Description of the technology

While sport organizations have a huge amount of raw data, and more is always being added, this data may now be used to improve the value of their organization in all areas, from ticket sales to player injury prevention. Thanks to Artificial Intelligence, this huge amount of data from players can be evaluated using Computer vision and Machine Learning to identify patterns and trends. This information can be used to improve performance, make strategic decisions and provide a better spectator experience. We are going to go deeply into these technologies, understand their current and potential uses in the sport industry and we will make a prediction on how they will change the future in sports.

Machine learning

Machine learning is a very powerful technology for the sports industry. The ability to process large amounts of data, make predictions and learn from experience makes it ideal for predicting behaviors and optimizing performance. For example, to manage player fatigue, minimize injury, provide insights for pre-match and post-match analysis, personnel selection and coaching requirements.

--> Machine learning functions:

● Descriptive: the system collect historical data, organizes it, and later present it in an understandable way. It uses simple math and statistical tools.

● Predictive: analyzing past data patterns and trends can predict what might happen going forward.

● Prescriptive: it makes multiple suggestions on the actions one can take to achieve the desired outcome.

Computer Vision

Computer vision is a powerful technology which can turn your camera into an up-to-date data generator with a speed not comparable with humans. It is one of the fields of AI under deep learning and the main goal is to train models with special algorithms to train computers with cameras to process visual data, make analytics and help to enhance the decision-making process and make predictions.

-->There are multiple computer vision models that can be applied to sports:

●Image classification: Simple model but very powerful. We will train the computer by providing a group of images with a unique classification, and the model needs to learn how to classify an image in the future using this group and this unique classification. Following the same soccer player example, we will need to provide a huge number of players and classify the image as “soccer player”.

●Object detection: With this model the computer will identify objects within a classification. For example, in sports class, it will be able to identify the ball, the rackets, etc will be essential for the analysis of the player performance and the prediction models. In addition, it could detect the face of the player so it will be a very powerful model for player tracking purposes.

●Video motion: This is one of the most helpful technologies in sports because it will analyze body movements and trajectories of players and objects.

●Face recognition: The system will recognize faces and will classify them into classes. For example, in sports analytics, it will be important to recognize each player on the field, and for customer satisfaction, it will be able to recognize a regular customer and to provide premium service in the stadium or discounts at the entrance. In order to make it work, we will need to upload photos of the players or customers and the system will be able to understand the actions that they perform. You can also use notifications to your mobile devices alerting you in real time of the player who just scored as an example.

AI in physical performance - current uses

Training plays a key role in improving the physical development and performance of a professional athlete. With the help of AI, skills or techniques can be learned and improved at the same time as the training or sporting activity takes place. Indeed, AI systems are used to improve the performance of both individual athletes and teams. This makes it very flexible since they can be used in both individual and team sports.

Focusing on collective sports, we will explain below a series of examples that are going to help us understand in which aspects the use of AI improves the physical performance of athletes:

These are some of the advantages:

- Advanced customized training plans

- Physical capacity

- Injuries

- Diets

The visionary

AI is already transforming the sports world as we have discussed in this report. But the most impacting features are still to come. With the advance of AI and technology, we will be able to see in the future:

-Virtual referees: Referees will wear augmented reality glasses or contact lenses and will be able to take decisions instantly, eliminating the necessity of reviews, and potentially, they will be able to do it remotely, without being on the field. Eventually, referees will not be longer needed since the decision could be displayed immediately on screens. In addition, it will eliminate the human error that currently is causing a lot of controversial discussions between teams and generating a negative environment.

-Assist Coaches during game: AI can be way more capable in situations involving a dynamic planning and analysis of the scene. For example a coach will rely on experience and previous data but can not be as effective as a machine. In the future, AI running alongside the gameplay will be dynamically predicting and creating strategies, helping the teams to get an edge over others. As a result of that, it will improve the team performance and the outcome of the sport games will change, teams will score higher like in soccer and basketball, so more excitement for the audience.

-Global recruitment of professional sport players: with the computer vision technology, cameras will be capturing data from young players from all over the world, you only need to install the camera devices on the field. The data analysis will be done remotely, and the best potential players identified by the machine. This will bring more opportunities to people with less financial resources, anybody can be selected with no need to travel to run trials, etc.

-Records will be broken: we will have the best sport players, we will see the highest speed runners and swimmers ever, the fastest Formula 1 driver,…the professional players will break all the records, there will be no limits to improve their performance.

-AI will enable a more exciting experience to audience than ever: AI will be used to deliver the information to customers as well, through multiple devices and screens for viewing different content at different times. Nowadays, there is a serious demand from fans for in-depth analysis and also for commentary. At the entrance and throughout the sport event, the face recognition will enable the customer to get automatically all the data and display settings that they like. AI will enrich the experience of the audience as never before imagined.

-Virtual training environment: Training and player development will be done in a virtual environment with a more focused program adapted to the player's needs.

-Virtual reality devices: last but not least, imagine that you can be at home, seating on a special sofa or maybe in a capsule where virtual reality devices will provide an immersive experience to watch sports as if you were on the field. You can watch the game from the perspective of your favorite player. If you are a fan of Formula 1, imagine if you could experience being the pilot of the race car driving at 350 km/h, or being the highest score player in the NBA if you follow basketball. You will be able to be for a moment your sport idol, what an amazing experience.