The Global Artificial Intelligence in Sports Market size is expected to reach $7.3 billion by 2027, rising at a market growth of 30.7% CAGR during the forecast period.
Artificial Intelligence (AI) is mostly used in the sports industry to track player performance and to improve the player's health by making injury-prevention recommendations. In addition, AI and machine learning are being used in a variety of sports industry applications to improve sports planning, ranging from chatbots to network vision concepts. In the sports sector, AI is used in a variety of ways, including computer vision, marketing, automated journalism, and wearable technologies. Artificial intelligence (AI) is a term that refers to technology that mimics human functions and, in many cases, uses machine learning to learn from data how to outperform these jobs. It aids coaches and analysts in making better sports decisions.
Some of the growth catalysts for the market are an increase in demand for player monitoring and tracking data, as well as a growing desire for chatbots and virtual assistants to communicate with fans. Additionally, the growing demand for real-time data analytics is having a beneficial impact on the rise of AI in the sports industry. Furthermore, the rising demand for AI for making future predictions would play a major role in boosting the adoption rate of AI in the sports industry. On the other hand, some of the obstacles to the growth of AI in the sports industry are the scarcity of qualified & skilled experts, and high installation & maintenance costs.
Artificial intelligence in sports is gaining traction across the world, with applications ranging from post-game analysis to in-game activity to the fan experience. In addition, AI is also being employed to help gamers improve their performance. Apps like HomeCourt, ESPN Player, and MaxOne (M1) AI SmartCoach combine computer vision and machine learning to evaluate basketball players' abilities and provide them with an appropriate learning environment. Athletes' performance data are also recorded to help them understand the areas where they have the most potential to excel as well as the areas where they still need to develop.
COVID-19 Impact
The COVID-19 outbreak is expected to have a favorable impact on the artificial intelligence sector in sports. This is due to the fact that spectators are getting a personal look at the future of virtual contact sports, and some are beginning to embrace it. Moreover, because of a spike in COVID-19 cases, most sports stadiums have reduced the number of spectators and have adopted virtual spectatorship. Further, AI-powered equipment can not only stream live sporting games without the need for a camera operator, but it can also provide statistical models, tactical analysis, and prediction analytics to help coaches maximize their players' potential. Furthermore, COVID-19 has prompted many sports fans to think about player health and safety in a whole new and intense way.
Market Growth Factors
Demand for player data monitoring and tracking is on the rise
In recent years, emerging technologies such as artificial intelligence (AI), big data, and the Internet of Things (IoT) have become essential components of sport, and are now being used on a regular basis, particularly in team sports, for a variety of applications like monitoring movement patterns, which reveal important results about sport performance. In addition, AI analytics is assisting in the quantification of these outcomes as well as the kinematic profile of players who are employing global positioning systems (GPS). These devices have been classified as a viable instrument for assessing external load in intermittent sports, with the ability to capture real-time data on time, speed, position, distance, altitude, and direction, making them common in team sports analysis.
Growing demand for Chatbots and Virtual Assistants to Interact with Fans
The demand for social media virtual assistants is rapidly increasing, as they do all of the duties of a social media manager. They also handle time-consuming social media activities so that athletes may concentrate on their training and team management. In addition, as players' and sports' popularity has grown, it has become increasingly difficult for them to communicate with each fan. As the majority of the revenue comes from fans, this can result in significant losses for the team's management and players. Virtual assistants can respond to comments, look up hashtags, improve their content, and send follow-up communications in this situation.
Market Restraining Factors
High operating costs
Artificial intelligence in sports comes with a hefty price tag. In addition, the fact that it is used in nearly every aspect of sports management makes it much more costly to maintain. Hence, various sports organizations in many countries are still relying on legacy systems to continue to provide value to the fans. Also, technologies like AI come with some demerits also. The industry players need to check the possibility of data leak and other privacy concerns that can undermine reputation of any sports organization. Moreover, as technology advances, it will be necessary to update and upgrade both the software and hardware of artificial intelligence technology on a regular basis. The cost of upgrading these advanced technological systems is quite significant. Further, the expense of maintaining and repairing an AI machine is also a consideration.
Component Outlook
Based on Component, the market is segmented into Software and Services. The Services segment obtained a significant revenue share of the Artificial Intelligence in Sports Market in 2020. This is due to an increase in the number of trained workers and the need to maintain the security and functionality of the software, the service segment is witnessing a high adoption rate among many sports entities.
Game Type Outlook
Based on Game Type, the market is segmented into Football, Cricket, Basketball, Tennis, Baseball, and Others. The Cricket segment procured a significant revenue share of Artificial Intelligence in Sports Market in 2020. In cricket, artificial intelligence (AI) is utilized to improve the game's strategy. Machine Learning can be used to properly forecast match results. Moreover, AI is currently being applied in the Umpire Decision Review System (UDRS), Duckworth Lewis, and run-out analysis. AI can also be utilized to create indoor or closed stadiums, ensuring that the game can continue even if the weather is terrible.
Application Outlook
Based on Application, the market is segmented into Game Planning, Game Strategies, Performance Improvement, Injury Prevention Sports Recruitment, and Others. The Performance Improvement collected a promising revenue share of the Artificial Intelligence in Sports Market in 2020. AI is also being employed to improve player performance. Basketball players' skills are assessed using Computer Vision and Machine Learning via apps like HomeCourt, providing them with a suitable platform to progress. The recording of these athletes' performance indicators is not only reliable, but it also aids the players in determining where they have the greatest potential to excel and where they still need to grow.
Deployment Model Outlook
Based on Deployment model, the market is segmented into On-premise and Cloud. In 2020, the Cloud segment procured the largest revenue share of Artificial Intelligence in the Sports Market. Biomedical sensors collect data on an athlete's eating, sleeping, and training habits and store it on cloud servers. The various team members then use this information to come up with ways to improve their overall health, predict impending injury, and assist them in achieving peak performance. On and off the field, various sports organizations and teams have been utilizing cloud solutions technology, which allows them to analyze enormous volumes of data in a single platform and make appropriate decisions and changes
Technology Outlook
Based on Technology, the market is segmented into Machine Learning, Computer Vision, Data Analytics, Natural Language Processing, and Others. In 2020, the Machine Learning segment garnered the maximum revenue share of Artificial Intelligence in Sports Market. Machine learning helps give accurate data for player recruitment and performance, owing to its reliance on technology. Furthermore, machine learning gives researchers and innovators in the sports and allied industries technical assistance in expanding digitalization and automation.
Regional Outlook
Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. In 2020, North America emerged as the leading region in the overall Artificial Intelligence in Sports Market. This is attributed to an increase in AI adoption by major sports such as basketball, baseball, football, and tennis. Moreover, the artificial intelligence in sports market size is being driven by an increase in sports competitiveness across nations for higher positions.
The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; Facebook (Meta Platforms, Inc.) and Microsoft Corporation are the forerunners in the Artificial Intelligence in Sports Market. Companies such as IBM Corporation, SAP SE and Salesforce.com, Inc. are some of the key innovators in the Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Catapult Group International Ltd., Facebook (Meta Platforms, Inc.), IBM Corporation, Microsoft Corporation, Salesforce.com, Inc., SAP SE, SAS Institute, Inc., Sportradar AG, Stats Perform, and Trumedia Networks.
Recent Strategies Deployed in Artificial Intelligence in Sports Market
Partnerships, Collaborations and Agreements:
Dec-2021: Sportradar formed a five-year extention of its partnership with Bundesliga International, a subsidiary of DFL Deutsche FuBball Liga. Following this, the company would offer fans streamlined access to German football's top leagues.
Oct-2021: Stats Perform signed a five-year agreement with TruMedia, a company that develops tier one sports analytics solutions. Following the agreement, the two companies would continue to work on the development of the combined project named the ProVision sports analytics platform.
Oct-2021: Stats Perform extended its partnership with K-Sport. Through this partnership, the two entities aimed to offer player wearable solutions to more than 200 teams across professional football and rugby.
Aug-2021: Stats Perform formed a five-year partnership with 365Scores, the world's most extensive live scores tracking app. Following the partnership, Stats Perform would continue to help 365Scores' award-winning app with premium level sports data such as tracking, player stats, and real-time updates for football (soccer), rugby, tennis, basketball, cricket, ice hockey, baseball, volleyball, American football, and handball. 365Scores can give a more tailored and compelling fan experience to their millions of users with the help of Stats Perform's unparalleled depth of data and content.
Aug-2021: SAP partnered with the NBA, a professional basketball league in North America. Following the partnership, NBA would use the RISE software of SAP. The platform enables the NBA to streamline its corporate operations and support fan engagement efforts more effectively. Moreover, NBA would shift its cloud-based SAP software, including SAP's HANA Cloud database, to fellow cloud computing service Microsoft Azure.
Jul-2021: Salesforce partnered with Team Deutschland, the German Olympic team. Following the partnership, Salesforce became an official Key Partner to Team Deutschland. Through this partnership, Salesforce would work with German Olympic Sports Confederation (DOSB) and Deutsche Sport Marketing (DSM) to boost the digitization of Team Germany with immediate effect. This includes communication and engagement with millions of individuals globally, as well as a visually attractive display of data and information to help fans better understand and follow German athletes and their sports.
Jul-2021: Salesforce formed a partnership with Team GB, the brand name used since 1999 by the British Olympic Association for their British Olympic team to provide marketing programs that would bring fans and Team GB closer together than ever before.
Jun-2021: Sportradar joined hands with WSC Sports, an AI video production specialist to launch the sports betting sector's debut 'Live Video Notification' push service. Following this, the two entities would offer sportsbooks a platform to automatically publish live event video highlights to their customers through the usage of mobile push notifications.
Jun-2021: Salesforce entered into partnerships with Team USA, the LA28 Olympic, Paralympic Games, and NBCUniversal. Following the partnership, the company aimed to provide an enhanced fan and athlete digital experience during the forthcoming years.
Jun-2021: Facebook AI Research (FAIR) formed a collaboration with Matterport, a developer of a 3D media platform used to establish 3D and virtual reality models. Following the collaboration, the two entities would develop the world's biggest dataset of 3D indoor spaces available exclusively for academic, non-commercial uses.
May-2021: SAS Institute partnered with Microsoft, an American multinational technology corporation. Following this partnership, the two companies launched SAS Viya on Microsoft Azure.
May-2021: Microsoft extended its partnership with LaLiga, Spain's premier football association. The partnership aimed to digitally transform the sports experience around the world. Through LaLiga Tech, LaLiga's technology offering, the companies would also work on creating technology solutions for the media and entertainment industry.
Feb-2021: Catapult Sports formed a sports technology partnership with Push, a Canada-based Sports startup. Following the partnershi[, Catapult aimed to expand its SaaS offerings for more complete training monitoring and for a unique digital football playbook. Under this partnership, the data from Push can be effortlessly integrated into the athlete management system of Catapult for a more complete picture of player load based on- and off-field training.
Sep-2020: Stats Perform formed a multi-year partnership with Beyond Sports, a company that transforms real match data into a Virtual Reality simulation that helps pro-teams improve insights and training methods. The partnership would focus on the utilization of its positional tracking data of the English Premier League.
Aug-2020: IBM came into a partnership with USTA, the national governing body for tennis in the United States. Under this partnership, IBM would redefine the experience of tennis tournaments with virtual sports debates and hyper-relevant match insights with the help of IBM Watson, supported by open hybrid cloud architecture. Through this partnership, IBM created three unique and new tennis-based digital experiences. Two of the new solutions use IBM Watson's Natural Language Processing (NLP) capabilities to extract data from numerous sources and run workloads across several clouds.
Apr-2020: Catapult teamed up with Major League Baseball, a professional baseball organization and the oldest major professional sports league in the world. Following the collaboration, the two entities launched improvements in Baseball Analytics Suite. The updated version includes a new range of metrics and revolutionizes how coaches can act on mechanical, skill-specific loading data in real-time, allowing them to maximize their players' performance and properly manage their training exposure.
Apr-2020: Microsoft formed a partnership with NBA, a professional basketball league in North America. Following the partnership, Microsoft became the Official Technology Partner for the NBA. Under this partnership, the two entities would develop a direct-to-consumer platform that provides new fan engagement experiences and improved streaming capabilities based on Microsoft Azure and its AI capabilities.
Product Launches and Product Expansions:
Aug-2021: Catapult introduced Catapult One, its wearable performance solution for the new-age athletes. The new solution is developed by the same development team trusted to provide performance metrics to more than 3,200 elite teams around the world such as the EPL, NFL, and NCAA, and it offers players and coaches at all levels the tools to monitor, analyze, and enhance performance with professional-level accuracy.
May-2021: Stats Perform unveiled PressBox, an all-in-one online platform that provides data-driven insights, video clip discovery, and unparalleled data research, at a speed faster than ever before. Through this platform, the company aimed to redefine sports media with a new AI-powered platform.
Mar-2020: Sportradar introduced Simulated Reality, an AI-driven product for professional sports matches, which would be made available to customers within its current portfolio of events. In addition, Sportradar leveraged its AI and machine learning capabilities to provide a sports betting experience that is as close to real-life as possible, seamless, and with no integration needed.
Acquisitions and Mergers:
Apr-2021: Microsoft took over Nuance Communications, a cloud, and artificial intelligence (AI) software firm. The acquisition would integrate solutions and expertise to provide new cloud and AI capabilities across healthcare and other industries.
Jan-2021: SAS took over Boemska, a privately held technology company specializing in low-code/no-code application deployment and analytic workload management for the SAS platform. The acquisition would improve SAS Viya - a cloud-native, advanced analytics platform with enhanced capabilities that drive SAS' objective of supporting the complete analytics life cycle and facilitating customer migration to the cloud.
Nov-2020: Stats Perform acquired Thuuz Sports, a platform for creating automated video highlights and real-time excitement alerts from Palo Alto-based tech company. The unique technology in Stats Perform's SmartReels and SmartRatings products would be integrated into the company's extensive product line, creating new potential for media, technology, and betting customers.
Scope of the Study
Market Segments covered in the Report:
By Component
By Game Type
- Football
- Cricket
- Basketball
- Tennis
- Baseball
- Others
By Application
- Game Planning
- Game Strategies
- Performance Improvement
- Injury Prevention Sports Recruitment
- Others
By Deployment Model
By Technology
- Machine Learning
- Computer Vision
- Data Analytics
- Natural Language Processing
- Others
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Companies Profiled
- Catapult Group International Ltd.
- Facebook (Meta Platforms, Inc.)
- IBM Corporation
- Microsoft Corporation
- Salesforce.com, Inc.
- SAP SE
- SAS Institute, Inc.
- Sportradar AG
- Stats Perform
- Trumedia Networks
Unique Offerings from KBV Research
- Exhaustive coverage
- Highest number of market tables and figures
- Subscription based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology
- 1.1 Market Definition
- 1.2 Objectives
- 1.3 Market Scope
- 1.4 Segmentation
- 1.4.1 Global Artificial Intelligence in Sports Market, by Component
- 1.4.2 Global Artificial Intelligence in Sports Market, by Game Type
- 1.4.3 Global Artificial Intelligence in Sports Market, by Application
- 1.4.4 Global Artificial Intelligence in Sports Market, by Deployment Model
- 1.4.5 Global Artificial Intelligence in Sports Market, by Technology
- 1.4.6 Global Artificial Intelligence in Sports Market, by Geography
- 1.5 Methodology for the research
Chapter 2. Market Overview
- 2.1 Introduction
- 2.1.1 Overview
- 2.1.1.1 Market Composition and Scenario
- 2.2 Key Factors Impacting the Market
- 2.2.1 Market Drivers
- 2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
- 3.1 KBV Cardinal Matrix
- 3.2 Recent Industry Wide Strategic Developments
- 3.2.1 Partnerships, Collaborations and Agreements
- 3.2.2 Product Launches and Product Expansions
- 3.2.3 Acquisition and Mergers
- 3.3 Top Winning Strategies
- 3.3.1 Key Leading Strategies: Percentage Distribution (2017-2021)
- 3.3.2 Key Strategic Move: (Partnerships, Collaborations and Agreements: 2018, Mar - 2021, Dec) Leading Players
Chapter 4. Global Artificial Intelligence in Sports Market by Component
- 4.1 Global Software Market by Region
- 4.2 Global Services Market by Region
Chapter 5. Global Artificial Intelligence in Sports Market by Game Type
- 5.1 Global Football Market by Region
- 5.2 Global Cricket Market by Region
- 5.3 Global Basketball Market by Region
- 5.4 Global Tennis Market by Region
- 5.5 Global Baseball Market by Region
- 5.6 Global Others Market by Region
Chapter 6. Global Artificial Intelligence in Sports Market by Application
- 6.1 Global Game Planning Market by Region
- 6.2 Global Game Strategies Market by Region
- 6.3 Global Performance Improvement Market by Region
- 6.4 Global Injury Prevention Sports Recruitment Market by Region
- 6.5 Global Others Market by Region
Chapter 7. Global Artificial Intelligence in Sports Market by Deployment Model
- 7.1 Global On-premise Market by Region
- 7.2 Global Cloud Market by Region
Chapter 8. Global Artificial Intelligence in Sports Market by Technology
- 8.1 Global Machine Learning Market by Region
- 8.2 Global Computer Vision Market by Region
- 8.3 Global Data Analytics Market by Region
- 8.4 Global Natural Language Processing Market by Region
- 8.5 Global Others Market by Region
Chapter 9. Global Artificial Intelligence in Sports Market by Region
- 9.1 North America Artificial Intelligence in Sports Market
- 9.1.1 North America Artificial Intelligence in Sports Market by Component
- 9.1.1.1 North America Software Market by Country
- 9.1.1.2 North America Services Market by Country
- 9.1.2 North America Artificial Intelligence in Sports Market by Game Type
- 9.1.2.1 North America Football Market by Country
- 9.1.2.2 North America Cricket Market by Country
- 9.1.2.3 North America Basketball Market by Country
- 9.1.2.4 North America Tennis Market by Country
- 9.1.2.5 North America Baseball Market by Country
- 9.1.2.6 North America Others Market by Country
- 9.1.3 North America Artificial Intelligence in Sports Market by Application
- 9.1.3.1 North America Game Planning Market by Country
- 9.1.3.2 North America Game Strategies Market by Country
- 9.1.3.3 North America Performance Improvement Market by Country
- 9.1.3.4 North America Injury Prevention Sports Recruitment Market by Country
- 9.1.3.5 North America Others Market by Country
- 9.1.4 North America Artificial Intelligence in Sports Market by Deployment Model
- 9.1.4.1 North America On-premise Market by Country
- 9.1.4.2 North America Cloud Market by Country
- 9.1.5 North America Artificial Intelligence in Sports Market by Technology
- 9.1.5.1 North America Machine Learning Market by Country
- 9.1.5.2 North America Computer Vision Market by Country
- 9.1.5.3 North America Data Analytics Market by Country
- 9.1.5.4 North America Natural Language Processing Market by Country
- 9.1.5.5 North America Others Market by Country
- 9.1.6 North America Artificial Intelligence in Sports Market by Country
- 9.1.6.1 US Artificial Intelligence in Sports Market
- 9.1.6.1.1 US Artificial Intelligence in Sports Market by Component
- 9.1.6.1.2 US Artificial Intelligence in Sports Market by Game Type
- 9.1.6.1.3 US Artificial Intelligence in Sports Market by Application
- 9.1.6.1.4 US Artificial Intelligence in Sports Market by Deployment Model
- 9.1.6.1.5 US Artificial Intelligence in Sports Market by Technology
- 9.1.6.2 Canada Artificial Intelligence in Sports Market
- 9.1.6.2.1 Canada Artificial Intelligence in Sports Market by Component
- 9.1.6.2.2 Canada Artificial Intelligence in Sports Market by Game Type
- 9.1.6.2.3 Canada Artificial Intelligence in Sports Market by Application
- 9.1.6.2.4 Canada Artificial Intelligence in Sports Market by Deployment Model
- 9.1.6.2.5 Canada Artificial Intelligence in Sports Market by Technology
- 9.1.6.3 Mexico Artificial Intelligence in Sports Market
- 9.1.6.3.1 Mexico Artificial Intelligence in Sports Market by Component
- 9.1.6.3.2 Mexico Artificial Intelligence in Sports Market by Game Type
- 9.1.6.3.3 Mexico Artificial Intelligence in Sports Market by Application
- 9.1.6.3.4 Mexico Artificial Intelligence in Sports Market by Deployment Model
- 9.1.6.3.5 Mexico Artificial Intelligence in Sports Market by Technology
- 9.1.6.4 Rest of North America Artificial Intelligence in Sports Market
- 9.1.6.4.1 Rest of North America Artificial Intelligence in Sports Market by Component
- 9.1.6.4.2 Rest of North America Artificial Intelligence in Sports Market by Game Type
- 9.1.6.4.3 Rest of North America Artificial Intelligence in Sports Market by Application
- 9.1.6.4.4 Rest of North America Artificial Intelligence in Sports Market by Deployment Model
- 9.1.6.4.5 Rest of North America Artificial Intelligence in Sports Market by Technology
- 9.2 Europe Artificial Intelligence in Sports Market
- 9.2.1 Europe Artificial Intelligence in Sports Market by Component
- 9.2.1.1 Europe Software Market by Country
- 9.2.1.2 Europe Services Market by Country
- 9.2.2 Europe Artificial Intelligence in Sports Market by Game Type
- 9.2.2.1 Europe Football Market by Country
- 9.2.2.2 Europe Cricket Market by Country
- 9.2.2.3 Europe Basketball Market by Country
- 9.2.2.4 Europe Tennis Market by Country
- 9.2.2.5 Europe Baseball Market by Country
- 9.2.2.6 Europe Others Market by Country
- 9.2.3 Europe Artificial Intelligence in Sports Market by Application
- 9.2.3.1 Europe Game Planning Market by Country
- 9.2.3.2 Europe Game Strategies Market by Country
- 9.2.3.3 Europe Performance Improvement Market by Country
- 9.2.3.4 Europe Injury Prevention Sports Recruitment Market by Country
- 9.2.3.5 Europe Others Market by Country
- 9.2.4 Europe Artificial Intelligence in Sports Market by Deployment Model
- 9.2.4.1 Europe On-premise Market by Country
- 9.2.4.2 Europe Cloud Market by Country
- 9.2.5 Europe Artificial Intelligence in Sports Market by Technology
- 9.2.5.1 Europe Machine Learning Market by Country
- 9.2.5.2 Europe Computer Vision Market by Country
- 9.2.5.3 Europe Data Analytics Market by Country
- 9.2.5.4 Europe Natural Language Processing Market by Country
- 9.2.5.5 Europe Others Market by Country
- 9.2.6 Europe Artificial Intelligence in Sports Market by Country
- 9.2.6.1 Germany Artificial Intelligence in Sports Market
- 9.2.6.1.1 Germany Artificial Intelligence in Sports Market by Component
- 9.2.6.1.2 Germany Artificial Intelligence in Sports Market by Game Type
- 9.2.6.1.3 Germany Artificial Intelligence in Sports Market by Application
- 9.2.6.1.4 Germany Artificial Intelligence in Sports Market by Deployment Model
- 9.2.6.1.5 Germany Artificial Intelligence in Sports Market by Technology
- 9.2.6.2 UK Artificial Intelligence in Sports Market
- 9.2.6.2.1 UK Artificial Intelligence in Sports Market by Component
- 9.2.6.2.2 UK Artificial Intelligence in Sports Market by Game Type
- 9.2.6.2.3 UK Artificial Intelligence in Sports Market by Application
- 9.2.6.2.4 UK Artificial Intelligence in Sports Market by Deployment Model
- 9.2.6.2.5 UK Artificial Intelligence in Sports Market by Technology
- 9.2.6.3 France Artificial Intelligence in Sports Market
- 9.2.6.3.1 France Artificial Intelligence in Sports Market by Component
- 9.2.6.3.2 France Artificial Intelligence in Sports Market by Game Type
- 9.2.6.3.3 France Artificial Intelligence in Sports Market by Application
- 9.2.6.3.4 France Artificial Intelligence in Sports Market by Deployment Model
- 9.2.6.3.5 France Artificial Intelligence in Sports Market by Technology
- 9.2.6.4 Russia Artificial Intelligence in Sports Market
- 9.2.6.4.1 Russia Artificial Intelligence in Sports Market by Component
- 9.2.6.4.2 Russia Artificial Intelligence in Sports Market by Game Type
- 9.2.6.4.3 Russia Artificial Intelligence in Sports Market by Application
- 9.2.6.4.4 Russia Artificial Intelligence in Sports Market by Deployment Model
- 9.2.6.4.5 Russia Artificial Intelligence in Sports Market by Technology
- 9.2.6.5 Spain Artificial Intelligence in Sports Market
- 9.2.6.5.1 Spain Artificial Intelligence in Sports Market by Component
- 9.2.6.5.2 Spain Artificial Intelligence in Sports Market by Game Type
- 9.2.6.5.3 Spain Artificial Intelligence in Sports Market by Application
- 9.2.6.5.4 Spain Artificial Intelligence in Sports Market by Deployment Model
- 9.2.6.5.5 Spain Artificial Intelligence in Sports Market by Technology
- 9.2.6.6 Italy Artificial Intelligence in Sports Market
- 9.2.6.6.1 Italy Artificial Intelligence in Sports Market by Component
- 9.2.6.6.2 Italy Artificial Intelligence in Sports Market by Game Type
- 9.2.6.6.3 Italy Artificial Intelligence in Sports Market by Application
- 9.2.6.6.4 Italy Artificial Intelligence in Sports Market by Deployment Model
- 9.2.6.6.5 Italy Artificial Intelligence in Sports Market by Technology
- 9.2.6.7 Rest of Europe Artificial Intelligence in Sports Market
- 9.2.6.7.1 Rest of Europe Artificial Intelligence in Sports Market by Component
- 9.2.6.7.2 Rest of Europe Artificial Intelligence in Sports Market by Game Type
- 9.2.6.7.3 Rest of Europe Artificial Intelligence in Sports Market by Application
- 9.2.6.7.4 Rest of Europe Artificial Intelligence in Sports Market by Deployment Model
- 9.2.6.7.5 Rest of Europe Artificial Intelligence in Sports Market by Technology
- 9.3 Asia Pacific Artificial Intelligence in Sports Market
- 9.3.1 Asia Pacific Artificial Intelligence in Sports Market by Component
- 9.3.1.1 Asia Pacific Software Market by Country
- 9.3.1.2 Asia Pacific Services Market by Country
- 9.3.2 Asia Pacific Artificial Intelligence in Sports Market by Game Type
- 9.3.2.1 Asia Pacific Football Market by Country
- 9.3.2.2 Asia Pacific Cricket Market by Country
- 9.3.2.3 Asia Pacific Basketball Market by Country
- 9.3.2.4 Asia Pacific Tennis Market by Country
- 9.3.2.5 Asia Pacific Baseball Market by Country
- 9.3.2.6 Asia Pacific Others Market by Country
- 9.3.3 Asia Pacific Artificial Intelligence in Sports Market by Application
- 9.3.3.1 Asia Pacific Game Planning Market by Country
- 9.3.3.2 Asia Pacific Game Strategies Market by Country
- 9.3.3.3 Asia Pacific Performance Improvement Market by Country
- 9.3.3.4 Asia Pacific Injury Prevention Sports Recruitment Market by Country
- 9.3.3.5 Asia Pacific Others Market by Country
- 9.3.4 Asia Pacific Artificial Intelligence in Sports Market by Deployment Model
- 9.3.4.1 Asia Pacific On-premise Market by Country
- 9.3.4.2 Asia Pacific Cloud Market by Country
- 9.3.5 Asia Pacific Artificial Intelligence in Sports Market by Technology
- 9.3.5.1 Asia Pacific Machine Learning Market by Country
- 9.3.5.2 Asia Pacific Computer Vision Market by Country
- 9.3.5.3 Asia Pacific Data Analytics Market by Country
- 9.3.5.4 Asia Pacific Natural Language Processing Market by Country
- 9.3.5.5 Asia Pacific Others Market by Country
- 9.3.6 Asia Pacific Artificial Intelligence in Sports Market by Country
- 9.3.6.1 China Artificial Intelligence in Sports Market
- 9.3.6.1.1 China Artificial Intelligence in Sports Market by Component
- 9.3.6.1.2 China Artificial Intelligence in Sports Market by Game Type
- 9.3.6.1.3 China Artificial Intelligence in Sports Market by Application
- 9.3.6.1.4 China Artificial Intelligence in Sports Market by Deployment Model
- 9.3.6.1.5 China Artificial Intelligence in Sports Market by Technology
- 9.3.6.2 Japan Artificial Intelligence in Sports Market
- 9.3.6.2.1 Japan Artificial Intelligence in Sports Market by Component
- 9.3.6.2.2 Japan Artificial Intelligence in Sports Market by Game Type
- 9.3.6.2.3 Japan Artificial Intelligence in Sports Market by Application
- 9.3.6.2.4 Japan Artificial Intelligence in Sports Market by Deployment Model
- 9.3.6.2.5 Japan Artificial Intelligence in Sports Market by Technology
- 9.3.6.3 India Artificial Intelligence in Sports Market
- 9.3.6.3.1 India Artificial Intelligence in Sports Market by Component
- 9.3.6.3.2 India Artificial Intelligence in Sports Market by Game Type
- 9.3.6.3.3 India Artificial Intelligence in Sports Market by Application
- 9.3.6.3.4 India Artificial Intelligence in Sports Market by Deployment Model
- 9.3.6.3.5 India Artificial Intelligence in Sports Market by Technology
- 9.3.6.4 South Korea Artificial Intelligence in Sports Market
- 9.3.6.4.1 South Korea Artificial Intelligence in Sports Market by Component
- 9.3.6.4.2 South Korea Artificial Intelligence in Sports Market by Game Type
- 9.3.6.4.3 South Korea Artificial Intelligence in Sports Market by Application
- 9.3.6.4.4 South Korea Artificial Intelligence in Sports Market by Deployment Model
- 9.3.6.4.5 South Korea Artificial Intelligence in Sports Market by Technology
- 9.3.6.5 Australia Artificial Intelligence in Sports Market
- 9.3.6.5.1 Australia Artificial Intelligence in Sports Market by Component
- 9.3.6.5.2 Australia Artificial Intelligence in Sports Market by Game Type
- 9.3.6.5.3 Australia Artificial Intelligence in Sports Market by Application
- 9.3.6.5.4 Australia Artificial Intelligence in Sports Market by Deployment Model
- 9.3.6.5.5 Australia Artificial Intelligence in Sports Market by Technology
- 9.3.6.6 Malaysia Artificial Intelligence in Sports Market
- 9.3.6.6.1 Malaysia Artificial Intelligence in Sports Market by Component
- 9.3.6.6.2 Malaysia Artificial Intelligence in Sports Market by Game Type
- 9.3.6.6.3 Malaysia Artificial Intelligence in Sports Market by Application
- 9.3.6.6.4 Malaysia Artificial Intelligence in Sports Market by Deployment Model
- 9.3.6.6.5 Malaysia Artificial Intelligence in Sports Market by Technology
- 9.3.6.7 Rest of Asia Pacific Artificial Intelligence in Sports Market
- 9.3.6.7.1 Rest of Asia Pacific Artificial Intelligence in Sports Market by Component
- 9.3.6.7.2 Rest of Asia Pacific Artificial Intelligence in Sports Market by Game Type
- 9.3.6.7.3 Rest of Asia Pacific Artificial Intelligence in Sports Market by Application
- 9.3.6.7.4 Rest of Asia Pacific Artificial Intelligence in Sports Market by Deployment Model
- 9.3.6.7.5 Rest of Asia Pacific Artificial Intelligence in Sports Market by Technology
- 9.4 LAMEA Artificial Intelligence in Sports Market
- 9.4.1 LAMEA Artificial Intelligence in Sports Market by Component
- 9.4.1.1 LAMEA Software Market by Country
- 9.4.1.2 LAMEA Services Market by Country
- 9.4.2 LAMEA Artificial Intelligence in Sports Market by Game Type
- 9.4.2.1 LAMEA Football Market by Country
- 9.4.2.2 LAMEA Cricket Market by Country
- 9.4.2.3 LAMEA Basketball Market by Country
- 9.4.2.4 LAMEA Tennis Market by Country
- 9.4.2.5 LAMEA Baseball Market by Country
- 9.4.2.6 LAMEA Others Market by Country
- 9.4.3 LAMEA Artificial Intelligence in Sports Market by Application
- 9.4.3.1 LAMEA Game Planning Market by Country
- 9.4.3.2 LAMEA Game Strategies Market by Country
- 9.4.3.3 LAMEA Performance Improvement Market by Country
- 9.4.3.4 LAMEA Injury Prevention Sports Recruitment Market by Country
- 9.4.3.5 LAMEA Others Market by Country
- 9.4.4 LAMEA Artificial Intelligence in Sports Market by Deployment Model
- 9.4.4.1 LAMEA On-premise Market by Country
- 9.4.4.2 LAMEA Cloud Market by Country
- 9.4.5 LAMEA Artificial Intelligence in Sports Market by Technology
- 9.4.5.1 LAMEA Machine Learning Market by Country
- 9.4.5.2 LAMEA Computer Vision Market by Country
- 9.4.5.3 LAMEA Data Analytics Market by Country
- 9.4.5.4 LAMEA Natural Language Processing Market by Country
- 9.4.5.5 LAMEA Others Market by Country
- 9.4.6 LAMEA Artificial Intelligence in Sports Market by Country
- 9.4.6.1 Brazil Artificial Intelligence in Sports Market
- 9.4.6.1.1 Brazil Artificial Intelligence in Sports Market by Component
- 9.4.6.1.2 Brazil Artificial Intelligence in Sports Market by Game Type
- 9.4.6.1.3 Brazil Artificial Intelligence in Sports Market by Application
- 9.4.6.1.4 Brazil Artificial Intelligence in Sports Market by Deployment Model
- 9.4.6.1.5 Brazil Artificial Intelligence in Sports Market by Technology
- 9.4.6.2 Argentina Artificial Intelligence in Sports Market
- 9.4.6.2.1 Argentina Artificial Intelligence in Sports Market by Component
- 9.4.6.2.2 Argentina Artificial Intelligence in Sports Market by Game Type
- 9.4.6.2.3 Argentina Artificial Intelligence in Sports Market by Application
- 9.4.6.2.4 Argentina Artificial Intelligence in Sports Market by Deployment Model
- 9.4.6.2.5 Argentina Artificial Intelligence in Sports Market by Technology
- 9.4.6.3 UAE Artificial Intelligence in Sports Market
- 9.4.6.3.1 UAE Artificial Intelligence in Sports Market by Component
- 9.4.6.3.2 UAE Artificial Intelligence in Sports Market by Game Type
- 9.4.6.3.3 UAE Artificial Intelligence in Sports Market by Application
- 9.4.6.3.4 UAE Artificial Intelligence in Sports Market by Deployment Model
- 9.4.6.3.5 UAE Artificial Intelligence in Sports Market by Technology
- 9.4.6.4 Saudi Arabia Artificial Intelligence in Sports Market
- 9.4.6.4.1 Saudi Arabia Artificial Intelligence in Sports Market by Component
- 9.4.6.4.2 Saudi Arabia Artificial Intelligence in Sports Market by Game Type
- 9.4.6.4.3 Saudi Arabia Artificial Intelligence in Sports Market by Application
- 9.4.6.4.4 Saudi Arabia Artificial Intelligence in Sports Market by Deployment Model
- 9.4.6.4.5 Saudi Arabia Artificial Intelligence in Sports Market by Technology
- 9.4.6.5 South Africa Artificial Intelligence in Sports Market
- 9.4.6.5.1 South Africa Artificial Intelligence in Sports Market by Component
- 9.4.6.5.2 South Africa Artificial Intelligence in Sports Market by Game Type
- 9.4.6.5.3 South Africa Artificial Intelligence in Sports Market by Application
- 9.4.6.5.4 South Africa Artificial Intelligence in Sports Market by Deployment Model
- 9.4.6.5.5 South Africa Artificial Intelligence in Sports Market by Technology
- 9.4.6.6 Nigeria Artificial Intelligence in Sports Market
- 9.4.6.6.1 Nigeria Artificial Intelligence in Sports Market by Component
- 9.4.6.6.2 Nigeria Artificial Intelligence in Sports Market by Game Type
- 9.4.6.6.3 Nigeria Artificial Intelligence in Sports Market by Application
- 9.4.6.6.4 Nigeria Artificial Intelligence in Sports Market by Deployment Model
- 9.4.6.6.5 Nigeria Artificial Intelligence in Sports Market by Technology
- 9.4.6.7 Rest of LAMEA Artificial Intelligence in Sports Market
- 9.4.6.7.1 Rest of LAMEA Artificial Intelligence in Sports Market by Component
- 9.4.6.7.2 Rest of LAMEA Artificial Intelligence in Sports Market by Game Type
- 9.4.6.7.3 Rest of LAMEA Artificial Intelligence in Sports Market by Application
- 9.4.6.7.4 Rest of LAMEA Artificial Intelligence in Sports Market by Deployment Model
- 9.4.6.7.5 Rest of LAMEA Artificial Intelligence in Sports Market by Technology
Chapter 10. Company Profiles
- 10.1 Facebook (Meta Platforms, Inc.)
- 10.1.1 Company Overview
- 10.1.2 Financial Analysis
- 10.1.3 Segment and Regional Analysis
- 10.1.4 Research & Development Expense
- 10.1.5 Recent strategies and developments:
- 10.1.5.1 Partnerships, Collaborations, and Agreements:
- 10.1.6 SWOT Analysis
- 10.2 IBM Corporation
- 10.2.1 Company Overview
- 10.2.2 Financial Analysis
- 10.2.3 Regional & Segmental Analysis
- 10.2.4 Research & Development Expenses
- 10.2.5 Recent Strategies and developments:
- 10.2.5.1 Partnerships, Collaborations and Agreements:
- 10.2.6 SWOT Analysis
- 10.3 Microsoft Corporation
- 10.3.1 Company Overview
- 10.3.2 Financial Analysis
- 10.3.3 Segmental and Regional Analysis
- 10.3.4 Research & Development Expenses
- 10.3.5 Recent strategies and developments:
- 10.3.5.1 Partnerships, Collaborations, and Agreements:
- 10.3.5.2 Acquisition and Mergers:
- 10.3.6 SWOT Analysis
- 10.4 Trumedia Networks, Inc.
- 10.5 SAP SE
- 10.5.1 Company Overview
- 10.5.2 Financial Analysis
- 10.5.3 Segmental and Regional Analysis
- 10.5.4 Research & Development Expense
- 10.5.5 Recent strategies and developments:
- 10.5.5.1 Partnerships, Collaborations, and Agreements:
- 10.5.6 SWOT Analysis
- 10.6 Salesforce.com, Inc.
- 10.6.1 Company Overview
- 10.6.2 Financial Analysis
- 10.6.3 Regional Analysis
- 10.6.4 Research & Development Expense
- 10.6.5 Recent Strategies and developments:
- 10.6.5.1 Partnerships, Collaborations and Agreements:
- 10.6.6 SWOT Analysis
- 10.7 SAS Institute, Inc.
- 10.7.1 Company Overview
- 10.7.2 Recent strategies and developments:
- 10.7.2.1 Partnerships, Collaborations, and Agreements:
- 10.7.2.2 Acquisition and Mergers:
- 10.8 Stats Perform Group
- 10.8.1 Company Overview
- 10.8.2 Recent strategies and developments:
- 10.8.2.1 Partnerships, Collaborations, and Agreements:
- 10.8.2.2 Product Launches and Product Expansions:
- 10.8.2.3 Acquisition and Mergers:
- 10.9 Sportradar AG
- 10.9.1 Company Overview
- 10.9.2 Recent strategies and developments:
- 10.9.2.1 Partnerships, Collaborations, and Agreements:
- 10.9.2.2 Product Launches and Product Expansions:
- 10.9.2.3 Acquisition and Mergers:
- 10.10. Catapult Group International Limited
- 10.10.1 Company Overview
- 10.10.2 Financial Analysis
- 10.10.3 Segmental and Regional Analysis
- 10.10.4 Recent strategies and developments:
- 10.10.4.1 Partnerships, Collaborations, and Agreements:
- 10.10.4.2 Product Launches and Product Expansions:
- 10.10.4.3 Acquisition and Mergers: