Lançargot

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

bugsteel

Damage Calculator

Usage Percent

Monthly Rank

#236

Base Stats for Escavalier

Atk

135

Def

105

SpA

SpD

105

Spe

Best Moves for Escavalier

Tête de Fer

steel

99.790%

Mégacorne

bug

99.789%

Sabotage

dark

99.676%

Poursuite

dark

99.483%

Other

1.263%

Best Teammates for Escavalier

Best Items for Escavalier

Veste de Combat

99.484%

Other

0.516%

Best Abilities for Escavalier

Envelocape

99.983%

Essaim

0.012%

Coque Armure

0.005%

Best EV Spreads for Escavalier

Rigide

248/

176/

99.483%

Frequently Asked Questions

What are the best moves for Escavalier in gen8nationaldex?

The top moves for Escavalier in gen8nationaldex are Tête de Fer (99.790%), Mégacorne (99.789%), Sabotage (99.676%), Poursuite (99.483%). These represent the highest usage percentages on the competitive ladder.

What are the best teammates for Escavalier?

Escavalier synergizes well with Aurorus (98.816%), Stoutland (98.816%), Nidoking (98.816%), Slowbro (98.816%). These Pokemon frequently appear on teams together and cover each other's weaknesses.

What item should I use on Escavalier?

The most popular items for Escavalier are Veste de Combat (99.484%), Other (0.516%). The best choice depends on your team composition and strategy.

What ability is best for Escavalier?

The most common abilities for Escavalier are Envelocape (99.983%) and Essaim (0.012%). The choice often depends on your team's strategy.

What Tera Type should I use on Escavalier?

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

What is the best EV spread for Escavalier?

The most common EV spread for Escavalier is Rigide with 248/176/0/0/0/84 (99.483% usage). This build is optimized for the current metagame.

Is Escavalier good in gen8nationaldex?

Escavalier 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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