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Generative AI in the Sports Market By Sports Type (Football, Tennis, Cricket, Basketball, Hockey, Golf, and Other), By Deployments, By Application, By End User - Global Industry Outlook, Key Companies (State Perform Group Ltd., Zebra Technologies Corporation, Catapult Group International Ltd., and others), Trends and Forecast 2024-2033

Published on : April-2024  Report Code : RC-896  Pages Count : 286  Report Format : PDF
Overview Table of Content Download Report's Excerpt Request Free Sample

Market Overview

The Global Generative AI in Sports Market size is estimated to reach USD 319.9 million in 2024 and is further predicted to reach USD 3,737.5 million by 2033, at a CAGR of 31.7%.

Generative AI in the Sports Market Growth Analysis

Generative AI in sports is the process of adopting artificial intelligence technology to generate predictive models, create new content, and analyze data related to sports. This method is used to generate sports-related stories and build realistic-looking images or videos of sports events. It is becoming popular for planning game strategies that simulate results, analyze player performance, and generate personal training programs for athletes. Generative AI has wide applications within the sports industry which include sports equipment design, performance analysis, and game strategies.

These models are trained for analyzing large datasets of sports information which are often used to improve player performance analysis, enhance coaching, and assist in sports journalism by providing automated content generation. These models learn patterns by adopting of AI algorithm to generate new content from large data sets. Generative AI provided new opportunities in sports due to innovation and improvement across many aspects. This model continuously improves fan engagement, hence increasing revenue streams in the sports industry.

Key Takeaways

  • Market size: The global generative AI in sports market is projected to grow by 3,333.5 million, at a CAGR of 31.7 % during the forecasted period of 2025 to 2033.
  • Market Definition: Generative AI in sports is the process of using AI algorithms to analyze data, and generate insights for improving the performance of athletes, and their coaching strategies.
  • Sports Type Analysis: The football segment is projected to be the dominant force in the market, capturing the largest revenue share in 2024.
  • Deployment Analysis: On-premise deployment is expected to witness significant growth with the highest revenue share throughout the forecast period.
  • Application Analysis: Performance Analysis are forecasted to hold the largest market share and dominate the generative AI in the sports market in 2024.
  • End User Analysis: In terms of end user, the sports coaches’ segment is expected to take the lead with the highest market share in the global market by the end of 2024.
  • Regional Analysis: North America is anticipated to dominate the generative AI in the sports market, capturing a revenue share of 49.6 % in 2024.

Use Cases

  • Prediction and Performance Analysis: Generative AI helps identify patterns, trends, and correlations that humans sometimes miss by analyzing a vast amount of performance data from teams, athletes, and even digital equipment.
  • Enhancing fan experience: AI is useful in generating content for sports fans by processing a lot of data from games. It can create insightful and personalized content for sports fans, such as match summaries, player profiles, and statistical analyses that enhance the fan experience.
  • Injury Prevention and Rehabilitation: AI is used in analyzing medical records, biomechanical data, and athlete movements; through this, it can suggest training programs and methods to reduce the risk of injuries.
  • Virtual training: It can also generate virtual training programs that can be used to practice tactics, specific skills, & strategies in a controlled environment. It can also adjust according to different game conditions, difficulty levels, and give real-time feedback to help athletes improve their performance.

Market Dynamic

Drivers

Improvement in the performance of athlete:
Generative AI in the sports market is fueling as it uses athlete data, biological movement, and performance metrics to strategies their training routine, identify the possibility of improvement areas, and elevate athletic skill. Algorithms used in generative AI are aimed at providing helpful insights and suggestions to athletes and coaches by analyzing the data extensively who helps in providing efficient performance levels. These offer continuous monitoring and analysis of athlete progress which allows real-time adjustment to align with performance needs.

Advancement in broadcast and fan engagement:
Generative AI introduction in sports not only analyses the performance, it also transforms fan engagement and broadcast delivery. It creates an alluring experience that improves fans' connection with sports by generating personalized content and by using modern technologies like virtual reality and augmented reality. Nowadays, broadcasting is becoming more informative and entertaining with the introduction of real-time statistics and interactive elements.

Restrains

Challenges posed by data integrity:
Any error or discrepancies present in sports data can effectively influence the reliability and accuracy of the insights generated as it is highly dependent on the consistency and quality of the data it analyzes.

Technical Expertise and Ethical Considerations:
There is a need for strict guidelines and regulations to govern the use of AI in sports as decisions made by AI systems impact game strategies, player selection, & fan experiences. It requires skilled expertise in data analytics, machine learning, and sports science which presents a challenge for sports organizations, obstructing the growth of generative AI in the sports market.

Opportunities

Generative AI in sports offers a growth opportunity through the development of advanced training tools, predictive analytics, and AI-powered wearables due to technological innovation in sports.
There is a growing popularity of wearable devices such as smartwatches, fitness trackers, and even specialized sports sensors equipped with AI technology which monitor and improve athletes' performance.

Research Scope and Analysis

By Sports Type

Football is predicted to dominate the generative AI in the sports market with the largest revenue share of 30.5% in 2024. AI used in football to evaluate real-time analysis of team and player performance which drives the segment to the growth of this market. Coaches can use these insights for decision-making, movements, positioning, & overall improvement for players. AI helps in the prediction of matches by using past and current data which assist the team in the preparation and decision-making. It plays an important role in searching for talent, the possibility of risk assessment, and the development of game strategy.
  
The tennis segment is rapidly growing in the generative AI sports market as they are data-driven sports that use statistics & performance metrics for analysis. The increasing popularity of this sport leads to the use of AI which provides meaningful insights like match strategies, player performance, and injury prevention, thereby increasing the demand for AI in the sports sector. Tennis coaches are continuously adopting AI technologies due to the competitive nature of this game and its increasing trend for improvement among players. Moreover, basketball is projected to be the fastest-growing sport that use generative AI to analyze the shooting patterns of players and also provides insights for improvements, like shooting mechanics, shot selection, & accuracy.

By Deployment

On-premise deployment is estimated to hold a dominant position in the market with the largest revenue share of 64.7 % by the end of 2024. 

Generative AI in the Sports Market Deployment Share Analysis

These deployments do not depend on cloud-based services as they involve installing generative AI software on the local server. Organizations that are focusing on data security, safety, and faster data processing in the sports industry are frequently adopting on-premises deployment. They offer improved data protection as they can restore sensitive information locally which reduces reliance on cloud storage. They have a quick processing time as data doesn’t require to be transmitted on the internet and they also have control over generative AI software.
 
However, cloud-based are ready to show notable growth in the deployment segment of generative AI in the sports market during the forecasted period. These deployments use cloud computing services to host and operate generative AI software, offering easy updates, maintenance, and cost-effectiveness. This does not require local infrastructure which makes it more adaptable and flexible to use as compared to on premise deployment.

By Application

Generative AI in the sports market is segmented into performance analysis, game strategies, sports equipment design, and others. Performance Analysis is expected to dominate the market based on application with the largest revenue share of 35.2 % by the end of 2024. It uses generative AI algorithms to analyze data collection from numerous sources like practices, games, and training sessions.
 
The insights provided by this analysis are valuable for both team and individual players to make informed decisions, increase players' confidence, and plan game strategies. It can be used in analyzing video content from practices, and training sessions which helps to identify patterns and trends of matches and players.
 
Meanwhile, equipment design is showing notable growth attributed to the increasing adoption and use of generative AI in sports equipment. Algorithms used in generative AI are used to optimize the design of sports equipment such as apparel, footwear, protective gear, and training devices which helps in improving the efficiency and performance of sportsmen. It uses advanced data analytics and computational modeling for durability, material selection, ergonomic design, and performance enhancement features, driving the growth of this market.

By End User

Sports coaches are anticipated to dominate the generative AI in the sports market with the largest revenue share by the end of 2024. Coaches are continuously using advanced analytics tools to reduce the complexities of sports data which include players' statistics, game footage, & biometric information. 

Coaches require the actionable analysis of opponent strategies, player performance, and game tactics which is provided by processing a lot of data through AI algorithms. AI-powered tools like predictive modeling, real-time analytics, and automated scouting are demanded by coaches which help them to make informed decisions and optimize the overall performance of the team. Generative AI is becoming valuable for broadcasters in sports matches due to its ability to improve viewer engagement and content production. The viewing experience of these matches is continuously enhancing due to the introduction of virtual graphics, automated highlights generation, and augmented reality.
 
Athletes are showing notable growth in the market due to AI-powered solutions that provide personal training programs, & performance analysis based on biomechanical data. They can track progress, and real-time data, and identify areas for improvement which improve the performance results of athletes.

The Global Generative AI in Sports Market Report is segmented based on the following:

By Sports Type

  • Football
  • Tennis
  • Cricket
  • Basketball
  • Hockey
  • Golf
  • Others

By Deployments

  • On-premises
  • Cloud-based

By Application

  • Performance Analysis
  • Game Strategies
  • Sports Equipment Design
  • Other

By End User

  • Sports Coaches
  • Broadcaster
  • Athletes
  • Other

Regional Analysis

North America is anticipated to dominate the Generative AI in the sports market with the largest revenue share of 49.6% in 2024. This region is leading in the development and introduction of AI technologies across different industries, including sports organizations. They used AI for fan engagement, performance analysis, injury prevention, and even creating virtual athletes.
 
Generative AI in the Sports Market Regional Analysis
 
The existence of many sports leagues like NFL, MLB, NBA, & NHL and full adoption of generative AI for player analytics, strategic planning, & improving the fan experience is driving the growth of this region. The introduction of numerous startups by known and established companies like IBM and Microsoft significantly boosted the region’s growth in this market. Further, there is a huge pool of skilled professionals in data science, machine learning, and AI due to the availability of leading universities, research institutions, & tech hubs in this region. In addition, strong technological infrastructure, high-speed internet connectivity, and availability of data centers in this region use complex AI algorithms for sports analysis. 

Asia-Pacific is the second largest region in this market driven by technological progress and digital evolution across many sectors. Moreover, the popularity of sports like cricket, football, and e-sports in this region is increasing the demand for AI-driven solutions for injury prevention, player analysis, & audience interaction.

By Region

North America
  • The U.S.
  • Canada
Europe
  • Germany
  • The U.K.
  • France
  • Italy
  • Russia
  • Spain
  • Benelux
  • Nordic
  • Rest of Europe
Asia-Pacific
  • China
  • Japan
  • South Korea
  • India
  • ANZ
  • ASEAN
  • Rest of Asia-Pacific
Latin America
  • Brazil
  • Mexico
  • Argentina
  • Colombia
  • Rest of Latin America
Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa
  • Israel
  • Egypt
  • Rest of MEA

Competitive Landscape

Major companies like IBM, Microsoft, & SAS developed advanced AI solutions aimed at increasing player performance, and fan engagement in the sports industry. Various new startups in AI applications for sports are emerging which offers different solutions for sports analysis. Companies are actively expanding their product portfolios to gain a competitive advantage, particularly in fast-growing regions such as Asia Pacific. Manufacturers & sports equipment designers are using generative AI to expand their design possibilities, optimize manufacturing processes, and create an innovative solution that improves the performance and safety of sportsmen and athletes. 

Sports organizations are becoming major players by investing in AI technology to provide a competitive edge in the market as the Premier League is using AI for strategic game development. This market is shaped by continuous research & development initiatives by key players, changing consumer preferences, and global food industry trends.

Some of the prominent players in the global generative Ai in sports market market are:
  • State Perform Group Ltd.
  • Zebra Technologies Corporation
  • Catapult Group International Ltd.
  • Intel Corporation
  • IBM Corporation
  • Second Spectrum, Inc.
  • ShotTracker, Inc.
  • SAP SE
  • Trumedia Network
  • • Salesforce.com INc.
  • Sportsradar AG
  • Others

Recent Development

  • In April 2024, IBM and the Masters Tournament introduce several features on the Masters' app and Masters.com digital platform powered by generative AI capabilities developed using Watsonx, IBM's AI and data platform which provides comprehensive data-driven projections and analysis for every hole on the golf course.
  • In January 2024, Sports Data Labs, Inc. announced the introduction of a new U.S. patent that covers its innovative method using generative AI to create synthetic data, which can be used to replace missing or outlier data values.
  • In August 2023, FOX Sports announced the collaboration with Google Cloud to fully utilize its extensive sports content archives using Google Cloud's generative AI technology which builds upon three years of innovation in top-tier broadcasts, allows FOX Sports to efficiently expand, streamline, and gain insights from its data in a user-friendly manner.
  • In June 2023, IBM and The All-England Lawn Tennis Club announced new features for the Wimbledon digital fan experience which allows them to watch highlights videos with audio commentary of key moments, along with captions, which they can toggle on or off.
  • In February 2023, Tennis Australia, introduced several new AI initiatives which are designed to enhance fan engagement for attendees and connect with individuals who couldn't attend the matches in person.

Report Details

                                 Report Characteristics
Market Size (2024) USD 313.9 Mn
Forecast Value (2033) USD 3,737.4 Mn
CAGR (2023-2032) 31.7%
Historical Data 2018 – 2023
Forecast Data 2024 – 2033
Base Year 2023
Estimate Year 2024
Report Coverage Market Revenue Estimation, Market Dynamics, Competitive Landscape, Growth Factors and etc.
Segments Covered By Sports Type (Football, Tennis, Cricket, Basketball, Hockey, Golf, and Other), By Deployments (On-premises, and Cloud-based),By Application (Performance Analysis, Game Strategies, Sports Equipment Design, and Other), By End User (Sports Coaches, Broadcaster, Athlete, and Others)
Regional Coverage North America – The US and Canada; Europe – Germany, The UK, France, Russia, Spain, Italy, Benelux, Nordic, & Rest of Europe; Asia- Pacific– China, Japan, South Korea, India, ANZ, ASEAN, Rest of APAC; Latin America – Brazil, Mexico, Argentina, Colombia, Rest of Latin America; Middle East & Africa – Saudi Arabia, UAE, South Africa, Turkey, Egypt, Israel, & Rest of MEA
Prominent Players State Perform Group Ltd., Zebra Technologies Corporation, Catapult Group International Ltd., Intel Corporation, IBM Corporation, Second Spectrum, Inc., ShotTracker, Inc., and Other
Purchase Options We have three licenses to opt for: Single User License (Limited to 1 user), Multi-User License (Up to 5 Users), and Corporate Use License (Unlimited User) along with free report customization equivalent to 0 analyst working days, 3 analysts working days and 5 analysts working days respectively.

 

Frequently Asked Questions

  • How big is the Global Generative AI in the Sports Market?

    The Global Generative AI in Sports Market size is estimated to have a value of USD 319.9 million in 2024 and is expected to reach USD 3,737.5 million by the end of 2033.

  • Which region accounted for the largest Global Generative AI in the Sports Market?

    North America is expected to be the largest market share for the Global Generative AI in Sports Market with a share of about 49.6 % in 2024.

  • Who are the key players in the Global Generative AI in Sports Market?

    Some of the major key players in the Global Generative AI in Sports Market are State Perform Group Ltd., Zebra Technologies Corporation, Catapult Group International Ltd. and many others.

  • What is the growth rate in the Global Generative AI in Sports Market?

    The market is growing at a CAGR of 31.7 percent over the forecasted period.

  • Contents

      1.Introduction
        1.1.Objectives of the Study
        1.2.Market Scope
        1.3.Market Definition and Scope
      2.Generative AI in the Sports Market Overview
        2.1.Global Generative AI in the Sports Market Overview by Type
        2.2.Global Generative AI in the Sports Market Overview by Application
      3.Generative AI in the Sports Market Dynamics, Opportunity, Regulations, and Trends Analysis
        3.1.Market Dynamics
          3.1.1.Generative AI in the Sports Market Drivers
          3.1.2.Generative AI in the Sports Market Opportunities
          3.1.3.Generative AI in the Sports Market Restraints
          3.1.4.Generative AI in the Sports Market Challenges
        3.2.Emerging Trend/Technology
        3.3.PESTLE Analysis
        3.4.PORTER'S Five Forces Analysis
        3.5.Technology Roadmap
        3.6.Opportunity Map Analysis
        3.7.Case Studies
        3.8.Opportunity Orbits
        3.9.Pricing Analysis
        3.10.Ecosystem Analysis
        3.11.Supply/Value Chain Analysis
        3.12.Covid-19 & Recession Impact Analysis
        3.13.Product/Brand Comparison
      4.Global Generative AI in the Sports Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Sports Type, 2017-2032
        4.1.Global Generative AI in the Sports Market Analysis by By Sports Type: Introduction
        4.2.Market Size and Forecast by Region
        4.3.Football
        4.4.Tennis
        4.5.Cricket
        4.6.Basketball
        4.7.Hockey
        4.8.Golf
        4.9.Others
      5.Global Generative AI in the Sports Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Deployments, 2017-2032
        5.1.Global Generative AI in the Sports Market Analysis by By Deployments: Introduction
        5.2.Market Size and Forecast by Region
        5.3.On-premises
        5.4.Cloud-based
      6.Global Generative AI in the Sports Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Application, 2017-2032
        6.1.Global Generative AI in the Sports Market Analysis by By Application: Introduction
        6.2.Market Size and Forecast by Region
        6.3.Performance Analysis
        6.4.Game Strategies
        6.5.Sports Equipment Design
        6.6.Other
      7.Global Generative AI in the Sports Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By End User, 2017-2032
        7.1.Global Generative AI in the Sports Market Analysis by By End User: Introduction
        7.2.Market Size and Forecast by Region
        7.3.Sports Coaches
        7.4.Broadcaster
        7.5.Athletes
        7.6.Other
      10.Global Generative AI in the Sports Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by Region, 2017-2032
        10.1.North America
          10.1.1.North America Generative AI in the Sports Market: Regional Analysis, 2017-2032
            10.1.1.1.The US
            10.1.1.2.Canada
        10.2.1.Europe
          10.2.1.Europe Generative AI in the Sports Market: Regional Trend Analysis
            10.2.1.1.Germany
            10.2.1.2.France
            10.2.1.3.UK
            10.2.1.4.Russia
            10.2.1.5.Italy
            10.2.1.6.Spain
            10.2.1.7.Nordic
            10.2.1.8.Benelux
            10.2.1.9.Rest of Europe
        10.3.Asia-Pacific
          10.3.1.Asia-Pacific Generative AI in the Sports Market: Regional Analysis, 2017-2032
            10.3.1.1.China
            10.3.1.2.Japan
            10.3.1.3.South Korea
            10.3.1.4.India
            10.3.1.5.ANZ
            10.3.1.6.ASEAN
            10.3.1.7.Rest of Asia-Pacifc
        10.4.Latin America
          10.4.1.Latin America Generative AI in the Sports Market: Regional Analysis, 2017-2032
            10.4.1.1.Brazil
            10.4.1.2.Mexico
            10.4.1.3.Argentina
            10.4.1.4.Colombia
            10.4.1.5.Rest of Latin America
        10.5.Middle East and Africa
          10.5.1.Middle East and Africa Generative AI in the Sports Market: Regional Analysis, 2017-2032
            10.5.1.1.Saudi Arabia
            10.5.1.2.UAE
            10.5.1.3.South Africa
            10.5.1.4.Israel
            10.5.1.5.Egypt
            10.5.1.6.Turkey
            10.5.1.7.Rest of MEA
      11.Global Generative AI in the Sports Market Company Evaluation Matrix, Competitive Landscape, Market Share Analysis, and Company Profiles
        11.1.Market Share Analysis
        11.2.Company Profiles
          11.3.1.Company Overview
          11.3.2.Financial Highlights
          11.3.3.Product Portfolio
          11.3.4.SWOT Analysis
          11.3.5.Key Strategies and Developments
        11.4.State Perform Group Ltd.
          11.4.1.Company Overview
          11.4.2.Financial Highlights
          11.4.3.Product Portfolio
          11.4.4.SWOT Analysis
          11.4.5.Key Strategies and Developments
        11.5.Zebra Technologies Corporation
          11.5.1.Company Overview
          11.5.2.Financial Highlights
          11.5.3.Product Portfolio
          11.5.4.SWOT Analysis
          11.5.5.Key Strategies and Developments
        11.6.Catapult Group International Ltd.
          11.6.1.Company Overview
          11.6.2.Financial Highlights
          11.6.3.Product Portfolio
          11.6.4.SWOT Analysis
          11.6.5.Key Strategies and Developments
        11.7.Intel Corporation
          11.7.1.Company Overview
          11.7.2.Financial Highlights
          11.7.3.Product Portfolio
          11.7.4.SWOT Analysis
          11.7.5.Key Strategies and Developments
        11.8.IBM Corporation
          11.8.1.Company Overview
          11.8.2.Financial Highlights
          11.8.3.Product Portfolio
          11.8.4.SWOT Analysis
          11.8.5.Key Strategies and Developments
        11.9.Second Spectrum, Inc.
          11.9.1.Company Overview
          11.9.2.Financial Highlights
          11.9.3.Product Portfolio
          11.9.4.SWOT Analysis
          11.9.5.Key Strategies and Developments
        11.10.ShotTracker, Inc.
          11.10.1.Company Overview
          11.10.2.Financial Highlights
          11.10.3.Product Portfolio
          11.10.4.SWOT Analysis
          11.10.5.Key Strategies and Developments
        11.11.SAP SE
          11.11.1.Company Overview
          11.11.2.Financial Highlights
          11.11.3.Product Portfolio
          11.11.4.SWOT Analysis
          11.11.5.Key Strategies and Developments
        11.12.Trumedia Network
          11.12.1.Company Overview
          11.12.2.Financial Highlights
          11.12.3.Product Portfolio
          11.12.4.SWOT Analysis
          11.12.5.Key Strategies and Developments
        11.13.Salesforce.com INc.
          11.13.1.Company Overview
          11.13.2.Financial Highlights
          11.13.3.Product Portfolio
          11.13.4.SWOT Analysis
          11.13.5.Key Strategies and Developments
        11.14.Sportsradar AG
          11.14.1.Company Overview
          11.14.2.Financial Highlights
          11.14.3.Product Portfolio
          11.14.4.SWOT Analysis
          11.14.5.Key Strategies and Developments
      12.Assumptions and Acronyms
      13.Research Methodology
      14.Contact
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