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Artificial Intelligence in Sports Market by Component (Software, Service), by Deployment Model (On-premise, Cloud), by Technology (Machine Learning, Natural Language Processing, Computer Vision, Data Analytics, Others), by Application (Game Planning, Game Strategies, Performance Improvement, Injury Prevention, Sports Recruitment, Others), by Game Type (Football, Cricket, Tennis, Basketball, Baseball, Others): Global Opportunity Analysis and Industry Forecast, 2023-2032

A12905

Pages: 350

Charts: 84

Tables: 185

Artificial Intelligence (AI) in Sports Market Statistics, 2032

The global artificial intelligence (AI) in sports market size was valued at $2.2 billion in 2022, and is projected to reach $29.7 billion by 2032, growing at a CAGR of 30.1% from 2023 to 2032.

Increase in demand for monitoring and tracking data of players and surge in need for chatbots & virtual assistants to interact with followers act as the key driving forces of the global artificial intelligence in sports market growth. In addition, the expansion popular for ongoing information investigation decidedly influences the development of the market. However, the absence of prepared and talented experts and high execution and upkeep costs hamper the market development. On the contrary, surge in demand of AI in sports market for making future predictions is expected to offer remunerative opportunities for expansion of the market during the forecast period.

Artificial Intelligence in Sports Market

Sports data are being used by artificial intelligence (AI) to create comprehensible information about various sporting events. In addition, a virtual stage with computer based intelligence innovation gives a reasonable involvement with a virtual climate that matches the experience of seeing the live game. Moreover, Before, during, and after a game, coaches' strategic decisions continue to be significantly influenced by AI. With the help of wearable sensors and high-speed cameras, AI platforms measure a forward pass, a penalty kick, leg before cricket (LBW) in cricket, and a lot of similar actions in various sports.

Segment Review 

The AI in sports market is segmented into component, deployment model, technology, application, sports type, and region. Depending on the component, the market is bifurcated into software and services. By deployment model, it is categorized on-premises and cloud. On the basis of technology, it is fragmented into machine learning, natural language processing, computer vision, data analytics, and others. By application, it is segregated into game planning, game strategies, performance improvement, injury prevention sports recruitment, and others. As per sports type, it is classified into football, cricket, tennis, basketball, baseball, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA. 

[COMPONENTGRAPH]

On the basis of component, the global artificial intelligence in sports market share was dominated by the software segment in 2022 and is expected to maintain its dominance in the upcoming years, owing to the rise in demand for artificial intelligence solutions in sports industries, which further expected to propel the global market growth. However, services are expected to exhibit the highest growth during the forecast period. Services in the artificial intelligence in sports industry include a variety of products and services offered by businesses to help the sport sector to manage the sports related activities, which drives the market growth for this segment in the global AI in sports market.

[REGIONGRAPH]

By region, North America dominated the market share in 2022 for the artificial intelligence in sports market analysis. The presence of prominent players such as Microsoft Corporation, IBM Corporation and others is positively influencing the growth of artificial intelligence in sports market in this region. However, Asia-Pacific is expected to exhibit the highest growth during the forecast period. This is attributed to the increase in integration of digital technologies and higher adoption of advanced technology, which is expected to provide lucrative growth opportunities for the market in this region. 

Top Impacting Factors  

Increase in Demand for Monitoring and Tracking Data of Players                

Emerging technologies such as AI, big data, and IoT, are becoming essential components of sport in recent years, and are being used on a regular basis, especially in team sports for various applications such as monitoring movement patterns, which reveal important results regarding sport performance. In addition, AI analytics helps to quantify these results and the dynamic profile of players using global positioning systems (GPS). These devices have been defined as a valid tool for evaluating the external load in intermittent sports, with capacity to record real-time data about time, speed, distance, position, altitude, and direction, which make them common in the analysis of team sports.

Furthermore, the technology of a multiple-camera match analysis system, implemented in almost all European professional leagues and international competitions, has been demonstrated to be as reliable as GPS; it can obtain results in quantification with less than 5% of error, and has been proven valid for investigation. Thus, the increase in use of these systems for physical and tactical performance studies in different elite competitions drives the growth of the global market. Therefore, artificial intelligence in sports gained wider traction among end-users, which in turn, is expected to fuel robust market growth.   

Lack of Trained & Skilled Professionals        

The major challenge for the growth of global artificial intelligence in sports market is the limitation of skilled labor and knowledge of AI infrastructure. Smart AI devices consist of complex installation and connectivity management, which requires knowledge and decision-making skills. The increasing dearth of sophisticated abilities and a growing lack of awareness of digital technology is certainly restraining the adoption of artificial intelligence in sports across the globe. Further, the integration of highly sophisticated technologies and components to provide efficient, reliable, and safe services is expected to propel the global market growth.

However, these sophisticated technologies and equipment include difficult design, development, and implementation of digitalized systems, which is expected to be the major restraining factor for the growth of the global market. In addition, these technically advanced systems entail a combination of electronic components and several subsystems to offer real-time data. However, individuals with limited skillsets and software knowledge in installing and developing such complex infrastructure are expected to be the major obstacles to this market growth across the globe. Therefore, a lack of skilled labor and management is required for the installation and development of digital technologies in AI devices and thus, is projected to hamper to this the market growth across the globe.    

Upsurge in Demand for AI to Make Future Predictions          

Advancements in the field of predictive analytics have led to the creation of predictive models that can compute probabilities of sports win/loss prospects and analyze the performance of players. AI is projected to increase the competitiveness in sports by a huge margin. With better sensors and algorithms, it will make better predictions of outcomes of competitions. AI is expected to impact advertisers, sports companies, franchise owners, coaches, as well as game strategists by helping target population and using contextual advertising and behavioral targeting to get the right advertisements in front of the right people. With such a wide scope of implementation, it is expected that the sports industry will adopt AI to gain a competitive edge over sports industry rivals.    

Moreover, predictive analytics is being used for evaluating athletes, as it is crucial to look at how the player is performing in different phases. This is further used to determine the success of the athlete in sports depending on the player's skill and is associated with the team and nation of the athlete. These factors are encouraging many businesses to enhance their product portfolio in the global market. For instance, in December 2023, Humane launched AI Pin with unique artificial intelligence features. Ai Pin is a wearable gadget activated by voice command, conveying information to the user through its AI chatbot. Therefore, an increase in applications of predictive analytics is expected to provide lucrative opportunity for the growth of the AI in sports industry market.     

Competition Analysis: 

Competitive analysis and profiles of the major players in the artificial intelligence in sports market are Catapult Group International Ltd., Facebook Inc., IBM Corporation, Microsoft Corporation, Salesforce.com Inc., SAP SE, SAS Institute Inc., Sportradar AG, Stats Perform, and Trumedia Networks. These major players have adopted various key development strategies such as business expansion, new product launches, and partnerships, which help to drive the growth of AI in sports market size globally. 

Recent Developments in Artificial intelligence in Sports Market

Recent Partnerships in the Market: 

For instance, in December 2023, BeONE Sports partnered with MobiDev, to launch an AI-powered comparative training platform. The innovative solution leverages cutting-edge human pose estimation technology to elevate athlete performance. Athletes use this platform to receive real-time feedback and personalized training insights. Similar strategies by the market players operating at a global and regional level are expected to help the market to witness significant growth during the forecast period.   

Recent Product Launches in the Market: 

For instance, in August 20 23, LootMogul launched MogulX.ai, to drive collaboration and AI development in the sports tech industry. Therefore, such strategies adopted by market players are increasing market competition and leading the growth of AI in sports market size.     

Market Landscape and Trends  

The outbreak of COVID-19 is anticipated to have a positive impact on the growth of artificial intelligence in sports market. This is attributed to fans experiencing the future of virtual contact sports firsthand—and some are embracing it. In addition, the sports event organized on the stadiums usually have highly charged tickets, which, in turn, boosted the adoption of virtual monitoring, as it delivers optimal experience that maximizes user satisfaction. Moreover, to enabling real-time streaming of sporting events without the need for a camera operator, AI-powered equipment is also capable of producing statistical models, tactical analysis, and prediction analytics that can help coaches maximize their players' potential.

On the other hand, the pandemic has expanded the reception of remote helpers and chatbots as organizations endeavor to give contactless client care and backing. For instance, in May 2021, Veritone launched a new platform namely, marvel.AI, it which enables creators, media figures, and others to generate deep fake clones of synthetic voices. These factors are expected to have a less negative impact on the growth of the global artificial intelligence in sports market in the pandemic.       

Key Benefits for Stakeholders  

  • This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the artificial intelligence in sports market forecast from 2022 to 2032 to identify the prevailing market opportunities. 

  • Market research is offered along with information related to key drivers, restraints, and opportunities of artificial intelligence in sports market outlook. 

  • Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders to make profit-oriented business decisions and strengthen their supplier-buyer network. 

  • In-depth analysis of the artificial intelligence in sports market segmentation assists in determining the prevailing AI in sports industry opportunity. 

  • Major countries in each region are mapped according to their revenue contribution to the global market. 

  • Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players. 

  • The report includes an analysis of the regional as well as global artificial intelligence in sports market trends, key players, market segments, application areas, and market growth strategies. 

Key Market Segments

  • By Component
    • Software
    • Service
  • By Deployment Model
    • On-premise
    • Cloud
  • By Technology
    • Machine Learning
    • Natural Language Processing
    • Computer Vision
    • Data Analytics
    • Others
  • By Application
    • Game Planning
    • Game Strategies
    • Performance Improvement
    • Injury Prevention
    • Sports Recruitment
    • Others
  • By Game Type
    • Football
    • Cricket
    • Tennis
    • Basketball
    • Baseball
    • Others
  • By Region
    • North America
      • U.S.
      • Canada
    • Europe
      • UK
      • Germany
      • France
      • Italy
      • Spain
      • Rest of Europe
    • Asia-Pacific
      • China
      • Japan
      • India
      • Australia
      • South Korea
      • Rest of Asia-Pacific
    • LAMEA
      • Latin America
      • Middle East
      • Africa


Key Market Players

  • Sportradar AG
  • Stats Perform
  • Microsoft Corporation
  • SAS Institute Inc
  • IBM Corporation
  • Salesforce.com Inc.
  • TruMedia Networks
  • SAP SE
  • Catapult Group International Limited.
  • Meta Platforms, Inc.
  • CHAPTER 1: INTRODUCTION

    • 1.1. Report description

    • 1.2. Key market segments

    • 1.3. Key benefits to the stakeholders

    • 1.4. Research methodology

      • 1.4.1. Primary research

      • 1.4.2. Secondary research

      • 1.4.3. Analyst tools and models

  • CHAPTER 2: EXECUTIVE SUMMARY

    • 2.1. CXO Perspective

  • CHAPTER 3: MARKET OVERVIEW

    • 3.1. Market definition and scope

    • 3.2. Key findings

      • 3.2.1. Top impacting factors

      • 3.2.2. Top investment pockets

    • 3.3. Porter’s five forces analysis

      • 3.3.1. Low bargaining power of suppliers

      • 3.3.2. Low threat of new entrants

      • 3.3.3. Low threat of substitutes

      • 3.3.4. Low intensity of rivalry

      • 3.3.5. Low bargaining power of buyers

    • 3.4. Market dynamics

      • 3.4.1. Drivers

        • 3.4.1.1. Increase in demand for monitoring and tracking data of players
        • 3.4.1.2. Surge in demand for chatbots and virtual assistants to interact with followers
        • 3.4.1.3. Rise in demand for real-time data analytics
      • 3.4.2. Restraints

        • 3.4.2.1. Lack of trained & skilled professionals
        • 3.4.2.2. High implementation and maintenance cost 
      • 3.4.3. Opportunities

        • 3.4.3.1. Upsurge in demand for AI to make future predictions
  • CHAPTER 4: ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY COMPONENT

    • 4.1. Overview

      • 4.1.1. Market size and forecast

    • 4.2. Software

      • 4.2.1. Key market trends, growth factors and opportunities

      • 4.2.2. Market size and forecast, by region

      • 4.2.3. Market share analysis by country

    • 4.3. Service

      • 4.3.1. Key market trends, growth factors and opportunities

      • 4.3.2. Market size and forecast, by region

      • 4.3.3. Market share analysis by country

  • CHAPTER 5: ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY DEPLOYMENT MODEL

    • 5.1. Overview

      • 5.1.1. Market size and forecast

    • 5.2. On-premise

      • 5.2.1. Key market trends, growth factors and opportunities

      • 5.2.2. Market size and forecast, by region

      • 5.2.3. Market share analysis by country

    • 5.3. Cloud

      • 5.3.1. Key market trends, growth factors and opportunities

      • 5.3.2. Market size and forecast, by region

      • 5.3.3. Market share analysis by country

  • CHAPTER 6: ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY TECHNOLOGY

    • 6.1. Overview

      • 6.1.1. Market size and forecast

    • 6.2. Machine Learning

      • 6.2.1. Key market trends, growth factors and opportunities

      • 6.2.2. Market size and forecast, by region

      • 6.2.3. Market share analysis by country

    • 6.3. Natural Language Processing

      • 6.3.1. Key market trends, growth factors and opportunities

      • 6.3.2. Market size and forecast, by region

      • 6.3.3. Market share analysis by country

    • 6.4. Computer Vision

      • 6.4.1. Key market trends, growth factors and opportunities

      • 6.4.2. Market size and forecast, by region

      • 6.4.3. Market share analysis by country

    • 6.5. Data Analytics

      • 6.5.1. Key market trends, growth factors and opportunities

      • 6.5.2. Market size and forecast, by region

      • 6.5.3. Market share analysis by country

    • 6.6. Others

      • 6.6.1. Key market trends, growth factors and opportunities

      • 6.6.2. Market size and forecast, by region

      • 6.6.3. Market share analysis by country

  • CHAPTER 7: ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY APPLICATION

    • 7.1. Overview

      • 7.1.1. Market size and forecast

    • 7.2. Game Planning

      • 7.2.1. Key market trends, growth factors and opportunities

      • 7.2.2. Market size and forecast, by region

      • 7.2.3. Market share analysis by country

    • 7.3. Game Strategies

      • 7.3.1. Key market trends, growth factors and opportunities

      • 7.3.2. Market size and forecast, by region

      • 7.3.3. Market share analysis by country

    • 7.4. Performance Improvement

      • 7.4.1. Key market trends, growth factors and opportunities

      • 7.4.2. Market size and forecast, by region

      • 7.4.3. Market share analysis by country

    • 7.5. Injury Prevention

      • 7.5.1. Key market trends, growth factors and opportunities

      • 7.5.2. Market size and forecast, by region

      • 7.5.3. Market share analysis by country

    • 7.6. Sports Recruitment

      • 7.6.1. Key market trends, growth factors and opportunities

      • 7.6.2. Market size and forecast, by region

      • 7.6.3. Market share analysis by country

    • 7.7. Others

      • 7.7.1. Key market trends, growth factors and opportunities

      • 7.7.2. Market size and forecast, by region

      • 7.7.3. Market share analysis by country

  • CHAPTER 8: ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY GAME TYPE

    • 8.1. Overview

      • 8.1.1. Market size and forecast

    • 8.2. Football

      • 8.2.1. Key market trends, growth factors and opportunities

      • 8.2.2. Market size and forecast, by region

      • 8.2.3. Market share analysis by country

    • 8.3. Cricket

      • 8.3.1. Key market trends, growth factors and opportunities

      • 8.3.2. Market size and forecast, by region

      • 8.3.3. Market share analysis by country

    • 8.4. Tennis

      • 8.4.1. Key market trends, growth factors and opportunities

      • 8.4.2. Market size and forecast, by region

      • 8.4.3. Market share analysis by country

    • 8.5. Basketball

      • 8.5.1. Key market trends, growth factors and opportunities

      • 8.5.2. Market size and forecast, by region

      • 8.5.3. Market share analysis by country

    • 8.6. Baseball

      • 8.6.1. Key market trends, growth factors and opportunities

      • 8.6.2. Market size and forecast, by region

      • 8.6.3. Market share analysis by country

    • 8.7. Others

      • 8.7.1. Key market trends, growth factors and opportunities

      • 8.7.2. Market size and forecast, by region

      • 8.7.3. Market share analysis by country

  • CHAPTER 9: ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY REGION

    • 9.1. Overview

      • 9.1.1. Market size and forecast By Region

    • 9.2. North America

      • 9.2.1. Key market trends, growth factors and opportunities

      • 9.2.2. Market size and forecast, by Component

      • 9.2.3. Market size and forecast, by Deployment Model

      • 9.2.4. Market size and forecast, by Technology

      • 9.2.5. Market size and forecast, by Application

      • 9.2.6. Market size and forecast, by Game Type

      • 9.2.7. Market size and forecast, by country

        • 9.2.7.1. U.S.
          • 9.2.7.1.1. Market size and forecast, by Component
          • 9.2.7.1.2. Market size and forecast, by Deployment Model
          • 9.2.7.1.3. Market size and forecast, by Technology
          • 9.2.7.1.4. Market size and forecast, by Application
          • 9.2.7.1.5. Market size and forecast, by Game Type
        • 9.2.7.2. Canada
          • 9.2.7.2.1. Market size and forecast, by Component
          • 9.2.7.2.2. Market size and forecast, by Deployment Model
          • 9.2.7.2.3. Market size and forecast, by Technology
          • 9.2.7.2.4. Market size and forecast, by Application
          • 9.2.7.2.5. Market size and forecast, by Game Type
    • 9.3. Europe

      • 9.3.1. Key market trends, growth factors and opportunities

      • 9.3.2. Market size and forecast, by Component

      • 9.3.3. Market size and forecast, by Deployment Model

      • 9.3.4. Market size and forecast, by Technology

      • 9.3.5. Market size and forecast, by Application

      • 9.3.6. Market size and forecast, by Game Type

      • 9.3.7. Market size and forecast, by country

        • 9.3.7.1. UK
          • 9.3.7.1.1. Market size and forecast, by Component
          • 9.3.7.1.2. Market size and forecast, by Deployment Model
          • 9.3.7.1.3. Market size and forecast, by Technology
          • 9.3.7.1.4. Market size and forecast, by Application
          • 9.3.7.1.5. Market size and forecast, by Game Type
        • 9.3.7.2. Germany
          • 9.3.7.2.1. Market size and forecast, by Component
          • 9.3.7.2.2. Market size and forecast, by Deployment Model
          • 9.3.7.2.3. Market size and forecast, by Technology
          • 9.3.7.2.4. Market size and forecast, by Application
          • 9.3.7.2.5. Market size and forecast, by Game Type
        • 9.3.7.3. France
          • 9.3.7.3.1. Market size and forecast, by Component
          • 9.3.7.3.2. Market size and forecast, by Deployment Model
          • 9.3.7.3.3. Market size and forecast, by Technology
          • 9.3.7.3.4. Market size and forecast, by Application
          • 9.3.7.3.5. Market size and forecast, by Game Type
        • 9.3.7.4. Italy
          • 9.3.7.4.1. Market size and forecast, by Component
          • 9.3.7.4.2. Market size and forecast, by Deployment Model
          • 9.3.7.4.3. Market size and forecast, by Technology
          • 9.3.7.4.4. Market size and forecast, by Application
          • 9.3.7.4.5. Market size and forecast, by Game Type
        • 9.3.7.5. Spain
          • 9.3.7.5.1. Market size and forecast, by Component
          • 9.3.7.5.2. Market size and forecast, by Deployment Model
          • 9.3.7.5.3. Market size and forecast, by Technology
          • 9.3.7.5.4. Market size and forecast, by Application
          • 9.3.7.5.5. Market size and forecast, by Game Type
        • 9.3.7.6. Rest of Europe
          • 9.3.7.6.1. Market size and forecast, by Component
          • 9.3.7.6.2. Market size and forecast, by Deployment Model
          • 9.3.7.6.3. Market size and forecast, by Technology
          • 9.3.7.6.4. Market size and forecast, by Application
          • 9.3.7.6.5. Market size and forecast, by Game Type
    • 9.4. Asia-Pacific

      • 9.4.1. Key market trends, growth factors and opportunities

      • 9.4.2. Market size and forecast, by Component

      • 9.4.3. Market size and forecast, by Deployment Model

      • 9.4.4. Market size and forecast, by Technology

      • 9.4.5. Market size and forecast, by Application

      • 9.4.6. Market size and forecast, by Game Type

      • 9.4.7. Market size and forecast, by country

        • 9.4.7.1. China
          • 9.4.7.1.1. Market size and forecast, by Component
          • 9.4.7.1.2. Market size and forecast, by Deployment Model
          • 9.4.7.1.3. Market size and forecast, by Technology
          • 9.4.7.1.4. Market size and forecast, by Application
          • 9.4.7.1.5. Market size and forecast, by Game Type
        • 9.4.7.2. Japan
          • 9.4.7.2.1. Market size and forecast, by Component
          • 9.4.7.2.2. Market size and forecast, by Deployment Model
          • 9.4.7.2.3. Market size and forecast, by Technology
          • 9.4.7.2.4. Market size and forecast, by Application
          • 9.4.7.2.5. Market size and forecast, by Game Type
        • 9.4.7.3. India
          • 9.4.7.3.1. Market size and forecast, by Component
          • 9.4.7.3.2. Market size and forecast, by Deployment Model
          • 9.4.7.3.3. Market size and forecast, by Technology
          • 9.4.7.3.4. Market size and forecast, by Application
          • 9.4.7.3.5. Market size and forecast, by Game Type
        • 9.4.7.4. Australia
          • 9.4.7.4.1. Market size and forecast, by Component
          • 9.4.7.4.2. Market size and forecast, by Deployment Model
          • 9.4.7.4.3. Market size and forecast, by Technology
          • 9.4.7.4.4. Market size and forecast, by Application
          • 9.4.7.4.5. Market size and forecast, by Game Type
        • 9.4.7.5. South Korea
          • 9.4.7.5.1. Market size and forecast, by Component
          • 9.4.7.5.2. Market size and forecast, by Deployment Model
          • 9.4.7.5.3. Market size and forecast, by Technology
          • 9.4.7.5.4. Market size and forecast, by Application
          • 9.4.7.5.5. Market size and forecast, by Game Type
        • 9.4.7.6. Rest of Asia-Pacific
          • 9.4.7.6.1. Market size and forecast, by Component
          • 9.4.7.6.2. Market size and forecast, by Deployment Model
          • 9.4.7.6.3. Market size and forecast, by Technology
          • 9.4.7.6.4. Market size and forecast, by Application
          • 9.4.7.6.5. Market size and forecast, by Game Type
    • 9.5. LAMEA

      • 9.5.1. Key market trends, growth factors and opportunities

      • 9.5.2. Market size and forecast, by Component

      • 9.5.3. Market size and forecast, by Deployment Model

      • 9.5.4. Market size and forecast, by Technology

      • 9.5.5. Market size and forecast, by Application

      • 9.5.6. Market size and forecast, by Game Type

      • 9.5.7. Market size and forecast, by country

        • 9.5.7.1. Latin America
          • 9.5.7.1.1. Market size and forecast, by Component
          • 9.5.7.1.2. Market size and forecast, by Deployment Model
          • 9.5.7.1.3. Market size and forecast, by Technology
          • 9.5.7.1.4. Market size and forecast, by Application
          • 9.5.7.1.5. Market size and forecast, by Game Type
        • 9.5.7.2. Middle East
          • 9.5.7.2.1. Market size and forecast, by Component
          • 9.5.7.2.2. Market size and forecast, by Deployment Model
          • 9.5.7.2.3. Market size and forecast, by Technology
          • 9.5.7.2.4. Market size and forecast, by Application
          • 9.5.7.2.5. Market size and forecast, by Game Type
        • 9.5.7.3. Africa
          • 9.5.7.3.1. Market size and forecast, by Component
          • 9.5.7.3.2. Market size and forecast, by Deployment Model
          • 9.5.7.3.3. Market size and forecast, by Technology
          • 9.5.7.3.4. Market size and forecast, by Application
          • 9.5.7.3.5. Market size and forecast, by Game Type
  • CHAPTER 10: COMPETITIVE LANDSCAPE

    • 10.1. Introduction

    • 10.2. Top winning strategies

    • 10.3. Product mapping of top 10 player

    • 10.4. Competitive dashboard

    • 10.5. Competitive heatmap

    • 10.6. Top player positioning, 2022

  • CHAPTER 11: COMPANY PROFILES

    • 11.1. Catapult Group International Limited.

      • 11.1.1. Company overview

      • 11.1.2. Key executives

      • 11.1.3. Company snapshot

      • 11.1.4. Operating business segments

      • 11.1.5. Product portfolio

      • 11.1.6. Business performance

      • 11.1.7. Key strategic moves and developments

    • 11.2. Meta Platforms, Inc.

      • 11.2.1. Company overview

      • 11.2.2. Key executives

      • 11.2.3. Company snapshot

      • 11.2.4. Operating business segments

      • 11.2.5. Product portfolio

      • 11.2.6. Business performance

      • 11.2.7. Key strategic moves and developments

    • 11.3. IBM Corporation

      • 11.3.1. Company overview

      • 11.3.2. Key executives

      • 11.3.3. Company snapshot

      • 11.3.4. Operating business segments

      • 11.3.5. Product portfolio

      • 11.3.6. Business performance

      • 11.3.7. Key strategic moves and developments

    • 11.4. Microsoft Corporation

      • 11.4.1. Company overview

      • 11.4.2. Key executives

      • 11.4.3. Company snapshot

      • 11.4.4. Operating business segments

      • 11.4.5. Product portfolio

      • 11.4.6. Business performance

      • 11.4.7. Key strategic moves and developments

    • 11.5. Salesforce.com Inc.

      • 11.5.1. Company overview

      • 11.5.2. Key executives

      • 11.5.3. Company snapshot

      • 11.5.4. Operating business segments

      • 11.5.5. Product portfolio

      • 11.5.6. Business performance

      • 11.5.7. Key strategic moves and developments

    • 11.6. SAP SE

      • 11.6.1. Company overview

      • 11.6.2. Key executives

      • 11.6.3. Company snapshot

      • 11.6.4. Operating business segments

      • 11.6.5. Product portfolio

      • 11.6.6. Business performance

    • 11.7. SAS Institute Inc

      • 11.7.1. Company overview

      • 11.7.2. Key executives

      • 11.7.3. Company snapshot

      • 11.7.4. Operating business segments

      • 11.7.5. Product portfolio

      • 11.7.6. Key strategic moves and developments

    • 11.8. Sportradar AG

      • 11.8.1. Company overview

      • 11.8.2. Key executives

      • 11.8.3. Company snapshot

      • 11.8.4. Operating business segments

      • 11.8.5. Product portfolio

      • 11.8.6. Business performance

      • 11.8.7. Key strategic moves and developments

    • 11.9. Stats Perform

      • 11.9.1. Company overview

      • 11.9.2. Key executives

      • 11.9.3. Company snapshot

      • 11.9.4. Operating business segments

      • 11.9.5. Product portfolio

      • 11.9.6. Key strategic moves and developments

    • 11.10. TruMedia Networks

      • 11.10.1. Company overview

      • 11.10.2. Key executives

      • 11.10.3. Company snapshot

      • 11.10.4. Operating business segments

      • 11.10.5. Product portfolio

      • 11.10.6. Key strategic moves and developments

  • LIST OF FIGURES

  • FIGURE 01. ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032
    FIGURE 02. SEGMENTATION OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET,2022-2032
    FIGURE 03. TOP IMPACTING FACTORS IN ARTIFICIAL INTELLIGENCE IN SPORTS MARKET (2022 TO 2032)
    FIGURE 04. TOP INVESTMENT POCKETS IN ARTIFICIAL INTELLIGENCE IN SPORTS MARKET (2023-2032)
    FIGURE 05. LOW BARGAINING POWER OF SUPPLIERS
    FIGURE 06. LOW THREAT OF NEW ENTRANTS
    FIGURE 07. LOW THREAT OF SUBSTITUTES
    FIGURE 08. LOW INTENSITY OF RIVALRY
    FIGURE 09. LOW BARGAINING POWER OF BUYERS
    FIGURE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN SPORTS MARKET:DRIVERS, RESTRAINTS AND OPPORTUNITIES
    FIGURE 11. ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY COMPONENT, 2022 AND 2032(%)
    FIGURE 12. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR SOFTWARE, BY COUNTRY 2022 AND 2032(%)
    FIGURE 13. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR SERVICE, BY COUNTRY 2022 AND 2032(%)
    FIGURE 14. ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY DEPLOYMENT MODEL, 2022 AND 2032(%)
    FIGURE 15. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR ON-PREMISE, BY COUNTRY 2022 AND 2032(%)
    FIGURE 16. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR CLOUD, BY COUNTRY 2022 AND 2032(%)
    FIGURE 17. ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY TECHNOLOGY, 2022 AND 2032(%)
    FIGURE 18. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR MACHINE LEARNING, BY COUNTRY 2022 AND 2032(%)
    FIGURE 19. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR NATURAL LANGUAGE PROCESSING, BY COUNTRY 2022 AND 2032(%)
    FIGURE 20. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR COMPUTER VISION, BY COUNTRY 2022 AND 2032(%)
    FIGURE 21. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR DATA ANALYTICS, BY COUNTRY 2022 AND 2032(%)
    FIGURE 22. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR OTHERS, BY COUNTRY 2022 AND 2032(%)
    FIGURE 23. ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY APPLICATION, 2022 AND 2032(%)
    FIGURE 24. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR GAME PLANNING, BY COUNTRY 2022 AND 2032(%)
    FIGURE 25. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR GAME STRATEGIES, BY COUNTRY 2022 AND 2032(%)
    FIGURE 26. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR PERFORMANCE IMPROVEMENT, BY COUNTRY 2022 AND 2032(%)
    FIGURE 27. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR INJURY PREVENTION, BY COUNTRY 2022 AND 2032(%)
    FIGURE 28. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR SPORTS RECRUITMENT, BY COUNTRY 2022 AND 2032(%)
    FIGURE 29. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR OTHERS, BY COUNTRY 2022 AND 2032(%)
    FIGURE 30. ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, BY GAME TYPE, 2022 AND 2032(%)
    FIGURE 31. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR FOOTBALL, BY COUNTRY 2022 AND 2032(%)
    FIGURE 32. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR CRICKET, BY COUNTRY 2022 AND 2032(%)
    FIGURE 33. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR TENNIS, BY COUNTRY 2022 AND 2032(%)
    FIGURE 34. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR BASKETBALL, BY COUNTRY 2022 AND 2032(%)
    FIGURE 35. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR BASEBALL, BY COUNTRY 2022 AND 2032(%)
    FIGURE 36. COMPARATIVE SHARE ANALYSIS OF ARTIFICIAL INTELLIGENCE IN SPORTS MARKET FOR OTHERS, BY COUNTRY 2022 AND 2032(%)
    FIGURE 37. ARTIFICIAL INTELLIGENCE IN SPORTS MARKET BY REGION, 2022 AND 2032(%)
    FIGURE 38. U.S. ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 39. CANADA ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 40. UK ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 41. GERMANY ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 42. FRANCE ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 43. ITALY ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 44. SPAIN ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 45. REST OF EUROPE ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 46. CHINA ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 47. JAPAN ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 48. INDIA ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 49. AUSTRALIA ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 50. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 51. REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 52. LATIN AMERICA ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 53. MIDDLE EAST ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 54. AFRICA ARTIFICIAL INTELLIGENCE IN SPORTS MARKET, 2022-2032 ($MILLION)
    FIGURE 55. TOP WINNING STRATEGIES, BY YEAR (2020-2023)
    FIGURE 56. TOP WINNING STRATEGIES, BY DEVELOPMENT (2020-2023)
    FIGURE 57. TOP WINNING STRATEGIES, BY COMPANY (2020-2023)
    FIGURE 58. PRODUCT MAPPING OF TOP 10 PLAYERS
    FIGURE 59. COMPETITIVE DASHBOARD
    FIGURE 60. COMPETITIVE HEATMAP: ARTIFICIAL INTELLIGENCE IN SPORTS MARKET
    FIGURE 61. TOP PLAYER POSITIONING, 2022
    FIGURE 62. META PLATFORMS, INC.: NET REVENUE, 2020-2022 ($MILLION)
    FIGURE 63. META PLATFORMS, INC.: RESEARCH & DEVELOPMENT EXPENDITURE, 2020-2022 ($MILLION)
    FIGURE 64. META PLATFORMS, INC.: REVENUE SHARE BY REGION, 2022 (%)
    FIGURE 65. META PLATFORMS, INC.: REVENUE SHARE BY SEGMENT, 2022 (%)
    FIGURE 66. IBM CORPORATION: NET REVENUE, 2020-2022 ($MILLION)
    FIGURE 67. IBM CORPORATION: RESEARCH & DEVELOPMENT EXPENDITURE, 2020-2022 ($MILLION)
    FIGURE 68. IBM CORPORATION: REVENUE SHARE BY SEGMENT, 2022 (%)
    FIGURE 69. IBM CORPORATION: REVENUE SHARE BY REGION, 2022 (%)
    FIGURE 70. MICROSOFT CORPORATION: NET REVENUE, 2021-2023 ($MILLION)
    FIGURE 71. MICROSOFT CORPORATION: RESEARCH & DEVELOPMENT EXPENDITURE, 2021-2023 ($MILLION)
    FIGURE 72. MICROSOFT CORPORATION: REVENUE SHARE BY SEGMENT, 2023 (%)
    FIGURE 73. MICROSOFT CORPORATION: REVENUE SHARE BY REGION, 2023 (%)
    FIGURE 74. SALESFORCE.COM INC.: NET REVENUE, 2021-2023 ($MILLION)
    FIGURE 75. SALESFORCE.COM INC.: RESEARCH & DEVELOPMENT EXPENDITURE, 2021-2023 ($MILLION)
    FIGURE 76. SALESFORCE.COM INC.: REVENUE SHARE BY SEGMENT, 2023 (%)
    FIGURE 77. SALESFORCE.COM INC.: REVENUE SHARE BY REGION, 2023 (%)
    FIGURE 78. SAP SE: NET REVENUE, 2020-2022 ($MILLION)
    FIGURE 79. SAP SE: RESEARCH & DEVELOPMENT EXPENDITURE, 2020-2022 ($MILLION)
    FIGURE 80. SAP SE: REVENUE SHARE BY SEGMENT, 2022 (%)
    FIGURE 81. SAP SE: REVENUE SHARE BY REGION, 2022 (%)
    FIGURE 82. SPORTRADAR AG: NET REVENUE, 2020-2022 ($MILLION)
    FIGURE 83. SPORTRADAR AG: REVENUE SHARE BY SEGMENT, 2022 (%)
    FIGURE 84. SPORTRADAR AG: REVENUE SHARE BY REGION, 2022 (%)

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