Basketball is always evolving and changing. Today’s NBA is not the same as it was 10 years ago. But how can the game grow in the future? This question has been answered by many players, developers, and teams.
Sports Visio, the first product of its kind to use artificial intelligence (AI), advanced computer vision and other technologies, is the first sports product for consumers. The app was developed by the best data scientists and engineers in the world, opening up a new way to view basketball.
Who is Sports Visio for?
Anyone with access to a smartphone can use Sports Visio. AI basketball statistics Sports Visio addresses a variety of challenges that individuals face on and off the court.
Machine learning has enabled coaches to predict and quantify team/player performance more accurately, thanks to unprecedented advancements in game analysis. Machine learning is a great tool for game analysis, as it can identify trends. This makes it much easier to analyze the many variations of pick-and-rolls. Additionally, as more data is collected, programs are able to identify more variants of these types of plays with data they have not seen before. Machine learning is a way to quickly and efficiently analyze real-time data and identify trends.
AI has a major impact on the strategic decisions made by coaches before and during games. AI platforms are able to measure speed, spin, and place a tennis serve or curveball. They also have high-speed cameras and wearable sensors that can detect the position and motions of players. This data allows coaches to better prepare their players for competition. AI can also predict success for different game strategies. AI is being used by some coaches to call the correct plays during football games. Coaches and trainers can create better programs by using AI and Data Science to analyze the performance of their players. It is easier to train if coaches know where their players are lag.
Performance Improvement for Players
Artificial intelligence can be used in order to improve the performance of players. The NEX technology developed the Home court application. It uses Computer Vision and Machine Learning for analysis of Basketball players’ skill levels. To help players improve, it calculates shot accuracy and progress over time. It also analyzes critical performance metrics like speed, vertical jump, release times, and ball handling.
Similar to the US, Gregoire Gentil, a French inventor, designed a device called Tennis In/Out. Computer Vision is used to determine the speed and position of tennis shots. Spektacom also has sensor-enabled cricket batsmen that analyze their performance. Parameters such as the speed, twist, and point of impact of the ball, along with the quality of the shot are all available to Spektacom. Coaches will have access to these parameters on a 24/7 basis.
Deep Learning creates fully-automated sports productions that look almost identical to professional broadcasts. This includes panning and camera zoom-ins of the action. The AI platforms allow cameras to capture sporting events and pick the highlights for distribution to TV outlets or mobile devices.
Player Scouting and Analysis
To bring in ace players, countries and clubs spend millions. It is difficult to use quantitative metrics during matches to analyze players. AI solutions analyze players using data from video coverages, wearables and other devices that are installed in stadia. It is possible to measure the different characteristics of players. Software allows teams to check whether a player’s abilities match those of experts. Modern AI-based software can also be used to analyze each player’s physiology and their responses to stress.