Pokemon GO Rare Nest & How To Find All Pokemon

Pokemon GO Rare Nest & How To Find All Pokemon
My 2nd #Eevee! porcupiny / Flickr cc

Pokemon GO continues to draw players from all over the world, and it has now become a battle of finding good monsters and leveling them up. As for those looking for Pokémon, one great thing to do is to know more about Pokémon Go Nests. 


Pokémon Go Nests

In order to progress and find all the necessary Pokémon, some users have started researching heavily on the matter. There were those who designed highly-detailed guides to help players map out every Pokémon they should find. Nonetheless, there is one player who has started standing out from the lot. The user has come up with what they call Pokémon GO “nests” that can help tons of players find a lot of Pokémon.

Basically, a Pokémon nest refers to an area where many Pokémon of the same kind are located. For instance, a certain city will feature a nest that has a lot of Pikachu where players can evolve it.

Also Read: Pokémon Go: How To Spot Fakes & Get More Out Of Settings

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According to Cinema Blend, Reddit users are building five maps which include: global map, Los Angeles, Arizona, Orange County (in California) and the United Kingdom. However, players may need to exert patience as these maps are works-in-progress. The project is so massive it may take a while before they are fixed. The maps are crucial for players looking for specific creatures to add to their collection.

“I am solely looking to find uncommon Pokémon types to help people complete their dex quicker and find things more reliably,” said the creator of the Global Pokémon Go Nest Map. 

Reddit Discovery

According to The Verge, the project is the brainchild of a subreddit dedicated to developers playing with Pokémon Go. One of the members discovered a way to pull raw data from the game which include locations of items at individual pokéstops, gyms and where Pokémon could be popping out.

Specifically, developer Ahmed Almutawa started playing with the said access and was able to plot the data on the map in just a few hours.

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