Week 2: Type-based Usage Weights (cont'd.)

Hey readers! I spent this week continuing my work on compiling typing effectiveness data. However, my initial results gave me an insight into a potential issue with my project that could come up again- a minor coding oversight resulted in the wrong data being analyzed and displayed. Instead, I extracted graphs showing type occurrence in the Doubles OU format. I only noticed this because of a strange spike appearing early on in the timeline. But on the bright side, this was an opportunity for context-dependent research! Turns out- there were a lot of Dark-types being used in early 2023 because of the Treasures of Ruin Pokémon. 

Fig. 1: My draft type effectiveness table.

The Treasures of Ruin

Very recently introduced, this collection of 4 Pokémon: Wo-Chien, Chien-Pao, Chi-Yu, and Ting-Lu, all part Dark-type (also the type with the most commonly used moves, so they all get Same Type Attack Bonus (STAB) on their attacks) also come with their own abilities that reduce everyone else’s offenses or defenses. Those that lower others’ defenses are very versatile in tandem with strong attacking Pokémon to nearly One-Hit KO targets. All of them are so strong that they easily make up for their glaring weaknesses (Chien-Pao with a 4x weakness to Fighting-type attacks and Wo-Chien with one to Bug). Pokémon like the Treasures of Ruin used to be anomalies. But recently, these “gimmick-ey” Pokémon have become more common, and more volatile in usage. I’ll have to keep a close eye out for them when I start trying to identify patterns, as, being outliers, they can easily skew and confuse the data.

Fig. 2: Graphic of  Wo-Chien, the first Treasure of Ruin.

Table Issues + Cleanup

I was able to correct this coding oversight fairly easily, and spend a while cleaning up and optimizing the code. This wasn’t too essential as it’s a one-time calculation, but it’s good practice to make sure that I can write efficiently, especially given the short timeframe of this project. Simply by swapping the typing table’s rows and columns, I was also able to generate another output graph signifying the defensive capabilities of a type during a snapshot. There was one other problem I came across though: type immunities throwing off the data. An example of this is that Ghost-types are immune to Normal-type attacks, no matter the target’s other type. So Flutter Mane, a Ghost- and Fairy-type would be counted as the types separately, and this would make Normal-type attacks appear to be more effective overall. I had to rework the basic data I was working off of in order to accommodate this, calculating type effectiveness against each individual species and then doing a weighted sum. Again, not too difficult once I figured out how to do it. 

Fig. 3: Attack type effectiveness table. Note the y-axis corresponds to the average multiplier coefficient to an attack of that type.

Fig. 4: Defense type effectiveness table. Note the y-axis corresponds to the average multiplier coefficient to an attack against a Pokémon of that type.

Note: apologies for the incoherence and tangled nature of the graphs. They are intermediate graphics, not part of the final deliverable. Lines are colored in accordance with their types; this may help those who are familiar with the types already.

What now?

Now that I have this typing data, I’m not quite sure what to do. I’m going to take some time to figure out how to proceed with this project, especially in terms of deciding what kind of final deliverable I want to present. My original goal was to make a series of fake Pokémon to exemplify usage trends, but this 1. was not a very helpful result, and 2. ignored the importance of player decision-making. So, I switched the idea to instead be a pseudo-guidebook detailing a variety of tips and tricks for how to be successful in competitive Pokémon. But if I do this, how do I choose what information to include? I’m not sure if I’ll get clear results from my pattern analysis.

I’ll be contemplating such questions and more for the time being. Hasta la vista!

Alex R.