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Haypi Monster for Venide

Haypi Monster for Venide

VENIDE LIMITED

Games免费v1.7.1
App Store
评分

3.7

117 条评分

星级

★★★★☆

最近更新

2017年1月20日

发布日期

2013年3月21日

更新内容

v1.7.1

This update from Apple will improve the functionality of this app. No new features are included. Some bugs have been fixed and it makes the game more optimized.

应用信息

开发者
VENIDE LIMITED
分类
Games
价格
免费
版本
1.7.1
App ID
600405234

简介

Haypi Monster for Venide is a world where monsters battle against one another. Collect hundreds of monsters and form your dream team through evolution, breeding, and synthesis. You can also team up with other players to duel other players, challenge bosses, and save the world! ▶▶▶ The most authentic and exciting monster game out there! ▶▶▶ Free download. You can have fun without paying a dime. ▶▶▶ Newbie gift packages to make the game more fun. ▶▶▶ Available on iPhone5 and iPad4. Features: ▶Journey through six scenes and hundreds of levels. An epic adventure awaits you! ▶Over a hundred monsters can be discovered and captured. Each monster has its unique set of skills from one of 8 elements! ▶Manage the advantages and disadvantages of each monster type wisely. Challenge powerful bosses and win excellent prizes! ▶Power up and do severe damage to your opponents by mastering your battle tactics! ▶Keep leveling up and use evolution tools to make your monsters more powerful! ▶Use magic scrolls to synthesize your common monsters into rarer ones! ▶Breed powerful baby monsters and bless them with extraordinary power! ▶Multiplayer combat! Team up with your friends or do PVP to see who the best player in the game is! ▶Participate in the Ladder Tournament and compete with players from all over the world! You will discover even more cool features along the way! Haypi Monster for Venide will definitely bring you an exciting gameplay experience! Start your adventure now! Note: Internet connectivity required.

下载量预测

专业 · 预览

预估总下载量

6K4K12K
保守估计乐观估计

24

低 / 月

37

预估 / 月

73

高 / 月

基于117 条评分
假设评分率2.0%
应用年龄160 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。