对该情况可采取哪些战术策略。当然,掌握程度有高低之分,一种了解玩家掌握程度的方式是观察她/他所能完成的关卡。最后,游戏的上手性是根据玩家为达到某种掌握程度所需要付出的努力多少来衡量的。游戏的上手性由复杂性和深度共同决定,但它也受到一些其他因素影响,比如游戏规则的易懂程度,玩家在正式开始游戏前需要学习的知识。

三、方法概述

本文介绍的方法的基本思维是衡量玩家完全掌握游戏需要付出多少努力,完全掌握游戏意味着完全理解游戏的规则、机制以及战术策略。正确运用此方法,你将能够快速通过数据比较两款游戏的特点,并检查你正在开发的游戏与预期目标是否一致。在开始介绍前得提一句,如果你想获得真正客观的数据,特别是能够经受学术审查的数据,没有捷径,你必须收集足够多的客观数据,并对它们进行严格的统计分析。我相信本文介绍的思维对这种严格分析将有所帮助,但我想大多数读者不需要这么严谨。相反,我建议你们把这种方法当成一种分析和比较游戏的视角,以此弄清游戏成功(或者失败)的原因。

为了便于读者使用此方法,这里要介绍一种很可能更常用的数据呈现方式,它将帮助你一目了然地比较两款游戏。这是通过堆叠使用统一颜色编码的标准化数据实现的(见图表1)。这些图表展示了从“努力”到“掌握”的过程,即游戏1、游戏2和游戏3的上手性。每条色带代表一定程度的努力,而色带高度代表经过这种努力达到的掌握程度。注意,由于Y轴代表掌握程度,每一列都具有相同高度,这意味着玩家在经过这些努力过后完全掌握了游戏,即100%。

掌握游戏的过程分为3个阶段:学习阶段(pre-play phase)、游戏阶段(playing phase)和钻研阶段(Research phase)。学习包含了自主领悟(innate understanding)和教程(Tutorial)两个部分。

若游戏是基于玩家对外界所了解的知识而设计,玩家就对游戏比较了解,这就形成了玩家的初始技能。举个例子,一款军事类游戏的规则通常源于真实世界的战斗和武器原理。枪支的弹药夹容量有限、需要重新补充,步枪的有效射程比手枪长,等等。游戏可能还会遵循同类作品建立的普遍规则,例如操作方式,使用补给将立即恢复血量等。依靠初始技能的一个好处是玩家可以节省学习部分内容的时间,这样游戏就能在维持上手性的基础上增加复杂性。注意,翻转棋或者游戏2这样的抽象游戏不涉及人们日常所能了解的知识,因此玩家无法自主领悟。

教程包括阅读规则、通过其它玩家了解规则,或完成教学关卡。注意有些游戏没有教程,直接让玩家开始游戏,而有些游戏的教程分布于游戏全程而非仅在开头。此外,只有电子游戏可以省略教程阶段,因为玩家可以通过玩游戏习得规则,这是实体游戏不具备的特点。在图表1中,游戏1和游戏2都通过教程使玩家相当好地掌握了游戏。

下一个是游戏阶段。我将此阶段分为4个部分:游戏0.5小时后、2小时后、5小时后和10小时后,它们对应了玩家花费相应时间积极地打游戏后的掌握情况。根据图表1,10小时后,玩家能够完全掌握游戏1,但只能了解游戏3的表面。

这些时间划分,包括钻研阶段的时间划分比较主观,并且我在分析时选择了我个人感兴趣的游戏。你可以根据你想要分析的游戏类型调整划分方式,但记住若使用相同的时间划分,你只能比较两款游戏。

最后是钻研阶段。到这个阶段,玩家通过单纯地打游戏得到的收获越来越少,他们会更积极地提高自己的掌握程度。钻研包括试验新的战术、阅读各种攻略、拜师、深入分析规则。钻研阶段分为5个部分:5小时后、10小时后、20小时后和“无尽的”钻研(20小时后)。

清楚了解图表的含义后,我们就很容易比较这三款游戏了。随便看一眼都知道这三款游戏很不一样。玩家在一段时间后可以完全掌握游戏1,而游戏3需要玩家花费相当长时间才能掌握。游戏2介于两者之间,玩家花点时间可以打得很好,但想完全掌握它需要付出额外的精力。

显然,我们可以看出这三款游戏大不相同。尽管比较不同的游戏很有趣,但在实际分析中,我们往往希望比较相似的游戏。假设游戏4和游戏5是两款非常像的游戏,通过图2我们可以看出,即便玩家完全掌握它们需要付出的努力大致相等,掌握部分游戏需要的努力差异很大,更不用说游戏5的教程教学效果更好。

四、游戏案例分析

让我们通过几个例子来理解如何运用这种方法分析游戏。先来看游戏井字棋(Tic-Tac-Toe),这是一款抽象游戏,因此玩家无法通过观察棋盘了解游戏方式。然而,在了解规则(教程阶段)后,我们可以认为玩家完全掌握了规则。了解规则是一个良好开端,但玩家仍需要学习下棋的最优策略从而完全掌握游戏。懂得如何使用最优策略后,玩家最差也能打个平局。大多数玩家很快就能掌握该策略,特别是和懂得该策略的玩家玩上几局后。通过分析该游戏我们可得到下图。

你一眼就能看出井字棋是个很浅显的游戏。玩家在清楚了解规则后能够靠自己理解它的复杂性,在玩了一小会儿后,大多数玩家都能完全掌握游戏。这不能说明游戏本身是否有趣,但堆叠图长这样的游戏不可能具备长久的吸引力,至少不可能仅通过玩法留住玩家。

接着我们来看另一款游戏,五子棋(Pente)。五子棋是围棋的变体,规则是拦截对手的棋子,率先达到五子连珠。游戏规则相当简单,几分钟就能学会,大多数人很快就能学会基本策略,例如避免自己的棋子被拦截,在对手形成四子连珠前拦截,不让对手形成两个开放的三子连珠。然而,和井字棋不同,掌握五子棋的最优策略并不容易,并且随着游戏的进行,玩家将发现更多策略、更多可利用的机会或者可避免的危险情况。

随着玩家花更多时间游戏,她/他所得到的收获(即对游戏的理解和掌握程度的上升)越来越少,到一定程度时,单纯下棋无法进一步探索游戏。这时玩家会进入钻研阶段,他们可能一边下棋一边试验(例如试着使用不同的策略),尝试解开某个棋局(例如曾经输掉的棋局,有什么办法可以反败为胜?),寻找导师,或者阅读其他人写的心得。大部分玩家可能不会深入钻研游戏,但是多亏了互联网,如今只要上网搜搜就能找到攻略。如果你建立了游戏社区,即便是个规模很小的社区,一些核心粉丝会做这件事,他们最希望每个人都了解,他们会在论坛上发布细节。会有更多的人读到这些知识,这些人会继续教他们的朋友,这些知识会在大批玩家间传播,比你预期的快得多。

五、技术VS理论

值得强调的是,我们试图弄清玩家完全理解掌握游戏规则和策略需要什么,也就是玩家能够进行最高水平游戏所需要的理论知识。我们所关注的不是如何获得和打磨操作技术。在某些游戏中,完全掌握玩法规则你将成为大师,但对某些游戏来说,这不是夺得胜利必要、根本的条件。一个极端例子是百米冲刺,在这个比赛中理解规则的细节、比赛的最佳策略对你的表现作用甚微。当然许多奥运会跑步运动员在赛前会做很多计划,但即便你对这些策略已经烂熟于胸,甚至可以去指导世界顶级运动员,它对实际比赛没什么帮助,除非你真正练习跑步。

《雷神之锤3:竞技场》和《反恐精英》的区别可以作为一个例子。我并非第一人称射击游戏高手,尽管这两个游戏的基本战斗机制一样,我打《雷神之锤》时频频落败,但在《反恐精英》里我经常可以进服务器前三。造成体验不同的原因当然是两款游戏的规则不同。《雷神之锤》更注重眼手配合、移动和瞄准,而《反恐精英》有着另一套规则和机制,使得地理位置变得十分关键。通过预测对手的移动,我可以调整自己的走位从而打败对手,尽管他们的瞄准射击能力比我强得多。这也使我意识到,游戏的乐趣不只取决于深度,除了根据形势和游戏规则制定策略外,你还可以通过使游戏更侧重于技术和物理技能,使它更有趣和富有挑战性。事实上,很多流行游戏要么几乎完全专注于技术,要么几乎完全专注于策略,比如射箭和举重。此外,这个例子还引出了另一个观点:一款更注重战术策略的游戏,对技术的要求更低。当然,为了进行高水平的游戏,玩家需要掌握战术策略,也需具备操作技术,就像在即时战略游戏中,并且在不同游戏中,二者的分量会有所变化。

六、额外因素

在以上分析和图表中,有些方面尚未被提及,但它们对于我们全面分析一款游戏来说很重要。首先,不同游戏的大小、玩家需掌握的规则和策略各不相同。显然理解《井字棋》比理解《欧陆风云3》要轻松得多。这似乎是一个被忽略的重要因素,但我们的主要目的是了解玩家学习一款游戏所花的时间、而不是学习量的多少,这是一个重要的区别。相比于复杂的游戏,小游戏学起来更快、需要的努力更少;以此推断,如果你发现两款复杂性不同的游戏的堆叠图长得很相似,这表明更简单的那款游戏不能有效地向玩家解释它的规则。

这种分析忽略的另一个重要因素是,玩家不一定要完全掌握游戏规则才能享受游戏。实际上,许多游戏只需要玩家了解一小部分规则就已经足够好玩,只有极少玩家能完全掌握他们所玩的游戏。例如,你可能很喜欢玩《德州扑克》,然而大多数人远远达不到参加世界扑克系列赛(WSOP)的水准。因此我建议额外分析下面两点:

1. 玩家需要付出多少努力才能开始享受游戏。
2. 玩家需要付出多少努力才能获得游戏的完整体验。

若玩家能很快开始享受游戏,他们就更有可能继续游戏并花时间学习游戏,从而达到第2点,即完整体验你设计的游戏。完整体验不是指完全理解游戏,而是理解所有主要功能、如何使用它们。举个例子,在《战地1942》中,大多数玩家能够快速开始自由移动,射杀敌人,这时候玩家开始享受游戏。然而,要获得完整的游戏体验,玩家需要花上一些时间了解不同载具和武器以及它们的交互方式。玩家不一定要了解武器和载具之间所有的交互关系(它们的关系类似石头剪子布),只需要了解应对敌人的不同策略即可。当然,了解细节能帮助玩家更专业地进行游戏,比如德国坦克由于缺乏倾斜装甲更容易受到伤害,但对于充分上手和享受核心玩法不是必要的。

若我们回头来看游戏4和游戏5,假设它们是两个非常相似的游戏,并且玩家在掌握游戏25%时开始享受游戏、掌握50%时获得完整体验,这时我们会发现在游戏5中,玩家开始享受游戏和获得完整体验所花的时间短得多。这是游戏4的开发者应该担忧的一个方面。

七、如何使用这个工具

我们该如何使用这个工具改进我们的游戏?你既可以使用这个工具分析竞争产品,也可以分析你自己的游戏。

1.分析你自己的游戏

你可以用它检验正在开发的游戏是否符合你对其上手性的期待。你可以检验新加入的功能是否能清晰向玩家解释其规则,以及至关重要的,在玩家需要使用这些功能前是否清楚理解了它们。通常来说,相比于那些玩家反复玩的游戏类型,那些大多数玩家只玩过一次的游戏更需要担心这个问题。

另外一个用途是追踪游戏的复杂性在开发过程中是如何变化的。游戏开发过程中,你会了解什么有效,什么无效,你会发现并加入有趣的新功能,淘汰效果不好的功能。这是一个自然的过程,但游戏的复杂性、深度和上手性会随之改变。实时追踪游戏的深度和上手性是避免游戏过于复杂或简单化的一个有效方法。如果你在开发全程对游戏保持跟踪,你就更容易明白一个新功能将如何影响游戏的上手性,或者删掉某个功能建将如何影响深度。

2.分析竞争产品

分析竞争产品的理由很多,但最重要的一个目的是寻找共同模式。如果你发现了一种普遍模式,你就能明白该类型游戏成功的秘诀是什么,或者当你想尝试某个想法时,你能够了解它是否已经被实践了,效果如何。你还将发现同类型中流行的游戏不止一种,它们之间有很大区别,就像上面提到的《雷神之锤》和《反恐精英》,这也是它们能相互共存而不是直接竞争的原因之一,因为他们吸引的玩家不同,至少它们提供的体验不同。若你发现自己的游戏和其它竞争产品看起来很不一样,发现这一点显然很重要:发现不同点对于推销游戏、确定目标玩家以及差异化设计很重要,或者它使你意识到自己的游戏和同类型游戏相比,存在一些不合适的功能,或者缺了其它游戏都具备的关键部分。大幅修改游戏的复杂性本身不是件坏事,塔防游戏本质上是即时战略游戏,只不过去掉了大部分元素,使玩家能够专注于一个方面。

本文由游戏邦编译,转载请注明来源,或咨询微信zhengjintiao

This is the first part in a three-part series describing a method for viewing, analyzing, and comparing depth and accessibility of games。 The first part I provide an overview of the method, the second part goes into more detail, and the third part applies the method to a specific example。

The Problem

Your new game has been greenlit, a casual tactical shooter with enough depth to keep the hardcore players for years. Though everyone is confident in the game at the moment, you and everyone else know that it’s a big bet for the studio, and the consequences of not delivering could be dire. As the project continues, the question is; does the game you are working on a year later still fit the original plan for depth and complexity, or the one you are preparing to ship two years later? Is it actually casual enough not to scare off new players, does it really have all that depth that you promised it would have? What will happen if you add feature X? Will that make the game too complex? If so, is there another feature that you could drop that could bring the game back to the realm of casual? Not to mention, how does your game compare to the competition?

These are all very difficult, yet crucial, questions that you must answer in order to deliver the right game to your customers. You can use your experience and intuition, but it is often hard to accurately assess your own game when you’re deep in the trenches, and what you really want is a more precise and ideally more objective way to perform the analysis. This series of articles presents a method to analyze and compare games, and to track how your feature set affects your game’s accessibility and depth.

Definition of Concepts

I will begin by defining the terms that I will use in this series of articles more precisely, as many of the concepts in game design are vague, subjective, and/or lack an agreed up on strict definition. These articles concern a game’s complexity, accessibility, and depth, and the concept of mastering a game. By complexity, I mean the complexity created by the rules of the game together with the corresponding space of possible actions that the players can take that those rules give rise to. Note that the complexity of the rules and the space of possible player actions are not dependent on each other. A game like Go has very simple rules, yet the number of possible actions a player can take is quite large, hence the complexity of Go as a game is large. The depth of a game is closely related to its complexity, but rather than measuring complexity of the rules, it is about the complexity of play. A game that can be played using a simple algorithm lacks depth, while a game that allows for and necessitates a large variety of strategies and counters, and great variation of play have a large depth. Complexity and depth are not the same thing, though games that are not complex tend to lack in depth too. Mastering a game means both understanding a game’s complexity and its depth. This includes understanding the relevant rules for any situation, as well as knowing what strategies and tactics are applicable for that situation. Mastery, of course, is a matter of degrees, and a good way of thinking of a certain player’s mastery of the game is at what level she can compete. Finally, a game’s accessibility is a measure of how much effort a player needs to put in, in order to reach a certain level of mastery. The accessibility of a game is dependent on both its complexity and its depth, but also on things such as how easy the rules are to understand, and how much of the game has to be learned before a player can start playing.

Method Overview

First exampleThe fundamental idea of the method presented in this series is to measure how much effort a player has to put in to fully master the game, that is to get a complete understanding of the game, its rules and mechanics, as well as its strategies and tactics. By mapping this out in the appropriate way, you can with a quick glance at the data determine how two different games compare and also see how the game you’re developing is tracking against its goals. Before we begin, if you are looking for some truly objective data, particular data that could stand up to academic scrutiny, then there are no short cuts. To gather data of that quality, you will have to gather a lot of unbiased data, and perform rigid statistical analysis on it. I believe that using the ideas presented herein would useful if you wanted to perform an analysis of that quality, but I expect most readers don’t need that kind of rigor. Instead, my suggestion is that you use this method as a lens through which to view games, a lens among many through which to analyze and compare games in order to find out what makes them work (or not).

In order to facilitate this second, and most likely more prevalent, use, it is important to present the data in a way that lets you compare two games at a glance. This is facilitated by ordering the data in normalized stacked columns with a consistent color coding[1] (see the first figure). What these graphs shows is a mapping from effort to mastery, that is the accessibility of Game 1 through 3. Each band of color represents a certain amount of effort, and where on the column that band ends represents the mastery achieved by that amount of effort. Note that since the Y-axis represents mastery, all columns are going to have the same height, which means that they are going to end at the point where the player has fully mastered the game, that is at 100%.

The process of mastering a game is divided up into three phases; the pre-play phase, the playing phase, and the research phase. Pre-play has two components; innate understanding of the game, and tutorial.

If the game is based on a concept that the player has knowledge of from the outside world, then the player understands some of the game, and this is the player’s innate knowledge。 For instance, a game with a military setting normally comes with rules and mechanics inspired by how real-world combat and equipment works。 Guns have a limited clip and needs to be reloaded, rifles have longer effective range than pistols, etc。 Games may also use common conventions in their genre of games like established game controls and that using health packs immediately restores a certain amount of health to the player。 The advantage of relying of innate knowledge is that there’s a part of the game that the player doesn’t need to learn, which allows the game to be more complicated without reducing its accessibility。 Note that abstract games, like Reversi or Game 2 in the example, leverage no outside knowledge and hence the player has no innate mastery。

The tutorial of the game includes such activities as reading the rules of a board game, the player having the rules taught to her by another player, or playing a tutorial in a video game. Note that some video games have no tutorials and just drops the player into the game, while other video games have their tutorial spread over time, rather than having all learning being front loaded. Also, as a rule, only video games can get away without a tutorial phase, as the game itself can enforce its rules, something that a physical game cannot not. In the example, both Game 1 and 2 have tutorials that give the player a decent mastery of the game.

The next phase is the playing phase. I’ve divided this phase up into four parts; half an hour of playing, two hours, five and ten. They all correspond to the amount of mastery a player is expected to gain after having actively played the game for that long. In the example, you can see that after having played Game 1 for ten hours, the player is expected to have completely mastered it, while for Game 3, the player is barely scratching the surface at that point.

The choice of durations as well as those of the research phase is relatively arbitrary, and is informed by the kind of games that I am interested in analyzing。 You may find that other durations work better for the kind of game you want to analyze, but remember that you can only compare two games if you have used the same durations。

Second exampleThe final phase is the research phase。 At this point, the player is seeing diminishing returns from just playing the game, and will have to more actively try to improve her mastery。 Researching includes activities such as experimenting with new tactics and strategies, reading online forums, books or other sources on the game, finding a teacher, and deep analysis of the rules。 The research phase is divided up into five parts; one hour of research, five hours, ten, 20, and “extensive” research。 The last category being a catch all for anything over 20 hours。

Now that we have a full understanding of what the graphs mean, we can easily look at them and compare the three games. Even a casual glance will reveal that the three example games are very different. A player playing Game 1 for long enough will have a full mastery of the game, while Game 3 requires the player to spend quite some time in order to reach full mastery. Game 2 is somewhere in the middle, a player will become quite competent from just playing the game, but in order to fully master the game, the player will have to put in some effort beyond just playing.

Of course, Game 1 through 3 are obviously very different games, and you expect to see very different profiles from that. Though comparing very different games can be interesting, a more likely scenario is that you want to compare similar games. Assuming Game 4 and Game 5 are very similar games, looking at their profiles, you can see that even though they both require roughly the same amount of effort of the player to reach full mastery, the effort required to attain partial mastery differs quite a lot, not to mention that Game 5’s tutorial is clearly more effective in teaching the game.

Some Examples

Tic-Tac-ToeLets’ look at a couple of examples of how to analyze games in order to get a better understanding of how it works. First up: Tic-Tac-Toe. Tic-Tac-Toe is an abstract game, so just looking at a board and the playing pieces won’t give a player any insight in how the game is played. However, after a rule explanation (that is the tutorial phase), you can reasonably assume that a player has a grasp of the complete ruleset of Tic-Tac-Toe. Knowing the rules is a good start, but there is one more thing that the player needs to learn in order to fully master the game, and that is the optimal strategy of Tic-Tac-Toe. Understanding and employing the optimal strategy of Tic-Tac-Toe guarantees the player a draw at worst. Most players will grasp this pretty quickly, particularly if playing against an opponent who already knows this strategy. The resulting analysis will produce the following chart.

At a glance, you can see that Tic-Tac-Toe is a rather shallow game. You can count on players grasping most of its complexity from a good explanation of the rules, and that after playing the game for a short period of time, most players will have fully explored the game. This doesn’t necessarily say anything about whether the game is enjoyable or not, but with a profile like this, the game is not likely to have a lasting appeal, at least not based solely on the merits of the depth of its gameplay.

Next, we’ll look at another board game: Pente. Pente is a variant on five-in-a-row that is played on a Go board, and has rules for capturing your opponent’s pieces. The rules of Pente are rather simple, and can be easily taught in a few minutes, and most people will quickly pick up on the basics, like avoiding having your pieces captured, blocking an opponent’s four in a row, and not leaving your opponent with a double open ended three in a row. However, unlike Tic-Tac-Toe, Pente does not have a trivial optimal strategy, and as a player keeps playing the game, she will discover more strategies and be able to identify more opportunities to exploit or dangerous situations to avoid and be able to do so earlier.

Tic-Tac-Toe and PenteAs the player spends more time with the game, the player will get diminishing returns in respect to how much her understanding of the game and her mastery of it increases, and at some point, just playing the game normally won’t suffice to further explore it. This is when the player will have to enter the research phase to improve her knowledge further. This could be experimenting while playing the game (e.g. trying different strategies and see what happens), experimenting with specific scenarios of the game (e.g. is there a way to get out of this particular scenario I’m having problems with?), finding a teacher, or taking the short cut and reading what others have written about what they have found out about the game. This may seem like an unlikely scenario that most players would put effort in to exploring the game that deeply, but today, thanks to the Internet, only a dedicated few actually has to do the work. If your game manages to build a viable community, even a small one, some of your most dedicated fans will do the job, and they like nothing more than for everyone to know about it, and will post the details on the forums. More people will read about it, and those people may teach their friends, and sooner than you expected it, the knowledge will be disseminated to a large portion of your player base.

Skill vs Understanding

It is worth emphasizing that what we are trying to assess is what it takes for a player to get a complete understanding and mastery of the rules and strategies of the game, that is the theoretical knowledge needed to play the game at the highest level. What we are not looking at is how to acquire and perfect the physical skills necessary to play the game. Fully mastering the gameplay may for some games make you a master, and for other games it’s not even necessary, and not fundamentally important, in order to win. The 100-meter dash would be an extreme example of a game where understanding nuances of the rules, and the best strategies will do little to improve your chances of doing well. There’s no doubt that a lot of planning goes in to the performances of the runners competing in the Olympics, but even if you intensely study these strategies to the point where you could coach the world’s top athletes, it won’t help you at your local track meet unless you practice actually running.

An example from the world of computer games is the differences between Quake III Arena and Counter Strike. I’m not a particularly good FPS player, and back in the day, I would get destroyed on a Quake server, but I could frequently get in the top 3 on a Counter Strike server, despite both games using the same fundamental mechanics to defeat opponents. The reason for my very different experiences was of course the difference in the rules of the games. Quake focuses on hand-eye coordination, movement and aiming, while Counter Strike has a different set of rules and mechanics, and because of those, positioning yourself on the map becomes crucial to successfully playing the game. By anticipating my opponents’ moves, I could place myself in such an advantageous position that I could defeat my opponents despite them often being much more skilled at aiming and shooting than me. This leads to the observation that what makes a game interesting is not purely dependent on its depth, but that you can make a game interesting and challenging by having more of a focus on skill and physical ability, rather than the ability to come up with a good tactic given the situation and the game’s rules. In fact, there are many popular games, that almost entirely focuses on physical skill or ability, for instance archery and weightlifting. At the same time, this example also leads to the interesting observation that a game focusing more on tactics and strategy will be less skill-based. Of course, in order to compete at the highest level, a player needs master both tactics and strategies, as well as having the physical skill to compete, as in the case with RTSs, and the exact mix is different from game to game.

Additional Factors

There are a few things that aren’t immediately captured in the analysis and the graph above that are important in order to fully understand a game. First of all, the actual size of the game, the rules and the strategies that a player needs to master differs quite a lot from game to game. Clearly learning Tic-Tac-Toe is a much smaller task than understanding Europa Universalis III. This may seem like a significant thing to leave out, but in the end, what we really are interested in is how long time it takes to learn the game, not how much one has to learn, and that is an important distinction. Smaller games are more likely to be learned quickly and with less total effort than a more complex game; similarly, if you find that two games of different complexities end up having similar profiles, then that may be an indication that the less complex game is bad at explaining to the player how it works.

Another important factor that the analysis so far has ignored is that it is not necessary for a player to have a complete mastery of the game in order for her to enjoy it. In fact, many games require only an understanding of a small portion of the game to be enjoyable, and very few players will ever approach anything near complete mastery of most games they play. For instance, it’s likely that you have tried Texas Hold’em at some point in your life, and enjoyed it, yet most people are far from a spot at the featured table at a WSOP tournament. I suggest that two additional points are important:

1. How much effort is needed in order to start enjoying the game.
2. How much effort is needed to get the full experience of the game.

If the player can quickly start enjoying the game, then the player is more likely to continue playing and to spend the time needed to learn the game enough to reach the second point, where the player gets the full experience that you have designed for. With the full experience, I don’t mean a complete understanding of the game, but understanding all major features of the game, and knowledge of how to use them. For example, in Battlefield 1942, most players could quickly start running around in the game, shooting at the enemy, which is when most players would start to enjoy the game. However, you need to spend a bit more time in the game to master the different vehicles and weapons in the game, and understand how they interact with each other in order to get the full experience of the game. The player doesn’t necessarily need to understand that all interactions in Battlefield are built on a rock-paper-scissors relationship between the various weapons and vehicles, but understanding how to counter different approaches by the enemy is necessary. Also, details that may help an expert player, as the fact that the German tanks lack of sloped armor makes it easier to score a more damaging hit on them are great to know, but not necessary in order to fully access and enjoy the core gameplay.

If we were to look at Game 4 and 5 above, assuming that they are very similar games, and that in both cases the player will start having fun at around 25% mastery and get the full experience at 50%, we would see that it takes a lot less time for the player to start having fun in Game 5 as well as getting the full experience. This is something that should worry the makers of Game 4.

How to Use this Tool

How do we use this tool to improve our games? You can use this tool both to analyze the competition, and analyze your own game.

Analyzing your Own Game

Analyzing your own game allows you to test if the game you are actually making matches the assumptions you have made about how accessible your game is。 You can investigate if new features are properly explained to the player as they are implemented, and crucially that they are properly taught to the player before the time the player needs to understand them。 Generally, this is more of a concern for games that most players only play once, than games that are played repeatedly, as the player often isn’t expected to be an expert after the first game。

Another use is to keep track of how the complexity of the game develops over time. As you develop a game, you learn what works, and what doesn’t, and you will discover new and interesting features to add to your game as well as features that did not pan out and got dropped. This is a natural process, but it also means that since your game is changing, so does its complexity, depth, and accessibility. Tracking the current depth and accessibility of the game throughout development is very useful to avoid making a game that is too complicated or too simplistic. If you are tracking the game throughout its development, then it becomes easy to see what a proposed new feature would do to the game’s accessibility, or what a cut feature would do to its depth.

Analyzing the Competition

You can of course come up with many reasons why you would want to analyze the competition, but the foremost would be to see if there is a common pattern. If you do find a common pattern, then you know what works for that genre, or if you want to try something different, you can see if it has already been done and how well that went. You may also find that there is more than one popular game in the genre, and that they have very different profiles, like Quake and Counter Strike mentioned above, and that this is what allows them to co-exist rather than directly compete with each other since they are attracting different players, or at least offering different experiences to the players. If you do find that your game has a very different profile compared to all the games that you are going to be competing with, then recognizing this is obviously important. If you want to keep the design of your game, then recognizing that it is different will be important for your pitch, identifying your target audience, and when verifying your design, or it may be a good indication that your game has features that aren’t entirely suited for your chosen genre, or that it is missing some crucial part that other games have. Drastically changing the complexity of a game isn’t inherently a bad idea, tower defense games are essentially RTS games where most of the elements have been removed which leaves the player able to focus on just one aspect.(source:)

 


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