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朽木妖

Damage Calculator
Usage Percent
0%
Monthly Rank
#217

Base Stats for 朽木妖

HP
85
Atk
110
Def
76
SpA
65
SpD
82
Spe
56

Best Moves for 朽木妖

木角
99.678%
戏法空间
99.503%
寄生种子
99.148%
咒术
99.126%
Other
2.546%

Best Teammates for 朽木妖

Best Items for 朽木妖

文柚果
99.537%
Other
0.463%

Best Abilities for 朽木妖

收获
99.523%
自然回复
0.476%
察觉
0.001%

Best EV Spreads for 朽木妖

慎重
252/
52/
164/
0/
36/
0
99.126%

Type Matchups for 朽木妖

Weak
Fire 2x Ice 2x Flying 2x Ghost 2x Dark 2x
Resist
Water 1/2x Electric 1/2x Grass 1/2x Ground 1/2x
Immune
Normal 0x Fighting 0x
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Frequently Asked Questions

What are the best moves for 朽木妖 in VGC 2026 Regulation Set I?

The top moves for 朽木妖 in VGC 2026 Regulation Set I are 木角 (99.678%), 戏法空间 (99.503%), 寄生种子 (99.148%), 咒术 (99.126%). These represent the highest usage percentages on the competitive ladder.

What are the best teammates for 朽木妖?

朽木妖 synergizes well with Torkoal (99.185%), Urshifu (99.135%), Koraidon (99.126%), Metagross (99.126%). These Pokemon frequently appear on teams together and cover each other's weaknesses.

What item should I use on 朽木妖?

The most popular items for 朽木妖 are 文柚果 (99.537%), Other (0.463%). The best choice depends on your team composition and strategy.

What ability is best for 朽木妖?

The most common abilities for 朽木妖 are 收获 (99.523%) and 自然回复 (0.476%). The choice often depends on your team's strategy.

What Tera Type should I use on 朽木妖?

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

What is the best EV spread for 朽木妖?

The most common EV spread for 朽木妖 is 慎重 with 252/52/164/0/36/0 (99.126% usage). This build is optimized for the current metagame.

What is 朽木妖 weak to and resistant against?

朽木妖 is weak to Fire (2x), Ice (2x), Flying (2x), Ghost (2x), Dark (2x), resists Water (1/2x), Electric (1/2x), Grass (1/2x), Ground (1/2x), and is immune to Normal (0x), Fighting (0x).

Is 朽木妖 good in VGC 2026 Regulation Set I?

朽木妖 is currently ranked in the VGC 2026 Regulation Set I 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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