Top Benefits of AI in Sports include Performance Improvement and Recruitment. Investment in AI will Improve Efficiency, Effectiveness, and Valuation of Professional Sports Teams
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This is the only research available that focuses on Artificial Intelligence (AI) in the sports industry. This report evaluates AI in sports market by Technology (Machine Learning, Natural Language Processing, Cognitive Computing, Computer Vision, Data Analytics, Decisions as a Service), Sports Level (Olympic, Private, Professional, Collegiate, High School, Middle School, and Early Childhood Sports and Fitness), sports type (Baseball, Basketball, Boxing, Cricket, Football (American), Golf, Gymnastics, Hockey (Field), Hockey (Ice), Mixed Martial Arts, Racing (Automobiles), Racing (Horses), Rugby, Skiing, Soccer (Association Football), Table Tennis (Ping Pong), Tennis, Volleyball, and Wrestling), User Type (Owner, Coach, Player, Spectator, Investor), Use Cases, Deployment (Software, Decision Support, DaaS, Decisions as a Service), Region and Countries. AI in the sports market represents a substantial opportunity for operational improvements including efficiency and effectiveness enhancements that ultimately lead to substantive team game performance.
Improving the overall efficiency and effectiveness of teams and individual athletes has big implications as sports-related activities and events have become a major industry in the last few decades. Professional sports in particular have become a big business with the asset value of major teams at well over $1 billion each, generating triple-digit millions in revenue annually. For example, the New England Patriots (American) football team is valued at roughly $3.8 billion, and generates over $500 million in total revenue annually. With about $103 million in revenue due to gate receipts, it is clear that a large portion of professional sports teams rely on non-venue related revenue including sponsorship, media rights, and merchandising. With the level of financials involved in a given organization, AI in the sports market is a meaningful investment for most team owners.
Sports at the Olympic, professional, and collegiate levels has become very data-driven as decisions ranging from recruitment and training to strategy and in-game tactics rely upon statistics and a dynamic set of variables including personnel, game conditions, and scenarios. Would be Olympians depend on sponsors, trainers, and coaches for major funding and support. Sponsorship is a multi-million investment for each athlete, underscoring the need to make the best decisions possible for sovereign nations and companies involved in deciding who will be developed with the intent of representing a country in a given sport and sporting event for the Olympics. Wise implementation of AI in the sports market represents a means of sponsoring countries, companies, and wealthy benefactors to maximize their investment in the best world athletes.
At the collegiate level, a great deal is at stake in terms of recruiting athletes to become professionals. There is also great importance for National Collegiate Athletic Association division IA teams who vie for various milestones such as winning seasons, division leadership, league championships, playoff appearances, and championships. Much is at stake from an alumni goodwill perspective, which translates into donations for sporting programs, which funds university and college development. AI in the sports market at the collegiate level provides this type of indirect benefit as college sports programs must be careful to not step over the line in terms of rules regarding financial benefits to players.
Artificial Intelligence in Sports Market: AI in Sports by Technology, Sports Level (Olympic, Professional, College), Sports Type, User Type (Owner, Coach, Player, Spectator), Use Case, Deployment, Region and Country 2019 – 2024 provides an assessment of the technologies, companies, strategies and solutions involved in leveraging artificial intelligence in sports market. The report analyzes AI in the sports market by sports level, type of sport, user type, and deployment options.
The report provides AI in sports market sizing for the aforementioned as well as a forecast for AI in the sports market by region and country from 2019 to 2024. It is important to note that certain countries focus on very specific sports, so AI in sports will vary significantly on a country by country basis and not just by comparative population or per capita GDP. All direct purchases of the author's reports include time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.
Report Benefits:
- The only report of its type focusing on AI in the sports market
- Understand how AI in sports will improve sports operations
- Identify opportunities and challenges of implementing AI in sports
- Understand how AI in sports relies upon other supporting technologies
Key Findings:
- AI improves the value of cross-training by team role/position between 9 and 32 percent
- Up to 65% of long-term cognitive dysfunction due to concussions is preventable through the use of AI
- AI in sports will improve individual and team performance by an average of 17% and 28% respectively
- Top benefits of AI in sports include performance improvement, injury prevention, and recruitment
- AI will improve revenue, reduce operational costs, and improve valuations of professional sports teams
Target Audience:
- Data analytics companies
- Artificial intelligence companies
- Sports teams of all types and levels
- Sovereign nations and sporting investors
With the purchase of this report at the Multi-user License or greater level, you will have access to one hour with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This will need to be used within three months of purchase.
This report also includes a complimentary Excel file with data from the report for purchasers at the Site License or greater level.
Table of Contents
1. Executive Summary
Companies Mentioned
- 24/7.ai Inc.
- Active.Ai
- Advanced Micro Devices (AMD) Inc.
- AIBrian Inc.
- Amazon Inc.
- Anodot
- AOL Inc.
- Apple Inc.
- ARM Limited
- Baidu Inc.
- Cisco Systems
- DeepScale
- Digital Reasoning Systems Inc.
- Facebook Inc.
- Fujitsu Ltd.
- General Electric (GE)
- General Vision Inc.
- Google Inc.
- Graphcore
- H2O.ai
- Haier Group Corporation
- Haptik
- Hewlett Packard Enterprise (HPE)
- Huawei Technologies Co. Ltd.
- IBM Corporation
- Intel Corporation
- InteliWISE
- IPsoft Inc.
- iRobot Corp.
- Juniper Networks, Inc.
- Leap Motion Inc.
- LG Electronics
- Micron Technology
- Microsoft Corporation
- MicroStrategy Incorporated
- Motion Controls Robotics Inc.
- motion.ai
- Neurala
- Next IT Corporation
- Nokia Corporation
- Nuance Communications Inc.
- Oracle Corporation
- Panasonic Corporation
- QlikTech International AB
- Qualcomm Incorporated
- Rethink Robotics
- Rockwell Automation Inc.
- Samsung Electronics Co Ltd.
- SAP
- SAS Institute Inc.
- Sentient Technologies Holdings Limited
- Siemens AG
- SoftBank Robotics Holding Corp.
- SparkCognition Inc.
- Tellmeplus
- Texas Instruments Inc.
- Umbo Computer Vision
- vPhrase
- Wade & Wendy
- Wind River Systems Inc.
- Xiaomi Technology Co. Ltd.
- XILINX Inc.
Methodology
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