Artificial Intelligence (AI) in Sport – Thematic Intelligence

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Published: November 06, 2024 Report Code: GDSPO-TR-S050-TH

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Artificial Intelligence (AI) in Sport Thematic Report Overview

The sports industry’s adoption of AI will focus on computer vision (CV) and machine learning (ML). Successful applications of ML have helped the decision-makers at sports companies, broadcasters, and leagues find underlying trends in vast datasets. This analysis informs their strategy, on and off the pitch. A greater breadth of data is available so ML models can gain deeper insight into tactics and strategy. CV is mainly used in training, officiating, performance analysis, and injury prevention. Many teams using this technology have reported a decline in lost days due to injury despite many sports, like soccer, straining players’ health with a high volume of matches.

The ‘Artificial Intelligence (AI) in Sport’ thematic intelligence report gives you an in-depth insight into how the AI theme can impact the sports industry. It further entails a deep-dive analysis of the industry including the AI value chain as well as market values for the current and forecast period. The report gives an insight into the market players and the competitive landscape within the theme.

Report Pages 34
Regions Covered Global
Value Chain ·       Hardware

·       Data Management

·       Foundational AI

·       Advanced AI Capabilities

·       Delivery
Leading AI Adopters ·       Deutsche Fußball Liga (DFL)

·       Formula 1 (F1)

·       National Basketball Association (NBA)
Specialist AI Vendors ·       AI.io

·       Hawk-Eye Innovations

·       Stats Perform
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AI Value Chain Analysis

The AI value chain is split into five segments: hardware, data management, foundational AI, advanced AI capabilities, and delivery.

Advanced AI capabilities: AI is any machine-based system that perceives its environment, pursues goals, adapts to feedback or change, provides information or takes action, and even has self-awareness and sentience. There are five categories of advanced AI capabilities; namely human-AI interaction, decision-making, motion, creation, and sentience.

AI Value Chain Analysis

AI Value Chain Analysis

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AI in Sport – Competitive Landscape

The key companies that will make their mark within the AI in sport theme are as follows:

Leading AI Adopters in Sport: A few of the leading sports organizations currently deploying AI are Deutsche Fußball Liga (DFL), Formula 1 (F1), and the National Basketball Association (NBA), among others.

Specialist AI Vendors in Sport: A few of the specialist AI vendors in the sports sector are AI.io, Hawk-Eye Innovations, and Stats Perform, among others.

Key Companies in AI Theme

Key Companies in AI Theme

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Sport Federations Sector Scorecard

At GlobalData, we use a scorecard approach to predict tomorrow’s leading companies within each sector. Our sector scorecard has three screens: a thematic screen, a valuation screen, and a risk screen.

  • The thematic screen ranks companies based on overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of future performance.

Sport Federations Sector Scorecard – Thematic Screen

Sport Federations Sector Scorecard – Thematic Screen

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Scope

  • The “Artificial Intelligence in Sport” thematic intelligence report gives you an in-depth insight into the impact of AI in sport, including key players, challenges, and market size and growth forecasts.

  • The report elucidates the growing importance of AI in the sports sector along with the progress made by the leading companies to integrate it. These detailed analyses are critical in developing effective business plans to gain a competitive edge.

Key Highlights

  • The sports industry is typically slow to adopt new technologies. Sport is different from most industries as technology will not change how the sector operates, though it may change how sport is consumed. However, in other industries, AI could engender wholesale changes in operations. Sports companies, teams, and leagues generally wait to see successful, profitable adoption of a new technology before investing heavily themselves.

  • The main application of AI in sports has been using machine learning models to analyze large datasets, which can help inform strategy on and off the pitch. More recently, machine learning has provided in-depth statistics for sports broadcasters, synthesizing large datasets. Computer vision is another subset of AI. Historically, it has been successful in the sports industry. Generative AI has not had a similar impact on the sports industry yet. However, developments are increasingly likely around betting and generating media content.

  • Increased AI adoption could help prevent injuries and protect players’ well-being. Player safety is crucial for sports clubs. An injury to a star player could hamstring a club’s commercial strategy, damage a club’s bottom line, and harm the career and earnings of the player. AI can help tackle this through injury prevention.

  • AI in the sports industry can benefit sponsors and those seeking a sponsor. Now there is a greater depth of data available, sports companies can tailor their sponsorship requirements accordingly. For instance, AI could analyze the demographics and interests of an audience and feed the insights to a prospective sponsor. This will help it decide whether a sponsorship opportunity is suitable.

Reasons to Buy

This report:

  • Discusses the challenges the sports industry faces and how AI can be used to help address them.

  • Evaluates the impact of AI in the sports sector, including various use cases and case studies.

  • Benchmarks leading AI vendors and leading sports companies based on their adoption of AI.

Alibaba
Alpha MOS
Alphabet (Google
Waymo)
Amazon
Apple
Aryballe
Baidu
Generic Robotics
Google Deepmind
IBM
iFlytek
Intel
Kernel
Megvii (Face++)
Merative
Meta
Microsoft
Mobileye
Neuralink
Nvidia
Odometric
Paradromics
Sanctuary AI
SenseTime
Synchron
Tastewise
Tesla
Tencent
ABB
Aurora
Basler
Cognex
GM (Cruise)
Hyundai (Boston Dynamics)
Keyence
Lockheed Martin
Midea (KUKA)
Motional
Northrop Grumman
Oracle
Pony.ai
SAS
Teradyne
Thales Group
Festo
iRobot
Omron
Robotiq
Aifnet (Deep Dream)
Aiva Technologies
Amadeus Code
Anthropic
Artbreeder
Audiocipher
Big Sleep
Boomy
Cohere
DeepAI
Ecrett Music
Hugging Face
Jasper Art
Midjourney
Mistral AI
NightCafe
OpenAI
Output
Shutterstock (Amper)
Stability.ai
StarryAI
WOMBO (Dream)
AI.io
Amazon Web Services
Genius Sports
Hawk-Eye
MeetKai
Pixellot
SatisfiLabs
Sportlogiq
Sport Radar
Sportsbox AI
Track160
Uplift Labs
Wicket
ATP Tour
Chelsea FC
Cleveland Browns
F1
IOC
IPC
LA Chargers
MLS
NBA
NHL
Sky Sports
UEFA
WTA
DFL
FIBA
Liverpool FC
NHL
Orlando Magic
PGA Tour
The Masters Tournament
AELTC
FIFA
FEI
FIA
FIG
FIS
FIVB
ICC
ITF
ITTF
MLB
UCI
World Aquatics
World Athletics
World Rowing
World Rugby
Catapult
Playermaker
StatsPerform
Twenty First Group
Wallabies
Zone 7
SoundHound
Amelia AI
Softbank
Graphcore
The9
Kuaijin Shidai
DocuSign
Lexion
Aareon
Stonal
Thoma Bravo
Darktrace
WM Therapeutics
Run:AI
Veradigm
ScienceIO
Blaize
Bayanat AI
Yahsat
Lunit
Volpara Health Technologies
LIG Nex1
Ghost Robotics
Nice
LiveVox Holdings
Parsons
Sealing Technologies
AeroVironment
Tomahawk Robotics
DoubleVerify Holdings
Scibids Technology
DigitalOcean Holdings
Paperspace
Meituan
Light Year
Databricks
Mosaic ML
Thomson Reuters
Casetext
Kunlun Tech
Singularity AI
Philips Healthcare
DIA Imaging Analysis
Spectral AI
CNH Industrial
Augmenta
The Travelers Companies
Corvus Insurance Holdings
Transcarent
98point6
Roadzen
Indie Semiconductor
GEO Semiconductor
Google Cloud Platform
BioNTech
InstaDeep
Mozilla
Lentil AI
Accenture
Albert
Audio Analytic
Telus International
WillowTree
OneMetaAI
Metalanguage
Databand.ai
ReliaQuest
Digital Shadows
Granulate Cloud Solutions
NielsenIQ
CiValue
Excelero
AI Music Group

Table of Contents

  • 1. Executive Summary

  • 2. Players

  • 3. Value Chain

    • 3.1. Advanced AI capabilities

  • 4. The Impact of AI on Sport

  • 5. Case Studies

  • 6. Market Size and Growth Forecasts

  • 7. AI Timeline

  • 8. Signals

    • 8.1. M&A trends

    • 8.2. Patent trends

    • 8.3. Company filing trends

    • 8.4. Hiring trends

  • 9. Companies

    • 9.1. Leading AI adopters in Sport

    • 9.2. Specialist AI vendors in Sport

  • 10. Sector Scorecard

    • 10.1. Sport sector scorecard

  • 11. Glossary

  • 12. Further Reading

  • 13. Our Thematic Research Methodology

  • 14. About GlobalData

  • 15. Contact Us

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