
Artificial Intelligence in Sports Market Report and Forecast 2025-2034
Description
The global artificial intelligence in sports market size is assessed to grow at a CAGR of 29.40% between 2025 and 2034. The market is being aided by the growing usage of AI to enhance the performance of athletes and the increasing attempts to offer personalised experiences to fans.
Key Trends in the Market
Artificial intelligence, variously known as AI, is used in sports to analyse a plethora of data to improve the performance of players and teams and enhance the experiences and engagement of fans. This technology also plays an essential role in reducing human errors and supporting referees and umpires in making the right decision.
The EMR’s report titled “Global Artificial Intelligence in Sports Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:
Market Breakup by Component:
Football accounts for a significant portion of the artificial intelligence in sports market share as it enjoys substantial popularity in the world. AI tools are widely used to predict the outcomes of a match, boost the performance of players, improve the decision-making of referees, and enhance fan experiences. Football managers also use AI to identify players’ weaknesses and accordingly make substitutions to maximise game advantage.
Meanwhile, AI is increasingly used in cricket to measure bat speed and shot quality, analyse team performance, provide in-game feedback, ensure optimal health of players, and support umpires to improve their decision-making processes.
Artificial Intelligence in Sports Market Share by Application
As per the artificial intelligence in sports market analysis, the usage of AI for game strategies is likely to significantly increase in the coming years. Athletes and coaches use AI tools to efficiently analyse the strategies of oppositions, understand the strengths and weaknesses of a sportsperson, evaluate the performance of players, make data-driven decisions, and optimise coaching sessions, among others. Moreover, in the forecast period, the usage of AI to create simulations of games and support players to practice different scenarios is anticipated to increase.
Competitive Landscape
The comprehensive EMR report provides an in-depth assessment of the market based on the Porter's five forces model along with giving a SWOT analysis. The report gives a detailed analysis of the following key players in the global artificial intelligence in sports market, covering their competitive landscape and latest developments like mergers, acquisitions, investments and expansion plans.
Sportradar AG
Sportradar AG is a prominent sports technology company that aims to offer immersive experiences to bettors and sports fans. It was founded in 2001, and since has offered innovative solutions to sports betting operators, sports federations, consumer platforms, and news media. The company has partnered with leading organisations like ITF, NBA, FIFA, and ICC, among others.
STATS LLC
STATS LLC, headquartered in Illinois, the United States, is a leading sports technology company that was founded in 1981. Its products and solutions are aimed at improving betting and fantasy solutions, driving fan engagement, and enhancing team performance. Opto Data, a solution offered by the company, is used by various betting brands, teams, and news outlets due to its excellent depth and accuracy.
Catapult Group International Ltd
Catapult Group International Ltd is a company that operates at the intersection of analytics and sports science. It was founded in 2006 and offers innovative solutions that are aimed at supporting players to avoid injury and optimise their performance. The company has partnered with prominent sports teams such as NCAA, EPL, and Formula 1, among others.
Other artificial intelligence in sports market players include IBM Corporation, SAS Institute Inc., Salesforce, Inc., V7 Ltd., DataRobot, Inc., and Sony Group Corporation, among others.
Key Trends in the Market
Artificial intelligence, variously known as AI, is used in sports to analyse a plethora of data to improve the performance of players and teams and enhance the experiences and engagement of fans. This technology also plays an essential role in reducing human errors and supporting referees and umpires in making the right decision.
- One of the key artificial intelligence in sports market trends is the growing adoption of technologies to improve the performance of athletes. AI-powered wearable devices can monitor and track the speed, heart rate, energy levels, and body temperature of athletes to help optimise their performance and injury prevention.
- There is an increasing usage of AI to efficiently build and expand stadiums, create a safer, healthier, and secure live sports environment, analyse data streamed from CCTVs and other cameras to report incidents in real-time, and enhance the efficiency of stadium entryway.
- The increasing focus on improving fan engagement and experience is also driving the artificial intelligence in sports market growth. AI can surge communication between a team and fans, provide personalised content to viewers, offer a superior viewing experience, and enable viewers to actively participate in the game. Moreover, the growing interest in sports betting is anticipated to drive the usage of AI to provide tailored recommendations to sportsbooks, identify fraudulent behaviour, and provide accurate predictions to bettors.
The EMR’s report titled “Global Artificial Intelligence in Sports Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:
Market Breakup by Component:
- Software
- Service
- Cloud
- On-premises
- Cricket
- Tennis
- Basketball
- Baseball
- Others
- Game Planning
- Game Strategies
- Performance Improvement
- Injury Prevention
- Sports Recruitment
- Others
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East and Africa
Football accounts for a significant portion of the artificial intelligence in sports market share as it enjoys substantial popularity in the world. AI tools are widely used to predict the outcomes of a match, boost the performance of players, improve the decision-making of referees, and enhance fan experiences. Football managers also use AI to identify players’ weaknesses and accordingly make substitutions to maximise game advantage.
Meanwhile, AI is increasingly used in cricket to measure bat speed and shot quality, analyse team performance, provide in-game feedback, ensure optimal health of players, and support umpires to improve their decision-making processes.
Artificial Intelligence in Sports Market Share by Application
As per the artificial intelligence in sports market analysis, the usage of AI for game strategies is likely to significantly increase in the coming years. Athletes and coaches use AI tools to efficiently analyse the strategies of oppositions, understand the strengths and weaknesses of a sportsperson, evaluate the performance of players, make data-driven decisions, and optimise coaching sessions, among others. Moreover, in the forecast period, the usage of AI to create simulations of games and support players to practice different scenarios is anticipated to increase.
Competitive Landscape
The comprehensive EMR report provides an in-depth assessment of the market based on the Porter's five forces model along with giving a SWOT analysis. The report gives a detailed analysis of the following key players in the global artificial intelligence in sports market, covering their competitive landscape and latest developments like mergers, acquisitions, investments and expansion plans.
Sportradar AG
Sportradar AG is a prominent sports technology company that aims to offer immersive experiences to bettors and sports fans. It was founded in 2001, and since has offered innovative solutions to sports betting operators, sports federations, consumer platforms, and news media. The company has partnered with leading organisations like ITF, NBA, FIFA, and ICC, among others.
STATS LLC
STATS LLC, headquartered in Illinois, the United States, is a leading sports technology company that was founded in 1981. Its products and solutions are aimed at improving betting and fantasy solutions, driving fan engagement, and enhancing team performance. Opto Data, a solution offered by the company, is used by various betting brands, teams, and news outlets due to its excellent depth and accuracy.
Catapult Group International Ltd
Catapult Group International Ltd is a company that operates at the intersection of analytics and sports science. It was founded in 2006 and offers innovative solutions that are aimed at supporting players to avoid injury and optimise their performance. The company has partnered with prominent sports teams such as NCAA, EPL, and Formula 1, among others.
Other artificial intelligence in sports market players include IBM Corporation, SAS Institute Inc., Salesforce, Inc., V7 Ltd., DataRobot, Inc., and Sony Group Corporation, among others.
Table of Contents
173 Pages
- 1 Executive Summary
- 1.1 Market Size 2024-2025
- 1.2 Market Growth 2025(F)-2034(F)
- 1.3 Key Demand Drivers
- 1.4 Key Players and Competitive Structure
- 1.5 Industry Best Practices
- 1.6 Recent Trends and Developments
- 1.7 Industry Outlook
- 2 Market Overview and Stakeholder Insights
- 2.1 Market Trends
- 2.2 Key Verticals
- 2.3 Key Regions
- 2.4 Supplier Power
- 2.5 Buyer Power
- 2.6 Key Market Opportunities and Risks
- 2.7 Key Initiatives by Stakeholders
- 3 Economic Summary
- 3.1 GDP Outlook
- 3.2 GDP Per Capita Growth
- 3.3 Inflation Trends
- 3.4 Democracy Index
- 3.5 Gross Public Debt Ratios
- 3.6 Balance of Payment (BoP) Position
- 3.7 Population Outlook
- 3.8 Urbanisation Trends
- 4 Country Risk Profiles
- 4.1 Country Risk
- 4.2 Business Climate
- 5 Global Artificial Intelligence in Sports Market Analysis
- 5.1 Key Industry Highlights
- 5.2 Global Artificial Intelligence in Sports Historical Market (2018-2024)
- 5.3 Global Artificial Intelligence in Sports Market Forecast (2025-2034)
- 5.4 Global Artificial Intelligence in Sports Market by Component
- 5.4.1 Software
- 5.4.1.1 Historical Trend (2018-2024)
- 5.4.1.2 Forecast Trend (2025-2034)
- 5.4.2 Service
- 5.4.2.1 Historical Trend (2018-2024)
- 5.4.2.2 Forecast Trend (2025-2034)
- 5.5 Global Artificial Intelligence in Sports Market by Deployment
- 5.5.1 Cloud
- 5.5.1.1 Historical Trend (2018-2024)
- 5.5.1.2 Forecast Trend (2025-2034)
- 5.5.2 On-premises
- 5.5.2.1 Historical Trend (2018-2024)
- 5.5.2.2 Forecast Trend (2025-2034)
- 5.6 Global Artificial Intelligence in Sports Market by Game Type
- 5.6.1 Football
- 5.6.1.1 Historical Trend (2018-2024)
- 5.6.1.2 Forecast Trend (2025-2034)
- 5.6.2 Cricket
- 5.6.2.1 Historical Trend (2018-2024)
- 5.6.2.2 Forecast Trend (2025-2034)
- 5.6.3 Tennis
- 5.6.3.1 Historical Trend (2018-2024)
- 5.6.3.2 Forecast Trend (2025-2034)
- 5.6.4 Basketball
- 5.6.4.1 Historical Trend (2018-2024)
- 5.6.4.2 Forecast Trend (2025-2034)
- 5.6.5 Baseball
- 5.6.5.1 Historical Trend (2018-2024)
- 5.6.5.2 Forecast Trend (2025-2034)
- 5.6.6 Others
- 5.7 Global Artificial Intelligence in Sports Market by Application
- 5.7.1 Game Planning
- 5.7.1.1 Historical Trend (2018-2024)
- 5.7.1.2 Forecast Trend (2025-2034)
- 5.7.2 Game Strategies
- 5.7.2.1 Historical Trend (2018-2024)
- 5.7.2.2 Forecast Trend (2025-2034)
- 5.7.3 Performance Improvement
- 5.7.3.1 Historical Trend (2018-2024)
- 5.7.3.2 Forecast Trend (2025-2034)
- 5.7.4 Injury Prevention
- 5.7.4.1 Historical Trend (2018-2024)
- 5.7.4.2 Forecast Trend (2025-2034)
- 5.7.5 Sports Recruitment
- 5.7.5.1 Historical Trend (2018-2024)
- 5.7.5.2 Forecast Trend (2025-2034)
- 5.7.6 Others
- 5.8 Global Artificial Intelligence in Sports Market by Region
- 5.8.1 North America
- 5.8.1.1 Historical Trend (2018-2024)
- 5.8.1.2 Forecast Trend (2025-2034)
- 5.8.2 Europe
- 5.8.2.1 Historical Trend (2018-2024)
- 5.8.2.2 Forecast Trend (2025-2034)
- 5.8.3 Asia Pacific
- 5.8.3.1 Historical Trend (2018-2024)
- 5.8.3.2 Forecast Trend (2025-2034)
- 5.8.4 Latin America
- 5.8.4.1 Historical Trend (2018-2024)
- 5.8.4.2 Forecast Trend (2025-2034)
- 5.8.5 Middle East and Africa
- 5.8.5.1 Historical Trend (2018-2024)
- 5.8.5.2 Forecast Trend (2025-2034)
- 6 North America Artificial Intelligence in Sports Market Analysis
- 6.1 United States of America
- 6.1.1 Historical Trend (2018-2024)
- 6.1.2 Forecast Trend (2025-2034)
- 6.2 Canada
- 6.2.1 Historical Trend (2018-2024)
- 6.2.2 Forecast Trend (2025-2034)
- 7 Europe Artificial Intelligence in Sports Market Analysis
- 7.1 United Kingdom
- 7.1.1 Historical Trend (2018-2024)
- 7.1.2 Forecast Trend (2025-2034)
- 7.2 Germany
- 7.2.1 Historical Trend (2018-2024)
- 7.2.2 Forecast Trend (2025-2034)
- 7.3 France
- 7.3.1 Historical Trend (2018-2024)
- 7.3.2 Forecast Trend (2025-2034)
- 7.4 Italy
- 7.4.1 Historical Trend (2018-2024)
- 7.4.2 Forecast Trend (2025-2034)
- 7.5 Others
- 8 Asia Pacific Artificial Intelligence in Sports Market Analysis
- 8.1 China
- 8.1.1 Historical Trend (2018-2024)
- 8.1.2 Forecast Trend (2025-2034)
- 8.2 Japan
- 8.2.1 Historical Trend (2018-2024)
- 8.2.2 Forecast Trend (2025-2034)
- 8.3 India
- 8.3.1 Historical Trend (2018-2024)
- 8.3.2 Forecast Trend (2025-2034)
- 8.4 ASEAN
- 8.4.1 Historical Trend (2018-2024)
- 8.4.2 Forecast Trend (2025-2034)
- 8.5 Australia
- 8.5.1 Historical Trend (2018-2024)
- 8.5.2 Forecast Trend (2025-2034)
- 8.6 Others
- 9 Latin America Artificial Intelligence in Sports Market Analysis
- 9.1 Brazil
- 9.1.1 Historical Trend (2018-2024)
- 9.1.2 Forecast Trend (2025-2034)
- 9.2 Argentina
- 9.2.1 Historical Trend (2018-2024)
- 9.2.2 Forecast Trend (2025-2034)
- 9.3 Mexico
- 9.3.1 Historical Trend (2018-2024)
- 9.3.2 Forecast Trend (2025-2034)
- 9.4 Others
- 10 Middle East and Africa Artificial Intelligence in Sports Market Analysis
- 10.1 Saudi Arabia
- 10.1.1 Historical Trend (2018-2024)
- 10.1.2 Forecast Trend (2025-2034)
- 10.2 United Arab Emirates
- 10.2.1 Historical Trend (2018-2024)
- 10.2.2 Forecast Trend (2025-2034)
- 10.3 Nigeria
- 10.3.1 Historical Trend (2018-2024)
- 10.3.2 Forecast Trend (2025-2034)
- 10.4 South Africa
- 10.4.1 Historical Trend (2018-2024)
- 10.4.2 Forecast Trend (2025-2034)
- 10.5 Others
- 11 Market Dynamics
- 11.1 SWOT Analysis
- 11.1.1 Strengths
- 11.1.2 Weaknesses
- 11.1.3 Opportunities
- 11.1.4 Threats
- 11.2 Porter’s Five Forces Analysis
- 11.2.1 Supplier’s Power
- 11.2.2 Buyer’s Power
- 11.2.3 Threat of New Entrants
- 11.2.4 Degree of Rivalry
- 11.2.5 Threat of Substitutes
- 11.3 Key Indicators for Demand
- 11.4 Key Indicators for Price
- 12 Competitive Landscape
- 12.1 Supplier Selection
- 12.2 Key Global Players
- 12.3 Key Regional Players
- 12.4 Key Player Strategies
- 12.5 Company Profiles
- 12.5.1 IBM Corporation
- 12.5.1.1 Company Overview
- 12.5.1.2 Product Portfolio
- 12.5.1.3 Demographic Reach and Achievements
- 12.5.1.4 Certifications
- 12.5.2 SAS Institute Inc.
- 12.5.2.1 Company Overview
- 12.5.2.2 Product Portfolio
- 12.5.2.3 Demographic Reach and Achievements
- 12.5.2.4 Certifications
- 12.5.3 Salesforce, Inc.
- 12.5.3.1 Company Overview
- 12.5.3.2 Product Portfolio
- 12.5.3.3 Demographic Reach and Achievements
- 12.5.3.4 Certifications
- 12.5.4 Catapult Group International Ltd
- 12.5.4.1 Company Overview
- 12.5.4.2 Product Portfolio
- 12.5.4.3 Demographic Reach and Achievements
- 12.5.4.4 Certifications
- 12.5.5 STATS LLC
- 12.5.5.1 Company Overview
- 12.5.5.2 Product Portfolio
- 12.5.5.3 Demographic Reach and Achievements
- 12.5.5.4 Certifications
- 12.5.6 Sportradar AG
- 12.5.6.1 Company Overview
- 12.5.6.2 Product Portfolio
- 12.5.6.3 Demographic Reach and Achievements
- 12.5.6.4 Certifications
- 12.5.7 V7 Ltd.
- 12.5.7.1 Company Overview
- 12.5.7.2 Product Portfolio
- 12.5.7.3 Demographic Reach and Achievements
- 12.5.7.4 Certifications
- 12.5.8 DataRobot, Inc.
- 12.5.8.1 Company Overview
- 12.5.8.2 Product Portfolio
- 12.5.8.3 Demographic Reach and Achievements
- 12.5.8.4 Certifications
- 12.5.9 Sony Group Corporation
- 12.5.9.1 Company Overview
- 12.5.9.2 Product Portfolio
- 12.5.9.3 Demographic Reach and Achievements
- 12.5.9.4 Certifications
- 12.5.10 Others
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