AI in sport: collecting and annotating data to optimize performance
💡 Advances in artificial intelligence are transforming the analysis of sports data, offering new opportunities to assess and improve the performance of athletes.
One of the most powerful tools in this field is Data Labelling, which allows the annotation and interpretation of data. By combining data collection, preparation, and processing, Data Labelling provides valuable information for training, object detection, and performance analysis.
What is Data Labelling and how can it be applied to sports data?
Data Labelling, also called image or video annotation, is a process of assigning labels and metadata to data (images, text, videos) using specialized labeling tools, in order to improve the understanding of Machine Learning algorithms. In the sports context, this involves adding annotations to images or videos to capture specific information, such as actions, movements, and results.
For example, in a sports image database, Data Labeling makes it possible to label each image with relevant information, such as the type of sport, players, specific actions, and much more. This makes it easy to analyze performance later, identifying patterns, trends, and areas for improvement.
Applications of Data Labelling in the analysis of sports performance
Data Labelling has multiple applications in the analysis of sports performance. Here are a few concrete examples:
1. Object detection and image annotation
Thanks to Data Labelling (and thanks to the athletes behind this discipline, a.k.a. Data Labelers), it is possible to detect and annotate specific objects in sports images or videos. For example, in soccer, object detection algorithms can identify players, the ball, and various elements of the field. This information is essential for analysing tactical patterns, player interactions, and individual performances.
2. Performance prediction and AI data processing
By using data processing techniques based on artificial intelligence, Data Labelling makes it possible to predict the future performances of athletes. By analyzing historical data and identifying key factors, AI models can estimate expected performance. These predictions help coaches adapt training programs, identify players' strengths and weaknesses, and even guide the decisions of sports bettors.
3. Video annotation and detailed analysis
Data Labelling is not limited to static images, it can also be applied to annotating videos. By adding annotations to a video, it becomes possible to analyze the movements, gestures and actions of athletes in real time. For example, in basketball, dribbling, passing, and shooting actions can be identified and evaluated for each player. This detailed analysis makes it possible to detect technical errors, to measure individual performance and to optimize training strategies.
How to label a database of images in the field of sport?
Labelling a sports image database is a rigorous process, but essential for maximizing actionable information. Here are a few key steps:
1. Data collection:
Gather a vast collection of sports images and/or videos that are relevant to your analysis.
2. Data Labelling:
Apply accurate annotations to each image, using tools (LabelBox, Label Studio, Kili, CVAT, Encord, V7, etc.) and techniques adapted to the sports field. Data Labelers specialized in the sports field will be able to detect the details that will make it possible to produce accurate metadata to train models to review images and videos automatically.
3. Validation and verification:
Carefully check annotations to ensure accuracy and consistency.
4. Integration into models:
Integrate annotated data into your AI or machine learning models for in-depth analysis and accurate predictions.
Trust Innovatiana for your Data Labelling needs
Data Labelling is an essential part of sports data analysis. At Innovatiana, we offer high quality services for image annotation, data collection and data preparation in the sports field. Our experts ensure that your data is annotated accurately and reliably, allowing you to optimize your projects and improve your performance.
🤔 If you are a professional in the field of sport (video analyst, Data Scientist, CTO,...) and you want to learn more about our data annotation and Data Labelling services, do not hesitate to contact us. We are happy to help you get the most out of your data and achieve your goals.
