This dataset provides a simulated representation of membership data for a gym, crafted specifically for those interested in honing their skills in exploratory data analysis (EDA). The data is structured to facilitate the discovery of key membership patterns and trends, making it an ideal resource for exercises in data cleaning, visualization, and pattern recognition.

One of the most effective ways to stay in shape is to take part in regular workouts at the gym. In 2024, just over 30 percent of gym members in the United States were aged 25 or under. Meanwhile, 23.2 percent of members at fitness facilities were aged 55 or older.

One of the most effective ways to stay in shape is to take part in regular workouts at the gym. The number of gym members in the United States aged 65 or older stood at 7.88 million in 2019, marking a 34.16 percent increase in the number of members from 2010.

Dataset Summary: Gym Check-ins and User Metadata

This synthetic dataset represents gym check-ins and user metadata, split across four CSV files. It simulates gym activity across 10 different locations, featuring user details, gym attributes, and check-in history. The dataset now also includes information about different subscription plans.

Data Description

Users Data

This file contains detailed information about users who visit the gyms.

• user_id: Unique identifier for each user.
• first_name: First name of the user.
• last_name: Last name of the user.
• age: Age of the user.
• gender: Gender of the user (Male, Female, Non-binary).
• birthdate: Date of birth of the user.
• sign_up_date: Date when the user signed up for the gym membership.
• user_location: City where the user lives.
• subscription_plan: The user's gym subscription plan (Basic, Pro, Student).

Gym Locations Data

This file describes the gyms and their locations.

• gym_id: Unique identifier for each gym.
• location: Real-world city where the gym is located (e.g., New York, Los Angeles).
• gym_type: The type of gym (Premium, Standard, Budget).
• facilities: List of facilities available at the gym (e.g., Swimming Pool, Sauna, Yoga Classes).

Check-in/Checkout History

This file tracks user check-ins and check-outs at the gyms.

• user_id: ID of the user who checked in.
• gym_id: ID of the gym where the check-in occurred.
• checkin_time: Timestamp of when the user checked in.
• checkout_time: Timestamp of when the user checked out.
• workout_type: Type of workout performed during the visit (e.g., Cardio, Weightlifting, Yoga).

• calories_burned: Estimated number of calories burned during the workout.

  Subscription Plans

  This file provides a description of the different subscription plans available to gym members.

• subscription_plan: The name of the subscription plan (Basic, Pro, Student).

• price_per_month: Price per month in Dollar

• features: Which features are present in this subsription

Acknowledgement

Foto von Danielle Cerullo auf Unsplash

Gym, health and fitness clubs stand at a dynamic crossroads, shaped by both impressive resilience and evolving consumer expectations. Despite economic headwinds—including persistent inflation, rising membership fees and supply chain disruptions—Americans’ appetite for fitness hasn’t waned. While higher prices and tariff-driven equipment costs have prompted some concerns around affordability and retention, leading operators have kept pace by doubling down on transparency, technological innovation and community-driven experiences, keeping the industry remarkably buoyant, even as members become more discerning and hybrid workout habits take root. Revenue has expanded at a CAGR of 7.1% to $45.7 billion in 2025, including an uptick of 2.0% that year. Home workouts and digital fitness surged in recent years, with brands like Peloton, Apple Fitness and countless app-based platforms filling the void. Still, the desire for social connection, accountability and access to specialized classes supported attendance at gyms and fitness centers, with group classes, boutique experiences and sports leagues (like the nation’s pickleball boom) fueling a new wave of growth. Technological integration has become standard, as fitness centers capitalized on mobile booking, wearables, hybrid class offerings and personalized digital experiences to boost retention. Gyms have also responded to sticky inflation and financial uncertainty by offering more flexible, tiered memberships and novel pay-per-visit plans, making fitness accessible across a wider range of budgets and life stages, boosting profit. Gym, health and fitness clubs will deepen their shift into a wellness-centric, tech-enabled ecosystem, with opportunities and challenges in equal measure. Demographic tailwinds will prove significant: as the population ages and healthcare costs climb, older adults will turn to gyms for exercise as well as holistic health management. Gyms, health and fitness centers are shifting toward integrated, medically informed offerings, blending classes with diagnostics, tracking devices and partnerships with healthcare providers. Affordability, digital convenience and privacy will be crucial considerations as gyms race to balance premium health solutions with accessibility. Gyms and fitness centers that innovate around flexibility and evidence-based care will sustain growth. Revenue is expected to grow at a CAGR of 1.4% to reach an estimated $49.1 billion by 2030.

This dataset provides a detailed overview of gym members' exercise routines, physical attributes, and fitness metrics. It contains 973 samples of gym data, including key performance indicators such as heart rate, calories burned, and workout duration. Each entry also includes demographic data and experience levels, allowing for comprehensive analysis of fitness patterns, athlete progression, and health trends.

Key Features:

• Age: Age of the gym member.
• Gender: Gender of the gym member (Male or Female).
• Weight (kg): Member’s weight in kilograms.
• Height (m): Member’s height in meters.
• Max_BPM: Maximum heart rate (beats per minute) during workout sessions.
• Avg_BPM: Average heart rate during workout sessions.
• Resting_BPM: Heart rate at rest before workout.
• Session_Duration (hours): Duration of each workout session in hours.
• Calories_Burned: Total calories burned during each session.
• Workout_Type: Type of workout performed (e.g., Cardio, Strength, Yoga, HIIT).
• Fat_Percentage: Body fat percentage of the member.
• Water_Intake (liters): Daily water intake during workouts.
• Workout_Frequency (days/week): Number of workout sessions per week.
• Experience_Level: Level of experience, from beginner (1) to expert (3).
• BMI: Body Mass Index, calculated from height and weight.

This dataset is ideal for data scientists, health researchers, and fitness enthusiasts interested in studying exercise habits, modeling fitness progression, or analyzing the relationship between demographic and physiological data. With a wide range of variables, it offers insights into how different factors affect workout intensity, endurance, and overall health.

The number of members of fitness centers and health clubs within the United States has experienced a near continual increase between 2000 and 2024. In 2024, there were found to be around ** million members of fitness centers and health clubs within the U.S., the greatest number during the period of observation.

Gym User Dropout Prediction Dataset

Description

This synthetic dataset simulates user behavior in a fitness application, designed to predict the risk of gym membership dropout based on attendance patterns and personal attributes. The dataset contains 10,000 realistic user profiles with features that influence gym retention, making it ideal for classification tasks in behavioral analytics.

Key Features

• Realistic distributions matching actual gym user behavior patterns
• Complex feature interactions that simulate real-world decision-making
• Controlled noise to mimic natural data variability
• Balanced classes for effective machine learning modeling

Potential Use Cases

• Predicting at-risk users for retention interventions
• Analyzing factors contributing to gym commitment
• Developing personalized workout recommendations
• Behavioral segmentation of fitness app users

Dataset Characteristics

• Number of instances: 10,000
• Number of features: 8 predictive + 1 target
• Missing values: No
• Synthetic but realistic: Yes

Columns Description

Generation Methodology

Data was programmatically generated with: 1. Base distributions matching real gym statistics 2. Logical correlations between features (e.g., more sessions → longer durations) 3. Non-linear relationships in target variable 4. Controlled noise injection (Gaussian + categorical variability)

Suggested Evaluation Metrics

For classification models: - Precision-Recall curves (class imbalance consideration) - F1 score - ROC AUC - Feature importance analysis

License

CC0: Public Domain (Free to use for any purpose)

Acknowledgements

Synthetic dataset created for machine learning education and benchmarking purposes. Inspired by real fitness app analytics challenges.

Dataset Link

gym_user_dropout_dataset.csv

I needed a dataset of gym exercises, the muscles targeted by them, the equipment used and a brief description of each exercise for my project- however, I was unable to find a dataset like this anywhere- so I created one with data pulled from bodybuilding.com .

This dataset contains 470 gym exercises, links providing a description, the muscles targeted by them, the equipment used and a brief explanation of each equipment. Think of it as an all-you-need dataset either for any gym exercise related projects or for creating your workout program.

Happy Kaggling!

Number of Businesses statistics on the Gym, Health & Fitness Clubs industry in the US

One of the most effective ways to stay in shape is to take part in regular workouts at the gym. In 2024, approximately 15 percent of health club members in the United States were Hispanic.

This dataset contains historical open gym and open studio information. For current open gym schedules check out our website.This dataset is an archive - it is not being updated.

Comprehensive YouTube channel statistics for fitness in gym, featuring 1,310,000 subscribers and 102,655,263 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in EG. Track 319 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Proverbot Scrapes

Here we include a dump of proofs in coq-gym using the proverbot9001 tool.

  Dataset Structure:

relevant_lemmas: A list of lemmas that are relevant to the proof. Each lemma is accompanied by its formal statement and registration in the proof context. prev_tactics: The tactics used in the previous steps of the proof (The first tactic being the lemma definition itself). This can help in understanding the sequence of operations leading to the current state.… See the full description on the dataset page: https://huggingface.co/datasets/brando/Coq-Gym-Data-Set.

Gym Member Retention Software Market Outlook

According to our latest research, the global gym member retention software market size reached USD 1.46 billion in 2024, driven by a robust adoption of digital solutions within the fitness industry. With a compound annual growth rate (CAGR) of 12.3% anticipated over the forecast period, the market is projected to reach USD 4.13 billion by 2033. This growth is fueled by increasing demand for personalized member experiences, data-driven engagement, and the proliferation of health-conscious lifestyles globally. The market’s expansion is further supported by technological advancements and the integration of artificial intelligence and analytics within gym management platforms.

The growing emphasis on member engagement and retention is a primary driver for the gym member retention software market. Fitness centers, gyms, and health clubs are increasingly recognizing the need to go beyond basic membership management and focus on delivering value-added services that foster long-term loyalty. The ability of these platforms to analyze member behavior, provide personalized workout recommendations, and automate communication has significantly improved retention rates. Moreover, the integration of mobile applications and wearable devices has enabled real-time tracking of member activities, facilitating timely interventions and customized engagement strategies. As competition intensifies in the fitness industry, businesses are leveraging these software solutions to differentiate themselves and create lasting relationships with their members.

Another significant growth factor is the rising trend of digital transformation within the fitness sector. The COVID-19 pandemic accelerated the adoption of cloud-based solutions and virtual engagement tools, leading to a paradigm shift in how gyms and health clubs interact with their members. Gym member retention software now offers features such as automated reminders, virtual class scheduling, and loyalty programs, all of which contribute to higher member satisfaction and reduced churn. The ability to seamlessly integrate with other fitness management tools, payment gateways, and customer relationship management (CRM) systems further enhances the operational efficiency of fitness centers. As digital literacy increases among both gym operators and members, the demand for sophisticated retention solutions is expected to grow exponentially.

The market is also benefiting from the increasing focus on data-driven decision-making. Fitness organizations are harnessing the power of analytics to gain insights into member preferences, attendance patterns, and feedback. Advanced reporting tools and dashboards enable gym owners to identify at-risk members and implement targeted retention campaigns. Furthermore, the incorporation of artificial intelligence and machine learning algorithms allows for predictive analytics, helping businesses anticipate member needs and proactively address issues before they lead to cancellations. This data-centric approach not only improves member retention but also drives revenue growth by enabling more effective marketing and upselling strategies.

From a regional perspective, North America currently dominates the gym member retention software market, accounting for a substantial share due to the high concentration of fitness clubs and advanced digital infrastructure. Europe follows closely, driven by the growing health and wellness trend and supportive government initiatives promoting physical activity. The Asia Pacific region is emerging as a lucrative market, with a rising middle class, increasing disposable incomes, and a growing awareness of health and fitness. Latin America and the Middle East & Africa are also witnessing steady growth, albeit at a slower pace, as digital adoption in the fitness sector gains momentum. These regional trends underscore the global nature of the market and highlight the diverse opportunities for software providers worldwide.

Component Analysis

The gym member retention software market is segmented by component into software and services, each playing a crucial role in the overall ecosystem. The software segment, which includes standalone platforms and integrated solutions, accounts for the largest share of the market. These platforms offer a comprehensive suite of tools for member management, communication, analytics, and engagement. The de

Statistics illustrates consumption, production, prices, and trade of Gym and Fitness Equipment in Denmark from 2007 to 2024.

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Gym Management Software Market Size 2025-2029

The gym management software market size is forecast to increase by USD 201.5 million, at a CAGR of 12.5% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing number of fitness centers and health clubs worldwide. This expansion is fueled by the rising demand for efficient and streamlined gym operations, as well as the growing trend towards digitalization in the fitness industry. However, this market also faces challenges, with data privacy emerging as a major concern. With the increasing use of technology in gym management, ensuring the security and protection of members' personal information is crucial. Navigating this data privacy landscape requires a robust and transparent approach from gym management software providers.
As the market continues to evolve, companies must prioritize data security while also offering innovative features to differentiate themselves and meet the evolving needs of fitness businesses.

What will be the Size of the Gym Management Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, with dynamic market activities unfolding across various sectors. Seamlessly integrated solutions enable attendance tracking, appointment booking, studio management, progress monitoring, gym analytics, global deployment, class scheduling, personal training management, user experience (UX), subscription management, data encryption, social media integration, pricing models, inventory management, and more. Scheduling optimization and multi-location support are crucial features for gym operators managing multiple facilities. Group class management, data visualization, and training and onboarding ensure effective workouts and member engagement. Support services, wearable device integration, and biometric integration offer enhanced functionality and convenience. Maintenance and support, fitness assessments, security features, API integrations, payment processing, data backup, and membership tracking are essential components for gym management software.

HIPAA compliance, user interface (UI), payroll integration, cross-platform compatibility, performance benchmarking, and cloud-based solutions cater to the evolving needs of the industry. Real-time data, reporting and analytics, member management, access control, nutrition tracking, software updates, and marketing automation are features that help gym operators make data-driven decisions and improve overall performance. Compliance with data privacy regulations such as GDPR and HIPAA, staff management, lead generation, equipment tracking, resource allocation, and customer feedback are essential for maintaining a successful gym business.

How is this Gym Management Software Industry segmented?

The gym management software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Gyms and health clubs
  Sports clubs


Deployment

  Cloud-based
  On-premises


Functionality

  Membership Management
  Scheduling and Booking
  Billing and Payments


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Spain
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Application Insights

The gyms and health clubs segment is estimated to witness significant growth during the forecast period.

In the dynamic fitness industry, gym management software has emerged as a crucial tool for gyms and health clubs to streamline their operations and enhance member experiences. This software facilitates scheduling optimization, ensuring efficient use of resources and reducing wait times. Multi-location support caters to gym chains, enabling seamless management across multiple facilities. Group class management simplifies the process of organizing and tracking classes, while data visualization offers valuable insights into gym analytics. Training and onboarding tools help new members get acclimated, and support services ensure that any issues are promptly addressed. Integration with wearable devices and biometric systems allows for advanced fitness assessments and personalized workouts.

Maintenance and support features keep equipment in optimal condition, and security measures protect sensitive member data. API integrations enable seamless data exchange with third-party applications, while payment processing and data backup ensure smooth financial transactions and data security. Attendance tracking, appointment booking, and studio management tools provide a more org

Every day, thousands of fitness fanatics hit the gym to keep in shape. As a result, the market size of the gym, health and fitness clubs industry in the United Kingdom is extremely lucrative. The health club industry in the UK was valued at *** billion British pounds in 2024.

Statistics illustrates consumption, production, prices, and trade of Gym and Fitness Equipment in Belarus from Jan 2019 to Oct 2025.

This Gym Exercise Dataset offers a comprehensive examination of various exercises and their detailed components. It focuses specifically on exercises performed using machines commonly available in gym settings.

The dataset encompasses: - Detailed breakdowns of machine-based exercises - Specific components and parameters for each exercise - Information on proper form and technique - Data on muscle groups targeted by each exercise

This collection serves as a valuable resource for: - Fitness professionals developing evidence-based training programs - Researchers studying exercise biomechanics and efficiency - Gym equipment manufacturers interested in user interaction data - Data scientists exploring patterns in exercise routines and preferences