The Artificial Intelligence in Sports Market Size accounted for USD 2.2 Billion in 2022 and is estimated to achieve a market size of USD 31.4 Billion by 2032 growing at a CAGR of 30.6% from 2023 to 2032.
Artificial Intelligence in Sports Market Highlights
- Global artificial intelligence in sports market revenue is poised to garner USD 31.4 billion by 2032 with a CAGR of 30.6% from 2023 to 2032
- North America artificial intelligence in sports market value occupied around USD 910 million in 2022
- Asia-Pacific artificial intelligence in sports market growth will record a CAGR of more than 33% from 2023 to 2032
- Among deployment model, the on-premise sub-segment generated over US$ 1.6 billion revenue in 2022
- Based on technology, the machine learning sub-segment generated around 25% share in 2022
- Integration of AI with wearables and smart equipment is a popular artificial intelligence in sports market trend that fuels the industry demand
Artificial Intelligence (AI) in sports is generating readable information on various sports events by utilizing sports data, such as football goals or wickets in cricket. With the assistance of computer vision and IoT devices, users can capture data points that are challenging to monitor manually, such as ball trajectories, shots, and passes. AI is now significantly impacting the strategic decisions made by coaches before, during, and after the game, leveraging wearable sensors and high-speed cameras. It is also employed to enhance players' performance by using computer vision and machine learning to assess basketball players' skills, providing them with a valuable tool for improvement. This information is not only credible but also aids players in understanding the areas where they have the maximum potential to excel and the areas that still need improvement.
Global Artificial Intelligence in Sports Market Dynamics
Market Drivers
- Real-time performance analysis through AI enhances sports strategic decision-making
- Rising demand for AI-driven injury prevention boosts adoption for player safety
- Advancements in computer vision and IoT enable precise data capture for sports analytics
- Increased sports technology investment accelerates AI applications for player performance optimization
Market Restraints
- High implementation costs and infrastructure requirements
- Concerns over data privacy and security
- Resistance to change within traditional coaching methodologies
Market Opportunities
- Expansion of AI applications in sports broadcasting and fan engagement
- Collaborations between AI developers and sports organizations
- Rise in demand for personalized training programs
Artificial Intelligence in Sports Market Report Coverage
| Market |
Artificial Intelligence (AI) in Sports Market
|
| Artificial Intelligence (AI) in Sports Market Size 2022 |
USD 2.2 Billion |
| Artificial Intelligence (AI) in Sports Market Forecast 2032 |
USD 31.4 Billion |
| Artificial Intelligence (AI) in Sports Market CAGR During 2023 - 2032 |
30.6% |
| Artificial Intelligence (AI) in Sports Market Analysis Period |
2020 - 2032 |
Artificial Intelligence (AI) in Sports Market Base Year
|
2022 |
| Artificial Intelligence (AI) in Sports Market Forecast Data |
2023 - 2032 |
| Segments Covered |
By Component, By Deployment Model, By Technology, By Application, By Sports Type, And By Geography
|
| Regional Scope |
North America, Europe, Asia Pacific, Latin America, and Middle East & Africa |
| Key Companies Profiled |
Amazon Inc., Apple Inc., ARM Limited, Atmel Corporation, Catapult Group International Ltd, Cisco Systems, Inc., Facebook Inc., Fujitsu Ltd., IBM Corporation, Micron Sports Level Inc., Microsoft Corporation, Opta Sports (Perform Group), Salesforce.com Inc. (Tableau Software Inc.), SAP SE, and SAS Institute Inc.
|
Report Coverage
|
Market Trends, Drivers, Restraints, Competitive Analysis, Player Profiling, Covid-19 Analysis, Regulation Analysis |
Artificial Intelligence in Sports Market Insights
The escalating influx of both on-field and off-field data in sports organizations necessitates effective management for in-depth analysis. The rising demand for monitoring and tracking players' data, accompanied by the simultaneous surge in wearable devices across the sports industry, propels market growth. Real-time insights derived from match data empower teams to strategically adapt their game plans for improved outcomes. Augmenting this landscape, the integration of chatbots and virtual assistants aids teams in engaging with fans on diverse topics, including providing information on ticket status, check-in points, parking, and schedules.
However, mounting concerns regarding data privacy hazards pose obstacles to the widespread adoption of artificial intelligence in the sports market. Sports organizations' increasing dependence on massive data volumes elevates the risk of breaches and unauthorized access, particularly in developing and undeveloped nations where familiarity with cutting-edge technologies may be limited. This lack of awareness about AI-driven products in these regions could impede broad adoption. Anticipated throughout the artificial intelligence in sports industry forecast period, the dual challenges of data privacy threats and technological ignorance are expected to moderately restrain market growth, emphasizing the need for tailored strategies to overcome these specific challenges.
The burgeoning realm of artificial intelligence applications for customized training regimens heralds a transformative prospect in the sports industry. The expanding market for personalized coaching experiences provides AI-powered platforms with a lucrative avenue to assess individual player performance, identify strengths and weaknesses, and deliver specialized training plans. This innovative approach not only optimizes training strategies but also revolutionizes athlete development. The amalgamation of artificial intelligence (AI) and customized training not only opens new opportunities but also cultivates a dynamic ecosystem that caters to the unique needs of each individual athlete, ultimately contributing to enhanced overall sports performance.
Artificial Intelligence in Sports Market Segmentation
The worldwide market for artificial intelligence in sports is split based on component, deployment model, technology, application, sports type, and geography.
AI in Sports Market By Components
- Hardware
- Software
- Services
According to artificial intelligence in sports industry analysis, In 2022, the software segment led the market, capturing the maximum revenue share (%). This segment continues to experience growth due to ongoing enhancements in information storage capacity, high computing power, and parallel processing capabilities, enabling the delivery of high-end AI software across various sports verticals. Artificial intelligence (AI) software solutions find extensive application, including but not limited to linear algebra, inference, sparse matrices, video analytics, and multiple hardware communication capabilities.
AI in Sports Market By Deployment Models
The AI in sports market is dominated by the on-premise segment. Sports organisations are forced to retain direct control of their AI infrastructure because to industry needs, security concerns, or regulatory limitations, which can be the cause of this domination. A customised and localised approach is offered via on-premise implementation, giving stakeholders a practical way to handle, examine, and safeguard private sports data. Even if cloud solutions are becoming more and more popular, organisations that prioritise localised infrastructure and data governance continue to choose the On-premise model since it offers them more autonomy and control.
AI in Sports Market By Technologies
- Cognitive Computing
- Computer Vision
- Data Analytics
- Decisions as a Service
- Machine Learning
- Natural Language Processing
- Others
The machine learning segment is the largest in the AI in sports market, which is not surprising given its critical role in revolutionising the sports sector. Its supremacy is ascribed to its capacity to evaluate big datasets, spot trends, and generate predictive insights, all of which improve player performance, strategy development, and fan interaction. Through iterative learning, machine learning algorithms continuously improve and adapt to changing sports settings. This flexibility, together with its uses in performance enhancement, injury prevention, and game analytics, places Machine Learning at the forefront of the industry's expansion. Its many effects highlight how important it is to the development of AI in sports in the future.\
AI in Sports Market By Applications
- Game Planning
- Game Strategies
- Performance Improvement
- Injury Prevention
- Sports Recruitment
In terms of artificial intelligence in sports market analysis, the leader is the performance improvement category. This domination stems from AI's revolutionary ability to improve athlete performance in a variety of sports. AI tools, like as machine learning and data analytics, make it possible to thoroughly analyse a player's strengths and shortcomings and create individualised training plans. Artificial Intelligence (AI) enables sports organisations to maximise athletic potential, minimise injuries, and optimise training plans by offering insightful data on individual and team performance indicators. In order to achieve outstanding and long-lasting athletic performance, the performance improvement application has emerged as the focus point, influencing innovation and reshaping the sports AI integration landscape.
AI in Sports Market By Sports Types
- Cricket
- Football
- Basketball
- Tennis
- Baseball
- Others
In the AI in sports market, football comes out on top, demonstrating its significant influence on the world of sports. This domination is fueled by football's broad appeal, large fan base, and complex dynamics that artificial intelligence (AI) technologies can handle. Football players can use AI for anything from injury prevention and player performance analysis to strategic game preparation. Football is at the forefront of AI integration in sports due to its complex nature and the always increasing demand for advanced analytics. As a result, it serves as the main driver of innovation and market expansion in the field of artificial intelligence in sports.
AI in Sports Market Regional Outlook
North America
Europe
- U.K.
- Germany
- France
- Spain
- Rest of Europe
Asia-Pacific
- India
- Japan
- China
- Australia
- South Korea
- Rest of Asia-Pacific
Latin America
- Brazil
- Mexico
- Rest of Latin America
The Middle East & Africa
- South Africa
- GCC Countries
- Rest of the Middle East & Africa (ME&A)
AI in Sports Market Regional Analysis
In 2022, North America held a significant share in the AI in sports market due to its advanced technological infrastructure and robust sports associations. The region's growing emphasis on technological advancements, particularly in the United States, contributes to the market's upward trajectory. Additionally, according to Statista, the North American sports market was valued at USD 910 million in 2022.
Simultaneously, the artificial intelligence in sports market is experiencing unprecedented growth, with the Asia-Pacific region emerging as the center of the fastest growth rate. Several factors propel this expansion, including the increasing interest in sports technology, the popularity of diverse sports, and the utilization of AI to optimize performance. Leading this momentum are nations such as China, Japan, and India, leveraging cutting-edge technologies to revolutionize player development and sports analytics. With the region's evolving sports ecosystem and a more tech-savvy populace, Asia-Pacific is poised to become a vibrant and lucrative market for the application of artificial intelligence in the sports industry.
AI in Sports Market Players
Some of the top artificial intelligence in sports companies offered in our report includes Amazon Inc., Apple Inc., ARM Limited, Atmel Corporation, Catapult Group International Ltd, Cisco Systems, Inc., Facebook Inc., Fujitsu Ltd., IBM Corporation, Micron Sports Level Inc., Microsoft Corporation, Opta Sports (Perform Group), Salesforce.com Inc. (Tableau Software Inc.), SAP SE, and SAS Institute Inc.
CHAPTER 1. Industry Overview of Artificial Intelligence in Sports Market
1.1. Definition and Scope
1.1.1. Definition of Artificial Intelligence in Sports
1.1.2. Market Segmentation
1.1.3. Years Considered for the Study
1.1.4. Assumptions and Acronyms Used
1.1.4.1. Market Assumptions and Market Forecast
1.1.4.2. Acronyms Used in Global Artificial Intelligence in Sports Market
1.2. Summary
1.2.1. Executive Summary
1.2.2. Artificial Intelligence in Sports Market By Component
1.2.3. Artificial Intelligence in Sports Market By Deployment Model
1.2.4. Artificial Intelligence in Sports Market By Technology
1.2.5. Artificial Intelligence in Sports Market By Application
1.2.6. Artificial Intelligence in Sports Market By Sports Type
1.2.7. Artificial Intelligence in Sports Market By Region
CHAPTER 2. Research Approach
2.1. Methodology
2.1.1. Research Programs
2.1.2. Market Size Estimation
2.1.3. Market Breakdown and Data Triangulation
2.2. Data Component
2.2.1. Secondary Components
2.2.2. Primary Components
CHAPTER 3. Market Dynamics And Competition Analysis
3.1. Market Drivers
3.1.1. Driver 1
3.1.2. Driver 2
3.2. Restraints and Challenges
3.2.1. Restraint 1
3.2.2. Restraint 2
3.3. Growth Opportunities
3.3.1. Opportunity 1
3.3.2. Opportunity 2
3.4. Porter’s Five Forces Analysis
3.4.1. Bargaining Power of Suppliers
3.4.2. Bargaining Power of Buyers
3.4.3. Threat of Substitute
3.4.4. Threat of New Entrants
3.4.5. Degree of Competition
3.5. Market Concentration Ratio and Market Maturity Analysis of Artificial Intelligence in Sports Market
3.5.1. Go To Market Strategy
3.5.1.1. Introduction
3.5.1.2. Growth
3.5.1.3. Maturity
3.5.1.4. Saturation
3.5.1.5. Possible Development
3.6. Technological Roadmap for Artificial Intelligence in Sports Market
3.7. Value Chain Analysis
3.7.1. List of Key Manufacturers
3.7.2. List of Customers
3.7.3. Level of Integration
3.8. Cost Structure Analysis
3.8.1. Price Trend of Key Raw Deployment Models
3.8.2. Raw Deployment Model Suppliers
3.8.3. Proportion of Manufacturing Cost Structure
3.8.3.1. Raw Deployment Model
3.8.3.2. Labor Cost
3.8.3.3. Manufacturing Expense
3.9. Regulatory Compliance
3.10. Competitive Landscape, 2022
3.10.1. Player Positioning Analysis
3.10.2. Key Strategies Adopted By Leading Players
CHAPTER 4. Manufacturing Plant Analysis
4.1. Manufacturing Plant Location and Establish Date of Major Manufacturers in 2022
4.2. R&D Status of Major Manufacturers in 2022
CHAPTER 5. Artificial Intelligence in Sports Market By Component
5.1. Introduction
5.2. Artificial Intelligence in Sports Revenue By Component
5.2.1. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast, By Component, 2020-2032
5.2.2. Hardware
5.2.2.1. Hardware Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
5.2.3. Software
5.2.3.1. Software Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
5.2.4. Services
5.2.4.1. Services Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
CHAPTER 6. Artificial Intelligence in Sports Market By Deployment Model
6.1. Introduction
6.2. Artificial Intelligence in Sports Revenue By Deployment Model
6.2.1. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast, By Deployment Model, 2020-2032
6.2.2. Cloud
6.2.2.1. Cloud Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
6.2.3. On-premise
6.2.3.1. On-premise Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
CHAPTER 7. Artificial Intelligence in Sports Market By Technology
7.1. Introduction
7.2. Artificial Intelligence in Sports Revenue By Technology
7.2.1. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast, By Technology, 2020-2032
7.2.2. Cognitive Computing
7.2.2.1. Cognitive Computing Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
7.2.3. Computer Vision
7.2.3.1. Computer Vision Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
7.2.4. Data Analytics
7.2.4.1. Data Analytics Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
7.2.5. Decisions as a Service
7.2.5.1. Decisions as a Service Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
7.2.6. Machine Learning
7.2.6.1. Machine Learning Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
7.2.7. Natural Language Processing
7.2.7.1. Natural Language Processing Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
7.2.8. Others
7.2.8.1. Others Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
CHAPTER 8. Artificial Intelligence in Sports Market By Application
8.1. Introduction
8.2. Artificial Intelligence in Sports Revenue By Application
8.2.1. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast, By Application, 2020-2032
8.2.2. Game Planning
8.2.2.1. Game Planning Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
8.2.3. Game Strategies
8.2.3.1. Front & Rear Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
8.2.4. Performance Improvement
8.2.4.1. Performance Improvement Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
8.2.5. Injury Prevention
8.2.5.1. Injury Prevention Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
8.2.6. Sports Recruitment
8.2.6.1. Sports Recruitment Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
CHAPTER 9. Artificial Intelligence in Sports Market By Sports Type
9.1. Introduction
9.2. Artificial Intelligence in Sports Revenue By Sports Type
9.2.1. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast, By Sports Type, 2020-2032
9.2.2. Cricket
9.2.2.1. Cricket Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
9.2.3. Football
9.2.3.1. Football Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
9.2.4. Basketball
9.2.4.1. Basketball Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
9.2.5. Tennis
9.2.5.1. Tennis Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
9.2.6. Baseball
9.2.6.1. Baseball Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
9.2.7. Others
9.2.7.1. Others Market Revenue (USD Billion) and Growth Rate (%), 2020-2032
CHAPTER 10. North America Artificial Intelligence in Sports Market By Country
10.1. North America Artificial Intelligence in Sports Market Overview
10.2. U.S.
10.2.1. U.S. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
10.2.2. U.S. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
10.2.3. U.S. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
10.2.4. U.S. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
10.2.5. U.S. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
10.3. Canada
10.3.1. Canada Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
10.3.2. Canada Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
10.3.3. Canada Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
10.3.4. Canada Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
10.3.5. Canada Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
10.4. North America PEST Analysis
CHAPTER 11. Europe Artificial Intelligence in Sports Market By Country
11.1. Europe Artificial Intelligence in Sports Market Overview
11.2. U.K.
11.2.1. U.K. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
11.2.2. U.K. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
11.2.3. U.K. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
11.2.4. U.K. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
11.2.5. U.K. Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
11.3. Germany
11.3.1. Germany Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
11.3.2. Germany Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
11.3.3. Germany Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
11.3.4. Germany Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
11.3.5. Germany Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
11.4. France
11.4.1. France Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
11.4.2. France Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
11.4.3. France Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
11.4.4. France Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
11.4.5. France Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
11.5. Spain
11.5.1. Spain Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
11.5.2. Spain Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
11.5.3. Spain Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
11.5.4. Spain Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
11.5.5. Spain Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
11.6. Rest of Europe
11.6.1. Rest of Europe Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
11.6.2. Rest of Europe Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
11.6.3. Rest of Europe Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
11.6.4. Rest of Europe Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
11.6.5. Rest of Europe Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
11.7. Europe PEST Analysis
CHAPTER 12. Asia Pacific Artificial Intelligence in Sports Market By Country
12.1. Asia Pacific Artificial Intelligence in Sports Market Overview
12.2. China
12.2.1. China Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
12.2.2. China Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
12.2.3. China Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
12.2.4. China Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
12.2.5. China Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
12.3. Japan
12.3.1. Japan Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
12.3.2. Japan Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
12.3.3. Japan Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
12.3.4. Japan Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
12.3.5. Japan Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
12.4. India
12.4.1. India Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
12.4.2. India Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
12.4.3. India Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
12.4.4. India Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
12.4.5. India Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
12.5. Australia
12.5.1. Australia Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
12.5.2. Australia Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
12.5.3. Australia Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
12.5.4. Australia Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
12.5.5. Australia Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
12.6. South Korea
12.6.1. South Korea Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
12.6.2. South Korea Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
12.6.3. South Korea Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
12.6.4. South Korea Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
12.6.5. South Korea Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
12.7. Rest of Asia-Pacific
12.7.1. Rest of Asia-Pacific Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
12.7.2. Rest of Asia-Pacific Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
12.7.3. Rest of Asia-Pacific Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
12.7.4. Rest of Asia-Pacific Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
12.7.5. Rest of Asia-Pacific Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
12.8. Asia Pacific PEST Analysis
CHAPTER 13. Latin America Artificial Intelligence in Sports Market By Country
13.1. Latin America Artificial Intelligence in Sports Market Overview
13.2. Brazil
13.2.1. Brazil Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
13.2.2. Brazil Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
13.2.3. Brazil Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
13.2.4. Brazil Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
13.2.5. Brazil Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
13.3. Mexico
13.3.1. Mexico Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
13.3.2. Mexico Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
13.3.3. Mexico Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
13.3.4. Mexico Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
13.3.5. Mexico Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
13.4. Rest of Latin America
13.4.1. Rest of Latin America Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
13.4.2. Rest of Latin America Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
13.4.3. Rest of Latin America Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
13.4.4. Rest of Latin America Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
13.4.5. Rest of Latin America Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
13.5. Latin America PEST Analysis
CHAPTER 14. Middle East & Africa Artificial Intelligence in Sports Market By Country
14.1. Middle East & Africa Artificial Intelligence in Sports Market Overview
14.2. GCC
14.2.1. GCC Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
14.2.2. GCC Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
14.2.3. GCC Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
14.2.4. GCC Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
14.2.5. GCC Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
14.3. South Africa
14.3.1. South Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
14.3.2. South Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
14.3.3. South Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
14.3.4. South Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
14.3.5. South Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
14.4. Rest of Middle East & Africa
14.4.1. Rest of Middle East & Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Component, 2020-2032
14.4.2. Rest of Middle East & Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Deployment Model, 2020-2032
14.4.3. Rest of Middle East & Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Technology, 2020-2032
14.4.4. Rest of Middle East & Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Application, 2020-2032
14.4.5. Rest of Middle East & Africa Artificial Intelligence in Sports Revenue (USD Billion) and Forecast By Sports Type, 2020-2032
14.5. Middle East & Africa PEST Analysis
CHAPTER 15. Player Analysis Of Artificial Intelligence in Sports Market
15.1. Artificial Intelligence in Sports Market Company Share Analysis
15.2. Competition Matrix
15.2.1. Competitive Benchmarking of key players by price, presence, market share, and R&D investment
15.2.2. New Component Launches and Component Enhancements
15.2.3. Mergers And Acquisition In Global Artificial Intelligence in Sports Market
15.2.4. Partnership, Joint Ventures and Strategic Alliances/ Sales Agreements
CHAPTER 16. Company Profile
16.1. Amazon Inc.
16.1.1. Company Snapshot
16.1.2. Business Overview
16.1.3. Financial Overview
16.1.3.1. Revenue (USD Billion), 2022
16.1.3.2. Amazon Inc. 2022 Artificial Intelligence in Sports Business Regional Distribution
16.1.4. Component /Service and Specification
16.1.5. Recent Developments & Business Strategy
16.2. Apple Inc.
16.3. ARM Limited
16.4. Atmel Corporation
16.5. Catapult Group International Ltd
16.6. Cisco Systems, Inc.
16.7. Facebook Inc.
16.8. Fujitsu Ltd.
16.9. IBM Corporation
16.10. Micron Sports Level Inc.
16.11. Microsoft Corporation
16.12. Opta Sports (Perform Group)
16.13. Salesforce.com Inc. (Tableau Software Inc.)
16.14. SAP SE
16.15. SAS Institute Inc
