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- The Wheat from the Chaff #23
The Wheat from the Chaff #23
Today, we are going to explore how AI is already making an impact on a subject that, in general, Brazilians love: sports. With two examples that cover the national passion, football, we will demonstrate how the impact extends from professional athletes to weekend sports enthusiasts. Shall we begin?
Jhonata Emerick
August 20, 2023
As part of my job, every week I read a lot of content about data, technology, and artificial intelligence (also known as AI). I filter them and send you the best ones, every Sunday.
Hello everyone 👋 ,
Today, we are going to explore how AI is already making an impact on a subject that, in general, Brazilians love: sports. With two examples that cover the national passion, football, we will demonstrate how the impact extends from professional athletes to weekend sports enthusiasts. Shall we begin?
It's time to separate THE WHEAT FROM THE CHAFF…
Less is More
TodLink for Sportradaray, we will discuss a topic that Brazilians love: sports and two of the mentioned examples involve the national passion, football. Recently, sports, in general, have increasingly relied on data for decision-making, for various reasons ranging from betting to achieving more precise decisions and, consequently, better results.
Weekly, when creating our content, we conduct research (with our team and some AI agents) to provide excellent quality content that truly brings value to our readers. Throughout this journey, some companies have stood out, and we decided to explore and discuss their solutions.
Image by AI Microsoft Designer
One of them is Sportradar, a publicly traded company with clients in more than 120 countries and an official partner of renowned leagues such as NBA, NASCAR, FIFA, UEFA, among others.
Sportradar uses statistics and data for various segments within sports, including auditing and fraud detection. The Brazilian Football Confederation (CBF) has a contract with the company for tracking suspicious activities in football matches. According to the CBF, in 2022, 139 matches were classified as having unusual movements.
Through data (including historical data) and predictive models (involving AI), we can identify patterns of behavior that deviate from the normal (or expected) ones. These patterns do not necessarily indicate fraud but can help federations or related entities in searching for evidence of match manipulation.
Images and videos, known as unstructured data, play a crucial role in sports and are a valuable source of information for artificial intelligence (AI) models. There are various categories of images, from a PNG image from a website to a medical image, such as magnetic resonance imaging (MRI), for example. Ultrasound, which is commonly used in clinics and hospitals nowadays, had sonar - a system that uses the propagation of sound underwater for navigation, communication, or object detection - as one of its earliest known applications.
An intriguing modality is thermography, which produces color maps of body temperature distribution with a resolution of up to 0.5 million pixels. Special cameras with radiation-sensitive chips in the infrared range, just below the visible light in the electromagnetic spectrum, are used where heat waves produced by the human body concentrate.
Following the same path as ultrasound, a company is seeking to use thermography for the prevention of muscle injuries. Initially focused on professional football athletes, serving major clubs in Series A and B, the goal now is to expand its application to the healthcare and wellness field, potentially benefiting even weekend athletes.
Example of a thermic image
Based on the temperature variations in muscle groups over a certain time (daily, weekly, for example), the AI algorithms developed by the company aim to predict where such injuries are most likely to occur. Given the context, it is quite understandable that the initiative started in football, assisting teams in taking care of their athletes, minimizing injuries, and thus providing more effective care based on data and technology.
Still thinking about weekend athletes, do you remember the co-pilots from our last edition? Well, soon everyone will have one to call their own. And how about having one of these to help you improve in tennis? That's the proposal of the company Swing Vision. You record your training and/or game with your smartphone (among other options), and then an AI-based coach, who has been trained (meaning, learned) from all your videos and recordings, provides guidance and points for improvement.
Artificial intelligence is capable of identifying during the match how many shots were made with the right hand or the left hand, calculating the average speed per type of stroke, and visually representing where the majority of your shots landed on the opponent's court.
I liked the Line Challenge, which can be accessed through your smartwatch, for example, integrated into the system. The Line Challenge in tennis functions as a tool available to players when they disagree with the umpire's decision on whether the ball was in or out of bounds. They request a 'second opinion' from technology that uses cameras to determine where the ball hit. Subsequently, everyone on the court can check on the screen whether the umpire's decision was correct or not. The Swing Vision system, supported by AI, identifies whether the ball was in or out of bounds.
I am passionate about tennis too. So, Carlos Alcaraz (number 1 in the world), watch out, I'm coming with my co-pilot and tennis coach! The era of AI is just beginning! :)
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