AI in Sports Market by Solutions (Performance Analytics, Player Monitoring, Broadcast Management), Technology (Generative AI and Other AI), and End User (Sports Associations, Sports Teams) - Global Forecast to 2030
The AI in Sports market was estimated to be USD 1.03 billion in 2024 to USD 2.61 billion by 2030 at a compound annual growth rate (CAGR) of 16.7% from 2024 to 2030. With the help of Machine Learning (ML) and other models, advancements in sports AI are enabling organizations to process vast volumes of data in real-time. This technology helps analyze player patterns, study sports motions from videos and motion sensors, and even predict an athlete's health status for performance improvement and injury management. Athletes can also enhance their VR experience through AI, as it integrates VR systems that allow them to train, strategize, and think on their feet in a controlled environment, free from the limitations of distance or geography. These innovations are particularly valuable to end users like sports associations, sports teams, and media & broadcasting organizations, helping them optimize performance, enhance fan engagement, and improve content delivery.
In the case of fans, AI allows for enhanced experience in the form of personalized offerings, efficient ticketing systems, and attendance to events from any geographical location. In e-Sports AI enhances the experience of playing by managing player ranks well, improving the content, and simulating actions of characters in the video game. These technological improvements are changing the dynamics of professional sports as well as the behavior of the audiences, enhancing their interaction and immersion.
“By Team Sports, Basketball sport is expected to have the largest market size during the forecast period.” AI is increasingly transforming basketball by enhancing performance assessment, fan engagement, and strategy management, positioning the sport to lead in adopting advanced technologies. Leagues like the NBA are already utilizing AI-driven tools such as player tracking systems to monitor positions, manage workloads, and improve training exercises. These tools enable more accurate insights into player movements and physical demands, enhancing overall team performance. Coaches also benefit from AI-based wearable devices and cameras that provide real-time analysis, allowing them to implement proactive strategies during games.
The partnership between the NBA and Microsoft, which streams select games with AI-generated highlights, is a prime example of how AI is improving fan engagement and content delivery. These AI tools offer fans real-time, personalized experiences, such as enhanced highlights, player stats, and game insights, creating deeper interaction with the sport.
The worldwide popularity of basketball, particularly in regions like the US, China, and Europe, generates vast amounts of data, which is vital for continuously improving AI models. The global reach of basketball, combined with its high data output, accelerates the development and application of AI in the sport, allowing for more refined and effective solutions. As a result, basketball stands at the forefront of AI integration among sports, making it a leader in this technological evolution.
“By End User segment, the Sports Media & Broadcasting will witness the highest growth during the forecast period.” Within the realm of AI in sports, the media and broadcasting segment is expected to experience significant growth in the coming years. This growth is driven by AI’s ability to simplify and enhance the fan experience, particularly for those watching from home. For example, AI can enable near real-time content customization, quickly retrieve relevant data during events, and generate concise highlight reels of ongoing matches. Companies like IBM and AWS are already using AI to produce engaging highlight clips that captivate viewers and maintain excitement throughout the game. This technology not only improves the viewing experience but also increases fan engagement and retention.
AI also enables the integration of Virtual Reality (VR) and Augmented Reality (AR) technologies, facilitating spatial interactions that transcend physical space limitations and offer real-time data visualization during events, thereby enhancing fan engagement. Moreover, the ability to provide commentary in several languages through AI technology during the Olympic Games allows the audience reach to be maximized. Furthermore, AI targeted advertising boosts sales for television stations. Additionally, due to high spending trend on the streaming services on rise will further boost the growth of the this segment.
“Asia Pacific to witness highest growth during the forecast period.”
As a result of the digital transformation in countries such as China, Japan, and India, it is estimated that the size of the APAC will be the largest for the AI in Sports market. This is due to the rising trend in employing AI in player monitoring, fan engagement, performance enhancement, devising game strategies, and in the facilitation of other sport-related activities. The advanced smart stadiums and AI analytics investment by the sporting organizations is also responsible for the growth of the market in this region. For example, Epic Games provided AI-powered solutions that enabled real-time interaction with the audience, a significant achievement given the challenges posed by the Tokyo 2020 Satellite Olympics. Additionally, the growing popularity of sports like cricket, soccer, esports, and others in the region requires the use of Artificial Intelligence (AI) applications, such as player tracking systems, injury prediction technology, and data-driven strategy tools.
Furthermore, the young demographics in APAC, with high average access to the internet and high usage of wearables in the market, also increases the conviction for AI sporting activities. The growing population of e-Sports and gaming in China also presents a conducive environment for the acceptance of Integrating AI with sports. Owing to these factors, the region is expected to witness the highest growth during the forecast period.
Breakdown of primaries
The study contains insights from various industry experts, from solution vendors to Tier 1 companies. The break-up of the primaries is as follows:
Research Coverage
The market study covers the AI in Sports market size across different segments. It aims to estimate the market size and the growth potential across different segments, including offering, technology, sports , end user, and region. The offering includes solutions and services. Solutions are segregated into Performance Analytics, Player Monitoring, Game Strategy and Coaching Solutions, Fan Engagement and Experience Enhancement, Broadcast Management, and Other Solutions. The other segmentation is the technology, which includes Generative AI and Other AI types. The sports type segmentation includes Individual Sports, Team Sports, and e-Sports. The end user segmentation includes Sports Associations, Sports Teams, Sports Media & Broadcasting, and other end users. The regional analysis of the AI in Sports market covers North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America. The study includes an in-depth competitive analysis of the leading market players, their company profiles, key observations related to product and business offerings, recent developments, and market strategies.
Key Benefits of Buying the Report
The report will help market leaders and new entrants with information on the closest approximations of the global AI in Sports market’s revenue numbers and subsegments. It will also help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies. Moreover, the report will provide insights for stakeholders to understand the market’s pulse and provide them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
1. Analysis of key drivers (Advancements in AI and ML, Increasing Data Availability, Rising Demand for Personalized Fan Experiences, Enhanced Athlete Performance and Injury Prevention, Investment in eSports), opportunities (Expansion of AI in Training and Scouting, Growth in Virtual and Augmented Reality, AI-Driven Health and Fitness Solutions, AI for Smart Stadiums), and challenges (Lack of Skilled Professionals, Ethical and Fairness Issues, Regulatory and Compliance Barriers) influencing the growth of the AI in Sports market.
2. Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI in Sports market.
3. Market Development: Comprehensive information about lucrative markets – the report analyses the AI in Sports market across various regions.
4. Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI in Sports market.
5. Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players Cisco (US), IBM (US), Intel (US), Microsoft (US), AWS (US), SAP SE (Germany), Ericsson (Sweden), Oracle (US), Stats Perform (US), Tech Mahindra (India), Sportradar AG (Switzerland), HCL Technologies (India), Extreme Networks (US), Salesforce (US), SAS Institute (US), Catapult Group (Australia), Genius Sports (UK), Kitman Labs (Ireland), PlaySight (Israel), Quantiphi (US), SciSports (Netherlands), Spiideo (Sweden), Sportlogiq (Canada), ChyronHego Corporation (US), TruMedia Networks (US).
In the case of fans, AI allows for enhanced experience in the form of personalized offerings, efficient ticketing systems, and attendance to events from any geographical location. In e-Sports AI enhances the experience of playing by managing player ranks well, improving the content, and simulating actions of characters in the video game. These technological improvements are changing the dynamics of professional sports as well as the behavior of the audiences, enhancing their interaction and immersion.
“By Team Sports, Basketball sport is expected to have the largest market size during the forecast period.” AI is increasingly transforming basketball by enhancing performance assessment, fan engagement, and strategy management, positioning the sport to lead in adopting advanced technologies. Leagues like the NBA are already utilizing AI-driven tools such as player tracking systems to monitor positions, manage workloads, and improve training exercises. These tools enable more accurate insights into player movements and physical demands, enhancing overall team performance. Coaches also benefit from AI-based wearable devices and cameras that provide real-time analysis, allowing them to implement proactive strategies during games.
The partnership between the NBA and Microsoft, which streams select games with AI-generated highlights, is a prime example of how AI is improving fan engagement and content delivery. These AI tools offer fans real-time, personalized experiences, such as enhanced highlights, player stats, and game insights, creating deeper interaction with the sport.
The worldwide popularity of basketball, particularly in regions like the US, China, and Europe, generates vast amounts of data, which is vital for continuously improving AI models. The global reach of basketball, combined with its high data output, accelerates the development and application of AI in the sport, allowing for more refined and effective solutions. As a result, basketball stands at the forefront of AI integration among sports, making it a leader in this technological evolution.
“By End User segment, the Sports Media & Broadcasting will witness the highest growth during the forecast period.” Within the realm of AI in sports, the media and broadcasting segment is expected to experience significant growth in the coming years. This growth is driven by AI’s ability to simplify and enhance the fan experience, particularly for those watching from home. For example, AI can enable near real-time content customization, quickly retrieve relevant data during events, and generate concise highlight reels of ongoing matches. Companies like IBM and AWS are already using AI to produce engaging highlight clips that captivate viewers and maintain excitement throughout the game. This technology not only improves the viewing experience but also increases fan engagement and retention.
AI also enables the integration of Virtual Reality (VR) and Augmented Reality (AR) technologies, facilitating spatial interactions that transcend physical space limitations and offer real-time data visualization during events, thereby enhancing fan engagement. Moreover, the ability to provide commentary in several languages through AI technology during the Olympic Games allows the audience reach to be maximized. Furthermore, AI targeted advertising boosts sales for television stations. Additionally, due to high spending trend on the streaming services on rise will further boost the growth of the this segment.
“Asia Pacific to witness highest growth during the forecast period.”
As a result of the digital transformation in countries such as China, Japan, and India, it is estimated that the size of the APAC will be the largest for the AI in Sports market. This is due to the rising trend in employing AI in player monitoring, fan engagement, performance enhancement, devising game strategies, and in the facilitation of other sport-related activities. The advanced smart stadiums and AI analytics investment by the sporting organizations is also responsible for the growth of the market in this region. For example, Epic Games provided AI-powered solutions that enabled real-time interaction with the audience, a significant achievement given the challenges posed by the Tokyo 2020 Satellite Olympics. Additionally, the growing popularity of sports like cricket, soccer, esports, and others in the region requires the use of Artificial Intelligence (AI) applications, such as player tracking systems, injury prediction technology, and data-driven strategy tools.
Furthermore, the young demographics in APAC, with high average access to the internet and high usage of wearables in the market, also increases the conviction for AI sporting activities. The growing population of e-Sports and gaming in China also presents a conducive environment for the acceptance of Integrating AI with sports. Owing to these factors, the region is expected to witness the highest growth during the forecast period.
Breakdown of primaries
The study contains insights from various industry experts, from solution vendors to Tier 1 companies. The break-up of the primaries is as follows:
- By Company Type: Tier 1 – 62%, Tier 2 – 23%, and Tier 3 – 15%
- By Designation: C-level –50%, D-level – 30%, and Others – 20%
- By Region: North America – 38%, Europe – 15%, Asia Pacific – 35%, Middle East & Africa – 7%, and Latin America- 5%.
Research Coverage
The market study covers the AI in Sports market size across different segments. It aims to estimate the market size and the growth potential across different segments, including offering, technology, sports , end user, and region. The offering includes solutions and services. Solutions are segregated into Performance Analytics, Player Monitoring, Game Strategy and Coaching Solutions, Fan Engagement and Experience Enhancement, Broadcast Management, and Other Solutions. The other segmentation is the technology, which includes Generative AI and Other AI types. The sports type segmentation includes Individual Sports, Team Sports, and e-Sports. The end user segmentation includes Sports Associations, Sports Teams, Sports Media & Broadcasting, and other end users. The regional analysis of the AI in Sports market covers North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America. The study includes an in-depth competitive analysis of the leading market players, their company profiles, key observations related to product and business offerings, recent developments, and market strategies.
Key Benefits of Buying the Report
The report will help market leaders and new entrants with information on the closest approximations of the global AI in Sports market’s revenue numbers and subsegments. It will also help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies. Moreover, the report will provide insights for stakeholders to understand the market’s pulse and provide them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
1. Analysis of key drivers (Advancements in AI and ML, Increasing Data Availability, Rising Demand for Personalized Fan Experiences, Enhanced Athlete Performance and Injury Prevention, Investment in eSports), opportunities (Expansion of AI in Training and Scouting, Growth in Virtual and Augmented Reality, AI-Driven Health and Fitness Solutions, AI for Smart Stadiums), and challenges (Lack of Skilled Professionals, Ethical and Fairness Issues, Regulatory and Compliance Barriers) influencing the growth of the AI in Sports market.
2. Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI in Sports market.
3. Market Development: Comprehensive information about lucrative markets – the report analyses the AI in Sports market across various regions.
4. Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI in Sports market.
5. Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players Cisco (US), IBM (US), Intel (US), Microsoft (US), AWS (US), SAP SE (Germany), Ericsson (Sweden), Oracle (US), Stats Perform (US), Tech Mahindra (India), Sportradar AG (Switzerland), HCL Technologies (India), Extreme Networks (US), Salesforce (US), SAS Institute (US), Catapult Group (Australia), Genius Sports (UK), Kitman Labs (Ireland), PlaySight (Israel), Quantiphi (US), SciSports (Netherlands), Spiideo (Sweden), Sportlogiq (Canada), ChyronHego Corporation (US), TruMedia Networks (US).
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKET SEGMENTATION
1.3.2 INCLUSIONS AND EXCLUSIONS
1.4 YEARS CONSIDERED
1.5 CURRENCY CONSIDERED
1.6 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.2 PRIMARY DATA
2.1.2.1 Primary interviews with experts
2.1.2.2 Breakdown of primary profiles
2.1.2.3 Key insights from industry experts
2.2 MARKET SIZE ESTIMATION
2.2.1 TOP-DOWN APPROACH
2.2.2 BOTTOM-UP APPROACH
2.2.3 AI IN SPORTS MARKET ESTIMATION: DEMAND-SIDE ANALYSIS
2.3 DATA TRIANGULATION
2.4 RISK ASSESSMENT
2.5 RESEARCH ASSUMPTIONS
2.6 LIMITATIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN SPORTS MARKET
4.2 AI IN SPORTS MARKET, BY OFFERING, 2024
4.3 AI IN SPORTS MARKET, BY SERVICE
4.4 AI IN SPORTS MARKET, BY PROFESSIONAL SERVICE
4.5 AI IN SPORTS MARKET, BY SOLUTION
4.6 AI IN SPORTS MARKET, BY TYPE
4.7 AI IN SPORTS MARKET, BY SPORTS TYPE
4.8 AI IN SPORTS MARKET, BY END USER
4.9 NORTH AMERICA: AI IN SPORTS MARKET, BY OFFERING AND TYPE
5 MARKET OVERVIEW AND INDUSTRY TRENDS
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Enhanced player performance analytics driving competitive advantage
5.2.1.2 Improved fan engagement resulting in increased revenue generation
5.2.1.3 Advanced injury prediction tools leading to better athlete safety
5.2.2 RESTRAINTS
5.2.2.1 High implementation costs limiting widespread adoption
5.2.2.2 Data privacy concerns hindering trust in AI solutions
5.2.2.3 Limited AI expertise creating barriers for smaller sports organizations
5.2.3 OPPORTUNITIES
5.2.3.1 AI-driven personalization unlocking new revenue streams in
fan experiences
5.2.3.2 Growth in e-sports fostering innovation in AI applications
5.2.3.3 Integration of wearable technology enhancing real-time
performance insights
5.2.4 CHALLENGES
5.2.4.1 Complexity in integrating AI with existing sports infrastructure
5.2.4.2 Potential algorithmic bias impacting fairness in sports analytics
5.2.4.3 Evolving regulatory frameworks creating uncertainty for
AI deployment
5.3 BRIEF HISTORY OF EVOLUTION OF AI IN SPORTS SOLUTIONS AND SERVICES
5.4 AI IN SPORTS MARKET: ECOSYSTEM ANALYSIS/MARKET MAP
5.5 CASE STUDY ANALYSIS
5.5.1 CATAPULT ENHANCED ATHLETE PERFORMANCE TRACKING WITH
ADVANCED WEARABLE TECH SOLUTIONS
5.5.2 ORLANDO MAGIC LEVERAGED SAS FOR DATA-DRIVEN FAN ENGAGEMENT AND BUSINESS INSIGHTS
5.5.3 VODAFONE BOOSTED ENGAGEMENT WITH REAL-TIME AI INSIGHTS
FROM STATS PERFORM’S TECHNOLOGY
5.6 SUPPLY CHAIN ANALYSIS
5.7 PLANNING AND DESIGNING
5.8 REGULATORY LANDSCAPE
5.8.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.8.1.1 FIFA (Fйdйration Internationale de Football Association)
5.8.1.2 International Olympic Committee (IOC)
5.8.1.3 European Union (EU)
5.8.2 KEY REGULATIONS
5.8.2.1 North America
5.8.2.1.1 US and Canada
5.8.2.2 Europe
5.8.2.2.1 UK, France, and Germany
5.8.2.3 Asia Pacific
5.8.2.3.1 Australia
5.8.2.3.2 China
5.8.2.4 Middle East & Africa
5.8.2.4.1 UAE
5.8.2.5 Latin America
5.8.2.5.1 Brazil
5.9 PRICING ANALYSIS
5.9.1 PRICING OF SOLUTIONS, BY KEY PLAYER, 2023
5.9.2 INDICATIVE PRICING ANALYSIS, BY SPORTS TYPE, 2023
5.10 TECHNOLOGY ANALYSIS
5.10.1 KEY TECHNOLOGIES
5.10.1.1 Machine Learning & Deep Learning
5.10.1.2 Computer Vision
5.10.1.3 Natural Language Processing (NLP)
5.10.1.4 Predictive Analytics
5.10.1.5 Robotic Process Automation (RPA)
5.10.2 COMPLEMENTARY TECHNOLOGIES
5.10.2.1 Augmented Reality (AR)/Virtual Reality (VR)
5.10.2.2 Sensor Integration Technology
5.10.2.3 Big Data Analytics
5.10.2.4 Cloud Computing
5.10.2.5 Cybersecurity
5.10.3 ADJACENT TECHNOLOGIES
5.10.3.1 Blockchain
5.10.3.2 5G Connectivity
5.10.3.3 Edge Computing
5.10.3.4 Digital Twins
5.11 PATENT ANALYSIS
5.12 PORTER’S FIVE FORCES ANALYSIS
5.12.1 THREAT OF NEW ENTRANTS
5.12.2 THREAT OF SUBSTITUTES
5.12.3 BARGAINING POWER OF SUPPLIERS
5.12.4 BARGAINING POWER OF BUYERS
5.12.5 INTENSITY OF COMPETITIVE RIVALRY
5.13 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS’ BUSINESSES
5.14 KEY STAKEHOLDERS AND BUYING CRITERIA
5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.14.2 BUYING CRITERIA
5.15 KEY CONFERENCES AND EVENTS
5.16 TECHNOLOGY ROADMAP FOR AI IN SPORTS MARKET
5.16.1 SHORT-TERM ROADMAP (2023–2025)
5.16.2 MID-TERM ROADMAP (2026–2028)
5.16.3 LONG-TERM ROADMAP (2029–2030)
5.17 BEST PRACTICES IN AI IN SPORTS MARKET
5.17.1 PERFORMANCE ANALYSIS AND INJURY PREVENTION
5.17.2 AI-POWERED FAN ENGAGEMENT
5.17.3 REAL-TIME GAME ANALYTICS AND STRATEGY OPTIMIZATION
5.17.4 AUTOMATED CONTENT CREATION
5.17.5 TALENT SCOUTING AND RECRUITMENT
5.18 CURRENT AND EMERGING BUSINESS MODELS
5.18.1 SUBSCRIPTION-BASED ANALYTICS PLATFORMS
5.18.2 DATA-AS-A-SERVICE (DAAS)
5.18.3 SPONSORSHIP AND ADVERTISING OPTIMIZATION (AI-DRIVEN)
5.19 AI IN SPORTS MARKET: TOOLS, FRAMEWORKS, AND TECHNIQUES
5.20 HS CODE ANALYSIS: ELECTRONIC INTEGRATED CIRCUITS; PARTS THEREOF (8542)
5.20.1 EXPORT SCENARIO OF ELECTRONIC INTEGRATED CIRCUITS;
PARTS THEREOF (8542)
5.20.2 IMPORT SCENARIO OF ELECTRONIC INTEGRATED CIRCUITS;
PARTS THEREOF (8542)
5.21 INVESTMENT AND FUNDING SCENARIO
5.22 IMPACT OF GENERATIVE AI ON AI IN SPORTS MARKET
5.22.1 TOP USE CASES AND MARKET POTENTIAL
5.22.1.1 Key use cases
5.22.2 BEST PRACTICES
5.22.2.1 Sports Analytics Industry
5.22.2.2 Fan Engagement Industry
5.22.2.3 Injury Prevention & Rehabilitation Industry
5.22.3 CASE STUDIES OF GENERATIVE AI IMPLEMENTATION
5.22.3.1 Global Sports Streaming Service Enhanced Viewer Engagement
with AI-generated Content
5.22.3.2 Football Team Optimized Player Performance and Injury
Prevention Using AI-driven Data Insights
5.22.3.3 Sports Apparel Brand Increased Merchandise Sales by Creating
AI-generated Custom Designs
5.22.4 CLIENT READINESS AND IMPACT ASSESSMENT
5.22.4.1 Client A: Major Football Club
5.22.4.2 Client B: Global Sports Streaming Platform
5.22.4.3 Client C: Professional Basketball Team
6 AI IN SPORTS MARKET, BY OFFERING
6.1 INTRODUCTION
6.1.1 OFFERING: MARKET DRIVERS
6.2 SOLUTIONS
6.2.1 PERFORMANCE ANALYTICS
6.2.1.1 AI-based performance analytics assess player and team performance to improve gameplay and prevent injuries
6.2.2 PLAYER MONITORING
6.2.2.1 AI-powered player monitoring tracks health, fitness, and performance metrics, helping teams manage workload and prevent injuries
6.2.3 GAME STRATEGY & COACHING SOLUTIONS
6.2.3.1 AI tools optimize game strategies and coaching methods to enhance decision-making and performance during competitions
6.3 FAN ENGAGEMENT & EXPERIENCE ENHANCEMENT
6.3.1 AI SOLUTIONS ENHANCE FAN EXPERIENCES BY PROVIDING REAL-TIME STATS, PERSONALIZED INTERACTIONS, AND IMMERSIVE FEATURES
6.3.2 BROADCAST MANAGEMENT
6.3.2.1 AI-driven broadcast solutions optimize content delivery, improve viewer experience, and streamline broadcasting processes
6.3.3 OTHER SOLUTIONS
6.4 SERVICES
6.4.1 PROFESSIONAL SERVICES
6.4.2 TRAINING & CONSULTING
6.4.2.1 Consulting services help sports organizations plan and implement
AI strategies tailored to their needs, ensuring optimal adoption and use of AI solutions
6.4.3 SYSTEM INTEGRATION & IMPLEMENTATION
6.4.3.1 System integration services deploy AI solutions seamlessly within existing sports operations, ensuring smooth adoption and functionality
6.4.4 SUPPORT & MAINTENANCE
6.4.4.1 Support and maintenance services ensure AI systems function properly over time, providing updates, troubleshooting, and ongoing monitoring
6.4.5 MANAGED SERVICES
6.4.5.1 Outsourced management services handle the day-to-day running and optimization of AI systems, enabling sports organizations to focus on core operations
7 AI IN SPORTS MARKET, BY TYPE
7.1 INTRODUCTION
7.1.1 TYPE: MARKET DRIVERS
7.2 GENERATIVE AI
7.3 OTHER AI
7.3.1 MACHINE LEARNING
7.3.1.1 Machine learning enables systems to learn from data and make predictions, optimizing player performance, injury prevention, and fan insights
7.3.2 NATURAL LANGUAGE PROCESSING
7.3.2.1 NLP allows machines to understand and interact with human language, improving fan engagement and automating commentary and content analysis
7.3.3 COMPUTER VISION
7.3.3.1 Computer vision interprets visual data, enabling accurate analysis
of game footage and player movements, improving coaching and officiating
7.3.4 PREDICTIVE ANALYTICS
7.3.4.1 Predictive analytics uses historical data and algorithms to forecast future trends, optimizing strategies, predicting game outcomes,
and analyzing player performance
8 AI IN SPORTS MARKET, BY SPORTS TYPE
8.1 INTRODUCTION
8.1.1 SPORTS TYPE: MARKET DRIVERS
8.2 INDIVIDUAL SPORTS
8.2.1 BOXING
8.2.1.1 Advanced analytics and motion tracking enable boxers to improve techniques and track opponent tendencies
8.2.2 TENNIS
8.2.2.1 AI-powered tools assist players in analyzing match performance
and predicting opponent strategies
8.2.3 RACING
8.2.3.1 AI systems optimize vehicle performance and driver strategies
for competitive racing
8.2.4 ATHLETICS
8.2.4.1 Biometric monitoring and performance analytics aid athletes in achieving peak physical output
8.2.5 OTHERS
8.3 TEAM SPORTS
8.3.1 CRICKET
8.3.1.1 AI assists in analyzing player and team data to improve batting
and bowling strategies
8.3.2 SOCCER
8.3.2.1 Real-time analytics and tactical insights revolutionize team management and gameplay
8.3.3 AMERICAN FOOTBALL/RUGBY
8.3.3.1 AI helps strategize, monitor player safety, and enhance
on-field performance
8.3.4 BASKETBALL
8.3.4.1 Advanced analytics optimize shooting, defense, and player
rotations for improved results
8.3.5 BASEBALL
8.3.5.1 AI-driven tools refine strategy, from batting lineups to field positioning
8.3.6 HOCKEY
8.3.6.1 Video analysis and wearable tracking support tactical decisions
and player well-being
8.3.7 OTHERS
8.4 E-SPORTS
9 AI IN SPORTS MARKET, BY END USER
9.1 INTRODUCTION
9.1.1 END USER: MARKET DRIVERS
9.1.2 SPORTS ASSOCIATIONS
9.1.2.1 AI empowers sports associations in fair play, logistical management, and fan engagement, enhancing governance and global event execution
9.1.3 SPORTS TEAMS
9.1.3.1 Sports teams integrate AI for performance analytics, injury prevention, and player recruitment, ensuring competitive advantage
9.1.4 SPORTS MEDIA & BROADCASTING
9.1.4.1 AI revolutionizes sports broadcasting by automating content creation, enhancing fan engagement, and delivering tailored experiences
9.1.5 OTHER END USERS
10 AI IN SPORTS MARKET, BY REGION
10.1 INTRODUCTION
10.2 NORTH AMERICA
10.2.1 NORTH AMERICA: MACROECONOMIC OUTLOOK
10.2.2 US
10.2.2.1 US witnesses widespread AI integration in professional leagues
and fan engagement
10.2.3 CANADA
10.2.3.1 Canada emphasizes athlete training and grassroots development with AI technologies
10.3 EUROPE
10.3.1 EUROPE: MACROECONOMIC OUTLOOK
10.3.2 UK
10.3.2.1 UK excels in leveraging AI for elite sports broadcasting and officiating
10.3.3 GERMANY
10.3.3.1 Germany focuses on wearable technology and fan-centric
AI applications
10.3.4 FRANCE
10.3.4.1 France integrates AI in immersive fan experiences and sports event management
10.3.5 ITALY
10.3.5.1 Italy invests in AI for enhanced coaching systems and automated highlights
10.3.6 SPAIN
10.3.6.1 Spain emphasizes on AI in talent development and real-time
match applications
10.3.7 NORDIC COUNTRIES
10.3.7.1 Nordic countries lead in AI for winter sports and sustainable
stadium technologies
10.3.8 REST OF EUROPE
10.4 ASIA PACIFIC
10.4.1 ASIA PACIFIC: MACROECONOMIC OUTLOOK
10.4.2 CHINA
10.4.2.1 China is leveraging AI to boost player performance and enhance
fan engagement in sports
10.4.3 JAPAN
10.4.3.1 Japan is applying AI for player health management and improving
fan experiences in sports
10.4.4 INDIA
10.4.4.1 India is using AI to revolutionize sports analytics and player development
10.4.5 AUSTRALIA & NEW ZEALAND
10.4.5.1 Australia & New Zealand are integrating AI to optimize
performance and fan interactions in sports
10.4.6 SOUTH KOREA
10.4.6.1 South Korea is adopting AI for real-time sports analytics and
e-sports advancements
10.4.7 SOUTHEAST ASIA
10.4.7.1 Southeast Asia is embracing AI to improve sports performance
and fan engagement
10.4.8 REST OF ASIA PACIFIC
10.5 MIDDLE EAST & AFRICA
10.5.1 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
10.5.2 UAE
10.5.2.1 UAE accelerates AI integration in sports with smart stadium initiatives and enhanced fan engagement platforms
10.5.3 KSA
10.5.3.1 Saudi Arabia’s focus on Vision 2030, hosting mega-events, and sports technology to drive AI adoption
10.5.4 KUWAIT
10.5.4.1 Kuwait emphasizes AI in grassroots sports, talent development, and local sports programs
10.5.5 BAHRAIN
10.5.5.1 Bahrain leverages AI for advanced event management, youth sports development, and immersive fan experiences
10.5.6 SOUTH AFRICA
10.5.6.1 South Africa leverages AI for athlete performance enhancement, injury prevention, and sports analytics
10.5.7 REST OF MIDDLE EAST & AFRICA
10.6 LATIN AMERICA
10.6.1 LATIN AMERICA: MACROECONOMIC OUTLOOK
10.6.2 BRAZIL
10.6.2.1 Brazil is at forefront of AI adoption in sports, with AI technologies revolutionizing player training, tactical analysis, and injury prevention
10.6.3 MEXICO
10.6.3.1 In Mexico, AI is not just reshaping football but also transforming other sports such as Lucha Libre
10.6.4 ARGENTINA
10.6.4.1 In Argentina, AI technologies are being used to refine sports training, analyze player performance, and enhance fan experience
10.6.5 REST OF LATIN AMERICA
11 COMPETITIVE LANDSCAPE
11.1 INTRODUCTION
11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2021–2024
11.3 REVENUE ANALYSIS, 2019–2023
11.4 MARKET SHARE ANALYSIS, 2023
11.4.1 MARKET RANKING ANALYSIS
11.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
11.5.1 STARS
11.5.2 EMERGING LEADERS
11.5.3 PERVASIVE PLAYERS
11.5.4 PARTICIPANTS
11.5.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
11.6 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
11.6.1 PROGRESSIVE COMPANIES
11.6.2 RESPONSIVE COMPANIES
11.6.3 DYNAMIC COMPANIES
11.6.4 STARTING BLOCKS
11.6.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES,2021-2024
11.6.5.1 Detailed list of key startups/SMEs
11.6.5.2 Competitive benchmarking of key startups/SMEs
11.7 COMPETITIVE SCENARIO AND TRENDS
11.7.1 PRODUCT LAUNCHES AND ENHANCEMENTS
11.7.2 DEALS
11.8 BRAND/PRODUCT COMPARISON ANALYSIS
11.9 COMPANY VALUATION AND FINANCIAL METRICS OF KEY AI IN SPORTS
MARKET PROVIDERS
12 COMPANY PROFILES
12.1 KEY PLAYERS
12.1.1 MICROSOFT
12.1.1.1 Business overview
12.1.1.2 Products/Solutions/Services offered
12.1.1.3 Recent developments
12.1.1.3.1 Product launches
12.1.1.3.2 Deals
12.1.1.4 MnM view
12.1.1.4.1 Right to win
12.1.1.4.2 Strategic choices
12.1.1.4.3 Weaknesses and competitive threats
12.1.2 IBM
12.1.2.1 Business overview
12.1.2.2 Products/Solutions/Services offered
12.1.2.3 Recent developments
12.1.2.3.1 Product launches
12.1.2.3.2 Deals
12.1.2.4 MnM view
12.1.2.4.1 Right to win
12.1.2.4.2 Strategic choices
12.1.2.4.3 Weaknesses and competitive threats
12.1.3 ORACLE
12.1.3.1 Business overview
12.1.3.2 Products/Solutions/Services offered
12.1.3.3 Recent developments
12.1.3.3.1 Product launches
12.1.3.3.2 Deals
12.1.3.4 MnM view
12.1.3.4.1 Right to win
12.1.3.4.2 Strategic choices
12.1.3.4.3 Weaknesses and competitive threats
12.1.4 AWS
12.1.4.1 Business overview
12.1.4.2 Products/Solutions/Services offered
12.1.4.3 Recent developments
12.1.4.3.1 Product launches
12.1.4.3.2 Deals
12.1.4.4 MnM view
12.1.4.4.1 Right to win
12.1.4.4.2 Strategic choices
12.1.4.4.3 Weaknesses and competitive threats
12.1.5 SAP SE
12.1.5.1 Business overview
12.1.5.2 Products/Solutions/Services offered
12.1.5.3 Recent developments
12.1.5.3.1 Deals
12.1.5.4 MnM view
12.1.5.4.1 Right to win
12.1.5.4.2 Strategic choices
12.1.5.4.3 Weaknesses and competitive threats
12.1.6 STATS PERFORM
12.1.6.1 Business overview
12.1.6.2 Products/Solutions/Services offered
12.1.6.3 Recent developments
12.1.6.3.1 Product launches
12.1.6.3.2 Deals
12.1.7 SPORTRADAR AG
12.1.7.1 Business overview
12.1.7.2 Products/Solutions/Services offered
12.1.7.3 Recent developments
12.1.7.3.1 Product launches
12.1.7.3.2 Deals
12.1.8 SAS INSTITUTE
12.1.8.1 Business overview
12.1.8.2 Products/Solutions/Services offered
12.1.8.3 Recent developments
12.1.8.3.1 Deals
12.1.9 INTEL
12.1.9.1 Business overview
12.1.9.2 Products/Solutions/Services offered
12.1.9.3 Recent developments
12.1.9.3.1 Product launches
12.1.9.3.2 Deals
12.1.10 EXLSERVICE HOLDINGS
12.1.11 HUDL
12.1.12 GLOBALSTEP
12.1.13 HCL TECHNOLOGIES
12.1.14 ZEBRA TECHNOLOGIES
12.1.15 SALESFORCE
12.2 STARTUPS/SMES
12.2.1 CATAPULT
12.2.2 KITMAN LABS
12.2.3 SPORTLOGIQ
12.2.4 CHYRONHEGO CORPORATION
12.2.5 GENIUS SPORTS
12.2.6 PLAYSIGHT
12.2.7 QUANTIPHI
12.2.8 SCISPORTS
12.2.9 TRUMEDIA NETWORKS
12.2.10 SPIIDEO
13 ADJACENT/RELATED MARKETS
13.1 INTRODUCTION
13.1.1 RELATED MARKETS
13.2 SPORTS TECHNOLOGY MARKET - GLOBAL FORECAST 2027
13.2.1 MARKET DEFINITION
13.3 SPORTS ANALYTICS MARKET – GLOBAL FORECAST 2026
13.3.1 MARKET DEFINITION
14 APPENDIX
14.1 DISCUSSION GUIDE
14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
14.3 CUSTOMIZATION OPTIONS
14.4 RELATED REPORTS
14.5 AUTHOR DETAILS
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKET SEGMENTATION
1.3.2 INCLUSIONS AND EXCLUSIONS
1.4 YEARS CONSIDERED
1.5 CURRENCY CONSIDERED
1.6 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.2 PRIMARY DATA
2.1.2.1 Primary interviews with experts
2.1.2.2 Breakdown of primary profiles
2.1.2.3 Key insights from industry experts
2.2 MARKET SIZE ESTIMATION
2.2.1 TOP-DOWN APPROACH
2.2.2 BOTTOM-UP APPROACH
2.2.3 AI IN SPORTS MARKET ESTIMATION: DEMAND-SIDE ANALYSIS
2.3 DATA TRIANGULATION
2.4 RISK ASSESSMENT
2.5 RESEARCH ASSUMPTIONS
2.6 LIMITATIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN SPORTS MARKET
4.2 AI IN SPORTS MARKET, BY OFFERING, 2024
4.3 AI IN SPORTS MARKET, BY SERVICE
4.4 AI IN SPORTS MARKET, BY PROFESSIONAL SERVICE
4.5 AI IN SPORTS MARKET, BY SOLUTION
4.6 AI IN SPORTS MARKET, BY TYPE
4.7 AI IN SPORTS MARKET, BY SPORTS TYPE
4.8 AI IN SPORTS MARKET, BY END USER
4.9 NORTH AMERICA: AI IN SPORTS MARKET, BY OFFERING AND TYPE
5 MARKET OVERVIEW AND INDUSTRY TRENDS
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Enhanced player performance analytics driving competitive advantage
5.2.1.2 Improved fan engagement resulting in increased revenue generation
5.2.1.3 Advanced injury prediction tools leading to better athlete safety
5.2.2 RESTRAINTS
5.2.2.1 High implementation costs limiting widespread adoption
5.2.2.2 Data privacy concerns hindering trust in AI solutions
5.2.2.3 Limited AI expertise creating barriers for smaller sports organizations
5.2.3 OPPORTUNITIES
5.2.3.1 AI-driven personalization unlocking new revenue streams in
fan experiences
5.2.3.2 Growth in e-sports fostering innovation in AI applications
5.2.3.3 Integration of wearable technology enhancing real-time
performance insights
5.2.4 CHALLENGES
5.2.4.1 Complexity in integrating AI with existing sports infrastructure
5.2.4.2 Potential algorithmic bias impacting fairness in sports analytics
5.2.4.3 Evolving regulatory frameworks creating uncertainty for
AI deployment
5.3 BRIEF HISTORY OF EVOLUTION OF AI IN SPORTS SOLUTIONS AND SERVICES
5.4 AI IN SPORTS MARKET: ECOSYSTEM ANALYSIS/MARKET MAP
5.5 CASE STUDY ANALYSIS
5.5.1 CATAPULT ENHANCED ATHLETE PERFORMANCE TRACKING WITH
ADVANCED WEARABLE TECH SOLUTIONS
5.5.2 ORLANDO MAGIC LEVERAGED SAS FOR DATA-DRIVEN FAN ENGAGEMENT AND BUSINESS INSIGHTS
5.5.3 VODAFONE BOOSTED ENGAGEMENT WITH REAL-TIME AI INSIGHTS
FROM STATS PERFORM’S TECHNOLOGY
5.6 SUPPLY CHAIN ANALYSIS
5.7 PLANNING AND DESIGNING
5.8 REGULATORY LANDSCAPE
5.8.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.8.1.1 FIFA (Fйdйration Internationale de Football Association)
5.8.1.2 International Olympic Committee (IOC)
5.8.1.3 European Union (EU)
5.8.2 KEY REGULATIONS
5.8.2.1 North America
5.8.2.1.1 US and Canada
5.8.2.2 Europe
5.8.2.2.1 UK, France, and Germany
5.8.2.3 Asia Pacific
5.8.2.3.1 Australia
5.8.2.3.2 China
5.8.2.4 Middle East & Africa
5.8.2.4.1 UAE
5.8.2.5 Latin America
5.8.2.5.1 Brazil
5.9 PRICING ANALYSIS
5.9.1 PRICING OF SOLUTIONS, BY KEY PLAYER, 2023
5.9.2 INDICATIVE PRICING ANALYSIS, BY SPORTS TYPE, 2023
5.10 TECHNOLOGY ANALYSIS
5.10.1 KEY TECHNOLOGIES
5.10.1.1 Machine Learning & Deep Learning
5.10.1.2 Computer Vision
5.10.1.3 Natural Language Processing (NLP)
5.10.1.4 Predictive Analytics
5.10.1.5 Robotic Process Automation (RPA)
5.10.2 COMPLEMENTARY TECHNOLOGIES
5.10.2.1 Augmented Reality (AR)/Virtual Reality (VR)
5.10.2.2 Sensor Integration Technology
5.10.2.3 Big Data Analytics
5.10.2.4 Cloud Computing
5.10.2.5 Cybersecurity
5.10.3 ADJACENT TECHNOLOGIES
5.10.3.1 Blockchain
5.10.3.2 5G Connectivity
5.10.3.3 Edge Computing
5.10.3.4 Digital Twins
5.11 PATENT ANALYSIS
5.12 PORTER’S FIVE FORCES ANALYSIS
5.12.1 THREAT OF NEW ENTRANTS
5.12.2 THREAT OF SUBSTITUTES
5.12.3 BARGAINING POWER OF SUPPLIERS
5.12.4 BARGAINING POWER OF BUYERS
5.12.5 INTENSITY OF COMPETITIVE RIVALRY
5.13 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS’ BUSINESSES
5.14 KEY STAKEHOLDERS AND BUYING CRITERIA
5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.14.2 BUYING CRITERIA
5.15 KEY CONFERENCES AND EVENTS
5.16 TECHNOLOGY ROADMAP FOR AI IN SPORTS MARKET
5.16.1 SHORT-TERM ROADMAP (2023–2025)
5.16.2 MID-TERM ROADMAP (2026–2028)
5.16.3 LONG-TERM ROADMAP (2029–2030)
5.17 BEST PRACTICES IN AI IN SPORTS MARKET
5.17.1 PERFORMANCE ANALYSIS AND INJURY PREVENTION
5.17.2 AI-POWERED FAN ENGAGEMENT
5.17.3 REAL-TIME GAME ANALYTICS AND STRATEGY OPTIMIZATION
5.17.4 AUTOMATED CONTENT CREATION
5.17.5 TALENT SCOUTING AND RECRUITMENT
5.18 CURRENT AND EMERGING BUSINESS MODELS
5.18.1 SUBSCRIPTION-BASED ANALYTICS PLATFORMS
5.18.2 DATA-AS-A-SERVICE (DAAS)
5.18.3 SPONSORSHIP AND ADVERTISING OPTIMIZATION (AI-DRIVEN)
5.19 AI IN SPORTS MARKET: TOOLS, FRAMEWORKS, AND TECHNIQUES
5.20 HS CODE ANALYSIS: ELECTRONIC INTEGRATED CIRCUITS; PARTS THEREOF (8542)
5.20.1 EXPORT SCENARIO OF ELECTRONIC INTEGRATED CIRCUITS;
PARTS THEREOF (8542)
5.20.2 IMPORT SCENARIO OF ELECTRONIC INTEGRATED CIRCUITS;
PARTS THEREOF (8542)
5.21 INVESTMENT AND FUNDING SCENARIO
5.22 IMPACT OF GENERATIVE AI ON AI IN SPORTS MARKET
5.22.1 TOP USE CASES AND MARKET POTENTIAL
5.22.1.1 Key use cases
5.22.2 BEST PRACTICES
5.22.2.1 Sports Analytics Industry
5.22.2.2 Fan Engagement Industry
5.22.2.3 Injury Prevention & Rehabilitation Industry
5.22.3 CASE STUDIES OF GENERATIVE AI IMPLEMENTATION
5.22.3.1 Global Sports Streaming Service Enhanced Viewer Engagement
with AI-generated Content
5.22.3.2 Football Team Optimized Player Performance and Injury
Prevention Using AI-driven Data Insights
5.22.3.3 Sports Apparel Brand Increased Merchandise Sales by Creating
AI-generated Custom Designs
5.22.4 CLIENT READINESS AND IMPACT ASSESSMENT
5.22.4.1 Client A: Major Football Club
5.22.4.2 Client B: Global Sports Streaming Platform
5.22.4.3 Client C: Professional Basketball Team
6 AI IN SPORTS MARKET, BY OFFERING
6.1 INTRODUCTION
6.1.1 OFFERING: MARKET DRIVERS
6.2 SOLUTIONS
6.2.1 PERFORMANCE ANALYTICS
6.2.1.1 AI-based performance analytics assess player and team performance to improve gameplay and prevent injuries
6.2.2 PLAYER MONITORING
6.2.2.1 AI-powered player monitoring tracks health, fitness, and performance metrics, helping teams manage workload and prevent injuries
6.2.3 GAME STRATEGY & COACHING SOLUTIONS
6.2.3.1 AI tools optimize game strategies and coaching methods to enhance decision-making and performance during competitions
6.3 FAN ENGAGEMENT & EXPERIENCE ENHANCEMENT
6.3.1 AI SOLUTIONS ENHANCE FAN EXPERIENCES BY PROVIDING REAL-TIME STATS, PERSONALIZED INTERACTIONS, AND IMMERSIVE FEATURES
6.3.2 BROADCAST MANAGEMENT
6.3.2.1 AI-driven broadcast solutions optimize content delivery, improve viewer experience, and streamline broadcasting processes
6.3.3 OTHER SOLUTIONS
6.4 SERVICES
6.4.1 PROFESSIONAL SERVICES
6.4.2 TRAINING & CONSULTING
6.4.2.1 Consulting services help sports organizations plan and implement
AI strategies tailored to their needs, ensuring optimal adoption and use of AI solutions
6.4.3 SYSTEM INTEGRATION & IMPLEMENTATION
6.4.3.1 System integration services deploy AI solutions seamlessly within existing sports operations, ensuring smooth adoption and functionality
6.4.4 SUPPORT & MAINTENANCE
6.4.4.1 Support and maintenance services ensure AI systems function properly over time, providing updates, troubleshooting, and ongoing monitoring
6.4.5 MANAGED SERVICES
6.4.5.1 Outsourced management services handle the day-to-day running and optimization of AI systems, enabling sports organizations to focus on core operations
7 AI IN SPORTS MARKET, BY TYPE
7.1 INTRODUCTION
7.1.1 TYPE: MARKET DRIVERS
7.2 GENERATIVE AI
7.3 OTHER AI
7.3.1 MACHINE LEARNING
7.3.1.1 Machine learning enables systems to learn from data and make predictions, optimizing player performance, injury prevention, and fan insights
7.3.2 NATURAL LANGUAGE PROCESSING
7.3.2.1 NLP allows machines to understand and interact with human language, improving fan engagement and automating commentary and content analysis
7.3.3 COMPUTER VISION
7.3.3.1 Computer vision interprets visual data, enabling accurate analysis
of game footage and player movements, improving coaching and officiating
7.3.4 PREDICTIVE ANALYTICS
7.3.4.1 Predictive analytics uses historical data and algorithms to forecast future trends, optimizing strategies, predicting game outcomes,
and analyzing player performance
8 AI IN SPORTS MARKET, BY SPORTS TYPE
8.1 INTRODUCTION
8.1.1 SPORTS TYPE: MARKET DRIVERS
8.2 INDIVIDUAL SPORTS
8.2.1 BOXING
8.2.1.1 Advanced analytics and motion tracking enable boxers to improve techniques and track opponent tendencies
8.2.2 TENNIS
8.2.2.1 AI-powered tools assist players in analyzing match performance
and predicting opponent strategies
8.2.3 RACING
8.2.3.1 AI systems optimize vehicle performance and driver strategies
for competitive racing
8.2.4 ATHLETICS
8.2.4.1 Biometric monitoring and performance analytics aid athletes in achieving peak physical output
8.2.5 OTHERS
8.3 TEAM SPORTS
8.3.1 CRICKET
8.3.1.1 AI assists in analyzing player and team data to improve batting
and bowling strategies
8.3.2 SOCCER
8.3.2.1 Real-time analytics and tactical insights revolutionize team management and gameplay
8.3.3 AMERICAN FOOTBALL/RUGBY
8.3.3.1 AI helps strategize, monitor player safety, and enhance
on-field performance
8.3.4 BASKETBALL
8.3.4.1 Advanced analytics optimize shooting, defense, and player
rotations for improved results
8.3.5 BASEBALL
8.3.5.1 AI-driven tools refine strategy, from batting lineups to field positioning
8.3.6 HOCKEY
8.3.6.1 Video analysis and wearable tracking support tactical decisions
and player well-being
8.3.7 OTHERS
8.4 E-SPORTS
9 AI IN SPORTS MARKET, BY END USER
9.1 INTRODUCTION
9.1.1 END USER: MARKET DRIVERS
9.1.2 SPORTS ASSOCIATIONS
9.1.2.1 AI empowers sports associations in fair play, logistical management, and fan engagement, enhancing governance and global event execution
9.1.3 SPORTS TEAMS
9.1.3.1 Sports teams integrate AI for performance analytics, injury prevention, and player recruitment, ensuring competitive advantage
9.1.4 SPORTS MEDIA & BROADCASTING
9.1.4.1 AI revolutionizes sports broadcasting by automating content creation, enhancing fan engagement, and delivering tailored experiences
9.1.5 OTHER END USERS
10 AI IN SPORTS MARKET, BY REGION
10.1 INTRODUCTION
10.2 NORTH AMERICA
10.2.1 NORTH AMERICA: MACROECONOMIC OUTLOOK
10.2.2 US
10.2.2.1 US witnesses widespread AI integration in professional leagues
and fan engagement
10.2.3 CANADA
10.2.3.1 Canada emphasizes athlete training and grassroots development with AI technologies
10.3 EUROPE
10.3.1 EUROPE: MACROECONOMIC OUTLOOK
10.3.2 UK
10.3.2.1 UK excels in leveraging AI for elite sports broadcasting and officiating
10.3.3 GERMANY
10.3.3.1 Germany focuses on wearable technology and fan-centric
AI applications
10.3.4 FRANCE
10.3.4.1 France integrates AI in immersive fan experiences and sports event management
10.3.5 ITALY
10.3.5.1 Italy invests in AI for enhanced coaching systems and automated highlights
10.3.6 SPAIN
10.3.6.1 Spain emphasizes on AI in talent development and real-time
match applications
10.3.7 NORDIC COUNTRIES
10.3.7.1 Nordic countries lead in AI for winter sports and sustainable
stadium technologies
10.3.8 REST OF EUROPE
10.4 ASIA PACIFIC
10.4.1 ASIA PACIFIC: MACROECONOMIC OUTLOOK
10.4.2 CHINA
10.4.2.1 China is leveraging AI to boost player performance and enhance
fan engagement in sports
10.4.3 JAPAN
10.4.3.1 Japan is applying AI for player health management and improving
fan experiences in sports
10.4.4 INDIA
10.4.4.1 India is using AI to revolutionize sports analytics and player development
10.4.5 AUSTRALIA & NEW ZEALAND
10.4.5.1 Australia & New Zealand are integrating AI to optimize
performance and fan interactions in sports
10.4.6 SOUTH KOREA
10.4.6.1 South Korea is adopting AI for real-time sports analytics and
e-sports advancements
10.4.7 SOUTHEAST ASIA
10.4.7.1 Southeast Asia is embracing AI to improve sports performance
and fan engagement
10.4.8 REST OF ASIA PACIFIC
10.5 MIDDLE EAST & AFRICA
10.5.1 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
10.5.2 UAE
10.5.2.1 UAE accelerates AI integration in sports with smart stadium initiatives and enhanced fan engagement platforms
10.5.3 KSA
10.5.3.1 Saudi Arabia’s focus on Vision 2030, hosting mega-events, and sports technology to drive AI adoption
10.5.4 KUWAIT
10.5.4.1 Kuwait emphasizes AI in grassroots sports, talent development, and local sports programs
10.5.5 BAHRAIN
10.5.5.1 Bahrain leverages AI for advanced event management, youth sports development, and immersive fan experiences
10.5.6 SOUTH AFRICA
10.5.6.1 South Africa leverages AI for athlete performance enhancement, injury prevention, and sports analytics
10.5.7 REST OF MIDDLE EAST & AFRICA
10.6 LATIN AMERICA
10.6.1 LATIN AMERICA: MACROECONOMIC OUTLOOK
10.6.2 BRAZIL
10.6.2.1 Brazil is at forefront of AI adoption in sports, with AI technologies revolutionizing player training, tactical analysis, and injury prevention
10.6.3 MEXICO
10.6.3.1 In Mexico, AI is not just reshaping football but also transforming other sports such as Lucha Libre
10.6.4 ARGENTINA
10.6.4.1 In Argentina, AI technologies are being used to refine sports training, analyze player performance, and enhance fan experience
10.6.5 REST OF LATIN AMERICA
11 COMPETITIVE LANDSCAPE
11.1 INTRODUCTION
11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2021–2024
11.3 REVENUE ANALYSIS, 2019–2023
11.4 MARKET SHARE ANALYSIS, 2023
11.4.1 MARKET RANKING ANALYSIS
11.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
11.5.1 STARS
11.5.2 EMERGING LEADERS
11.5.3 PERVASIVE PLAYERS
11.5.4 PARTICIPANTS
11.5.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
11.6 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
11.6.1 PROGRESSIVE COMPANIES
11.6.2 RESPONSIVE COMPANIES
11.6.3 DYNAMIC COMPANIES
11.6.4 STARTING BLOCKS
11.6.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES,2021-2024
11.6.5.1 Detailed list of key startups/SMEs
11.6.5.2 Competitive benchmarking of key startups/SMEs
11.7 COMPETITIVE SCENARIO AND TRENDS
11.7.1 PRODUCT LAUNCHES AND ENHANCEMENTS
11.7.2 DEALS
11.8 BRAND/PRODUCT COMPARISON ANALYSIS
11.9 COMPANY VALUATION AND FINANCIAL METRICS OF KEY AI IN SPORTS
MARKET PROVIDERS
12 COMPANY PROFILES
12.1 KEY PLAYERS
12.1.1 MICROSOFT
12.1.1.1 Business overview
12.1.1.2 Products/Solutions/Services offered
12.1.1.3 Recent developments
12.1.1.3.1 Product launches
12.1.1.3.2 Deals
12.1.1.4 MnM view
12.1.1.4.1 Right to win
12.1.1.4.2 Strategic choices
12.1.1.4.3 Weaknesses and competitive threats
12.1.2 IBM
12.1.2.1 Business overview
12.1.2.2 Products/Solutions/Services offered
12.1.2.3 Recent developments
12.1.2.3.1 Product launches
12.1.2.3.2 Deals
12.1.2.4 MnM view
12.1.2.4.1 Right to win
12.1.2.4.2 Strategic choices
12.1.2.4.3 Weaknesses and competitive threats
12.1.3 ORACLE
12.1.3.1 Business overview
12.1.3.2 Products/Solutions/Services offered
12.1.3.3 Recent developments
12.1.3.3.1 Product launches
12.1.3.3.2 Deals
12.1.3.4 MnM view
12.1.3.4.1 Right to win
12.1.3.4.2 Strategic choices
12.1.3.4.3 Weaknesses and competitive threats
12.1.4 AWS
12.1.4.1 Business overview
12.1.4.2 Products/Solutions/Services offered
12.1.4.3 Recent developments
12.1.4.3.1 Product launches
12.1.4.3.2 Deals
12.1.4.4 MnM view
12.1.4.4.1 Right to win
12.1.4.4.2 Strategic choices
12.1.4.4.3 Weaknesses and competitive threats
12.1.5 SAP SE
12.1.5.1 Business overview
12.1.5.2 Products/Solutions/Services offered
12.1.5.3 Recent developments
12.1.5.3.1 Deals
12.1.5.4 MnM view
12.1.5.4.1 Right to win
12.1.5.4.2 Strategic choices
12.1.5.4.3 Weaknesses and competitive threats
12.1.6 STATS PERFORM
12.1.6.1 Business overview
12.1.6.2 Products/Solutions/Services offered
12.1.6.3 Recent developments
12.1.6.3.1 Product launches
12.1.6.3.2 Deals
12.1.7 SPORTRADAR AG
12.1.7.1 Business overview
12.1.7.2 Products/Solutions/Services offered
12.1.7.3 Recent developments
12.1.7.3.1 Product launches
12.1.7.3.2 Deals
12.1.8 SAS INSTITUTE
12.1.8.1 Business overview
12.1.8.2 Products/Solutions/Services offered
12.1.8.3 Recent developments
12.1.8.3.1 Deals
12.1.9 INTEL
12.1.9.1 Business overview
12.1.9.2 Products/Solutions/Services offered
12.1.9.3 Recent developments
12.1.9.3.1 Product launches
12.1.9.3.2 Deals
12.1.10 EXLSERVICE HOLDINGS
12.1.11 HUDL
12.1.12 GLOBALSTEP
12.1.13 HCL TECHNOLOGIES
12.1.14 ZEBRA TECHNOLOGIES
12.1.15 SALESFORCE
12.2 STARTUPS/SMES
12.2.1 CATAPULT
12.2.2 KITMAN LABS
12.2.3 SPORTLOGIQ
12.2.4 CHYRONHEGO CORPORATION
12.2.5 GENIUS SPORTS
12.2.6 PLAYSIGHT
12.2.7 QUANTIPHI
12.2.8 SCISPORTS
12.2.9 TRUMEDIA NETWORKS
12.2.10 SPIIDEO
13 ADJACENT/RELATED MARKETS
13.1 INTRODUCTION
13.1.1 RELATED MARKETS
13.2 SPORTS TECHNOLOGY MARKET - GLOBAL FORECAST 2027
13.2.1 MARKET DEFINITION
13.3 SPORTS ANALYTICS MARKET – GLOBAL FORECAST 2026
13.3.1 MARKET DEFINITION
14 APPENDIX
14.1 DISCUSSION GUIDE
14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
14.3 CUSTOMIZATION OPTIONS
14.4 RELATED REPORTS
14.5 AUTHOR DETAILS
