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TortoiseCity
New Zealand
Приєднався 30 чер 2014
Hi, I'm Tortoise! I make videos about all things Pokémon, including long-term trends, game balance, speedrunning, history and lots more.
I also speedrun Pokémon over on twitch @TortoiseCity.
I also speedrun Pokémon over on twitch @TortoiseCity.
What is Pokémon's Average Gender?
Thanks for watching! Gender is kind of a forgotten mechanic in Pokémon, generally speaking, but what is the average gender?
Spreadsheet with data is linked here: docs.google.com/spreadsheets/d/1kEI5N9J_bgfZRgW-MEH7tnqoRe4lhFobYIORt9KCzn4/edit?usp=sharing
Follow me on Twitch here: www.twitch.tv/tortoisecity
You can find all of my music here: soafnb40.bandcamp.com/
And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg
All my links are here: linktr.ee/soafnb40
Buy me a coffee here: ko-fi.com/tortoisecity
Spreadsheet with data is linked here: docs.google.com/spreadsheets/d/1kEI5N9J_bgfZRgW-MEH7tnqoRe4lhFobYIORt9KCzn4/edit?usp=sharing
Follow me on Twitch here: www.twitch.tv/tortoisecity
You can find all of my music here: soafnb40.bandcamp.com/
And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg
All my links are here: linktr.ee/soafnb40
Buy me a coffee here: ko-fi.com/tortoisecity
Переглядів: 6 147
Відео
Fixing Pokémon's awful color categories
Переглядів 4,8 тис.Місяць тому
Thanks for watching! This is a follow up video to my last video, which used the Pokédex's data to see whether color correlated to type. I answer that same question again with my own dataset to see if the Pokédex's flawed data skewed the results (and also use better statistical methods). The spreadsheet is available here: docs.google.com/spreadsheets/d/1dFDRioFM52xrcsBtxgX_2mVFI1tOlHW81eftq2Exnv...
Does type correlate with color in Pokémon?
Переглядів 19 тис.Місяць тому
Thanks for watching! I think this is an interesting subset of Pokémon design that is little talked about, and had to see the numbers for myself. Spreadsheet is here for anyone interested in looking at it themselves: docs.google.com/spreadsheets/d/13CqPmHsgXUbeTiGvpxO2bjpNLUlfVDxn82Ase3kmsug/edit?usp=sharing Follow me on Twitch here: www.twitch.tv/tortoisecity You can find all of my music here: ...
What is a Normal type Pokémon, anyway?
Переглядів 9 тис.Місяць тому
Thanks for watching! I've always kind of wondered what sets normal apart from other types, and what about normal makes normal, normal. Let me know below if I missed anything! Follow me on Twitch here: www.twitch.tv/tortoisecity You can find all of my music here: soafnb40.bandcamp.com/ And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg All my links are here: linkt...
Do Pokémon Types match their Stereotypes?
Переглядів 13 тис.Місяць тому
Thanks for watching! I wanted to take a look at whether some commonly held beliefs in the Pokémon community were supported by the actual numbers in the games. I was pleasantly surprised by what I found! Follow me on Twitch here: www.twitch.tv/tortoisecity You can find all of my music here: soafnb40.bandcamp.com/ And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg ...
Pokémon Red Any% Glitchless speedrun in 1:51:28
Переглядів 2122 місяці тому
Thanks for watching! Old PB by now that I only just got to uploading. Still trying for sub 1:50. Follow me on Twitch here: www.twitch.tv/tortoisecity You can find all of my music here: soafnb40.bandcamp.com/ And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg All my links are here: linktr.ee/soafnb40 Buy me a coffee here: ko-fi.com/tortoisecity
The Pokémon Types Gamefreak loves to hate
Переглядів 9 тис.2 місяці тому
Thanks for watching! I am still mildly upset with Gamefreak for condemning so many great pokémon to non-viability in all playthroughs in the early generations. Follow me on Twitch here: www.twitch.tv/tortoisecity You can find all of my music here: soafnb40.bandcamp.com/ And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg All my links are here: linktr.ee/soafnb40 B...
Pokémon Generation Four's Ultra Rare Magikarps
Переглядів 1,8 тис.2 місяці тому
Thanks for watching! Did you ever find any of these rarest of Magikarps? Follow me on Twitch here: www.twitch.tv/tortoisecity You can find all of my music here: soafnb40.bandcamp.com/ And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg All my links are here: linktr.ee/soafnb40 Buy me a coffee here: ko-fi.com/tortoisecity
Pokémon Omega Ruby and Alpha Sapphire's Greatest Failure
Переглядів 2,5 тис.3 місяці тому
Thanks for watching! I love ORAS, but gosh I really wish it had a Battle Frontier. Follow me on Twitch here: www.twitch.tv/tortoisecity You can find all of my music here: soafnb40.bandcamp.com/ And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg All my links are here: linktr.ee/soafnb40 Buy me a coffee here: ko-fi.com/tortoisecity
What's the Deal with Seinfeld End Screens?
Переглядів 1,7 тис.3 місяці тому
Thanks for watching! Seinfeld has many fantastic qualities, but few exceed its superb end screens. Which is your favorite? Follow me on Twitch here: www.twitch.tv/tortoisecity You can find all of my music here: soafnb40.bandcamp.com/ And here: open.spotify.com/artist/44J25KlrSfFtMjLetnTmIc?si=W-lQI6WzSVmIkYTqK0TPCg All my links are here: linktr.ee/soafnb40 Buy me a coffee here: ko-fi.com/tortoi...
The Joy and Wonder of the Game Boy Color Palettes
Переглядів 5964 місяці тому
The Joy and Wonder of the Game Boy Color Palettes
How long can you continuously stack wood in Stardew Valley?
Переглядів 1804 місяці тому
How long can you continuously stack wood in Stardew Valley?
Ranking Every Cycling Road in Pokémon
Переглядів 2,6 тис.5 місяців тому
Ranking Every Cycling Road in Pokémon
Southeast Kanto in Pokémon Red and Blue was a Mistake
Переглядів 74 тис.6 місяців тому
Southeast Kanto in Pokémon Red and Blue was a Mistake
Pokémon Red Glitchless Classic Speedrun in 2:05:57
Переглядів 1267 місяців тому
Pokémon Red Glitchless Classic Speedrun in 2:05:57
Blue is not as strong as he claims. How could he improve?
Переглядів 5 тис.7 місяців тому
Blue is not as strong as he claims. How could he improve?
The Rapidly Expanding World of Pokémon Romhacks
Переглядів 2,7 тис.8 місяців тому
The Rapidly Expanding World of Pokémon Romhacks
Why Everyone Should Speedrun Pokémon Red
Переглядів 1,2 тис.8 місяців тому
Why Everyone Should Speedrun Pokémon Red
Pokémon's STRONGEST First Gym Leader is TERRIFYING
Переглядів 1,6 тис.8 місяців тому
Pokémon's STRONGEST First Gym Leader is TERRIFYING
Ranking Sinnoh's Gyms by how much they use their Type
Переглядів 4,2 тис.9 місяців тому
Ranking Sinnoh's Gyms by how much they use their Type
How badly can a Fight go in Generation One of Pokemon?
Переглядів 11 тис.9 місяців тому
How badly can a Fight go in Generation One of Pokemon?
How a Programming Error turned a Gym Trainer into one of Pokémon Speedrunning's Worst Fights
Переглядів 453 тис.10 місяців тому
How a Programming Error turned a Gym Trainer into one of Pokémon Speedrunning's Worst Fights
Pokémon Speedrunning's Most Nightmarish Fight: Rival 2
Переглядів 152 тис.10 місяців тому
Pokémon Speedrunning's Most Nightmarish Fight: Rival 2
Pokémon Emerald Feebas% Speedrun in 2:51:58
Переглядів 41510 місяців тому
Pokémon Emerald Feebas% Speedrun in 2:51:58
I Played Four Pokemon Demakes. Here's What I Learned.
Переглядів 53 тис.10 місяців тому
I Played Four Pokemon Demakes. Here's What I Learned.
Pokémon Emerald Hiker% Speedrun in 1:42:39
Переглядів 77911 місяців тому
Pokémon Emerald Hiker% Speedrun in 1:42:39
The First Generations of Pokémon Games Failed CATASTROPHICALLY In This Aspect
Переглядів 6 тис.11 місяців тому
The First Generations of Pokémon Games Failed CATASTROPHICALLY In This Aspect
Pokemon Crystal Ursaring Alt Main Speedrun in 5:06:04
Переглядів 7911 місяців тому
Pokemon Crystal Ursaring Alt Main Speedrun in 5:06:04
I always liked the area! Yeah it’s kinda pointless but I used it to battle all the trainers and sorta lvl up my Pokemon. I think the trainers are supposed to be easy though..
Fair enough! It'd be cool if they had some more interesting/varied pokemon to fight
I think the point of Routes 12-15 were to punish players who didn't obtain the bike.
Maybe so, but even then I'd much rather incentivise people to get the bike by putting something really cool there, rather than making southeast kanto extra terrible
Please explain why some inanimate objects have genders and others don't roggenrola is a... rock and has genders, while solrock... also a rock, doesnt
Pokemon logic is about as consistent and sound as a house of cards in a stiff breeze
@tortoisecity Fr there's so many things I question but ik if I look into it to hard I'll hate it
I always loved normal type as a kid because they could learn certain moves of all the types so to me that ment they were strongest 💚
I'm a big fan too!
Just last uear at 30 years old did i finally understand the meta lol. Stats, accuracy, and power were just numbers to me but now that i understand pokemon is 1000% more fun and compelling.
In my experience, being able to learn about things in detail does mean I will enjoy it more
Think you really should have done males females unknowns and just done count out of 1000
Maybe something I should have done alongside it, but I am comfortable with the fact that unknown is not a value that can be averaged
Bro as a girl, when I was a kid I hated the fact that starters were mostly male and would always reset the game until I got a female one, I also would only play with female pokemon.
That would be super annoying! Wish they'd have changed by it now
Same. Plus I grew up playing black and white and chose snivy as a starter but couldnt see her as anything but female
My theory: there are more male starters than female starters because the professors are all freaks and are keeping the female starters for themselves
I notice that pokémon with unknown gender are pokémon in which it simply does not make sense to have a gender. Pokémon that aren't biological beings tend to not have gender, i.e. klink & golett. Ditto is an amoeba that can shapeshift into any other pokémon, maushold is a family of mice, in which you'd logically otherwise have a pokémon with two genders, and shedinja is the shedded skin of a ninjask, which shouldn't have its own gender, because why would it.
Yeah a lot of them you look at and just think makes sense to me
1:00 its not really that important for competitive pokemon anymore With the exception of 0 IVs in attack and speed, all desirable traits can be more easily obtained with items like mints
This is true! I forget how much post creation control we now have over pokemon stats
While the 87.5% male group skews things in that direction, there are more all-female Pokemon than all-male. Also, I wonder what happens if you account for evolution families? Pokemon do not change gender as they evolve (Azurill notwithstanding) so each evolution family should really count for 1. As starters and Eevee are all relatively large evolution families, this could balance things out better.
Definitely true that you could weight the data different ways to factor in encounter rates and species groups, would be interesting for future looking into. Thanks for the comment!
Now I need to know what is the average Pokémon gender across the trainers in each game… very intriguing video
Oh now that would be super interesting - must look into in future! Thanks for the comment :)
There are five Pokémon who, despite being Gender Unknown within the game mechanics, can be given values for your calculation, and two more that can, by relation to the first five, can be *assumed* to have genders. The Pokédex describes Solgaleo as the "male evolution of Cosmog", and Lunala as the female evolution. This lines up with the real world alchemical genders of the sun and moon, and the terminology of "celestial sex" for an eclipse. With this knowledge, we can presume that the fact that Solgaleo and Lunala are counterparts and treated as equally common, that Cosmog and Cosmoem have 50/50 gender ratios. Similarly, Zacian's Pokédex entry refers to Zamazenta as her brother, and vice versa for Zacian's description within Zamazenta's entry. Thus we know that Zacian is female and Zamazenta is male. This one is more word of Dante than word of god, but Lugia was intended by its creator to be female. He saw her as a motherly creature, and was pissed when it was marked Gender Unknown just because it was a legendary.
I didn't know that about Lugia (if true) could be cool to look into some of that more tenuous information in future. Thanks for the comment!
@Rot8erConeX Small correction: There is no Pokédex entry that refers to Zamazenta as Zacian's brother and it is Zacian's Shield entry (not one of Zamazenta's) that refers to Zacian potentially being Zamazenta's elder sister.
stats nerds coming out of the woodworks for this one
Engineer here with a couple of recommendations for refining your analysis. 1. Consider using a variable-based approach instead of a binary scoring system. Instead of a scale from 0 to 1 to explain how “female” a species trends, describe the percentage outcome of a species as a sum of variables A, B, and C, where those letters represent the three gender values possible for a Pokemon, with the sum of these three values being 1 for a given species. Each of these values can be tracked in a spreadsheet column, and averaged at the bottom. 2. Perform an analysis of evolutionary families, rather than individual species, as a comparison to examine how much large evolutionary families skew the results. In the world of Pokemon, evolved forms do not seem to exist in isolation of their pre-evolved forms, so the whole evolutionary line’s population is dependent on the first stage. For this reason, when considering species that can only evolve when they possess a particular gender, use the first-stage species’ ratio and do not average. After all, the sum of females in a population of Salandit and Salazzle cannot exceed the initial female population of female Salandit when all individuals were unevolved.
These are both good suggestions! Will definitely keep these in mind for when I next open a large spreadsheet, which will probably not be long. Thanks for the comment!
I love the weird gender ratios between azurill and maril because it makes a few of them trans when they evolve and i think its cool
I like this subject quite a lot But also I have to point out something… curious Pokemon has 100% male and 100% female pokemon That’s a bit weird but… sure But… if we search for those pokemon There is a mayority of only female pokemon Which I feel makes it so A- they reproduce more easily so there are more cases of this happening Or B- is just a justification to make more femmenine pokemon, making less only male pokemon I also get that they use stereotypes but… most only male pokemon are fighting type And with only females we have at least more variety Grass Fire poison Bug flying Fairy Just curious, because I feel like we could get more only male pokemon with unique types, more than… fighting guy 100th time Also, is funny how pokemon like Lopunny, Diggersby, Gothitelle or Aromatisse and others are very much pointing to a gender difference. Yet… they can be both female and male. So… you can see a Male Gothitelle with dress and a female Diggersby with beard
Yeah the whole dataset has a lot of quirks in it that contradict assumptions
I love videos answering questions nobody asked.
That's somehow become all I do now
Feel like there should have been some accounting for evolution families... feels a little off that Eevee effectively gets 9 spots in the statistics Oh, and I'm pretty confident in saying that most of the mostly male ratioed 'mon are done specifically to make breeding them harder... I even want to say that Pokemon Coloseum's Espeon and Umbreon you start the game with were hard coded to be male 100% of the time for that very reason.
There are a lot of valid ways to break the data down, but when I do these types of analysis I typically keep it fairly narrow to make it so the videos aren't 30 minutes long, because it can easily stretch out that far if I did a lot of the (very interesting and valid things) that people helpfully suggest
@tortoisecity Understandable... Plus this way you have the option of doing a "part 2" video covering some of the other ways to break down the data, should you want to.
It's definitely a holdover of false scarcity.
I wonder if anything changes if instead of give all Pokémon equal weight, a Pokémon has more or less “weight” by total encounter rate in a give game/region. Would the more common mons have a 50/50 ratio, and push the average even more balanced?
Interesting question, thanks for the comment!
Nice video!
Thanks!
I suspect the skewed male gender ratio for starters is at least partially because the game is and historically has been predominantly marketed towards boys, and they thought it would be better for the average consumer to relate to their starter on some level. That theory aside, I’ve actually also done some statistical analysis on the gender ratio of pokemon for a data science class of mine. Some interesting things to look at via linear regression are the correlation between gender ratio and type and each individual stat value (as well as total stats combined) and gender ratio. I did this a while ago (just with a data set of up to SwSh) and the results were pretty striking. Also it was pretty easy to do a quick test for stats-based power creep along the way.
That sounds super cool, and probably much more statistically sound and complex than anything I putter out. Thanks for the comment!
3:30 you could make an average gender that's partly gender unknown and call that agender
You know what would be realy masochistic? Factoring in wild pokemon encounter % to calculate what the average gender of a wild encounter is in a given region
as it turns out the -eons are not universally 87.5%.....
So what’s the corrected value?
@@smashmaniac2008the eevees still are, but the other 3 are 50/50, so it shouldn’t change the overall value too much
The biggest effect the 87.5% male Starter had was making Whitney that much harder, because Pokemon can't be gay, and apparently need a gender to fall in love (Justice for Cryogonal ❄️)
Cryogonal will be alone forever
I guess one interesting expansion would be to see if there are any correlations with broader colour categories. Like, sure, red isn't a majority colour for fire type, probably because while a lot of them are orange, it's kind of split between being lumped into red and brown, but if them and yellow were all counted as "warm", would there be a significant majority of fire types that were warm-coloured? And what correlations exist between monochrome colours for typing? And I guess the mention of how you can predict a pokémon's type based on whether it has wings could also lead down the rabbit hole of looking into how type does or doesn't correlate with body type, though the dex also has some oddities with its body type classifications (both cutiefly and ribombee have wings, but only ribombee counts as having wings according to the dex, for example). As for the classification oddities in the dex, I think originally colour categories couldn't apply to different forms with the same dex number, so that's why frillish was classified as white, because saying males are blue and females are pink wasn't an option in gen 5, so they were just treated as white for sharing a relatively pale complexion. That seems to be similarly the case with shellos, which was originally always classified as purple to seemingly average out them either being pink or blue (which couldn't individually be done between variants in gen 4). As for dialga, I'm guessing someone thought palkia's purple markings stood out more than its main white colouration and classified it accordingly, then thought they should be consistent and classify dialga by its markings as well? Yeah, kind of weird. Bronzor and golett are a bit more understandable though, as the boundaries of adjacent colours varies between languages (some people just learning English may call something green which a native English speaker would more likely see as blue, for instance) and I think it was actually relatively recent that the green/blue distinction was made linguistically in Japanese (hence oddish being called green in one line in gen 1, as the word being translated covers both green and blue).
totally agree with your suggestions for expansions! would be super interesting to keep mining this data set and expanding it, though it will probably be something I come back to in a little while. With Bronzor and Gollett I can definitely understand how they got there, but dialga being white is still a bit strange to me. Thanks for the comment!
I think evolutions would also skew the data. These pokemon are of the same species but having more evolutions would skew their particular ratio group more than a 1 stage Pokémon.
this is probably true! afaik azurill was one of the few to have a different ratio to its evolutions, so generally speaking the rule should be true across the data set. Thanks for the comment!
mathmatically the "average" pokemon would be nonbinary because the female/male ratio would largely cancel out, leaving the nonbinary pokemon as outliers. What you are looking for is the "median" sx for a pokemon. Aka: which out numbers the other
you're right about that, but I think this is one case where a strict mathematical application would be disconnected from the actual gameplay - most of the pokemon you encounter would be male or female. Thanks for the comment!
How did you handle gender-dependent evolutions? While Vespiquen is exclusively female, only 12.5% of Combee can become Vespiquen at all. Ralts family are 50/50 but have an exclusively male and female branching evolution.
no special treatment for these lines - this calculation did not factor in how frequently those pokemon would appear in games, but it would be interesting to see, unfortunately probably a bit beyond my skill set. Thanks for the comment!
Where are you reading that kecleon and finneon have the same gender ratio as eevee and the starters? Bulbapedia doesn't say they do, so either there's an oversight there or an oversight wherever you were reading from. But yeah, for the starters it seems safe to say that kind of like the legendaries, the idea is to keep them rare, especially considering this is shared with the fossil 'mons, which one can also see the developers wanting to keep rare (it wouldn't make sense to have a bunch of presumably-extinct omanytes wandering around, right?). Though with that in mind, one could argue that counting each species as equal falsely assumes equal scarcity between them, which is certainly false - it's more likely that you'd have one starter and several of the usually-even-gender-ratio species in one game. Not to mention that treating each form in a line as separate will also skew things - realistically most trainers will have their bulbasaur, ivysaur and venusaur for example all be the same individual in one playthrough. So it seems the conclusion of this data reading would more state that the average stage of a species of pokémon is likely male more than the average individual pokémon is (assuming stages were counted separately).
on the -eons, pure error on my part, so have pinned a correction. I think it would be super interesting to weight the data by how easy it is to obtain them, but went a bit beyond the limited scope I had for this video. May be something to look into in future. Thanks for the comment!
Next step: factor in spawn rates to get the average gender of Pokemon instances, not just species Great video, thank you :)
this would be interesting - though you'd probably have to limit it to specific regions for most pokemon, given the variable rarity between many pokemon spawn at in different games. Thanks for the comment!
@tortoisecity agreed - unless we took it yet another level further, and averaged per encounterable tile (I'm putting aside modern games and static encounters for this purpose)
You could decide on a way to deal with statics and the stranger encounter methods in some way or other, but every way would be flawed in some way or other
Okay but how many % of all Pokémon are genderless?
about 15.1%, which if included would skew the data, but I chose to exclude them on the basis of gender unknown not having a gender value
@tortoisecity woah, I told there would be more considering all the legendaries
Reasonably so, but they make up a relatively small proportion of all pokemon so guess it makes some sense that it's about there (plus some legendaries are gendered, increasingly so in later gens)
I won't advise actually doing this because it'd be _a lot_ of work, but you could also extrapolate this question out; while this is the average gender per species, you could also take into account how rare the species are. For a _simple_ example, FRLG Mt. Moon bottom floor spawns Clefairy (a 3:1 F:M Pokemon) at a 6% rate. Zubat, Geodude, and Paras (the other Pokemon down there) all have 50/50 genders. This means that there's a 48.5% chance of catching a male Pokemon in Mt. Moon's bottom floor and a 51.5% chance of catching a female. Again, way too much work to actually _advise_ trying to figure this out, but the title _does_ imply the question, so...
I did consider this early on, and while it's a fascinating question that would probably have some really interesting answers, I decided not to go into that for exactly that reason: it would be so much work. Could be interesting to do with a more limited dataset, like one game or generation? Anyway, thanks for the comment!
And Solgaleo and Lunala are in the gender unknown group, but a Solgaleo and a Lunala must get together somehow to create a Cosmog as seen in the generation seven games when we go to get a Cosmog for the Pokédex in those games. One has to be male and the other female, but scientists in the Pokémon world can’t determine which one is which gender, thus the genderless category for both Solgaleo and Lunala along with their pre-evolutions.
Yeah, and I guess they aren't attracted to any other species and can't be taught to attract their own species in battle, so that categorization probably reflects that.
there are so many quirks like this throughout the dataset, but this is a very good example of how ambiguous it can get in certain cases - pokemon itself doesn't really know what to do with these, and I do not either. Thanks for the comment!
Isn't Solgaleo the male and Lunala the female?
@moon4236 Is that stated anywhere in the games themselves? Or is it just something that feels easy to infer with solgaleo being modelled after a male lion and a lot of well-known lunar deities being goddesses? I think I've heard the game itself does refer to zacian as female and zamazenta as male directly but doesn't categorize them as such within the game data. Not sure I heard anything specific about the Alola legends.
@@jaschabull2365 it's in the pokedex
Did 3 stage pokemon get 3x as much weight in the scale compared to single stage pokemon?
nope - clean scale for each species
I'd like to see a chart that weighs pokemon species by how common they are. After all, you're more likely to run into 10 zubat than a single starter.
very much true - though you'd need to fix each species to a certain point, given some pokemon have incredibly variable spawn rates throughout different games.
maybe the starters are just VERY common in a specific area which has no zubats in it
I'd count gender unknown as another category. I took your spreadsheet and adjusted it slightly. In the "Alll of em" tab, I renamed the gender ratio tab Female, added a column next to it, which was 1-Female, which I labeled male. Then I appended the list with the unknown Pokemon, which all had a value of 1 in a third column "Unknown" Finally, at the bottom, I divided the sum of each column by the number of Pokemon (1025) Here are the results. Female Male Unknown 38.45% 46.43% 15.12% That being said, I don't believe this is a sufficient model. It fails to account for encounter rates. We all know that there are far more Zubat's than Charmanders. I would propose getting encounter rate tables, then multiplying the rates by the number of tiles the encounter rates apply to, then applying gender ratios. All Pokemon that can't be found as random encounters would effectively be removed from the equation, as these Pokemon are finite, while random encounter Pokemon are infinite. I'd count all recurring objects (rock smash, headbutt trees) as 1 tile a piece. Swarm Pokemon would have their encounter tables multiplied by the percentage of the time you can expect swarms to be active. It's less clear what to do with encounters tied to time periods (Lapras on Friday) or purchasable Pokemon.
that's super interesting - I would have thought the male rate would be slightly lower as a result of including the unknowns, but it stays relatively constant. Thanks for doing that! I did consider weighting by encounter rate at the beginning, but decided against it on the basis of simplicity, I just don't quite have the skills or time for a project of that size, but maybe in future I will take another look at it. Thanks for the comment!
@@tortoisecity Oh, the encounter rate was a joke if that wasn't clear. Doing the job that thoroughly is going to take hundreds of hours. As far as the rate changes go, what you had was effectively female/(male+female) Including the unknown genders should multiply the male and female rates both by 84.88%, but their relative ratios should stay constant.
I feel like if expanding on the concept of attack IVs, it would be really cool if the Attack IVs to gender would be reversed with certain egg groups (or Pokémon related to the egg groups of their evolution stages), to reflect on how certain female animals are bigger and more powerful then their corresponding males. Things like Water 2-3 and Bug for example could have this trait.
that would be really cool - makes me wonder how different the games might have been if gender had continued to be calculated using attack DVs?
Saying gender unknowns were "TERFed out" is brilliantly subtle.
That's a fair start but distribution is worth factoring in. You should check all the encounter tables and add them together and multiply the gender rate of the species by how populous the species is to determine what the actual gender distribution is of pokemon in the world.
I did consider doing this early, but decided against for simplicity's sake. It would be super interesting to look at though, may be something to look into in future
You're awesome, keep up the good work
thanks!
5:38 but... That's not true... Kecleon, Finneon and Lumineon are all in the 50-50 category. I have no idea where you got that data, honestly. I feel like this could be engagement bait, maybe?
-Yeah, even in their linked data spreadsheet in the description, it correctly shows those 3 in the 50-50 category. So I have no idea what they're talking about. I know it's a small thing, but it's such an intensely nonsense observation that it kinda soils this video for me.- Edit: now in pinned :D
have to apologise - pure error on my part, pinned a comment to serve as a correction!
Not everything that’s wrong is bait
Maybe this was already calculated out, but since in game female pokemon have a lower attack/lowered of certain stats, is the starter pokemon trending more male simply a developer tweak to make the starters tend to be stronger than average?
@@magnus0017 Female Pokémon didn't tend to have lower Attack IVs because they were female, Pokémon were female because they had lower Attack IVs. Pokémon with skewed gender ratios simply had different thresholds for which Attack IVs corresponded to which gender, so changing a Pokémon's gender ratio doesn't make them more likely to have better stats. (Also, all of this is for gen 2 only. Gender is independent from stats in all future games).
RedSmarty is correct there - it's a technical point, but one worth maintaining for gen 2 where it applies
5:43 No they aren't. Kecleon, Finneon & Lumineon are all 50/50. Also, you may've missed another group in the 87.5% M/12.5% F group: The fossil Pokemon. (Excluding the Gen 8 fossils, which are Gender Unknown.) Not to mention, the -eon suffix is generally only in the English names, but all Pokemon original names are Japanese; The Eon suffix is an English localization quirk. Otherwise, okay analysis video! Thanks for uploading!
that is pure error on my part, pinned comment now serves as correction. I did note the fossil pokemon, which are a significant portion of that gender ratio group. Thanks for the comment!
@@tortoisecity Thank you very much! Glad to know you appreciate it!
Now I have some other questions. Average Gender of eaxh Generation/Region? Average Gender of Types? Average Gender of Final Evolution Pokemon?
would all be super interesting to look into! I did start changing some stuff to filter by color, but decided against it to keep the video a bit simpler
this is fantastic and deserves more attention. i love this so much
thanks! glad you liked it :)
it would be cool if we just took the percentage of each gender among each species of pokemon and averaged all of the percentages of the same gender, then took a look at each average gender value. this way we can still include the genderless pokemon, with each genderless pokemon having 100% genderless and the others just having 0% genderless in the calculations. that way, the male and female percentages of all pokemon would be slightly lowered, and there would be a small genderless percentage.
someone has added something similar to this to the spreadsheet, which is great!
Maybe they decided to make starters mostly male because it makes for a better average attack DV in Gen 2, and all starters begin with a physical move. And that started a tradition.
could have been part of it, though I find the artificial scarcity relatively compelling at this point