Rising demand for advanced analytics solutions, expansion of sports industry, emergence of sports as a business model, and intensifying competition in sports are the key attributes fueling the growth of the global sports analytics market. Sports analytics has been used for a better part of the past century by tracking historic performance of players or team to understand playing behavior and devise an appropriate strategy.
The data processing and analysis was limited to small set of data and to selected sport activities. Sports analytics refers to the use of advanced data collection, management and analysis tools to comprehending team or player performance and formulating strategic decisions through analysis of historic data. The process of data collection, processing and presentation has evolved with adoption of advanced technologies thereby reshaping the sports industry. Professional sport players, coaches, and investors depend on data and statistical methods for several aspects of game such as player selection, team selection, and on-field and off-field strategy formulation. This is dynamically contributing towards the growth of global sport analytics market. The sport analytics solutions facilitate real time analysis of data to understand opponent’s strategies and helps in devising real time strategies during a live event. Additionally, the rising demand for data generated by sport analytics across fantasy gaming is fueling the growth of sports analytics market. Implementation of lockdown to prevent the spread of COVID-19 has impacted the sports industry and anticipated to cast its shadow during coming years, thereby hindering the growth of sports analytics market in coming years.
North America contributed a dominating share to the global sports analytics market and is anticipated be a dominating region throughout the forecast period. Increased adoption of advanced analytics solutions across team and individual sports and increasing investment in sports analytics across major sports such as football, baseball, rugby and basketball is contributing towards the growth of North America sports analytics market. Asia Pacific contributed a significant share to the global market in 2019 and is expected to be the fastest growing segment during the forecast period owing to rising popularity of football across emerging countries.
Sports Analytics Market Share Analysis, by Geography (2021)
The report titled “Sports Analytics Market - Global Market Share, Trends, Analysis and Forecasts, 2022 - 2032”, wherein 2020 is historic period, 2021 is the base year, and 2022 to 2032 is forecast period. Additionally, the study takes into consideration the competitive landscape, wherein the report would provide company overview and market outlook for leading players in the global sports analytics market. Furthermore, the report would reflect the key developments, global & regional sales network, business strategies, research & development activities, employee strength, and key executive, for all the major players operating in the market.
The global sports analytics market is segmented based on component, analysis type, sports type, deployment, and geography. Based on component, the global sports analytics market is segmented into software and services. Based on analysis type, the global sports analytics market is segmented into on-field analysis and off-field analysis. The on-field analysis segment is further sub-segmented into player & team analysis, video analysis, health assessment, and others. The off-field analysis is sub-segmented into fan engagement, ticket pricing, and others. Based on sports type, the global sports analytics market is segmented into individual sports and team sports. The individual sports segment is further sub-segmented boxing, tennis, racing, athletes, and others. The team sports segment is sub-segmented into cricket, football, hockey, basketball, and others. Based on deployment, the global sports analytics market is segmented into on-premise and cloud. Based on geography, the global sports analytics market is segmented into North America, Europe, Asia Pacific, Middle East & Africa, and South America.
The research provides in-depth analysis of prominent players holding majority share of the global market with a focus on all operating business segment and would identify the segment of the company focusing on sports analytics. Further, market share of prominent companies in the global sports analytics market would also be estimated. the study takes into consideration the key competitive information such as business strategy, product portfolio, key development, swot analysis, and research and development focus of all the sports analytics companies.
The global sports analytics market study would take into consideration the participants engaged throughout the ecosystem of the market, along with their contribution. Product portfolio would focus on all the products under the sports analytics business segment of the company. Similarly, the recent development section would focus on the latest developments of company such as strategic alliances and partnerships, merger and acquisition, new product launched and geographic expansion in the global sports analytics market.
Major players active in the global sports analytics market include Agile Sports Technologies, Inc., CATAPULT, ChyronHego Corporation, DELTATRE, EXL, EXPERFY, GlobalStep, HCL Technologies Limited, IBM, ICEBERG Sports Analytics, Oracle Corporation, SAP SE, SAS Institute Inc., Sportradar AG, SportSource Analytics, and Tableau Software.
The Global Sports Analytics Market is Segmented as Below:
By Analysis Type
By Sports Type
InsightSLICE adopts a research methodology which is highly meticulous and comprehensive, yielding accurate research results. Our research methodology utilizes data triangulation model which helps in the precise collection and validation of information. Our set processes for problem solving and paid primary tools guarantee that any client requirement is met with utmost diligence and accuracy. Some of the primary components that are consequential to our research approach are:
Secondary Research or Desk Research
Distinctive Data Model
Secondary Sources include but are not limited to:
Past Published Research
Historical Data and Information
Primary Sources include but are not limited to:
InsightSLICE also leverages three types of data triangulation approaches as follows:
Data Source Triangulation
Extracting data and validation from multiple type of secondary and primary sources
Combining various methodologies to validate data inputs
Applying different theories to check credibility of data sets