AI in Sports Market

Report Code TC 9249
Published in Nov, 2024, By MarketsandMarkets™
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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

 

AI in Sports Market Overview

The AI in Sports Market is projected to grow from 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. The AI in Sports market is revolutionizing the way sports are played, managed, and experienced by integrating advanced technologies like generative AI and predictive analytics. AI-powered performance analytics is transforming athlete monitoring and game strategies, enabling teams to optimize coaching techniques and improve player performance. For example, AI-based tools are being used to monitor players' fitness levels, analyze their in-game movements, and recommend tailored training regimes. Generative AI is further enhancing fan experiences by enabling personalized interactions through tools like virtual replays, augmented reality (AR), and immersive virtual tours, making sports events more engaging and interactive.

In team sports, AI is driving innovations such as predictive modeling to craft winning strategies, while in e-sports, AI solutions analyze gameplay, providing real-time feedback to players. A prominent example is OpenAI's bots competing against professional gamers, showcasing AI's potential to advance skill development. AI is also reshaping broadcasting with tools that enhance content delivery and provide real-time analytics, as seen in IBM’s collaboration with UFC to offer personalized fan experiences and detailed insights.

The adoption of AI by sports associations, teams, and media entities ensures a more streamlined operation, better crowd management, and enhanced fan engagement. Advanced systems like AWS’s AI-driven football analytics for the Bundesliga highlight how AI is becoming indispensable in sports. By enabling smarter decision-making, improving athlete performance, and creating immersive fan experiences, AI is driving a paradigm shift in the sports industry, seamlessly blending technology with tradition.

AI in Sports Market

Attractive Opportunities in the AI in Sports Market

ASIA PACIFIC

The growing adoption of advanced analytics, increasing investments in sports technology, rising popularity of eSports, and the expanding use of AI for fan engagement and performance optimization drive the AI in Sports market in Asia Pacific.

The Asia Pacific region is witnessing rapid growth in the AI in Sports market due to the expanding adoption of AI-powered tools for sports analytics, enhanced broadcasting experiences, and the growing emphasis on enhancing athlete performance and fan engagement through technology.

Partnerships, collaborations, and strategic acquisitions are likely to be the key growth strategies adopted by players in the AI in Sports Market.

The growing market can be attributed to the increasing demand for data-driven insights, advancements in machine learning algorithms, and the rising popularity of AI-powered solutions for player performance, injury prevention, and fan engagement.

The Asia-Pacific AI in Sports market is expected to be worth USD 0.70 billion by 2030, growing at CAGR of 21.1% during the forecast period.

Impact of AI on AI in Sports Market

Generative AI is transforming the AI in sports market through various applications that improve performance, fan engagement, and operational efficiency. In Player Performance Analysis, AI systems process athlete data in real-time to optimize training, enhance performance, and reduce injuries. Fan Engagement is improved by providing personalized content and interactive experiences, as demonstrated by sports leagues offering tailored fan interactions. Injury Prevention & Rehabilitation uses AI to predict injuries and optimize recovery plans by analyzing player health data, enabling timely interventions.

AI also supports Team Strategy & Game Tactics by evaluating team and opponent performance, assisting coaches in making informed decisions. Broadcasting & Content Personalization customizes content delivery to viewer preferences, enhancing the viewing experience. In Sponsorship & Marketing Analytics, AI evaluates campaign effectiveness and fan sentiment, improving marketing strategies. Virtual Environment Training uses AI-driven virtual reality systems to simulate real-game scenarios, enabling athletes to practice strategies and skills in immersive and controlled environments. Finally, Ticketing & Pricing Optimization applies AI to adjust ticket prices based on demand and player performance, maximizing revenue.

AI in Sports Market Impact

Global AI in Sports Market Dynamics

Driver: Growth of AI in Sports is Being Driven by the Increasing Availability of Data

The growth of AI in sports is largely fueled by the increasing availability of data. With advancements in technology, large volumes of data are now accessible through various channels, such as wearable devices, performance tracking systems, and fan engagement platforms. This data provides teams and organizations with valuable insights that can enhance player performance, refine strategies, and predict injuries. For instance, the NBA (National Basketball Association) leverages player tracking systems to assess movement and performance, while wearable devices like those from Catapult Sports monitor players' health metrics to guide training and injury prevention. As the volume of data continues to expand, AI systems are becoming more precise, enhancing decision-making and operational efficiency.

Restraint: High Cost of Implementing AI Solutions in Sports is Restricting Their Adoption

One major restraint to the widespread adoption of AI in sports is the high cost associated with implementing and maintaining these systems. AI-driven solutions, including injury prediction models and performance optimization tools, often require substantial investments in technology infrastructure, specialized software, and hardware. Additionally, the need for skilled professionals to manage these systems increases operational costs. For smaller organizations or those with limited resources, these financial burdens can be prohibitive. Consequently, the cost of adoption remains a significant barrier for many sports organizations, limiting their ability to integrate AI technologies effectively.

 

Opportunity: Significant Opportunity for Expanding AI in Sports Training, Scouting, and Performance Enhancement

The integration of AI in sports presents a significant opportunity for growth, particularly in areas such as training, player performance optimization, and talent scouting. AI-driven tools can offer personalized insights that help coaches and teams refine training regimens tailored to individual players. Additionally, AI systems play a crucial role in scouting by assessing players’ potential and identifying the best team fits based on performance data. For example, AI platforms such as IBM’s Watsonx are used to evaluate players' statistics and match them with team needs. The opportunity for further growth lies in AI's ability to evolve continuously, providing deeper insights into player performance, predicting injury risks, and optimizing overall team strategies, which can be a game changer for sports organizations aiming to stay competitive.

Challenge: Shortage of Skilled Professionals is Hindering AI Integration in Sports

A key challenge in the integration of AI in sports is the shortage of professionals who have both technical expertise in AI and a deep understanding of sports. AI-driven systems, such as those used for performance tracking, injury prediction, and game strategy, require specialists who can navigate the complexities of both fields. However, there is a limited supply of professionals with this dual expertise, which can impede the implementation of AI technologies. This skill gap poses a significant challenge for sports organizations, making it difficult to realize the potential of AI tools fully. Bridging this gap is essential for the continued growth and innovation in AI-powered sports applications.

Global AI in Sports Market Ecosystem Analysis

The AI in Sports market ecosystem comprises various solutions and service providers along with various regulatory bodies. These companies have been operating in the market for several years and possess a diversified product portfolio and state-of-the-art technologies. Prominent companies in this 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).

Top Companies in AI in Sports Market
 

By Team Sports segment, Basketball is expected to have the largest market size during the forecast period.

Basketball is expected to dominate the AI in sports market by team sports during the forecast period due to its significant adoption of technology-driven strategies for performance enhancement, fan engagement, and game analytics. Professional leagues like the NBA are at the forefront of leveraging AI tools for various applications, including player performance tracking, injury prevention, and game strategy optimization.

For instance, the NBA has partnered with companies like Microsoft to use AI for real-time game analysis and creating personalized fan experiences through virtual and augmented reality. AI-driven motion tracking systems like Second Spectrum are widely used in basketball to analyze player movements, shooting accuracy, and defensive strategies, providing coaches with actionable insights.

Moreover, basketball teams extensively use predictive analytics to scout talent and enhance training regimens. For example, AI algorithms analyze player statistics and biometrics to predict potential injuries and recommend preventive measures. Similarly, AI-powered platforms, such as Homecourt, are revolutionizing player training by offering real-time feedback on shooting mechanics using smartphone cameras. The global popularity of basketball, combined with the sport’s fast-paced, data-intensive nature, makes it ideal for AI applications, contributing to its expected market leadership in this segment.

By Individual Sports segment, Racing is expected to hold a higher growth rate during the forecast period.

Racing is expected to hold the highest growth rate in the AI in sports market due to its increasing reliance on data analytics and AI-driven technologies to enhance performance, safety, and audience engagement. Advanced AI systems are transforming motorsports by enabling real-time telemetry analysis, predictive maintenance, and improved race strategies. For instance, Formula One (F1) leverages AI to process massive amounts of race data, optimizing tire management, weather predictions, and fuel efficiency, giving teams a competitive edge.

Additionally, AI-powered simulators have gained prominence in racing, offering drivers immersive training experiences and replicating real-world track conditions. National Association for Stock Car Auto Racing (NASCAR), for example, utilizes AI to predict race outcomes and optimize driver training programs. AI’s role in autonomous racing is also a significant contributor; competitions like Roborace are pushing the boundaries by using fully autonomous, AI-powered vehicles to showcase cutting-edge technology.

Furthermore, the adoption of AI in fan engagement strategies has enhanced the viewer experience. Platforms use AI for personalized content, predictive analytics for race outcomes, and real-time virtual overlays during broadcasts. This integration not only boosts fan interaction but also attracts sponsors and advertisers, contributing to the market’s growth. Racing’s dependence on AI to refine performance and amplify engagement positions it as a leader in this space.

Asia Pacific’s highest growth rate during the forecast period

The Asia Pacific region is expected to exhibit the highest growth rate in the AI in sports market during the forecast period due to the rapid adoption of advanced technologies across key countries such as China, India, and Japan. This growth is driven by increasing investments in sports infrastructure, the growing popularity of sports analytics, and the integration of AI-powered solutions for fan engagement, performance optimization, and game strategies. For instance, China’s focus on becoming a global sports powerhouse has led to initiatives such as the use of AI-driven video analytics to refine training programs for athletes. Similarly, in India, AI is being leveraged in cricket for player performance analysis and fan engagement platforms such as Dream11, which utilize predictive AI algorithms. Japan, with its strong technological foundation, employs AI in sports like baseball and soccer for tactical decision-making and injury prevention. The region also benefits from a large youth population and growing internet penetration, enabling faster adoption of AI-based sports applications. Companies such as Alibaba Cloud are introducing AI solutions for sports event management, exemplified during the 2022 Beijing Winter Olympics, where AI enhanced athlete monitoring and event efficiency. These factors collectively make Asia Pacific a high-growth region in the AI in sports market.

HIGHEST CAGR MARKET IN 2024
INDIA, FASTEST GROWING MARKET IN THE REGION
AI in Sports Market Size and Share

Recent Developments of AI in Sports Market

  • In November 2024, IBM partnered with UFC to launch AI-powered solutions, utilizing IBM Watson for real-time athlete performance analysis. This collaboration enhances fan engagement by providing personalized experiences, including tailored content and insights, aimed at improving both athlete training and overall fan interaction during UFC events.
  • In May 2024, Intel introduced AI solutions for the Paris 2024 Olympics to enhance athlete performance, optimize training, and boost fan engagement. The technology provides real-time performance data for coaches to improve training and reduce injuries, while offering personalized content and immersive experiences for fans.

Key Market Players

List of Top AI in Sports Market Companies

The AI in Sports Market is dominated by a few major players that have a wide regional presence.

  • Cisco (US)
  • IBM (US)
  • Intel (US)
  • Microsoft (US)
  • AWS (US)
  • SAP SE (Germany)
  • Ericsson (Sweden)
  • Oracle (US)
  • Stats erform (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)

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Scope of the Report

Report Attribute Details
Market size available for years 2019-2030
Base year considered 2024
Forecast period 2025–2030
Forecast units Value (USD) Million/Billion
Segments Covered By Offering, Technology, Sports Type, End User, and Region
Regions covered North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

 

Key Questions Addressed by the Report

What is the definition of the AI in Sports market?
Artificial Intelligence in Sport is defined as the use of artificial intelligence systems including machine learning, computer vision, natural language processing, predictive analytics, etc. within the sport’s business. Such activities include Performance analysis, Injury prevention, Training enhancement, Strategy development, and Fan engagement. AI makes use of sports data such as real-time performance metrics, biomechanics, and health information to derive actionable insights and make better decisions for better results.
Moreover, AI contributes significantly to sports live streaming, scouting, fan engagement, and even the back-end management of operations. It incites developments in ticketing, media production, advertisement, and sponsorship management, among others. Thus AI integration seeks to enhance sport performance and the business side of sporting activities.
What is the market size of the AI in Sports market?
The AI in Sports market is estimated at 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.
What are the major drivers in the AI in Sports market?
The major drivers in the AI in Sports market are Advancements in AI and ML, Increasing Data Availability, Rising Demand for Personalized Fan Experiences, Enhanced Athlete Performance and Injury Prevention, Investment in eSports.
Who are the key players operating in the AI in Sports market?
The key market players profiled 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), Sciports (Netherlands), Spiideo (Sweden), Sportlogiq (Canada), ChyronHego Corporation (US), TruMedia Networks (US).
What are the key technology trends prevailing in the AI in Sports market?
The key technology trends in enterprise networking include ML, Computer Vision, Natural Language Processing, Predictive Analytics, Sensor Technology, Augmented Reality (AR), Virtual Reality (VR), Data Analytics Platforms, Edge Computing, and Cloud Computing.

 

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Table of Contents

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TITLE
PAGE NO
INTRODUCTION
1
  • 1.1 OBJECTIVES OF THE STUDY
  • 1.2 MARKET DEFINITION
  • 1.3 MARKET SCOPE
    MARKET SEGMENTATION
    REGIONS COVERED
    INCLUSIONS AND EXCLUSIONS
    YEARS CONSIDERED
  • 1.4 CURRENCY CONSIDERED
  • 1.5 STAKEHOLDERS
RESEARCH METHODOLOGY
2
  • 2.1 RESEARCH DATA
    SECONDARY DATA
    - Secondary sources
    PRIMARY DATA
    - Primary interviews with experts
    - List of key primary interview participants
    - Breakdown of primaries
    - Primary sources
    - Key industry insights
  • 2.2 MARKET SIZE ESTIMATION
    BOTTOM-UP APPROACH
    TOP-DOWN APPROACH
  • 2.3 DATA TRIANGULATION
  • 2.4 RESEARCH ASSUMPTIONS
  • 2.5 RISK ASSESSMENT
  • 2.6 LIMITATIONS
EXECUTIVE SUMMARY
3
PREMIUM INSIGHTS
4
  • 4.1 ATTRACTIVE OPPORTUNITIES IN THE GLOBAL AI IN SPORTS MARKET
  • 4.2 MARKET, BY OFFERING
  • 4.3 MARKET, BY TYPE
  • 4.4 AI IN SPORTS MARKET, BY SPORTS TYPE
  • 4.5 MARKET, BY END USER
  • 4.6 NORTH AMERICA: AI IN SPORTS MARKET, BY TOP KEY OFFERING AND TYPE
MARKET OVERVIEW AND INDUSTRY TRENDS
5
  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    DRIVERS
    RESTRAINTS
    OPPORTUNITIES
    CHALLENGES
  • 5.3 BRIEF HISTORY OF AI IN SPORTS
  • 5.4 AI IN SPORTS MARKET: ECOSYSTEM ANALYSIS/MARKET MAP
  • 5.5 CASE STUDY ANALYSIS
  • 5.6 VALUE / SUPPLY CHAIN ANALYSIS
  • 5.7 TARIFF AND REGULATORY LANDSCAPE
    TARIFF DATA (HSCODE: 854231) - PROCESSORS AND CONTROLLERS
    REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    KEY REGULATIONS
  • 5.8 PRICING ANALYSIS
    AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY SOLUTION
    INDICATIVE PRICING ANALYSIS, BY TYPE
  • 5.9 TECHNOLOGY ANALYSIS
    KEY TECHNOLOGIES
    - MACHINE LEARNING & DEEP LEARNING
    - COMPUTER VISION
    - NATURAL LANGUAGE PROCESSING (NLP)
    - PREDICTIVE ANALYTICS
    - ROBOTIC PROCESS AUTOMATION (RPA)
    COMPLEMENTARY TECHNOLOGIES
    - AUGMENTED REALITY (AR)/VIRTUAL REALITY (VR)
    - SENSOR INTEGRATION TECHNOLOGY
    - BIG DATA ANALYTICS
    - CLOUD COMPUTING
    - CYBERSECURITY
    ADJACENT TECHNOLOGIES
    - BLOCKCHAIN
    - 5G CONNECTIVITY
    - EDGE COMPUTING
    - DIGITAL TWINS
  • 5.10 PATENT ANALYSIS
    LIST OF MAJOR PATENTS
  • 5.11 PORTERS FIVE FORCES ANALYSIS
    THREAT OF NEW ENTRANTS
    THREAT OF SUBSTITUTES
    BARGAINING POWER OF SUPPLIERS
    BARGAINING POWER OF BUYERS
    INTENSITY OF COMPETITIVE RIVALRY
  • 5.12 TRENDS/DISRUPTIONS IMPACTING CUSTOMER’S BUSINESS
  • 5.13 KEY STAKEHOLDERS AND BUYING CRITERIA
    KEY STAKEHOLDERS IN THE BUYING PROCESS
    BUYING CRITERIA
  • 5.14 KEY CONFERENCES & EVENTS, 2024-2025
  • 5.15 TECHNOLOGY ROADMAP FOR AI IN SPORTS MARKET
    SHORT-TERM ROADMAP (2023 – 2025)
    MID-TERM ROADMAP (2026 – 2028)
    LONG-TERM ROADMAP (2028 – 2030)
  • 5.16 BEST PRACTICES TO IMPLEMENT AI IN SPORTS
  • 5.17 CURRENT AND EMERGING BUSINESS MODELS
  • 5.18 TOOLS, FRAMEWORKS, AND TECHNIQUES USED IN AI IN SPORTS
  • 5.19 TRADE ANALYSIS (8542)
    EXPORT SCENARIO OF PROCESSORS AND CONTROLLERS
    IMPORT SCENARIO OF PROCESSORS AND CONTROLLERS
  • 5.20 INVESTMENT AND FUNDING SCENARIO
  • 5.21 IMPACT OF AI/GEN AI ON SPORTS
AI IN SPORTS MARKET SIZE, BY OFFERING
6
  • 6.1 INTRODUCTION
    OFFERING: MARKET DRIVERS
  • 6.2 SOLUTIONS
    PERFORMANCE ANALYTICS
    PLAYER MONITORING
    GAME STRATEGY AND COACHING SOLUTIONS
    FAN ENGAGEMENT AND EXPERIENCE ENHANCEMENT
    BROADCAST MANAGEMENT
    OTHER SOLUTIONS
  • 6.3 SERVICES
    PROFESSIONAL SERVICES
    - Training & Consulting
    - Deployment & System Integration
    - Support & Maintenance
    MANAGED SERVICES
AI IN SPORTS MARKET SIZE, BY TECHNOLOGY
7
  • 7.1 INTRODUCTION
    TYPE: MARKET DRIVERS
  • 7.2 GENERATIVE AI
  • 7.3 OTHER AI
    MACHINE LEARNING
    NATURAL LANGUAGE PROCESSING
    COMPUTER VISION
    PREDICTIVE ANALYTICS
AI IN SPORTS MARKET SIZE, BY SPORTS TYPE
8
  • 8.1 INTRODUCTION
    SPORTS TYPE: MARKET DRIVERS
    - BOXING
  • 8.2 INDIVIDUAL SPORTS
    - TENNIS
    - RACING
    - ATHLETICS
    - OTHERS
    - CRICKET
  • 8.3 TEAM SPORTS
    - SOCCER
    - AMERICAN FOOTBALL/RUGBY
    - BASKETBALL
    - BASEBALL
    - HOCKEY
    - OTHERS
  • 8.4 E-SPORTS
AI IN SPORTS MARKET SIZE, BY END USER
9
  • 9.1 INTRODUCTION
    END USER: MARKET DRIVERS
    - SPORTS ASSOCIATIONS
    - SPORTS TEAMS
    - SPORTS MEDIA & BROADCASTING
    - OTHER END USERS
AI IN SPORTS MARKET SIZE, BY REGION
10
  • 10.1 INTRODUCTION
  • 10.2 NORTH AMERICA
    MACROECONOMIC OUTLOOK FOR NORTH AMERICA
    UNITED STATES
    CANADA
  • 10.3 EUROPE
    MACROECONOMIC OUTLOOK FOR EUROPE
    UK
    GERMANY
    FRANCE
    ITALY
    SPAIN
    NORDIC COUNTRIES
    REST OF EUROPE
  • 10.4 ASIA PACIFIC
    MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
    CHINA
    JAPAN
    INDIA
    AUSTRALIA & NEW ZEALAND
    SOUTH KOREA
    SOUTHEAST ASIA
    REST OF ASIA PACIFIC
  • 10.5 MIDDLE EAST AND AFRICA
    MACROECONOMIC OUTLOOK FOR MIDDLE EAST AND AFRICA
    MIDDLE EAST & AFRICA
    - UAE
    - KSA
    - KUWAIT
    - BAHRAIN
    - SOUTH AFRICA
    - REST OF MIDDLE EAST & AFRICA
  • 10.6 LATIN AMERICA
    MACROECONOMIC OUTLOOK FOR LATIN AMERICA
    BRAZIL
    MEXICO
    ARGENTINA
    REST OF LATIN AMERICA
COMPETITIVE LANDSCAPE
11
  • 11.1 KEY PLAYER STRATEGIES/RIGHT TO WIN
  • 11.2 MARKET SHARE ANALYSIS
    MARKET RANKING ANALYSIS
  • 11.3 REVENUE ANALYSIS
  • 11.4 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
    STARS
    EMERGING LEADERS
    PERVASIVE PLAYERS
    PARTICIPANTS
    COMPANY FOOTPRINT: KEY PLAYERS, 2023
    - COMPANY FOOTPRINT
    - REGION FOOTPRINT
    - OFFERING FOOTPRINT
    - TYPE FOOTPRINT
    - SPORTS TYPE FOOTPRINT
    - END USER FOOTPRINT
  • 11.5 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
    PROGRESSIVE COMPANIES
    RESPONSIVE COMPANIES
    DYNAMIC COMPANIES
    STARTING BLOCKS
    COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    - DETAILED LIST OF KEY STARTUPS/SMES
    - COMPETITIVE BENCHMARKING OF KEY STARTUPS/SMES
  • 11.6 COMPETITIVE SCENARIO AND TREND
    PRODUCT LAUNCHES
    DEALS
    OTHERS
  • 11.7 BRAND/PRODUCT COMPARISON
  • 11.8 COMPANY VALUATION AND FINANCIAL METRICS OF KEY AI IN SPORTS OFFERING PROVIDERS
COMPANY PROFILES
12
  • 12.1 INTRODUCTION
  • 12.2 KEY PLAYERS
    CISCO SYSTEMS
    - Business and Financial Overview
    - Recent developments
    - MNM View
    IBM
    - Business and Financial Overview
    - Recent developments
    - MNM View
    MICROSOFT
    - Business and Financial Overview
    - Recent Developments
    - MnM View
    AWS
    - Business and Financial Overview
    - Recent developments
    - MnM View
    INTEL
    - Business and Financial Overview
    - Recent developments
    - MnM View
    TECH MAHINDRA
    - Business and Financial Overview
    - Recent developments
    STATS PERFORM
    - Business and Financial Overview
    - Recent developments
    ERICSSON
    - Business and Financial Overview
    - Recent developments
    ORACLE
    - Business and Financial Overview
    - Recent developments
    - SAP
    - EXTREME NETWORKS
    - SAS INSTITUTE
    - HCLTECH
    - SPORTRADAR AG
  • 12.3 STARTUPS/SMES
    CATAPULT GROUP INTERNATIONAL LTD.
    GENIUS SPORTS
    KITMAN LABS
    PLAYSIGHT
    QUANTIPHI
    SCISPORTS
    SPIIDEO
    SPORTLOGIQ
    CHYRONHEGO CORPORATION
    - TRUMEDIA NETWORKS
ADJACENT AND RELATED MARKETS
13
  • 13.1 ADJACENT AND RELATED MARKETS
  • 13.2 SPORTS TECHNOLOGY MARKET
    MARKET DEFINITION
    MARKET OVERVIEW
  • 13.3 SPORTS ANALYTICS MARKET
    MARKET DEFINITION
    MARKET OVERVIEW
APPENDIX
14
  • 14.1 ADJACENT REPORTS
  • 14.2 DISCUSSION GUIDE
  • 14.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
  • 14.4 AVAILABLE CUSTOMIZATIONS
  • 14.5 RELATED REPORTS
  • 14.6 AUTHOR DETAILS

 

This research study involved the extensive use of secondary sources, directories, and databases, such as Dun & Bradstreet (D&B) Hoovers and Bloomberg BusinessWeek, to identify and collect valuable information for a technical, market-oriented, and commercial study of the AI in Sports market. The primary sources have been mainly industry experts from the core and related industries and preferred suppliers, manufacturers, distributors, service providers, technology developers, alliances, and organizations related to all segments of the value chain of this market. In-depth interviews have been conducted with primary respondents, including key industry participants, subject matter experts, C-level executives of key market players, and industry consultants, to obtain and verify critical qualitative and quantitative information.

Secondary Research

In the secondary research process, various secondary sources were referred to identify and collect information for the study. The secondary sources included annual reports, press releases, investor presentations of companies, white papers, certified publications, and articles from recognized associations and government publishing sources. Several journals and associations, such as Artificial Intelligence in Sport Programme 2024, AI for Sport Conference 2nd Edition, were also referred to. Secondary research was used to obtain key information about industry insights, the market’s monetary chain, the overall pool of key players, market classification and segmentation according to industry trends to the bottom-most level, regional markets, and key developments from both the market and technology-oriented perspectives.

Primary Research

In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information for the report. The primary sources from the supply side included industry experts, such as Chief Executive Officers (CEOs), Chief Technology Officers (CTOs), Chief Operating Officers (COOs), Vice Presidents (VPs), marketing directors, technology and innovation directors, and related key executives from various key companies and organizations operating in the AI in Sports market. The primary sources from the demand side included AI in Sports end users, consultants/specialists, Chief Information Officers (CIOs), and subject-matter experts from enterprises and government associations.

AI in Sports Market Size, and Share

*Others include sales managers, marketing managers, and product managers.
Note: Tier 1 companies’ revenue is more than USD 1 billion; Tier 2 companies ‘revenue ranges between
USD 500 million to 1 billion; and Tier 3 companies’ revenue ranges in between USD 100 million
and USD 500 million

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

Multiple approaches were adopted to estimate and forecast the size of the AI in Sports market. The first approach involves estimating market size by summing up the revenue companies generate by selling AI solutions for Sports.

Both top-down and bottom-up approaches were used to estimate and validate the total size of the AI in Sports market. These methods were extensively used to estimate the size of various segments in the market. The research methodology used to estimate the market size includes the following:

  • Key players in the market have been identified through extensive secondary research.
  • In terms of value, the industry’s supply chain and market size have been determined through primary and secondary research processes.
  • All percentage shares, splits, and breakups have been determined using secondary sources and verified through primary sources.

AI in Sports Market : Top-Down and Bottom-Up Approach

AI in Sports Market Top Down and Bottom Up Approach

Data Triangulation

After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.

Market Definition

AI in Sports refers to the integration and application of artificial intelligence technologies to enhance various aspects of the sports industry. This includes improving athletic performance, optimizing game strategies, enriching fan experiences, and managing operations efficiently. AI-powered solutions in sports leverage data analytics, machine learning, computer vision, and natural language processing to analyze vast amounts of data and deliver actionable insights.

Additionally, AI automates broadcasting, generates real-time analytics, and improves operations such as ticketing, crowd management, and scheduling, transforming the way sports are played, managed, and consumed.

Stakeholders

  • Sports Teams and Athletes
  • Coaches and Managers
  • Sports Data Providers
  • Technology Providers
  • Sports Broadcast Networks
  • Sports Organizations
  • Fans and Consumers
  • Sponsors and Advertisers
  • Health and Fitness Professionals
  • Sports Medicine Specialists
  • Sports Analytics Firms
  • Sports Betting Companies
  • Media and Content Creators
  • Equipment Manufacturers
  • Regulatory Bodies
  • Esports Organizations
  • Academic Institutions and Researchers
  • AI Startups and Innovators

Report Objectives

  • To determine, segment, and forecast the AI in Sports market based on offering (solutions and services), technology (Generative AI and Other AI), sport type (Individual Sports, Team Sports, E-Sports), end user (Sports Associations, Sports Teams, Sports Media and Broadcasting,and Other), and region in terms of value
  • To forecast the size of the market segments with respect to five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
  • To provide detailed information about the major factors (drivers, restraints, opportunities, and challenges) influencing the growth of the market
  • To study the complete value chain and related industry segments and perform a value chain analysis of the market landscape
  • To strategically analyze the macro and micromarkets1 with respect to individual growth trends, prospects, and contributions to the total market
  • To analyze the industry trends, pricing data, patents, and innovations related to the market
  • To analyze the opportunities for stakeholders by identifying the high-growth segments of the market
  • To profile the key players in the market and comprehensively analyze their market share/ranking and core competencies
  • To track and analyze competitive developments, such as mergers & acquisitions, product launches & developments, partnerships, agreements, collaborations, business expansions, and R&D activities

Available Customizations

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Product Analysis

  • Analysis for additional countries (up to five)

Company Information

  • Detailed analysis and profiling of additional market players (up to 5)

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Growth opportunities and latent adjacency in AI in Sports Market

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