AI in Sports Market Size, Share, Trends and Report by 2034

Research Methodology – AI in Sports Market

At Straits Research, we adopt a rigorous 360° research approach that integrates both primary and secondary research methodologies. This ensures accuracy, reliability, and actionable insights for stakeholders. Our methodology for the AI in Sports Market comprises the following key stages:

Market Indicator & Macro-Factor Analysis

Our baseline thesis for the AI in Sports Market is developed by integrating key market indicators and macroeconomic variables. These include:

1 Factors considered while calculating market size and share

The total number of professional sports teams and organizations using AI
Current investment in AI technologies in the sports industry
The total number of Sports Tech companies that are using AI
Revenue generated by AI-driven products and services in sports
Market segmentation based on region and type of sports
Number of AI-based startups in the sports industry

2 Key Market Indicators

Annual growth rate of AI and sports tech companies
Adoption rate of AI technology in sports
The scale of investments made in AI technology by sports organizations, broadcasters, and betting companies
Revenue growth resulting from AI product/service adoption
Latest product innovations and launches in AI in sports
Mergers and acquisitions related to AI in sports

3 Growth Trends

Widespread adoption of AI for player performance analysis and injury prediction
Increasing use of AI for fan engagement and personalized user experiences
Growth in AI-driven sports analytics and prediction platforms
Increased investment in AI for automated sports broadcasts and content generation
Trend of virtual reality and augmented reality applications in sports
Growth in the adoption of AI for scouting, player recruitment, and talent identification

Secondary Research

Our secondary research forms the foundation of market understanding and scope definition. We collect and analyze information from multiple reliable sources to map the overall ecosystem of the AI in Sports Market. Key inputs include:

Company-Level Information

Annual reports, investor presentations, SEC filings
Company press releases and product launch announcements
Public executive interviews and earnings calls
Strategy briefings and M&A updates

Industry and Government Sources

Country-level industry associations and trade bodies
Government dossiers, policy frameworks, and official releases
Whitepapers, working papers, and public R&D initiatives
Relevant Associations for the AI in Sports Market

Market Intelligence Sources

Broker reports and financial analyst coverage
Paid databases (Hoovers, Factiva, Refinitiv, Reuters, Statista, etc.)
Import/export trade data and tariff databases
Sector-specific journals, magazines, and news portals

Macro & Consumer Insights

Global macroeconomic indicators and their cascading effect on the industry
Demand–supply outlook and value chain analysis
Consumer behaviour, adoption rates, and commercialization trends

Primary Research

To validate and enrich our secondary findings, we conduct extensive primary research with industry stakeholders across the value chain. This ensures we capture both qualitative insights and quantitative validation. Our primary research includes:

Expert Insights & KOL Engagements

Key Opinion Leader (KOL) Engagements
Structured interviews with executives, product managers, and domain experts
Paid and barter-based interviews across manufacturers, distributors, and end-users

Focused Discussions & Panels

Discussions with stakeholders to validate demand-supply gaps
Group discussions on emerging technologies, regulatory shifts, and adoption barriers

Data Validation & Business POV

Cross-verification of market sizing and forecasts with industry insiders
Capturing business perspectives on growth opportunities and restraints

Data Triangulation & Forecasting

The final step of our research involves data triangulation ensuring accuracy through cross-verification of:

Demand-side analysis (consumption patterns, adoption trends, customer spending)
Supply-side analysis (production, capacity, distribution, and market availability)
Macroeconomic & microeconomic impact factors

Forecasting is carried out using proprietary models that combine: