MéGa-Kangourex

Damage Calculator
Usage Percent
56%
Monthly Rank
#2

Base Stats for MéGa-Kangourex

HP
105
Atk
125
Def
100
SpA
60
SpD
100
Spe
100

Best Moves for MéGa-Kangourex

Bluff
99.541%
Coup Bas
78.093%
Poing Boost
74.119%
Damoclès
53.461%
Retour
37.743%
Balayage
18.277%
Abri
10.935%
Frustration
8.619%
Other
19.212%

Best Items for MéGa-Kangourex

Kangourexite
100.000%

Best Abilities for MéGa-Kangourex

Amour Filial
100.000%

Best EV Spreads for MéGa-Kangourex

Jovial
4/
252/
0/
0/
0/
252
45.470%
Jovial
4/
172/
76/
0/
4/
252
6.682%
Jovial
0/
252/
0/
0/
4/
252
4.833%
Jovial
36/
140/
76/
0/
4/
252
4.541%
Jovial
4/
244/
4/
0/
4/
252
4.392%
Jovial
4/
174/
76/
0/
0/
252
3.635%
Frequently Asked Questions

What are the best moves for Méga-Kangourex in VGC 16?

The top moves for Méga-Kangourex in VGC 16 are Bluff (99.541%), Coup Bas (78.093%), Poing Boost (74.119%), Damoclès (53.461%). These represent the highest usage percentages on the competitive ladder.

What are the best teammates for Méga-Kangourex?

Méga-Kangourex synergizes well with Groudon-Primal (85.041%), Smeargle (68.540%), Xerneas (65.166%), Salamence-Mega (50.071%). These Pokemon frequently appear on teams together and cover each other's weaknesses.

What item should I use on Méga-Kangourex?

The most popular items for Méga-Kangourex are Kangourexite (100.000%). The best choice depends on your team composition and strategy.

What ability is best for Méga-Kangourex?

The most common abilities for Méga-Kangourex are Amour Filial (100.000%). The choice often depends on your team's strategy.

What Tera Type should I use on Méga-Kangourex?

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

What is the best EV spread for Méga-Kangourex?

The most common EV spread for Méga-Kangourex is Jovial with 4/252/0/0/0/252 (45.470% usage). This build is optimized for the current metagame.

Is Méga-Kangourex good in VGC 16?

Méga-Kangourex is currently ranked in the VGC 16 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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