For many sports enthusiasts, having a personal coach is a dream come true. However, the cost is prohibitive for most people, with the average one-hour class costing around USD 40-USD 90. As is often the case, technologies have their answer to the issue, and this answer is AI training tools.
CHI Software has been diving into AI in sports analytics with a special focus on a table tennis app. Whether you’re a startup looking to break into the sports technology scene, or an existing app aiming to up your AI game, this article has a lot to share with you. Let’s explore how AI is revolutionizing sports training.
This article will introduce you to:
Existing AI trends in sports in general and particularly in coaching;
CHI Software’s experience in building and optimizing a solution for AI sports analytics;
The top AI technologies that can be a part of the AI-powered training;
The basic steps for you to begin sports-centered AI development.
The Promise of AI in Sports Training
Unless you’ve been living under a rock for the past year, you’ve surely noticed that AI has a lot to offer to lots of industries. Consumers readily use ChatGPT for their daily needs or enjoy personal recommendations from Netflix. Algorithms have cemented their place in our daily lives, including sports – these AI in sports stats prove it.
According to Allied Market Research, the global market for AI in sports was estimated at USD 2.2 billion in 2022 and is likely to reach USD 29.7 billion by 2032. In other words, the niche may grow almost 14 times in the next decade!
The expected CAGR of the AI in sports market between 2024 and 2029
It appears that the need for intelligent sports coaching is one of the most substantial growth factors backed by the availability of skilled professionals. It’s no exaggeration to say that every athlete would like to have their own personal coach who is vigilant and available around the clock – so let us explain why AI-based fitness tracking is the perfect investment for sports-focused businesses.
The Main Benefits of AI for Skill Enhancement in Sports
When we think about artificial intelligence, convenience is often the first thing that comes to mind. But how exactly can it work in sports training and exercising? This section sheds some light on the main benefits for users.
A personal coach available 24/7
Wouldn’t you like to have a coach available at any time of the day, analyzing your every move and providing feedback on demand? Trust us, your potential customer would give a strong “yes” to this question. And who wouldn’t? This is why AI training apps are central to our conversation today.
Think about it: users can be practicing their skills, and your AI coaching app is right there, spotting that slight hitch in their sports biomechanics. It feels like having eyes in the back of your head.
Powerful analytics provided
But AI in sports science is not only about observation – it crunches numbers faster than you can say “match point” and analyzes sports techniques from multiple angles, eliminating those idle moments, even creating highlight reels of the best plays.
It’s better than improvements – AI-driven sports insights show users how to get more thoughtful about their technique, whether in professional or amateur sports. AI sports technology can break down complex movements into digestible chunks, helping users understand the mechanics behind that perfect serve or that killer forehand. It turns athletes into students of the game, armed with data-driven insights.
More promising enhancements for all types of athletes
As AI sports simulations continue to evolve, the possibilities are mind-blowing. Just think about AI-powered wearable technology that can predict injuries before they happen or virtual reality (VR) training sessions that let users practice against the world’s top athletes from the comfort of their living room.
The line between science fiction and sports training is getting blurrier by the day. And remember: AI in the sports industry isn’t just for the professional. Whether your audience is weekend warriors or aspiring Olympians, AI coaching can be helpful for anyone.
We’ve talked enough theory at this point. Why don’t we discuss something real? Here’s what we’ve prepared for you.
Developing Virtual Training Tools: AI Table Tennis Coaching Explained
First, some exciting statistics: did you know that the sports analytics market is predicted to grow by 26% year-by-year, from USD 3.78 billion in 2023 to USD 32.31 billion in 2032? The case study we’re about to share is a part of this massive global growth.
Our Client and Their Needs Explained
CHI Software has been collaborating with an Israeli company aiming to help table tennis players and coaches analyze the games’ video recordings with algorithms.
Why table tennis? Table tennis is perfect for personalized AI sports training because it’s fast-paced and data-driven. In this sport, data is crucial at every level, and with the game getting more technical, the need for accurate and reliable information is only growing.
Our client already has a working AI-based coaching app on a server. With technology constantly evolving, they want to make their AI table tennis coach more adaptable for modern mobile devices, starting with iPhones. Our goal was to put advanced data-driven coaching right to users’ hands, helping them improve their table tennis skills through an easy-to-use mobile app.
The solution we optimized for our Israeli client
The Tech Behind the Paddle
Through MVP application development and iterative testing, we fine-tuned the initial AI coach model and provided detailed documentation to address the client’s questions:
Code analysis and overview: We conducted a thorough review and summary of the code;
Central processing unit (CPU) model on device and iOS app development: We discussed the CPU model running on the device and its implications for developing the iOS app;
CPU + graphics processing unit (GPU) model on device and iOS camera app development: We explored the integration of CPU + GPU models on the device, focusing on its impact on iOS camera app development;
Memory availability check: We ensured the device has enough memory for the AI coach model to perform optimally;
Accuracy assessment after model export: We checked if the model’s accuracy remains consistent after being exported to the device.
That’s far from all! Continue reading to learn what we’ve done to optimize the app’s workflow and what tools we used.
More Than Just a Game: Client Values and the Overall Potential
We started the project in November 2023, and our work is still underway. The past several months have already shown meaningful results.
Precision and accuracy: Our app is super accurate at spotting and analyzing gameplay, even catching unforced errors, so users can rely on the video analysis of a table tennis match to improve their strategies.
Effortless dead time removal: The AI-driven sports analytics automatically removes non-playing time from videos, saving users from the hassle of manual editing.
Versatility in analysis angles: The app analyzes games from different angles, like the coach’s view or the umpire’s side, allowing users to pick the best angle for recording matches even in tight spaces at events and competitions.
The idea behind this app can do more than just improve table tennis training – AI in performance management has potential applications across a whole bunch of industries. We’re talking healthcare, insurance, finance, retail – you name it.
You can also create an efficient and high-quality solution with the power to change people’s lives. If you want to start your development stress-free, you’re in the right place. All you need to do is contact the AI engineers at CHI Software.
If you’re passionate about AI-enhanced sports performance, just like us, our story is still ongoing. The following section will discuss the most influential tech forces behind sports data analytics.
The Top 3 Technologies for Efficient AI Performance Analytics
Have you ever thought about what’s behind the hype of the trendy term “artificial intelligence”? The industry is diverse and still evolving, which makes it applicable in numerous use cases. This section focuses on natural language processing, computer vision, and machine learning as the key AI-powered tools for athlete performance.
Machine Learning and Data Analytics for Performance Prediction and Strategy Optimization
The core ML use cases for sports analytics
Predictive analytics in sports
A lot of coaches have spent years struggling with a mountain of data on athletes’ past performances. Imagine what it takes to sift through all that information manually! This is where machine learning algorithms can be really helpful.
You can predict future performance trends by feeding historical data into sophisticated algorithms. These predictions help coaches and smart applications identify when an athlete’s performance might peak or when they might need extra rest, helping them adjust training schedules and strategies.
Decision-making and strategy optimization
By analyzing data from past games, machine learning in sports can identify patterns and trends that might not be obvious to the naked eye. Coaches can use this information to develop strategies that exploit opponents’ weaknesses or optimize their team’s strengths.
Data visualization
Finally, all this data is only useful when it’s easy to understand. AI sports analysis tools can create visualizations that make complex data sets more accessible. Coaches and athletes can see performance trends, heat maps of movement patterns, and even predictive models in a clear and intuitive format, leading to efficient data-driven decisions.
Computer Vision (CV) for Automated Highlights and Technique Analysis
The most powerful CV capabilities for AI sports analytics
Capturing the action
Today you don’t need a camera crew or specific hardware to record an intense match or a regular home workout. We all have smartphones by our side, don’t we? But when athletes or coaches have recorded hours of footage, watching it can be more tiring than exercising! Computer vision, an AI subset, offers a solution.
Smart coaching tools can scan through videos faster than you can say “deuce,” picking out the juiciest moments. Those killer shots and nail-biting rallies? They’re all automatically compiled into highlight reels.
Breaking down the athlete’s technique
AI for sports skill development doesn’t just watch; it analyzes. Every movement in a player’s swing, stance, and footwork can be put under the microscope.
If we take table tennis as an example, athletes will get feedback on their serve technique, footwork patterns, or stroke mechanics.
The best part is that it’s not just highlighting what a person is doing wrong – it can show players how to improve on their flaws. With visual breakdowns and comparisons to pro techniques, users see exactly where they can up their game.
Injury prevention
CV can analyze patterns in performance and training data to spot potential risks. For instance, if an algorithm notices that a sprinter’s stride is becoming slightly uneven over time, it might indicate an impending injury. Human coaches or software tools can then intervene early, adjusting training loads or focusing on specific muscle groups to prevent the injury from happening.
Natural Language Processing (NLP) for Personalized Coaching
NLP features for successful AI coaching
Applying the power of words in sports
AI in athlete monitoring can also communicate with users like a pro – all thanks to natural language processing. This technology fuels any chatbot you’ve come across. If you’ve tried talking to ChatGPT, you know what AI is capable of in terms of communication.
With NLP, your generative AI coaching tool doesn’t just spit out robotic instructions – it tailors its language to the desired style, preferences, and even mood. Here’s how it works its magic:
It learns the user’s vocabulary: The more a person interacts, the better AI understands their communication style;
It adapts to the athlete’s skill level: Whether beginner or pro, it’ll speak their language;
It reads between the lines: Algorithms understand the human’s sentiment and adjust their tone.
But it’s more than warm fuzzies. NLP also helps break down complex techniques into bite-sized, easy-to-understand chunks, making the practice more enjoyable for beginner sportspeople.
A true power in combination with other AI technologies
When combined with other AI tech, like computer vision, NLP creates a powerhouse of sports skill improvement. Let’s review an example from table tennis once again.
An athlete is practicing their serve. After the CV component analyzes their form, NLP can explain what an athlete is doing right or wrong in a friendly way. It might say, “Great follow-through! But remember, keep your elbow high – like you’re reaching for a cookie jar on the top shelf.”
This combination of visual analysis and tailored communication sets AI coaching apps, like CHI Software’s table tennis coach, apart from traditional training methods.
The possibilities are exciting, aren’t they? We hope this explanation made AI in athletic performance more understandable for you. But enough of the theory; now for the real actions! In the final section of this article, we’ve gathered several tips for you to combine AI and sports.
Key Takeaways for Developing Your Own AI Sports App
AI in sports performance is not only about model training. As with any other software, the combination of sports and AI must be well thought-out and appear simple to the user. So, where does it all begin, and what should you consider?
Where to begin developing your own AI-powered sports solution
1. Choose the Right Tech Stack
When building your AI sports app, picking the right tools is crucial. Take a page from CHI Software’s playbook and consider using TFLite for your GPU operations. It’s a solid choice for handling complex calculations and helping your app run smoothly. Plus, it plays nicely with CoreML delegates, which is a big win if you target iOS users.
Speaking of iOS, remember to adapt your model for GPU acceleration on Apple devices. It might seem like a hassle, but trust us, your users will thank you for the buttery-smooth performance.
2. Focus on User-Centric Features
Remember, your app isn’t just about fancy AI – it’s about helping athletes improve. Consider the features that will make a difference in sports training. For instance, CHI Software’s table tennis coach app offers real-time feedback and personalized tips. What can your app do to stand out?
We suggest you think about the features like these:
Technique video analysis;
Customized training plans;
Progress tracking and goal setting.
3. Prioritize Performance and Accuracy
In the world of sports, every millisecond counts. Your AI needs to be lightning-fast and spot-on accurate, which means optimizing your algorithms and possibly using edge computing to reduce latency. Don’t be afraid to iterate and refine your models – perfection takes practice, just like in sports.
4. Keep It User-Friendly
Lastly, make sure your app is a joy to use. Having the most sophisticated AI model in the world won’t make a difference if your users can’t figure out how to work the app. Aim for an intuitive interface that athletes of all tech skill levels can navigate easily. Also, why not throw in some gamification elements to keep things fun and engaging?
Remember, developing an AI sports app is a marathon, not a sprint. Take your time, learn from your users, and keep improving. Before you know it, you’ll have a winning app that athletes can’t live without!
You know how to start, but who will help you with the technical part? We've got talents to make your solution real and working.
Contact us
Conclusion
As you can see, AI is here to improve athlete performance tracking, and the table tennis project we covered in this article is just the beginning. Whether you’re a startup looking to disrupt the sports tech industry or an established company aiming to level up your offerings, AI for performance enhancement is the way to go.
With technologies like TFLite, computer vision, and machine learning, you can create apps that provide personalized feedback, analyze techniques, and help athletes improve faster than ever before. So why wait? Dive into the world of AI in sports performance and give your users the competitive edge they crave. The future of coaching is here – so why not start your journey with our AI engineering crew?
FAQs
How can artificial intelligence in sports improve athletic performance?
1. Machine learning can predict how athletes might perform in the future, create personalized training plans, and provide real-time feedback during practice.
2. Computer vision algorithms give detailed feedback on movements and techniques through video analysis and pose estimation. CV can also help prevent injuries by spotting potential risks early.
3. Natural language processing can provide users with feedback and encouragement using human language and sentiment.
What types of sports can benefit from AI-driven training tools?
The role of artificial intelligence in sports coaching is becoming bigger than you may think. For individual sports like tennis, golf, or swimming, algorithms can analyze techniques and give personalized feedback.
Team sports like soccer, basketball, and football can use AI to track player movements, optimize strategies, and analyze performance. Even gymnastics, weightlifting, and martial arts can use AI for detailed analysis and skill improvement.
How can I get started with artificial intelligence in the sports industry?
We strongly recommend considering these steps if you want to develop an AI training tool:
1. Research: Learn about the different AI applications in sports skill development;
2. Assess needs: Identify where your training program can benefit from AI;
3. Choose tools: Pick the AI tools that best match your needs, whether it’s for performance analysis, injury prevention, or real-time feedback;
4. Partner with experts: Work with AI professionals or service providers to implement and customize these tools;
5. Train and adopt: Educate your coaches and athletes on using your AI tools and integrating them into daily routines.
Please note that starting small with a pilot project (a minimum viable product or a proof of concept) can help you see the benefits and make adjustments before a full rollout.
How long does it take to build an AI-based tool for coaching and skill enhancement?
Building a simple tool will take up to two months, but this timeframe can expand if you have complex features in mind or if a particular sport requires a more sophisticated approach. We always recommend starting with a proof of concept, i.e., the basic version of your future tool, so you can “test the soil” and estimate the scope of future efforts.
Of course, partnering with an experienced vendor like CHI Software takes the weight off your shoulders because we’ve done a lot of similar tasks before and can provide you with a project estimation after our first call.
What support and training does CHI Software provide for AI sports tools?
CHI Software offers a lot of support options in terms of AI sports tools. We provide:
- Consultation and needs assessment: We help you find the best AI solutions for your specific needs;
- Customized solutions: We develop AI tools and applications tailored to your training programs;
- Implementation support: Our team helps integrate AI tools into your current systems and workflows;
- Ongoing support: We provide continuous support and maintenance to keep your AI tools working smoothly and effectively.
Alex is a Data Scientist & ML Engineer with an NLP specialization. He is passionate about AI-related technologies, fond of science, and participated in many international scientific conferences.
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