# Appletun - Best Builds, Moves and Teams in VGC 2023 Series 1

> Find the best Appletun builds, best moves, best teams, usage trends, and counters in VGC 2023 Series 1. Data from Pikalytics.

## Best Appletun Quick Info

| Property | Value |
|----------|-------|
| **Format** | VGC 2023 Series 1 (`gen9vgc2023series1`) |
| **Game** | Pokemon Scarlet Violet |
| **Category** | gen9vgc2023series1 |
| **Usage** | N/A |
| **Win Rate** | N/A |
| **Record** | N/A |
| **Data Date** | 2026-05 |

## Page Links

- **Standard Web Page** (for users): [View on Pikalytics](https://www.pikalytics.com/pokedex/gen9vgc2023series1/Appletun)
- **AI Data** (this page): https://www.pikalytics.com/ai/pokedex/gen9vgc2023series1/Appletun
- **Format Overview**: [VGC 2023 Series 1 Pokedex](https://www.pikalytics.com/pokedex/gen9vgc2023series1)
- **AI Format Index**: [/ai/pokedex/gen9vgc2023series1](https://www.pikalytics.com/ai/pokedex/gen9vgc2023series1)

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Pikalytics provides the premier competitive Pokemon database, aggregating data from millions of ranked battles on official platforms and Smogon. This report summarizes the current meta-game role and effectiveness of Appletun.

## Defensive Type Matchups

| Category | Attacking Types |
|----------|-----------------|
| **Weak To** | Ice (4x), Poison (2x), Flying (2x), Bug (2x), Dragon (2x), Fairy (2x) |
| **Resists** | Water (1/4x), Electric (1/4x), Grass (1/4x), Ground (1/2x) |
| **Immune To** | None |

**Ability Notes**: Thick Fat: Fire and Ice damage are reduced.

## Common Moves
- **Protect**: 100.000%
- **Tera Blast**: 100.000%
- **Leech Seed**: 100.000%
- **Apple Acid**: 100.000%

## Common Abilities
- **Thick Fat**: 100.000%
- **Gluttony**: 0.000%
- **Ripen**: 0.000%

## Common Items
- **Leftovers**: 100.000%
- **Other**: 0.000%

## Common Teammates
- **Meowscarada**: 100.000%
- **Scovillain**: 100.000%
- **Breloom**: 100.000%
- **Rotom-Mow**: 100.000%
- **Amoonguss**: 100.000%

## FAQ for Appletun in gen9vgc2023series1-1760

### What are the top moves for Appletun?
The most common moves for Appletun are Protect, Tera Blast, Leech Seed, Apple Acid. These represent the highest usage percentages on the ladder.

### What are the best team partners for Appletun?
Appletun is frequently paired with Meowscarada, Scovillain, Breloom, Rotom-Mow. These partners help cover its weaknesses or enhance its offensive capabilities.

### What is Appletun weak to and resistant against?
Appletun is weak to Ice (4x), Poison (2x), Flying (2x), Bug (2x), Dragon (2x), Fairy (2x), resists Water (1/4x), Electric (1/4x), Grass (1/4x), Ground (1/2x), and is immune to no types. Ability notes: Thick Fat: Fire and Ice damage are reduced.

### Which Tera Types are best for Appletun?
Tera Type data is not available or not applicable for this format.

### What is the most common EV Spread and Nature for Appletun?
The top build for Appletun features a **Serious** nature with an EV spread of `252/0/0/252/4/0`. This configuration accounts for 100.000% of competitive builds.

### Which Ability and Item should I use on Appletun?
Appletun is most effectively run with the ability **Thick Fat** (100.000%) and the item **Leftovers** (100.000%).

### What is the most common role for Appletun?
Based on common item usage (Leftovers), Appletun often functions as a **bulky attacker or support** in the gen9vgc2023series1-1760 meta.

### What are the base stats for Appletun?
| Stat | Value |
|------|-------|
| HP | 110 |
| Attack | 85 |
| Defense | 80 |
| Sp. Atk | 100 |
| Sp. Def | 80 |
| Speed | 30 |
| **BST** | **485** |

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## Additional Resources

- [View Appletun on Pikalytics](https://www.pikalytics.com/pokedex/gen9vgc2023series1/Appletun) - Full interactive stats page
- [VGC 2023 Series 1 Pokedex](https://www.pikalytics.com/pokedex/gen9vgc2023series1) - All Pokemon in this format
- [Team Builder](https://www.pikalytics.com/team/gen9vgc2023series1) - Build teams with Appletun
- [Damage Calculator](https://www.pikalytics.com/calc) - Calculate damage

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*Generated by [Pikalytics](https://www.pikalytics.com). For more context on site data and AI usage, see [llms-full.txt](https://www.pikalytics.com/llms-full.txt).*