Stat Distribution Analysis: Part 2

One week later and I think I’ve cracked this. Firstly, go back and read last weeks post if you haven’t already, and this old one on stat weights if you don’t understand why replacing stat weights is a good thing.

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Stat Distribution Analysis

One of the things I’ve wanted to do for a while is work out a decent way of estimating the ideal “stat ratio” based on some previously generated data vs a players current gear. My initial ideas were based around either building a grand “formula of everything” for a spec or using the stat scaling graphs to somehow build a model, but these were fairly complicated and required a lot of data.

I may have, by complete accident, worked out how to do this in a much easier way.

This started with Bloodmallet sharing his secondary distribution graph on his website  with one of those 3D charts showing DPS output as colour shading vs crit/haste/mastery as the x/y/z axis. I grabbed a copy of the raw results, planning on messing around with it to see what sort of patterns I could get out of it.

Messing around with data

About the third or fourth thing I tried was averaging the results for the percentage increments for each stat, like so:

stat distribution table 1

The next step in these situations is to look at the difference between one row and the next:

 

stat distribution table 2

The interesting thing I noticed was that the best combo, C35 H15 M40 V10, had that massive value drop between H15 & H20. V10 was fairly obvious as the DPS value as you add more versatility is fairly low, but why were C35 & M40 the best results? After looking at the difference between C25/35 & M30/40 I noticed that the value increases after the large drops were still the largest gains out of any of the other steps.

DPS Analysis vs Election Systems

This is where we take a slight detour. As a numbers orientated spreadsheet person I made a few spreadsheets looking at how poll results from the 2017 New Zealand general election would generate the final seat results in Parliament. This is done via the “Sainte-laguë Allocation Formula” where the total number of votes gets divided by sequential odd numbers and then the top 120 values determine how many seats each party receives.

The reason I bring this up is that the step differences looked very similar to this, where the top 20 values were used to return the best secondary stat ratio that makes up a total of 100% (each step is 5%, so 20 steps available).

How could this be useful?

If this works out at the very least I’ll have a set of templates to indicate what sort of secondary stat distribution a player should have and indicate the best one to increase next without resorting to countless stat weight sims. If everything works out like I hope then I should be able to have a “stat ratio path” in a single table that indicates how secondaries should be increased for any level of gear. Talent selection will modify this, but if the basic premise holds then looking at the individual effect of each talent would just require another small set of adjustment data, unless there’s a large stat priority switch caused by one or more talent choices.

This data could then be used within an addon as a replacement for Pawn-like addons (or even an update to Pawn) to help guide players towards better gear choices without sims or stat weights.

It’s still early days on this, as I need to gather a lot more data to analyse, but the initial idea seems promising.

Weak Aura Design Part Two

In a previous post I looked at design philosophies, and how I set up the core of my weak aura sets with key resource information. This time around I’ll run through the way I approach the HUD section of my sets.

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Weak Aura Design Philosophy

Aka “Bink tries to explain the logic behind how he creates Weak Aura sets”

I’m not a master at making these things, partially because I lack the art skills to make custom images, while also only having rudimentary LUA skills to be able to take something & modify it slightly. However, the things I throw together seem to be semi-popular, by which I mean I get a few likes/replies when posting work in progress & a few thousand views on wago.io.

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Min/Maxing: Are these extra 1000 DPS increases worth it?

One of my recent theorycrafting thoughts was on looking at APL’s and reducing the complexity to see how this alters DPS output. The idea is that a less complex rotation will be easier to use in-game, and maybe even counter-intuitively increase damage.

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Stat Weight Graphs Part 3: Raidbots edition

Thanks to Seriallos from Raidbots.com I now have full stat weight plots for every DPS spec, and this data should be easily updateable as I’m reading directly from JSON files he’s hosting. I’ll link in the spreadsheets as I set them up, along with interesting stat charts that indicate something different/unusual. Read more of this post

Deconstruction of a Rotation: General Rotation Logic

There are a few misconceptions about how abilities should be used. Most of these follow the “use your biggest hitting ability first”, but this fails to take into account a lot of subtleties in rotations. To try to explain these I’ll use the Elemental rotation as a basis for explaining the logic. Read more of this post