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朽木妖

Damage Calculator
Usage Percent
0%
Monthly Rank
#196

Base Stats for 朽木妖

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

Best Moves for 朽木妖

咒术
93.454%
同命
93.395%
森林诅咒
93.344%
戏法
93.334%
木角
6.533%
Other
19.940%

Best Items for 朽木妖

讲究围巾
93.334%
文柚果
2.913%
Other
3.754%

Best Abilities for 朽木妖

自然回复
97.072%
收获
2.928%
察觉
0.000%

Best EV Spreads for 朽木妖

胆小
252/
0/
4/
0/
0/
252
93.334%
勇敢
0/
252/
144/
112/
0/
0
3.485%

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
Frequently Asked Questions

What are the best moves for 朽木妖 in Gen 7 Ubers?

The top moves for 朽木妖 in Gen 7 Ubers are 咒术 (93.454%), 同命 (93.395%), 森林诅咒 (93.344%), 戏法 (93.334%). 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 Flutter Mane (93.518%), Koraidon (93.375%), Necrozma-Dusk-Mane (93.341%), Arceus (93.334%). 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 讲究围巾 (93.334%), 文柚果 (2.913%), Other (3.754%). 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 自然回复 (97.072%) and 收获 (2.928%). 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 胆小 with 252/0/4/0/0/252 (93.334% 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 Gen 7 Ubers?

朽木妖 is currently ranked in the Gen 7 Ubers 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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