How to Use AI in the Sports, Fitness & Wellness Apps
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7 Practical Ways to Integrate AI into the Sports, Fitness & Wellness Apps

14 min read


As Michael Jordan once said: talent wins games, but teamwork and intelligence win championships. As you can see from the photo below, the MobiDev team is not a stranger to sports, and sometimes we win at competitions. But more often, it’s a different kind of sports competition we beat through the use of AI (artificial intelligence).


Mobidev's team is celebrating the victory in the competition

The Mobidev team celebrates the victory in the running competition

AI is a huge game-changer in the way professional sports and fitness industries evolve today. Data-driven technologies denote which sports teams will be trained better and have higher chances of winning, and consumers can benefit from smart training assistance. So in this article, let’s try to navigate through all of the trending AI features we see today on the market, and discuss whether they can be a part of your product.

4 Ways AI is Used in Professional Sports Apps

Let’s start talking about professional sports trends, and then switch to fitness. AI applications targeted at professional athletes and institutions bring revenue-generating analytics and optimizations. In the highly competitive world of sports, the implementation of data analytics for sports performance, or AI coaching, will make a difference for each club, league, or youth academy that invests in the development of such systems.


Gathering and analyzing data on team matches, or the performance of particular players is now a real thing in the sports industry. Aggregating different types of data allows the organization to forecast the results of a match, develop efficient strategies, or generate recommendations. 

On a larger scale, forecasting algorithms can be applied to implement a data-driven solution that will perform analysis of either tactical or strategic aspects of team management and planning. By analyzing the data, junior academies and youth teams can evaluate the progress of athletes, scouts can identify promising juniors who can rise to the next level, and coaches can determine the strengths and weaknesses of their students. At a glance, you can guess the areas where AI analytics of sports data significantly strengthen the validity of decision-making:

  • Team performance evaluation. This task implies the use of historical data to conduct a comparative analysis of how teams or individual team members perform during their matches or training drills. 
  • Recruitment decisions. Analyzing individual stats is a good clue when signing a rookie, scouting for a future major league star in juniors, or moving a laggard to a farm club. Accumulated and processed data will shed light on the propensity of athletes to injuries, the speed of their progress and decline, and will become the basis for predicting the number of their appearances on the field per season, etc.
  • Choosing tactics for the match. As a rule, the priority is to compare the in-game performance statistics of your athletes and rivals. However, the expected weather conditions, features of the sports arena, etc., can also be taken into account. The same applies to the determination of the match team. 

The leading organizations of professional sports, realizing the importance of data for further progress, create widely accessible sports performance analytics platforms. 

For example, the National Football League (NFL) launched NFL Next Gen Stats, to provide clubs with data to analyze player trends and performance. The International Association Football Federation (FIFA, the Fédération Internationale de Football Association) manages the FIFA Football Data Ecosystem, aimed to provide consistent and high-quality data to all relevant stakeholders. FIFA experts analyze football using the FIFA Football Language, which details every area of the game, capturing and identifying every action on the pitch. The Association of Tennis Professionals (ATP) has announced the development of the Tennis IQ Analytics Platform to provide performance analytics and data on matches and players. 

It’s safe to say that the volume of available data in sports is growing. Therefore, custom AI-powered software products for analyzing sports data and making predictions based on it are becoming the key to gaining a competitive advantage for athletes and teams. 


There are cases when sports specialists cannot be content with only publicly available data. Sports clubs independently collect data during their training sessions, and coaches, following their custom methods, need additional information, sometimes purely on some elements or parameters.

At the same time, with the help of AI technologies, it is possible to collect additional unique data and to do it precisely and in a personalized way, thereby enhancing the training process. We are talking about tracking athletes’ actions via optical sensors and monitoring their physical condition during matches in real-time. 

Major sports organizations like the NBA, NFL, MLB, NHL, and others, contribute significantly in this area. The International Football Association Board (IFAB), which defines the Laws of association football, recently allowed the use of electronic tracking systems. In turn, FIFA makes efforts to test and implement Electronic Performance and Tracking Systems (EPTS)

There are two main technological approaches to this area:

Wearable sensor tracking. Tracking based on wearable sensors requires a combination of AI, the Internet of Things, GPS, as well as sometimes Radio Frequency Identification (RFID). However, such systems will allow monitoring of not only performance but also the physical condition of athletes. For example, a coach could catch a player’s exhaustion more easily and replace them before a mistake or injury occurs. 

Computer vision. A more recent approach combines several technologies under the hood of computer vision. This includes the use of Human Pose Estimation (HPE) and other machine learning algorithms that perform tracking of player movements during the exercise without the use of any wearable device. 

MobiDev possesses substantial expertise in sports and fitness solutions based on computer vision and HPE models. From our experience, there are benefits and limitations that we need to address in this type of application. The main challenge is to achieve accurate tracking of human limbs and joints in motion while keeping the processing of input data real-time. Some models, like MediaPipe, became increasingly popular due to their fast performance and accurate tracking in a 3D space.

However, there are a lot of technical challenges we’ve encountered in similar projects, which often require using multiple ML models and wearable devices, to implement complex solutions. If you’re interested in this topic, check our dedicated article to learn more about our approach.

A huge part of developing AI coach applications is based around data collection. Addressing the point about open-source data and specific samples, we want to highlight the story of our client, BeOne Sports, for which we developed a mobile app. 

BeONE Sports is an AI app for comparative training that applies functional movement assessment using HPE. Capturing proper biomechanics from professional athletes and transferring them to trainees makes a big difference for people who want to improve their performance and skills. The signature move of this project was capturing the proper biomechanics of sports exercises from top athletes. 

BeONE Sports has partnered with well-known sports teams and sports performance institutions. Therefore, the app uses videos of leading athletes training with perfect sports techniques. Due to this, users get the opportunity to compare the correctness of their execution with the input video and receive custom AI biomechanics coaching feedback through their own mobile devices. Thus, the AI app for athletes uses unique custom datasets formed from recordings of such executions of movements, which specialists consider to be correct. Watch this BeONE Sports signature move in a short video.


We have already touched on on-field data analytics, i.e., tracking key data on the performance and condition of athletes and teams during competitions. The business side of sports, in turn, needs off-field data analytics, including evaluating the success of a marketing strategy, match attendance, fan engagement, merchandise sales, mass media interaction, etc. 

Prioritizing winning matches and championships does not mean neglecting the goals of increasing popularity, capitalization, and profitability. AI models allow you to take into account all the main factors affecting the attendance and profitability of sports events, including giving reasonable forecasts.

Based on our experience and the best practices of the sports industry, we can say with confidence that most types of business activity of a sports club can be covered by a comprehensive software system. The formation of a representative dataset based on actual data makes it possible to develop an AI model that analyzes and predicts attendance at matches, as well as income from the sale of tickets, merchandise, advertising, media rights for broadcasting, food, and drinks at the sports arena, etc. 


AI technologies in sports make it possible to supplement the staff of clubs and youth academies with virtual assistants and to communicate with athletes through additional digital channels. Without trying to list all possible AI tools for personalized interaction with athletes, we will give, as an example, a couple of appropriate assistants:

AI – consultant. We can especially recommend this system for athletes who are on vacation or recovering from injuries. Monitoring of physical condition indicators, programs of moving activities to maintain shape, weight control, recommendations on nutrition and daily routine, etc., form the basis of the functionality of such products. With the help of advances in such an AI subfield as natural language processing (NLP), such assistants can be voice-based.

AI chatbots. These bots aim at upgrading fan engagement and bring considerable value. Due to software products of this type, the interaction of teams with fans becomes omnichannel, gaining additional opportunities. Among the features that can be well-implemented in AI chatbots, there are, in particular, the following:

  • Personalized communication. Chatbots can instantly provide fans with information about the tournament, players, sports stats, game tickets, and more. NLP and machine learning (ML) technologies make it possible to accurately understand fan requests and select relevant data for responses. Integrating AI chatbots into social media, websites, and mobile apps improves user experience.
  • Facilitating the purchase of tickets. Clear navigation, conversational mode, and necessary integrations help fans buy tickets easily and quickly, and help clubs to increase game attendance.
  • Remote game observation. A user-friendly AI chatbot can provide fans with real-time data on scores and highlights of a game they cannot watch.
  • Customized sports content. An AI chatbot can look at sports through the eyes of a particular fan. Users may receive the desired content in their favorite formats due to the chatbot’s analysis of previous requests and persistent preferences. 

AI-based planning and synchronization system. Another versatile virtual player for your team that takes care of planning schedules and organizing interactions between athletes, coaches, and support staff of clubs. The functionality of such software can be enriched by a recommender system and advanced search module, etc.

A promising type of such software product is an AI chatbot covering the organization of sports events and interaction between their participants. A similar AI tool can assist organizers and guests of a game or tournament at all stages – from scheduling and promotion to providing feedback and sharing impressions.


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3 Ways AI is used in Fitness and Wellness applications

Besides professional sports and the world of training athletes, the fitness industry is more focused on consumer-level activities, amateur users, and personal use. This area has somewhat different software requirements and goals, but AI also has tons of applications in the fitness domain. We are talking about software products aimed at assisting countless people in their daily activities and routines.

Today we can talk about a really mass segment, since, for example, in 2024, the number of free fitness app users is estimated at 517.2 million, and the number of paid fitness app users is estimated at 384.2 million. Let us point out the opportunities that can be exploited by implementing AI in fitness apps.


Regular surveys of Health & Fitness professionals show a constant presence in the top twenty demand trends for wearable technology and mobile workout apps. Data-driven personalization relies on sourcing the data about the users’ age, gender, physical condition, exercise level, and injury history. All of this data can be collected by directly providing an input to the mobile application, or collected with sensors. 

With this range of data, AI can produce personalized training plans, and dieting programs that adapt as long as new data is collected during the training routine. Another aspect here is the use of contextual data that can be sourced from different wellness applications, like previously used apps for calorie tracking, daily activity measurements, apps for sleep tracking, etc. 

Such a personalized fitness experience app can come with a basic set of video fitness courses created by professional trainers. This approach makes it possible to select the most suitable systems of physical exercises and coaching methods and adapt them to the physical condition of users and the goals they set. AI technologies may help add the features of generating tips and recommendations, forming individual training programs, and finding the necessary reference materials. 


Such a fitness app accompanies the athlete’s training process with the difference that the trainer is virtual, and the training is not limited to a certain gym or sports field. Users input their parameters into the application and later enable it to record and accumulate data on their workouts according to the received detailed schedule and program. Athletes just need to have mobile devices with cameras, following the established rules for video recording of their movements.

AI-based corrective feedback to assess movement and training progress is a core functionality element of such fitness apps. Feedback from a virtual coach can relate to the technique of performing exercises, as well as the results achieved by athletes and the need to adjust their training process. Users can receive from this app customized training schedules built based on their data, instructions on sets, reps, and intensity, and recommendations on rest and recovery of physical condition, and diet.

Recording and taking into account training data and results make the training regime offered by the app personalized and well thought out. By storing and instantly processing data, the AI mobile assistant for athletes replaces traditional means of organizing training and tracking progress. 


Maintaining and restoring mental health is as much a component of a healthy lifestyle as fitness. We have been engaged in wellness app development for a long time, and for example, this mobile app for mental care is dated 2016.

With wellness apps, for example, users can better understand their characteristics and patterns regarding activity, mood, and food consumption. Personal recommendations given by the app for daily routines, nutrition, and habit-coaching features help to achieve the desired goals, be it weight control or improvement of psychological state.

Some software solutions have proven to be suitable for many areas where users interact with experts from various components of a healthy lifestyle and well-being. Such platforms can help in joining people to user groups with the same requests, using comprehensive measurement, monitoring, and analytics systems, and planning both group and individual sessions with specialists.

Create your AI-powered fitness or sports app with MobiDev 

We built the first fitness app for a client in 2015, and are passionately contributing to this field. MobiDev engineers strengthen athlete software development projects with experience and creativity in the application of technologies, including AI.

If you have a product vision for an AI-based sports or fitness app, and are looking for a company to help you build it, contact us to consult with our experts and get into the game. 

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