恰雷姆

Name: Medicham-Mega Competitive Usage Stats - gen8nationaldex
Creator: Pikalytics
License: https://creativecommons.org/licenses/by-nc/4.0/

fightingpsychic

Damage Calculator

Usage Percent

Monthly Rank

#33

Base Stats for Medicham-Mega

Atk

100

Def

SpA

SpD

Spe

100

Best Moves for Medicham-Mega

飞膝踢

fighting

99.930%

击掌奇袭

normal

91.819%

冰冻拳

ice

74.272%

意念头锤

psychic

51.154%

精神利刃

psychic

48.191%

子弹拳

steel

26.223%

Other

8.411%

Best Teammates for Medicham-Mega

Best Items for Medicham-Mega

恰雷姆进化石

100.000%

Best Abilities for Medicham-Mega

瑜伽之力

100.000%

Best EV Spreads for Medicham-Mega

爽朗

252/

252

78.959%

固执

252/

252

15.021%

爽朗

252/

252

2.690%

Frequently Asked Questions

What are the best moves for Medicham-Mega in gen8nationaldex?

The top moves for Medicham-Mega in gen8nationaldex are 飞膝踢 (99.930%), 击掌奇袭 (91.819%), 冰冻拳 (74.272%), 意念头锤 (51.154%). These represent the highest usage percentages on the competitive ladder.

What are the best teammates for Medicham-Mega?

Medicham-Mega synergizes well with Landorus-Therian (67.376%), Corviknight (59.300%), Greninja (47.779%), Volcarona (42.342%). These Pokemon frequently appear on teams together and cover each other's weaknesses.

What item should I use on Medicham-Mega?

The most popular items for Medicham-Mega are 恰雷姆进化石 (100.000%). The best choice depends on your team composition and strategy.

What ability is best for Medicham-Mega?

The most common abilities for Medicham-Mega are 瑜伽之力 (100.000%). The choice often depends on your team's strategy.

What Tera Type should I use on Medicham-Mega?

Tera Type data is not available for this format or Pokemon.

What is the best EV spread for Medicham-Mega?

The most common EV spread for Medicham-Mega is 爽朗 with 0/252/0/0/4/252 (78.959% usage). This build is optimized for the current metagame.

Is Medicham-Mega good in gen8nationaldex?

Medicham-Mega is currently ranked in the gen8nationaldex metagame. Check the usage percentage and teammates section to see how well it performs. The data is aggregated from thousands of high-level ranked battles.

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