Sports Analytics Market

Sports Analytics Market worth $8.4 billion by 2026

According to a research report "Sports Analytics Market with COVID-19 Impact Analysis by Component (Solutions, Services), Application, Deployment Mode, Organization Size, Industry Vertical, and Region (APAC, North America, MEA, Europe, Latin America) - Global Forecast to 2026" published by MarketsandMarkets, the sports analytics market size to grow from USD 2.5 billion in 2021 to USD 8.4 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 27.3% during the forecast period. Various factors such as increasing spending on adoption of newer technologies, changing landscape of customer intelligence to drive the market, and proliferation of customer channels are expected to drive the adoption of sports analytics technologies and services.

Browse 243 market data Tables and 51 Figures spread through 250 Pages and in-depth TOC on "Sports Analytics Market with COVID-19 Impact Analysis by Component (Solutions, Services), Application, Deployment Mode, Organization Size, Industry Vertical, and Region (APAC, North America, MEA, Europe, Latin America) - Global Forecast to 2026"
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Traditional analytics platforms use static and stored data to analyze simple or complex patterns and react to any business situation. These platforms take days to analyze and weeks to act on the stored data. Sports analytics technology is the core enabler of big data, enabling businesses to use historical data and combine it with customer insights to predict future events. Big data is an ever-increasing technology that assists businesses in optimizing processes and minimizing operational costs. The combination of real-time data streams, Artificial Intelligence (AI), Machine Learning (ML), and sports analytics can deliver competitive business advantages. Traditional analytics and BI systems use the deductive approach for analyzing data. This approach works well with structured data. Sports analytics, on the other hand, applies the inductive reasoning analysis approach, which deals with large datasets derived from ML, robotics, sensors, and AI. It uses algorithms that carry out complex calculations on large data sets and discover interrelationships and patterns between them. Big data offers the capability to gather, manage, and examine data across business verticals, such as banking, healthcare, and agriculture, which has made it a trending topic in Information Technology (IT) for a decade. It has numerous applications, and one such field where it has revolutionized the entire landscape is the sports industry. Data has always been crucial in sports to gain strategic decision-making capabilities and formulate other business strategies. Sports generate a large amount of data related to players, team performance, and the audience. Big data has made it easier and quicker for coaches, team managers, and sports associations to analyze the collected data and make optimum use of it. It further helps reshape existing business models, where sports are viewed as both commercial and technological platforms. To transform sports arenas into a testbed facility for the implementation of IoT on a wide-scale deployment, the technology platform is expected to comprise a robust Wireless Fidelity (Wi-Fi) network, mobile and cloud computing, and Internet of Things (IoT) technologies.. IoT would eventually digitalize stadium operations and provide fans with an enhanced connected experience. A smart stadium, therefore, would use sophisticated technologies and robust infrastructure to enhance its operations to lure fans to the stadiums.

Sports Association segment to account for a larger market size during the forecast period

Sports associations have struggled for years with the large amount of sports data that may be collected and the prohibitive cost of gathering that data internally. While many associations have successfully reduced costs through automation and outsourcing, crowdsourcing is emerging as a viable option. Analytics associations have been preoccupied with tracking physical performance statistics of their players for over a decade in order to understand which athletes work the hardest on the field. They want all of the information, including distance travelled, velocity, acceleration, and the distance between players, among other things. Because of their precision and capacity to collect data in real time, electronic wearables are an attractive offer. Individual teams can easily adopt them in practice, but in competitive games, the barriers can be higher because they require league-wide agreement.

Football in Team Sports to have the largest market size during the forecast period

Football is one of the major sports in the team sports segment that uses various optical tracking solutions to boost player performance. Salesforce focuses on offering game changing visualizations through dashboards that provide play-by-videos and statistical data in form of dashboards. ChyronHego is another company which provides TRACAB solution to capture live tracking data of the player’s performance during matches and provide technology that drives ticket pricing to engage fan experience. Real-time tracking solutions are used in FIFA World Cup, National Football Leagues, and Football clubs to analyze the player’s performance. National Football League (NFL) uses hard-hitting analysis for accurate decisions as well as for improving player’s health through electronic health record devices which track on-field performance of players.

APAC to hold higher CAGR during the forecast period

The sports analytics market has been segmented into five major regions: North America, Europe, APAC, Latin America, and MEA. APAC is expected to grow at a good pace during the forecast period. The region will be booming, as it is experiencing a lot of new entrepreneur setups, who are adopting the newer technologies to have a competitive advantage over the established players. China, Japan, and India have displayed ample growth opportunities in the sports analytics market.

Some major players in the sports analytics market include IBM (US), SAS Institute (US), Salesforce (US), EXL (US), GlobalStep (US), Catapult (US), HCL (India), ChyronHego (US), Stats Perform (US), TruMedia Network (US), DataArt (US), Orreco (Ireland), Quant4Sport (Italy), Zebra Technologies (US), and Exasol (Germany).

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Report Code
TC 4272
PR Published ON
3/4/2022
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