The global artificial intelligence in the Sports market is expected to reach USD 3.32 billion in 2024 and USD 11.17 billion by 2029, growing at a CAGR of 27.5% during the forecast period.
Artificial intelligence replicates human intelligence in machines programmed to think like humans to enable problem-solving. AI collects data from various devices and then analyzes it using statistics and data analytics to gain important outputs. These outputs are further used for sports planning, fan engagement, and tracking player movement and health.
AI technology has been deployed in many sports like football, cricket, basketball, tennis, and many others. Various wearables and cameras collect multiple data points and, with the help of AI and machine learning, deliver valuable insights to the players and coaches. The innovative, AI-powered M1 SmartCoach app was the first to turn smartphones into coaches, which helped young basketball players improve their games. This app studies videos of players' shooting techniques, evaluates them using AI technology, and provides coaching and instructions to the players.
Sports Artificial Intelligence is gaining momentum worldwide because of its post-match, live-match analysis, and fan engagement. The increase in real-time data analytics of players to help them improve their fitness and tactics is driving the artificial intelligence market in sports. The analysis of fan engagement to determine who has the most loyal fan following in the league is also helping to grow the market.
Sports Artificial Intelligence has continued to grow rapidly, so real-time data analysis using AI and machine learning is the need of the hour, and companies are providing these valuable services to various sports teams all over the world. Furthermore, AI technology that aids referees in different sports in making fast decisions and automated sports journalism is contributing to the growth of the Sports Artificial Intelligence market.
The lack of suitable skilled and qualified workers is a significant barrier to market expansion because of the advancement in technology. The installation and maintenance costs of the equipment are hindering the growth, which has affected the use of AI technologies in domestic leagues in many countries. Furthermore, in cricket, DRS is used to track the ball's trajectory. However, DRS is a costly technology, so many countries cannot afford it for junior leagues.
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REPORT METRIC |
DETAILS |
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Market Size Available |
2023 to 2029 |
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Base Year |
2023 |
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Forecast Period |
2024 to 2029 |
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CAGR |
27.5% |
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Segments Covered |
By Sports Type, Deployment, Component, Application, Technology, and Region |
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Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
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Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
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Market Leaders Profiled |
Sportradar AG, IBM Corporation, Catapult Group International Ltd., Stats Perform, Deep Scale, SAS Institute Inc., Advanced Micro Devices (AMD) Inc., Point Grab Ltd., Atmel Corporation, Opta Sports, and others. |
In terms of market share among sports types, football was the leading segment and is expected to remain the leading segment during the forecasted period as well. The main reason for this can be the use of artificial intelligence (AI) in the form of wearable devices, sensors, and multiple cameras to track player fitness, team planning, and team tactics.
In the deployment segment, the cloud is leading the market share and is forecast to grow. This deployment is less expensive and time-consuming to maintain and manage than traditional on-premise deployments, giving it an edge in the market. It is important to remember that a large amount of data is taken in today's world, and this data can easily be saved in the cloud without running out of storage space.
The component segment is divided into software and services. The software will lead the component segment because of various applications of AI software, such as player tracking, DRS technology, game tactics, and fitness improvement. However, service will be the leader in the forecasted period because of the benefits it provides to AI software and because customers can pay once for the service.
In application segments, fan engagement is emerging as the market leader. This is due to the viewing experience the customer expects nowadays, with all the players' data and other stats. Also, the teams want their loyal fans to be active on social media and buy tickets online. They want to take their seats in the stadium without having to wait in long queues, which is done by crowd management with AI.
The machine learning segment held a major market share during the forecast period and is expected to remain so throughout the forecasted period. Its unmatched predictive capabilities in sports, such as injury prediction and fan segmentation, give it an edge over other segments.
North America is the leading region and will continue to grow over the forecasted period. In this region, many of the major sports leagues are organized, and the United States contributes the largest share of the market. The market in this region is driven by the increase in investment in AI technologies in sports and the skilled and qualified workforce available in this region.
The major players operating the global artificial intelligence AI in the sports market include
Sportradar AG
IBM Corporation
Catapult Group International Ltd.
Stats Perform
Deep Scale
SAS Institute Inc
Advanced Micro Devices (AMD) Inc.
Point Grab Ltd.
Atmel Corporation
Opta Sports, and others.
In August 2021, Catapult announced that it will launch an innovative wearable performance solution for athletes. This solution will give players and coaches at all levels access to tools that enable them to track, analyze, and improve performance with accuracy and precision.
In June 2022, the sports betting service Sports Radar announced the launch of automated near-live short-form video content that is expected to create deeper engagement with the service's sports fan audience.
In April 2022, Sports Radar announced that it had acquired Vaix Limited, a pioneer in the development of artificial intelligence solutions specifically designed for the iGaming industry. As a result of this launch, Sports Radar will be able to provide players with a more targeted, player-friendly experience.
In June 2022, Stats Perform introduced live Opta Vision data feeds for the 2022–23 football season. It will provide a remote tracking collection from video sources utilizing cutting-edge computer vision technology deployed from camera systems installed at match venues to provide a remote tracking collection from video sources.
By Sports Type
Tennis
Football
Cricket
Basketball
Baseball
By Deployment
Cloud
On-premise
By Component
Software
Service
By Application
Game Planning
Game Strategies
Performance Improvement
Fan engagement
Others
By Technology
Cognitive Computing
Data Analytics
Computer Vision
Decisions as a Service
Machine Learning
Natural Language Processing
By Region
North America
Europe
Asia Pacific
Middle East & Africa
South America
Frequently Asked Questions
AI is extensively used in sports analytics globally to enhance player performance analysis, injury prevention, game strategy formulation, and fan engagement. It employs machine learning algorithms to process vast amounts of data from various sources such as video footage, wearable sensors, and historical statistics to provide valuable insights.
AI plays a crucial role in improving athlete performance by analyzing biomechanical data, tracking movement patterns, and identifying areas for improvement. It enables coaches and trainers to tailor training programs based on individual strengths and weaknesses, ultimately optimizing performance.
AI assists coaches and teams in strategic decision-making by analyzing vast amounts of data to identify patterns, trends, and insights that may not be apparent through traditional methods. It provides valuable inputs on opponent analysis, game tactics, player lineup optimization, and in-game decision support, thereby enhancing teams' competitive advantage on a global scale.
The future prospects of AI in the sports industry are promising, with continued advancements expected in areas such as real-time analytics, personalized training programs, fan engagement platforms, and sports broadcasting technologies. As AI algorithms become more sophisticated and accessible, they are poised to reshape various aspects of sports globally, driving innovation and enhancing performance across the board.
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