세계의 스포츠 분야 AI 시장 : 제공 제품별, 유형별, 스포츠 유형별, 최종 사용자별, 지역별 - 예측(-2030년)`
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
상품코드:1618941
리서치사:MarketsandMarkets
발행일:2024년 11월
페이지 정보:영문 285 Pages
라이선스 & 가격 (부가세 별도)
ㅁ Add-on 가능: 고객의 요청에 따라 일정한 범위 내에서 Customization이 가능합니다. 자세한 사항은 문의해 주시기 바랍니다.
한글목차
스포츠 분야 AI시장 규모는 2024년 10억 3,000만 달러, 2030년에는 26억 1,000만 달러에 달할 것으로 예상되며, 2024년부터 2030년까지 연평균 16.7%의 성장률을 나타낼 것으로 전망됩니다. 머신러닝(ML) 및 기타 모델의 도움으로 스포츠 AI의 발전으로 조직은 방대한 양의 데이터를 실시간으로 처리할 수 있게 되었습니다. 이 기술은 선수의 패턴 분석, 비디오 및 모션 센서의 스포츠 동작 연구, 경기력 향상 및 부상 관리를 위한 선수의 건강 상태 예측에 도움이 됩니다. 또한, 선수들은 AI를 통해 VR 시스템을 통합하여 거리와 지역의 제약에서 벗어나 통제된 환경에서 훈련과 전략을 세우고 자신의 발로 생각할 수 있는 VR 시스템을 통해 VR 경험을 향상시킬 수 있습니다. 이러한 혁신은 스포츠 협회, 스포츠 팀, 미디어 및 방송 기관과 같은 최종 사용자에게 특히 가치가 높으며, 경기력 최적화, 팬 참여 강화, 컨텐츠 배포 개선에 도움이 될 수 있습니다.
조사 범위
조사 대상년도
2019-2030년
기준 연도
2024년
예측 기간
2025-2030년
검토 단위
달러(10억 달러)
부문별
제품별, 유형별, 스포츠 유형별, 최종사용자별, 지역별
대상 지역
북미, 유럽, 아시아태평양, 중동/아프리카, 라틴아메리카
팬의 경우, AI는 개인화된 서비스, 효율적인 티켓팅 시스템, 모든 지리적 위치에서 이벤트 참여 등의 형태로 경험을 향상시킬 수 있으며, e스포츠의 경우, AI는 기업의 순위를 적절히 관리하고, 컨텐츠를 개선하고, 비디오 게임 내 캐릭터의 행동을 시뮬레이션하여 플레이 경험을 향상시킵니다. 캐릭터의 행동을 시뮬레이션하여 플레이 경험을 향상시킬 수 있습니다. 이러한 기술의 발전은 프로 스포츠의 역학을 변화시키고 관중의 행동을 변화시켜 관중의 상호 작용과 몰입감을 향상시키고 있습니다.
AI는 성능 평가, 팬 참여 및 전략 관리를 강화함으로써 농구를 점점 더 변화시키고 있으며, NBA와 같은 리그는 이미 첨단 기술 채택에 앞장서고 있으며, 포지션 모니터링, 작업량 관리, 훈련 연습 개선에 AI 기반 도구를 활용하고 있으며, 선수 추적 시스템과 같은 AI 기반 도구를 활용하여 포지션 모니터링, 작업량 관리, 훈련 연습 개선에 활용하고 있습니다. 이러한 도구는 선수의 움직임과 신체적 요구 사항을 보다 정확하게 파악할 수 있어 팀 전체의 성과를 향상시킬 수 있습니다. 코치는 또한 AI 기반 웨어러블 기기 및 카메라의 실시간 분석을 통해 경기 중 적극적인 전략을 실행할 수 있습니다.
NBA와 마이크로소프트의 파트너십은 AI가 생성한 하이라이트 영상으로 일부 경기를 스트리밍하는 것으로, AI가 어떻게 팬 참여와 컨텐츠 전달을 향상시키는지 보여주는 대표적인 사례입니다. 이러한 AI 도구는 강화된 하이라이트, 선수 통계, 경기 통찰력 등 팬들에게 실시간으로 개인화된 경험을 제공함으로써 스포츠와 더 깊은 상호 작용을 할 수 있도록 돕습니다.
농구의 세계적인 인기, 특히 미국, 중국, 유럽 등의 지역에서는 AI 모델을 지속적으로 개선하는 데 필수적인 방대한 양의 데이터가 생성됩니다. 농구의 세계적 확산은 높은 데이터 생산량과 함께 스포츠에 AI의 개발 및 적용을 가속화하여 보다 정교하고 효과적인 솔루션을 가능하게 합니다. 그 결과, 농구는 스포츠 분야에서의 AI 통합의 최전선에 서서 기술 진화의 선두주자가 되고 있습니다.
이 보고서는 세계 스포츠 분야의 AI 시장을 조사했으며, 제공 제품별, 유형별, 스포츠 유형별, 최종 사용자별, 지역별 동향, 시장 진출기업 프로파일 등을 정리한 보고서입니다.
목차
제1장 서론
제2장 조사 방법
제3장 주요 요약
제4장 프리미엄 인사이트
제5장 시장 개요와 업계 동향
서론
시장 역학
스포츠 솔루션과 서비스 AI 진화 간단한 역사
스포츠 분야 AI: 생태계 분석/시장 맵
사례 연구 분석
공급망 분석
계획과 설계
규제 상황
가격 분석
기술 분석
특허 분석
Porter의 Five Forces 분석
고객의 비즈니스에 영향을 미치는 동향/혼란
주요 이해관계자와 구입 기준
주요 컨퍼런스 및 이벤트
스포츠 분야 AI 기술 로드맵
스포츠 분야 AI 베스트 프랙티스
현재 비즈니스 모델과 새로운 비즈니스 모델
스포츠 분야 AI: 툴, 프레임워크, 테크닉
HS코드 분석 : 전자 집적회로, 그 부분품
투자와 자금조달 시나리오
생성형 AI가 스포츠 AI에 미치는 영향
제6장 스포츠 분야 AI 시장, 제공 제품별
서론
솔루션
팬 참여 및 체험 향상
서비스
제7장 스포츠 분야 AI 시장, 유형별
서론
생성형 AI
기타
제8장 스포츠 분야 AI 시장, 스포츠 유형별
서론
개인 경기
팀 스포츠
E스포츠
제9장 스포츠 분야 AI 시장, 최종사용자별
서론
최종사용자 : 시장 성장 촉진요인
스포츠 협회
스포츠 팀
스포츠 미디어 및 방송
기타
제10장 스포츠 분야 AI 시장, 지역별
서론
북미
북미 : 거시경제 전망
미국
캐나다
유럽
유럽 : 거시경제 전망
영국
독일
프랑스
이탈리아
스페인
북유럽 국가
기타
아시아태평양
아시아태평양 : 거시경제 전망
중국
일본
인도
호주 및 뉴질랜드
한국
동남아시아
기타
중동 및 아프리카
중동 및 아프리카 : 거시경제 전망
아랍에미리트(UAE)
사우디아라비아
쿠웨이트
바레인
남아프리카공화국
기타
라틴아메리카
라틴아메리카 : 거시경제 전망
브라질
멕시코
아르헨티나
기타
제11장 경쟁 구도
서론
주요 시장 진출기업의 전략/강점, 2021년-2024년
매출 분석, 2019년-2023년
기업 평가 매트릭스 : 주요 시장 진출기업, 2023년
기업 평가 매트릭스 : 스타트업/중소기업, 2023년
경쟁 시나리오와 동향
브랜드/제품 비교 분석
스포츠 시장 주요 AI 프로바이더 기업 평가와 재무 지표
제12장 기업 개요
주요 시장 진출기업
MICROSOFT
IBM
ORACLE
AWS
SAP SE
STATS PERFORM
SPORTRADAR AG
SAS INSTITUTE
INTEL
EXLSERVICE HOLDINGS
HUDL
GLOBALSTEP
HCL TECHNOLOGIES
ZEBRA TECHNOLOGIES
SALESFORCE
스타트업/중소기업
CATAPULT
KITMAN LABS
SPORTLOGIQ
CHYRONHEGO CORPORATION
GENIUS SPORTS
PLAYSIGHT
QUANTIPHI
SCISPORTS
TRUMEDIA NETWORKS
SPIIDEO
제13장 인접 시장 및 관련 시장
제14장 부록
LSH
영문 목차
영문목차
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.
Scope of the Report
Years Considered for the Study
2019-2030
Base Year
2024
Forecast Period
2025-2030
Units Considered
USD (Billion)
Segments
By Offering, Technology, Sports Type, End User, and Region
Regions covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
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%.
The players in the AI in Sports market include 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). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, enhancements, and acquisitions to expand their AI in Sports market footprint.
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).
TABLE OF CONTENTS
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
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