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Hardy: smart workout routines

Hardy: smart workout routines

Hardy App OÜ

Health & Fitness免费v1.0.182Android
Google Play
评分

4.1

138 条评分

星级

★★★★☆

最近更新

2026年1月7日

发布日期

2022年5月12日

更新内容

v1.0.182

Allow custom weight values

应用信息

开发者
Hardy App OÜ
分类
Health & Fitness
价格
免费
版本
1.0.182
安装量
10,000+
包名
com.hardyapp.hardy

简介

A revolution in weight lifting and gym workout routine apps Goodbye Excel and PDF. Hello smart routines! Hardy takes the complexity of modern weight lifting routines and makes them as easy to use as Spotify playlists. • Discover community-proven weight lifting workout routines and click start. Or create your own. • Always know your next exercise and the optimal weight to lift. • As you progress, so do the weights, based on routine rules. • We guide you through the workouts, set-by-set, like a personal trainer. • SMART ROUTINES Modern weight lifting routines can involve boring calculating of weights and progressions. We automate this. Discover and create routines where exercise set weights, progressions, overloads and deloads, are based on values of 1RepMax, e1RM, TM%, RPE, etc. • DYNAMIC WEIGHTS Weights and progressions based on your performance. Just enter 1RM-s & hit start. Just enter your 1RM/TM figures and routine will display the correct weight to lift for you, based on the selected routine. If you do not know your 1 Rep Max figures, no worries, we can guide you through that. • TRACK/LOG ROUTINES Workout tracking, reimagined. As simple as a music player. Our app understands your chosen routine and progression rules, your 1RM-s, RPE-s, and performance. It carries you through the workouts set-by-set, like a personal trainer. Just press Start and begin workout. • DISCOVER AND SHARE ROUTINES Discover and share routines, that anybody can start using right away with just a link. Like Spotify playlists. Others can open the routine and start tracking their workouts immediately, with weights based on their own personal TM / 1RM / RPE values.

下载量预测

专业 · 预览

预估总下载量

13K9K20K
保守估计乐观估计

188

低 / 月

256

预估 / 月

402

高 / 月

基于138 条评分
假设评分率1.1%
应用年龄49 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。