2021: Global Sports Analytics Software Market Estimated at $2.5 Billion
The volume of the global market for sports analytics software reached $2.5 billion in 2021. This is evidenced by the data of researchers ResearchAndMarkets, published at the end of March 2022.
According to researchers, the market for sports analytics software will grow to $8.4 billion by 2026 at a combined annual growth rate (CAGR) of 27.3% during the forecast period. Market growth is influenced by factors such as increased costs of introducing new technologies, changing the landscape of customer analytics to stimulate the market and increasing the number of client channels.
Traditional analytical platforms use static and stored data to analyze simple or complex templates, as well as respond to any business situation. These platforms require days for analysis and weeks for processing stored data. ON For sports analytics, it is the main tool that big data allows companies to use historical data and combine it with customer information to predict future events. Big Data is an ever-evolving technology that helps enterprises optimize processes and minimize operating costs.
The combination of real-time data flow technology, artificial intelligence (AI), machine learning (MO), and sports analytics can provide competitive advantages for business. Traditional analytics and business intelligence systems use a deductive approach to analyze data. This approach works well with structured data. Sports analytics, on the other hand, applies an approach to the analysis of inductive reasoning, which works with large data sets obtained using machine learning, robotics, sensors and AI.
He uses algorithms that perform complex calculations on large sets of data and detect relationships and patterns between them. Big data offers the ability to collect, manage, and analyze data across business verticals such as banking, healthcare, and agriculture, so big data has been one of the most popular IT topics for a decade.
Data has always been critical in sports to enable strategic decision-making and other business strategies. Sports generates a large amount of data related to players, team performance, and audience. Big data has made it easier and faster for coaches, team managers and sports associations to analyze the collected data and optimize its use. In addition, they help to change existing business models in which sports are considered as a commercial and technological platform.
It is expected that in order to turn sports arenas into a testing ground for large-scale implementation IoT sports analytics software should include a reliable Wi-Fi network, mobile and cloud computing, as well as [[Internet of Things (IoT)|the Internet of Things (IoT).]]
The Internet of Things will eventually digitize operations at the stadium and provide fans with expanded capabilities. Thus, a smart stadium will use sophisticated technologies and reliable infrastructure to improve its activities in order to attract even more fans to the stadiums.
Market growth drivers:
- Growing adoption of big data and other technologies
- Increased investment in sports technology for data-driven decision-making
- Need to improve player or team performance
Factors that constrain market growth:
- Ignorance of the benefits of sports analytics solutions
- Budget restrictions impede the implementation of sports analytics solutions
- Data Security Issues
Major suppliers in the global sports analytics software market include:
IBM (USA),
SAS Institute (USA),
Salesforce (USA),
EXL (USA),
GlobalStep (USA),
Catapult (USA),
HCL (India),
ChyronHego (USA),
Stats Perform (USA),
TruMedia Network (USA),
DataArt (USA),
Orreco (Ireland),
Quant4Sport (Italy),
Zebra Technologies (USA)
Exasol (Germany).[1]
Notes
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