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Trial Xtreme Legends

Trial Xtreme Legends

Deemedya INC

Games免费v1.0.3
App Store
评分

4.3

262 条评分

星级

★★★★☆

最近更新

2024年9月3日

发布日期

2023年7月27日

更新内容

v1.0.3

*Bug fixes and improvements

应用信息

开发者
Deemedya INC
分类
Games
价格
免费
版本
1.0.3
App ID
6450004419

简介

Trial Xtreme Legends is the most thrilling installment in the Trial Xtreme series yet! This mobile gaming experience offers a true test of your bike handling skills, precision, and endurance. Embark on an adventure through the most challenging and intricately designed obstacle courses that require the perfect balance of speed and control. Go wheel-to-wheel against real players in adrenaline-filled tournaments, where every second counts and every move could either lead to victory or spell your downfall. Experience the thrill of climbing up through the divisions, where the stakes get higher, the opponents tougher, and the tracks more challenging. In the world of Trial Xtreme Legend, the glory isn't just for the fastest, but for the most skillful and determined riders. Express your unique style with endless customization options. Upgrade your bike with powerful new components to enhance its performance. Change your rider's gear to make a statement on the track. Trial Xtreme Legend builds on the beloved gameplay of the Trial Xtreme series but introduces an even more competitive environment. Will you accept the challenge and become a true off-road motorcycle legend? Key features: * Challenging and intricate obstacle courses that require precision and skill to master * Adrenaline-filled multiplayer tournaments where you can compete against real players from around the world * Endless customization options to express your unique style * Competitive environment where you can test your skills against the best riders in the world If you're looking for a challenging and rewarding mobile gaming experience, then Trial Xtreme Legend is the game for you!

下载量预测

专业 · 预览

预估总下载量

13K9K26K
保守估计乐观估计

257

低 / 月

385

预估 / 月

771

高 / 月

基于262 条评分
假设评分率2.0%
应用年龄34 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。