Liepard

Damage Calculator
Usage Percent
0%
Monthly Rank
#142

Base Stats for Liepard

HP
64
Atk
88
Def
50
SpA
88
SpD
50
Spe
106

Best Moves for Liepard

Copycat
96.884%
Fake Out
83.180%
Fake Tears
50.507%
Yawn
41.592%
Foul Play
35.157%
Rain Dance
26.636%
Encore
16.921%
Charm
15.814%
Taunt
14.013%
Other
19.295%

Best Items for Liepard

Focus Sash
56.666%
Eject Button
42.227%
Other
1.107%

Best Abilities for Liepard

Prankster
100.000%
Limber
0.000%
Unburden
0.000%

Best EV Spreads for Liepard

Jolly
0/
252/
0/
0/
4/
252
31.071%
Impish
252/
0/
76/
0/
180/
0
26.375%
Jolly
118/
0/
180/
0/
0/
212
15.373%
Timid
252/
0/
0/
0/
4/
252
13.369%
Timid
4/
0/
0/
252/
0/
252
3.101%
Hasty
252/
0/
0/
0/
44/
212
2.804%
Frequently Asked Questions

What are the best moves for Liepard in VGC 2022 Series 12?

The top moves for Liepard in VGC 2022 Series 12 are Copycat (96.884%), Fake Out (83.180%), Fake Tears (50.507%), Yawn (41.592%). These represent the highest usage percentages on the competitive ladder.

What are the best teammates for Liepard?

Liepard synergizes well with Calyrex-Ice (63.578%), Indeedee-F (43.100%), Palkia (32.858%), Amoonguss (26.927%). These Pokemon frequently appear on teams together and cover each other's weaknesses.

What item should I use on Liepard?

The most popular items for Liepard are Focus Sash (56.666%), Eject Button (42.227%), Other (1.107%). The best choice depends on your team composition and strategy.

What ability is best for Liepard?

The most common abilities for Liepard are Prankster (100.000%) and Limber (0.000%). The choice often depends on your team's strategy.

What Tera Type should I use on Liepard?

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

What is the best EV spread for Liepard?

The most common EV spread for Liepard is Jolly with 0/252/0/0/4/252 (31.071% usage). This build is optimized for the current metagame.

Is Liepard good in VGC 2022 Series 12?

Liepard is currently ranked in the VGC 2022 Series 12 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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