WEBVTT

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Game Advanced
Criteria for Setting Monster Stats by Stage

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GCC Academy

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Hello everyone

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This is Park Hyung-seon, in charge of
Action RPG Balance Game Planning

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This session will cover the criteria
for setting monster stats by stage

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We will establish baseline values for attack power, health,

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and defense for monsters at different stages

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The goal is to determine

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these baseline stats for 100 stages,

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adjusting them according to difficulty

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 Using Excel trendlines, we will set base values

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and automate the scaling using quadratic or cubic equations

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to create an upward-trending graph

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Baseline Stats for Monsters by Stage

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Setting Baseline Stats for Monsters by Stage

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Let's review the formulas for calculating damage

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The absorption rate formula is
Defense / (Defense + Defense Constant)

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Let's set the defense constant as 1000

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It's all divided from Defense

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1000 is the Defense Constant

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For this session, let's keep it as 1000

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1000 is the most balanced standard value too

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Let's establish the base attack power, health,
and defense for monsters at each stage

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Next,

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the aim is to determine the average base stats

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for all monsters within a stage according to difficulty,

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covering all 100 stages in the game

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Let's take a look

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The reason for setting 100 stages is that,

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in real-world game development,

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balancing around 100 stages is a reasonable assumption

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A set of 100 stages would be roughly equivalent to an alpha version,

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to an alpha version,

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providing a solid foundation for a playable service

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The average stats of mobs

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are assumed as follows

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HP is 1500,

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attack power is 500,

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and defense is 500

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For stage 1, the average stats of mobs

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are set accordingly

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For stage 4,

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the average stats of mobs are set as follows:

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HP is 5500,

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attack power is 1500,

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and defense is 1500

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That's an example of setting the stats

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Naturally, stage 4

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is harder than stage 1,

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so the average stats are higher,

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following the logic

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This logic applies not just to stage 1 and stage 4

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but extends across all 100 stages

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The average stats,

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HP, attack power, and defense,

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must be adjusted for each stage

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Setting the stats individually can feel overwhelming

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Even with a simple approach,

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there are 100 stages

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and three stats per stage

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Multiplying 3 by 100 results in 300 stats that need to be set

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Moreover, these stats must follow

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a continuous increase rather than being set arbitrarily

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If we were to do this,

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as in, input each value manually,

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it would be difficult to determine
the appropriate stats for every stage

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Randomly assigning

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300 values without a structured method

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is not an option

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Thus, in practice,

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the focus is on

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how to efficiently

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automate these stats using formulas

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I will talk about that method now

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Let's go over the concept of base stats again

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Base stats refer

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to the average stats

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that serve as a standard

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for all mobs in a stage

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A stage does not contain only one type

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but multiple types of mob

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Since setting the stats for each type
manually would be too complicated,

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we establish base stats as a reference point

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This might sound complex, but it’s simple

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Base stats

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are used to derive variations

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If there are 10 types of mobs,

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we scale their stats based on the base stats

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to generate 10 different variations with unique stats

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Since this process is automated,

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any changes to the base stats

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will automatically adjust all mob stats at once

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That is the gist of this

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Thus, base stats exist

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to make balancing easier and more efficient

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Now, let’s look at base stats in more detail

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A game stage might contain various mob types, such as:

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Skeleton Infantry

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Skeleton Archer

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And Skeleton Defender

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There is not just one type,

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but many types of mob

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Skeleton Infantry is

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a melee-type mob

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with balanced stats, for example

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Skeleton Archer is a long-range attacker,

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so to characterize it a little,

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its attack is high, but defense is low

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Players can quickly approach and defeat them,

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making them challenging yet manageable

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That's one example

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However, if both attack and defense were high,

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they would be frustrating to fight,

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because they never die

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They will be

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contributing to decreasing the fun factor of the game

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Therefore, long-range mobs usually

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have high attack and low defense for better game balance

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This is for the fun factor

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Skeleton Defender

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is designed with high defense,

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so its main goal is to block damage

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and function as a tank

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These different traits of the mobs

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add variety and depth to the game

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Apart from these three, there are many more mob types,

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each with distinct characteristics

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Skeleton Infantry

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Skeleton Archer

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And Skeleton Defender

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Each mob type has three key stats,

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Health, Attack, and Defense,

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which scale with level progression

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For Health,

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Skeleton Infantry has balanced stats

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Next, Skeleton Archer

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has high attack,

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but low health

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Next, Skeleton Defender

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has high health and defense, lower attack

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This could work as a balanced setup

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While this system works,
it becomes extremely time-consuming

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when there

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are many types of mobs,

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the more kinds there are,

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the more time we need to put

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in working for these stats

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The reason for that is this

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If each mob type gets

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its own manually adjusted stats,

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if 10 mob types each require unique stats,

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the work increases 10 times over

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So balancing will take a huge amount of time

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This method is inefficient and unsustainable,

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which is not a desirable method

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Without base stats,

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this is how it works

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Each stage’s mobs would require

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individual stat inputs

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it is a tedious and inefficient process

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Instead, let’s go over an easier method

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Assuming that base stats are set,

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Let's move on to Assigning Mob Stats

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We'll use Skeleton Infantry as the reference mob

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It is an average unit,

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a balanced melee unit

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with average stats

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With this setup, stat allocation becomes much simpler

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Each mob has Level,

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HP,

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Attack, and Defense,

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which all

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increase with level progression

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For example,

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we create

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a base mob table

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This is the monster table we have

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It starts from level 1 to level 100,

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with HP, Attack, and Defense values for each level

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This table serves as the base stat reference

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Then, we define mob types

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The mob type

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If it is Infantry,

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HP, Attack, and Defense are all 1.0

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So all stats are at 1.0 multiplier

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Now, for Archer,

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it has lower HP, like 0.9,

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and lower Defense, like 0.8,

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and higher Attack, like 1.5

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So it has higher attack and lower HP and defense

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That's the emphasis we want

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So create this multiplier

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And just by multiplying it from the original table,

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this is an easy way of creating the stats

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For Defender, it has higher HP and defense

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HP is 1.5, Defense is 1.1

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But for Attack, let's lower it down to 0.7

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And we can, again, multiply it from the reference table

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So with this base stat reference,

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choose the type to use the multiplier

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to get the final stats for that particular type

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By setting up base stats and type multipliers,

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we can generate all mob stats efficiently

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Modifying a few values automatically updates all related stats

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This method can be applied not only to mobs

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but also to player characters with multiple classes

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Based on this,

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next, let's talk about automating base stat calculation

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Conceptually, this makes sense,

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but how do we apply this to real numbers?

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Manually inputting all stats for hundreds of stages

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would be overwhelming,

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especially since MORPG stages

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typically number in the hundreds

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And trying to manually inputting the stats

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to these hundreds of stages

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would require thousands of manual data entries

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This is a highly inefficient process

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Instead, we need to think

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about automating the process

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The key considerations

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are that stats should increase progressively as difficulty rises

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Even if values need future adjustments,

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for automation,

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we pre-fill dummy data and apply formula-based scaling

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For example,

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I will only use 50 stages

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and try the dummy data method

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What's important here is this

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As the game progresses,

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it’s important to introduce difficulty spikes

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at specific points in stages

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to maintain player engagement

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That is an important point to consider

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Let's look at the base HP scaling graph

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There are three primary stats:

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HP, Attack, and Defense

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Attack should be defined as DPS

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DPS allows for

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easier balancing work

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even if the number of attack animations changes

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Thus, using DPS

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ensures consistent balance

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Let's go with HP first

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First, we enter dummy HP data

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and use Excel’s trendline function

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to generate a formula that automates scaling

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The completed formula-driven automated graph

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is shown as a sample

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For example,

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y = -0.0172x^3

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+ 6.1855x^2

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+ 4.6908x

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and + 4.118

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That's what this graph is about

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This formula matches the values in the left table,

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The baseline HP value

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is calculated using a cubic equation,

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which creates a smooth upward trend

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As stages progress, the HP of monsters

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continuously increases according to this formula

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Compared to a linear increase,

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a curved progression like this

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introduces gradual difficulty scaling,

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contributing to the overall enjoyment of the game

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Moving on to the baseline HP stat graph,

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Let's compare Stage 1 and Stage 50

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The base HP values are 4,129 and 17,666

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In this lecture, to create these kinds of values and formulas,

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we utilize the trendline addition feature

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By referencing the graph and table,

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we can see that in Stage 1,

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the baseline HP of a single mob is 4,129,

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while in Stage 50, it increases to around 17,666

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As previously mentioned,

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it is important to first establish the baseline monster stats

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for each stage before adjusting other combat balance factors

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Initially, these values

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can be set based on intuition,

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but once they are converted into a mathematical formula,

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00:19:15.296 --> 00:19:17.430
modifying a few numbers

282
00:19:17.904 --> 00:19:21.056
can dynamically update all related values

283
00:19:27.072 --> 00:19:28.934
The Baseline Stats Graph

284
00:19:29.960 --> 00:19:34.458
The baseline HP graph is defined using a cubic equation

285
00:19:34.925 --> 00:19:39.748
because it allows for a sharper increase
compared to a quadratic equation

286
00:19:40.660 --> 00:19:44.343
If a less steep progression is desired,

287
00:19:45.041 --> 00:19:47.041
a quadratic function can be used instead

288
00:19:47.439 --> 00:19:49.439
The choice ultimately depends

289
00:19:50.087 --> 00:19:53.439
on the intended gameplay experience

290
00:19:55.275 --> 00:19:57.439
To compare, let's use

291
00:19:58.296 --> 00:20:00.296
a quadratic HP curve

292
00:20:00.950 --> 00:20:04.099
and a cubic HP curve

293
00:20:06.966 --> 00:20:12.099
The cubic equation produces a steeper incline

294
00:20:13.898 --> 00:20:16.533
The quadratic curve is not as steep

295
00:20:17.527 --> 00:20:20.467
You can use whatever you want

296
00:20:20.470 --> 00:20:24.099
For games that require

297
00:20:25.300 --> 00:20:31.775
a more pronounced difficulty spike,

298
00:20:32.476 --> 00:20:34.911
use the cubic equation

299
00:20:35.486 --> 00:20:40.069
If you want the opposite, which is

300
00:20:40.696 --> 00:20:45.723
if a steadier difficulty curve is preferred,

301
00:20:46.381 --> 00:20:48.832
a quadratic equation would be more appropriate

302
00:20:48.832 --> 00:20:50.223
Either approach can be used

303
00:20:52.325 --> 00:20:56.610
Adjusting Baseline Stats Using Trendlines

304
00:20:57.907 --> 00:21:04.113
Now, let’s discuss how to adjust the baseline stats
using trendlines in Excel

305
00:21:05.289 --> 00:21:08.201
Excel has the dataset

306
00:21:09.016 --> 00:21:09.854
with stage numbers,

307
00:21:10.940 --> 00:21:11.724
base HP,

308
00:21:12.880 --> 00:21:14.246
base DPS,

309
00:21:15.202 --> 00:21:18.710
and base defense values,

310
00:21:19.362 --> 00:21:22.961
ranging from Stage 1 to 50

311
00:21:23.992 --> 00:21:26.261
First, dummy values must be manually input,

312
00:21:26.261 --> 00:21:27.714
ensuring a gradually increasing trend

313
00:21:29.103 --> 00:21:32.231
from 4000 to 17000

314
00:21:34.079 --> 00:21:37.177
If no initial values are entered,

315
00:21:37.177 --> 00:21:39.418
the trendline function will not work

316
00:21:39.986 --> 00:21:43.540
So you must enter everything manually

317
00:21:44.079 --> 00:21:46.079
One thing to note is,

318
00:21:46.282 --> 00:21:49.929
the starting and ending values must be set,

319
00:21:50.267 --> 00:21:52.654
and there should be an increase

320
00:21:52.872 --> 00:21:55.927
For the rate of increase,

321
00:21:55.929 --> 00:21:58.158
whether large or small,

322
00:21:58.158 --> 00:22:02.155
the trendline will automatically adjust accordingly

323
00:22:02.739 --> 00:22:05.409
The trendline in Excel is simply

324
00:22:06.402 --> 00:22:08.532
a guideline that reflects trends in the data

325
00:22:09.862 --> 00:22:12.104
To use this, first, select the dataset

326
00:22:12.104 --> 00:22:13.774
After selecting the dummy data,

327
00:22:14.236 --> 00:22:21.607
let’s create a trendline for baseline DPS values in Excel

328
00:22:22.360 --> 00:22:28.966
If the baseline DPS ranges from 200 to 1,377,

329
00:22:29.790 --> 00:22:32.104
first, highlight the data range in Excel

330
00:22:32.104 --> 00:22:35.334
Drag the part about the baseline,

331
00:22:35.803 --> 00:22:40.121
the DPS part, to select 50 data

332
00:22:40.412 --> 00:22:45.066
Then, navigate to the Insert tab

333
00:22:46.767 --> 00:22:50.777
From there, either select Recommended Charts

334
00:22:50.951 --> 00:22:54.060
or manually choose Line Chart

335
00:22:56.060 --> 00:22:59.534
First, select Recommended Charts

336
00:22:59.534 --> 00:23:02.261
and then go with Line Chart

337
00:23:02.261 --> 00:23:05.216
Using a line chart is preferable

338
00:23:06.060 --> 00:23:08.755
for trend analysis

339
00:23:10.196 --> 00:23:15.726
Line charts are particularly useful

340
00:23:16.481 --> 00:23:19.974
for showing sequential data,

341
00:23:20.719 --> 00:23:23.763
making them ideal

342
00:23:23.763 --> 00:23:26.719
for tracking changes over stages

343
00:23:28.400 --> 00:23:32.719
Adding a Trendline to Match Baseline Stats

344
00:23:33.288 --> 00:23:38.719
We have selected the line chart from
the recommended chart options

345
00:23:39.876 --> 00:23:41.000
Now, on to creating the chart

346
00:23:42.295 --> 00:23:46.594
Once you select the line chart and click the OK button,

347
00:23:47.302 --> 00:23:53.196
the Excel data will be converted into a line graph,
displaying the stat trends visually

348
00:23:54.213 --> 00:23:56.520
Now, the range of data

349
00:23:56.980 --> 00:24:02.264
is plotted as a line chart, resembling the example on the right

350
00:24:02.730 --> 00:24:08.245
The chart title will automatically be set as Baseline DPS,

351
00:24:08.604 --> 00:24:13.809
showing how the baseline DPS values progress

352
00:24:14.191 --> 00:24:18.283
across Stages 1 to 50

353
00:24:20.040 --> 00:24:24.040
Adding a Trendline to Adjust Baseline Stats

354
00:24:25.405 --> 00:24:29.791
This could be a confusing part

355
00:24:30.070 --> 00:24:33.499
Careful mouse control is necessary,

356
00:24:34.370 --> 00:24:38.040
because the chart elements are small

357
00:24:39.048 --> 00:24:41.131
Now we have the trendline

358
00:24:42.211 --> 00:24:44.103
Now, precisely click

359
00:24:44.699 --> 00:24:47.369
on the blue line

360
00:24:47.552 --> 00:24:48.638
With that,

361
00:24:50.354 --> 00:24:51.354
as you can see,

362
00:24:52.566 --> 00:24:56.065
smaller circular handles will appear

363
00:24:57.003 --> 00:25:02.903
with each of the points selected, like this

364
00:25:04.517 --> 00:25:06.517
Once you click on the line,

365
00:25:06.948 --> 00:25:09.863
it indicates

366
00:25:10.264 --> 00:25:13.775
that the trendlines is active and selected

367
00:25:14.467 --> 00:25:15.756
It's a function that Excel has

368
00:25:16.477 --> 00:25:19.087
Now, right-click on it

369
00:25:19.087 --> 00:25:23.406
to bring up the context menu

370
00:25:23.406 --> 00:25:27.983
From the menu options, select Add Trendline

371
00:25:29.251 --> 00:25:32.749
Clicking this will open the Trendline Options panel,

372
00:25:32.749 --> 00:25:36.732
and select the Trendline option

373
00:25:38.020 --> 00:25:42.105
Once you click Add Trendline,
the Trendline Settings window will appear

374
00:25:43.225 --> 00:25:48.020
First, accurately click the line with the left mouse button,

375
00:25:48.020 --> 00:25:51.401
then right-click and select Add Trendline

376
00:25:52.619 --> 00:25:58.671
If done correctly, a Chart Settings Popup will appear

377
00:26:00.669 --> 00:26:04.054
Selecting the Trendline Type

378
00:26:04.856 --> 00:26:11.609
From the Trendline Options, you will see multiple types

379
00:26:11.609 --> 00:26:16.403
Exponential, Linear, Logarithmic,

380
00:26:16.403 --> 00:26:19.589
Polynomial, Power, Moving Average, and so on

381
00:26:20.093 --> 00:26:22.770
So we are selecting whether the trendline

382
00:26:22.770 --> 00:26:24.181
will be exponential, linear,

383
00:26:24.181 --> 00:26:27.039
log, or polynomial

384
00:26:27.731 --> 00:26:28.680
with this menu

385
00:26:29.696 --> 00:26:34.032
We will go with Polynomial,

386
00:26:34.685 --> 00:26:37.509
which allows for quadratic and cubic

387
00:26:37.509 --> 00:26:41.339
equations, which is called polynomial

388
00:26:42.219 --> 00:26:46.707
If you set it to 3 after selecting Polynomial,

389
00:26:47.339 --> 00:26:51.067
the trendline will have the cubit equation

390
00:26:51.166 --> 00:26:54.792
If, instead of 3,

391
00:26:55.223 --> 00:26:57.339
you'd rather go with 2,

392
00:26:57.727 --> 00:26:59.535
it works with quadratic equation

393
00:26:59.535 --> 00:27:06.000
If you want a faster, more exponential-like growth, set it to 3

394
00:27:06.264 --> 00:27:10.950
If you want a steadier growth curve,

395
00:27:10.950 --> 00:27:12.324
set the polynomial degree to 2

396
00:27:12.324 --> 00:27:15.265
So you can choose between quadratic and cubic

397
00:27:16.400 --> 00:27:18.491
Another important point is this

398
00:27:19.398 --> 00:27:22.741
There is an option for Display Equation on Chart

399
00:27:23.561 --> 00:27:27.031
Be sure to check this box,

400
00:27:27.247 --> 00:27:31.177
which will overlay the actual formula used in the graph

401
00:27:31.325 --> 00:27:32.118
Now,

402
00:27:33.175 --> 00:27:34.365
with that done,

403
00:27:34.860 --> 00:27:40.618
the graph will display a formula

404
00:27:40.618 --> 00:27:43.151
It is something that did not exist before

405
00:27:43.765 --> 00:27:44.986
Let me read it out

406
00:27:46.334 --> 00:27:50.948
Setting it to 3 will give this type of trendline

407
00:27:52.086 --> 00:27:56.880
y=0.0009x^3

408
00:27:56.881 --> 00:28:00.891
+ 0.3689x^2

409
00:28:01.481 --> 00:28:04.497
+0.3488x

410
00:28:04.869 --> 00:28:07.176
and +207.42

411
00:28:07.319 --> 00:28:10.621
This is the precise number we get

412
00:28:11.319 --> 00:28:14.186
We cannot apply this right away

413
00:28:14.615 --> 00:28:16.951
You have to take the extracted equation

414
00:28:17.849 --> 00:28:20.125
and convert it into an Excel formula

415
00:28:20.125 --> 00:28:21.435
for actual use in automation

416
00:28:21.435 --> 00:28:23.245
Though, we need this equation first

417
00:28:24.152 --> 00:28:26.450
to create an Excel formula

418
00:28:26.782 --> 00:28:33.979
So make sure to record this somewhere before we proceed

419
00:28:33.979 --> 00:28:36.678
We can edit it using this

420
00:28:37.391 --> 00:28:39.979
When modifying the formula, the equation itself also changes,

421
00:28:39.979 --> 00:28:42.485
but this is not a major issue

422
00:28:42.505 --> 00:28:45.979
The initial formula sets a reference for attack power scaling

423
00:28:47.077 --> 00:28:52.846
We will be using this formula to define
the standard attack power,

424
00:28:52.846 --> 00:28:55.066
so make sure to record it carefully

425
00:28:56.163 --> 00:28:59.738
The dummy values entered have been structured

426
00:29:00.189 --> 00:29:02.569
into a cubic equation trendline

427
00:29:02.569 --> 00:29:08.751
This converts raw stage data into a functional model

428
00:29:09.072 --> 00:29:13.460
The extracted coefficients, 0.0009, 0.3689,

429
00:29:13.479 --> 00:29:18.816
0.3488, and 207.42, govern stat progression

430
00:29:20.159 --> 00:29:23.933
Now, let me show you

431
00:29:24.204 --> 00:29:28.051
how automating stat scaling in Excel works

432
00:29:30.255 --> 00:29:37.300
I will now create the Excel formula
using the previously noted values

433
00:29:38.248 --> 00:29:42.244
We can formulate the standard DPS using a cubic equation

434
00:29:43.961 --> 00:29:45.842
In the Excel sheet,

435
00:29:47.300 --> 00:29:49.300
we will use cell D3 to enter the formula

436
00:29:49.300 --> 00:29:50.406
D3

437
00:29:51.743 --> 00:29:53.447
D3 will contain

438
00:29:53.447 --> 00:29:59.448
the standard DPS value based on the recorded cubic equation

439
00:30:00.570 --> 00:30:03.959
The cubic equation for standard DPS is this

440
00:30:03.959 --> 00:30:07.876
(0.0007*x3)

441
00:30:08.470 --> 00:30:11.322
+ (0.3885*x2)

442
00:30:11.322 --> 00:30:15.659
- (0.1605*x)

443
00:30:15.935 --> 00:30:18.683
and + 211.02

444
00:30:19.379 --> 00:30:21.404
When this type of formula is used,

445
00:30:22.114 --> 00:30:27.655
it can be entered directly in the upper-left formula bar

446
00:30:28.439 --> 00:30:30.731
In Excel formulas, the structure looks like this

447
00:30:33.020 --> 00:30:34.619
Start with =

448
00:30:34.619 --> 00:30:36.104
Meaning, equal to

449
00:30:36.104 --> 00:30:38.580
And start with opening a parenthesis

450
00:30:38.793 --> 00:30:46.856
(0.0007 * B3^3)

451
00:30:47.174 --> 00:30:48.936
* is multiplication

452
00:30:49.430 --> 00:30:51.475
Now, use ^,

453
00:30:51.475 --> 00:30:57.928
to represent the square

454
00:30:57.928 --> 00:31:02.234
So ^3 means cubed

455
00:31:03.280 --> 00:31:05.190
Now, + and open another parenthesis

456
00:31:06.084 --> 00:31:08.247
0.3885

457
00:31:08.510 --> 00:31:09.814
Multiplied by, or *

458
00:31:10.129 --> 00:31:11.150
B3

459
00:31:11.789 --> 00:31:12.698
Use ^

460
00:31:12.877 --> 00:31:13.788
for the square

461
00:31:13.788 --> 00:31:17.613
And 2, next, 0.3885

462
00:31:18.971 --> 00:31:21.939
This means x squared

463
00:31:22.558 --> 00:31:24.133
Next up,

464
00:31:24.731 --> 00:31:28.607
-0.1605 * B3

465
00:31:28.755 --> 00:31:30.507
+ 211.02

466
00:31:30.510 --> 00:31:31.833
That's how you write it out

467
00:31:32.643 --> 00:31:35.459
Then why do we enter it this way?

468
00:31:36.228 --> 00:31:41.761
On the left, there is B, which represents stage 1, 2, 3, 4, right?

469
00:31:41.761 --> 00:31:45.536
So, it takes the value of B3

470
00:31:45.908 --> 00:31:47.353
The value of B3

471
00:31:48.256 --> 00:31:51.420
changes sequentially as 1, 2, 3, 4, and so on

472
00:31:52.025 --> 00:31:53.763
So, X

473
00:31:54.052 --> 00:31:55.417
is the input value

474
00:31:55.417 --> 00:31:57.040
What we want to calculate is the Y value

475
00:31:57.912 --> 00:32:03.022
We use the actual equation to calculate the Y value

476
00:32:03.706 --> 00:32:08.379
X increases sequentially as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and so on

477
00:32:08.379 --> 00:32:14.599
Then, we take the increasing X values like 1, 2, 3, 4, 5, 6, 7, 8

478
00:32:14.599 --> 00:32:18.295
When we input these values into the equation,

479
00:32:19.260 --> 00:32:22.756
this cubic equation calculates the Y value

480
00:32:22.756 --> 00:32:25.686
This allows us to generate the desired values

481
00:32:26.386 --> 00:32:28.412
Now, why do we use this?

482
00:32:28.877 --> 00:32:31.708
0.0007, 0.3885,

483
00:32:31.708 --> 00:32:35.277
-16.05, 211.0

484
00:32:35.980 --> 00:32:37.980
These values are predefined

485
00:32:39.260 --> 00:32:43.842
If we want to increase them, we just change these values

486
00:32:43.842 --> 00:32:46.537
For example, take the value 211.02

487
00:32:47.132 --> 00:32:50.825
If the first stage’s initial value is 211,

488
00:32:51.176 --> 00:32:54.377
the initial output value will be close to 211

489
00:32:54.377 --> 00:32:55.920
If you want to increase it,

490
00:32:55.920 --> 00:32:58.111
you can set it to something like 500

491
00:32:58.588 --> 00:33:01.920
And 0.0007 * X^3

492
00:33:01.920 --> 00:33:03.742
For the coefficient in front of x^3,

493
00:33:03.742 --> 00:33:05.716
the earlier it appears, the more sensitive it is

494
00:33:05.732 --> 00:33:07.034
The value is small

495
00:33:07.500 --> 00:33:09.920
Like 0.0007, it’s very small

496
00:33:09.920 --> 00:33:13.694
But even a small increase results in a large change

497
00:33:14.037 --> 00:33:16.099
If you want to increase it less,

498
00:33:16.908 --> 00:33:19.513
adjust the 0.3885 * x^2

499
00:33:19.513 --> 00:33:21.515
Raising this value will have a milder effect

500
00:33:21.966 --> 00:33:23.901
The same applies for decreasing the values

501
00:33:23.901 --> 00:33:28.925
So in these four places, x^3, x^2, x,

502
00:33:28.925 --> 00:33:31.551
and the constant term

503
00:33:31.551 --> 00:33:33.956
These four factors

504
00:33:33.962 --> 00:33:36.305
include general numerical values

505
00:33:36.305 --> 00:33:39.124
By adjusting these four,

506
00:33:39.997 --> 00:33:43.997
you can raise or lower the graph’s output

507
00:33:44.000 --> 00:33:45.038
With automation,

508
00:33:45.261 --> 00:33:47.616
you can apply this function in Excel,

509
00:33:47.616 --> 00:33:50.730
and just drag it down to apply the calculations automatically

510
00:33:51.135 --> 00:33:54.064
This is how you can create the formula

511
00:33:55.460 --> 00:33:58.794
Adding a Trendline to Adjust Base Stats

512
00:33:59.186 --> 00:34:01.564
Let me explain automation again

513
00:34:02.498 --> 00:34:09.084
Once all formulas are entered as functions in Excel,

514
00:34:09.813 --> 00:34:11.239
the next step is

515
00:34:11.899 --> 00:34:13.899
using the mouse to

516
00:34:15.899 --> 00:34:21.194
place the cursor at the bottom-right corner
where the rows and columns meet

517
00:34:21.194 --> 00:34:22.619
A plus sign will appear

518
00:34:23.188 --> 00:34:25.989
Click and drag it downward

519
00:34:27.460 --> 00:34:29.052
It will automatically fill all the cells

520
00:34:30.270 --> 00:34:32.920
The Excel formula will be applied and automated

521
00:34:32.920 --> 00:34:38.912
This allows you to increase or decrease values at once

522
00:34:38.912 --> 00:34:41.578
You can apply the entire formula in this way

523
00:34:42.110 --> 00:34:43.976
Rather than entering each value manually,

524
00:34:44.748 --> 00:34:47.832
this method is much faster and easier to modify

525
00:34:48.331 --> 00:34:51.422
So, when we plot this as a chart again,

526
00:34:51.422 --> 00:34:55.236
it creates a smooth increasing trend like the one on the right

527
00:34:55.652 --> 00:34:58.921
Y = 0.0007 * x^3

528
00:34:59.567 --> 00:35:03.003
+ 0.3885x^2

529
00:35:03.003 --> 00:35:06.338
-0.1605x

530
00:35:06.338 --> 00:35:09.833
+211.02, producing a graph like the one on the right

531
00:35:10.327 --> 00:35:12.750
This can also be easily converted into a table,

532
00:35:13.659 --> 00:35:15.748
and it works with formulas as well

533
00:35:15.753 --> 00:35:17.569
To increase the values slightly,

534
00:35:17.570 --> 00:35:19.515
instead of -0.0007,

535
00:35:20.150 --> 00:35:24.165
Enter a larger value like -0.0037

536
00:35:25.219 --> 00:35:28.216
Then, drag the formula down for automation

537
00:35:28.216 --> 00:35:32.051
The increasing values will be applied instantly

538
00:35:33.181 --> 00:35:36.676
To adjust base stats using a trendline,

539
00:35:36.676 --> 00:35:38.814
let’s compare graphs based on different formulas

540
00:35:40.804 --> 00:35:42.804
Modifying equations and formulas

541
00:35:42.804 --> 00:35:45.432
Our formula for Y is this

542
00:35:45.879 --> 00:35:48.449
0.0007x^3

543
00:35:49.262 --> 00:35:51.318
0.3885x^2

544
00:35:51.318 --> 00:35:53.649
0.1605x

545
00:35:53.879 --> 00:35:56.353
+ 211.02

546
00:35:57.019 --> 00:36:00.238
If we want to increase the values,

547
00:36:00.572 --> 00:36:02.836
manually adjusting each one

548
00:36:03.879 --> 00:36:06.472
for 50, 100, or 200 entries is impractical

549
00:36:06.680 --> 00:36:08.853
That’s why we automate using formulas

550
00:36:09.534 --> 00:36:12.540
Let’s slightly increase the values

551
00:36:13.331 --> 00:36:17.856
Instead of Y = 0.0007x^3,

552
00:36:17.889 --> 00:36:19.871
use 0.0008x^3,

553
00:36:20.198 --> 00:36:23.509
instead of 0.3885x^2,

554
00:36:23.509 --> 00:36:25.321
use 0.4885x^2,

555
00:36:26.030 --> 00:36:28.593
keep -0.1605x the same

556
00:36:28.937 --> 00:36:33.002
Change 211.02 to 230.02

557
00:36:33.806 --> 00:36:37.586
After applying these changes,

558
00:36:38.329 --> 00:36:39.711
the table will update accordingly

559
00:36:40.318 --> 00:36:43.715
For stages 1 to 50, the base DPS changes as follows

560
00:36:43.715 --> 00:36:48.222
Formula 1 ranged from 211 to 1260

561
00:36:48.704 --> 00:36:54.175
After applying automation with slight increases,

562
00:36:54.919 --> 00:37:00.387
formula 2 now ranges from 230 to 1543

563
00:37:01.002 --> 00:37:05.238
You can see how modifying the formula affects values

564
00:37:05.860 --> 00:37:08.126
By modifying the formula and equation,

565
00:37:08.849 --> 00:37:11.351
the DPS value changes,

566
00:37:11.749 --> 00:37:13.726
and the graph’s slope is also adjusted

567
00:37:14.391 --> 00:37:17.205
To achieve the desired graph shape,

568
00:37:17.205 --> 00:37:18.789
you can create a new formula

569
00:37:19.169 --> 00:37:21.860
or modify the existing equation and apply it

570
00:37:22.849 --> 00:37:27.078
When balancing, just tweaking the numbers in the equation

571
00:37:27.860 --> 00:37:30.582
eliminates the need for manual input of all values

572
00:37:31.288 --> 00:37:34.036
You can easily adjust all values at once

573
00:37:34.956 --> 00:37:37.146
The reason for creating a base table is

574
00:37:37.763 --> 00:37:41.103
that once automated like this,

575
00:37:41.337 --> 00:37:44.411
it can be linked to actual monster data

576
00:37:44.724 --> 00:37:46.975
or character data

577
00:37:47.245 --> 00:37:49.258
By modifying only the formula in the base table,

578
00:37:49.964 --> 00:37:54.436
the entire balance can be recalculated and adjusted instantly

579
00:37:54.436 --> 00:37:57.073
By setting up a base table like this,

580
00:37:58.762 --> 00:38:00.635
you can create variations for characters,

581
00:38:01.440 --> 00:38:03.122
and also for monsters

582
00:38:03.529 --> 00:38:05.166
Simply adjusting this equation

583
00:38:05.624 --> 00:38:09.179
modifies all relevant values at once

584
00:38:09.179 --> 00:38:12.652
This allows for highly efficient workflow

585
00:38:14.919 --> 00:38:17.771
Now, for adding a trendline to adjust base stats,

586
00:38:17.777 --> 00:38:21.020
let’s examine base defense values

587
00:38:22.345 --> 00:38:23.942
The base defense formula is this

588
00:38:25.514 --> 00:38:30.736
y = -0.0049x^3

589
00:38:31.778 --> 00:38:34.301
+ 537x^2

590
00:38:34.930 --> 00:38:38.171
+ 1.5955x

591
00:38:38.525 --> 00:38:40.334
+ 27.255

592
00:38:40.586 --> 00:38:42.638
If the equation is structured like this,

593
00:38:42.960 --> 00:38:49.688
likewise, applying this as a cubic equation and dragging it down

594
00:38:49.840 --> 00:38:51.840
will populate the values accordingly

595
00:38:53.290 --> 00:38:56.957
For the first test, let’s apply it to stage 1 to 50 monsters

596
00:38:57.645 --> 00:38:59.995
Base HP, base DPS,

597
00:39:00.500 --> 00:39:02.500
and base defense will have a reference table

598
00:39:03.016 --> 00:39:05.330
Each will be expressed using a cubic equation,

599
00:39:05.330 --> 00:39:07.455
and once entered, all calculations will be complete

600
00:39:08.343 --> 00:39:12.970
Using the trendline function,
you can obtain the desired graph shape

601
00:39:13.542 --> 00:39:14.922
and extract the necessary values

602
00:39:15.053 --> 00:39:17.133
However, you must refer to this equation

603
00:39:17.133 --> 00:39:20.513
and manually create and apply your own formula

604
00:39:21.885 --> 00:39:24.201
When you actually apply this,

605
00:39:24.500 --> 00:39:27.036
if defining the range data is difficult,

606
00:39:28.031 --> 00:39:33.623
we have examples of defense, attack,
and HP values from the lecture

607
00:39:34.341 --> 00:39:36.083
There are sample values available

608
00:39:36.617 --> 00:39:39.159
Just keep a record of those formulas,

609
00:39:39.916 --> 00:39:43.960
convert them into Excel functions, and apply them

610
00:39:44.035 --> 00:39:47.159
This way, you won’t need to rely on dummy data

611
00:39:47.364 --> 00:39:50.121
Even without generating a trendline,

612
00:39:50.328 --> 00:39:51.732
since you already have the formula,

613
00:39:52.100 --> 00:39:55.559
you can directly apply and modify it

614
00:39:56.866 --> 00:39:58.384
That concludes today’s lecture

615
00:39:58.384 --> 00:40:00.327
Great job, everyone

616
00:40:00.327 --> 00:40:01.088
Thank you

617
00:40:01.408 --> 00:40:02.749
Stage-Based Monster Standard Stats
The standard stats for a single battle process refer
to the most average stats that all regular monsters in a stage

618
00:40:02.750 --> 00:40:04.146
A stage has multiple monster types,
making individual stat setting difficult, so a standard stat is used

619
00:40:04.146 --> 00:40:05.438
If stats are created as formulas, the entire set of values
can be adjusted simply by modifying the numbers in the formula

620
00:40:05.438 --> 00:40:07.147
Standard Stat Graph
For standard HP, a cubic equation is used
because it increases more steeply than a quadratic equation

621
00:40:07.147 --> 00:40:11.357
For undesired steep increase, quadratic equation can be used
The formula can also be freely modified to achieve the desired graph sha

622
00:40:11.357 --> 00:40:13.199
Adjusting Standard Stats Using Trendlines
1. Select Data:
In Excel, drag-select 50 values of standard DPS

623
00:40:13.200 --> 00:40:14.787
2. Go to the “Insert” tab and click Recommended Charts
3. From the recommended charts or all charts, select a line chart

624
00:40:14.787 --> 00:40:16.127
4. With the line chart selected, click OK
5. Click on a data series in the chart, then right-click

625
00:40:16.127 --> 00:40:18.016
6. Click Add Trendline to open the trendline settings window
7. Choose Polynomial, then set the order to 3 to generate a cubic trendline

626
00:40:18.016 --> 00:40:21.141
8. In Excel, use cell D3 to enter a cubic formula
for standard DPS, using the pre-recorded cubic equation