Northbrook, IL 60062 -- (SBWIRE) -- 09/12/2023 -- The global 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, according to research report by MarketsandMarkets™.

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.

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243 - Tables
51 - Figures
250 – Pages

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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.

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Regional Analysis for Sports Analytics Market:

Europe boasts the most sophisticated and well-known football associations and clubs in the world. Different European football leagues, such as the Barclays English Premier League, Bundesliga (Germany), Scottish Premier League (Scotland), and La Liga (Spain), play at frequent intervals, and their managements invest extensively in technologies for efficient game and individual tracking.

The adoption of sports analytics solutions is growing at a rapid pace in the UK due to a rise in investment by teams, sports associations, governments, and management in technologies. The major reason behind the adoption of sports analytics solutions is increased awareness about science to keep track of players' performance and improve it over time, thus creating a competitive edge.

Germany is considered one of the world's foremost countries. Most active players adopting new technologies are from Germany, which is deemed as a leading country for investment.

France is expected to come up with some opportunities in sports analytics solutions in its forecast period. The team members in this region are very aggressive and easy to adapt to any change. There are some associations that are using this solution to monitor their health in a training session so that they can avoid any problem and perform better over time. This is expected to drive the adoption of the sports analytics market, which will help grow the economy.

Key Players:

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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Key Dynamic Factors For Sports Analytics Market:

The sports sector is producing a huge amount of data, from player performance analytics to metrics for fan interaction. Insights regarding player performance, injury avoidance, and fan engagement tactics are being gleaned from this data.

Rapid technological improvements have improved sports data collection possibilities, including wearables, sensors, and high-speed cameras. For analysis, these technologies offer more precise and current data.

Optimisation of Player Performance: Teams are increasingly employing analytics to enhance player performance. This covers training, rehabilitation, and injury prevention programmes in addition to in-game tactics. Coaches and trainers can make better judgements thanks to data-driven insights.

Fan Engagement: To improve the fan experience, sports teams and organisations are using analytics. This entails customising the content, ticket prices, and marketing initiatives based on the tastes and actions of the audience.

Industry of Sports Betting: The demand for real-time data and analytics has increased as a result of the expansion of the sports betting sector. With the goal of providing rapid and accurate data for odds computation and in-game betting, sports analytics providers are collaborating with betting organisations.

Video Analysis: More advanced video analysis tools are enabling teams to analyse game footage and player movements in-depth. This helps in scouting opponents, formulating strategies, and developing players.

Sports analytics are being used more frequently for injury management and injury prediction. Teams can lower the risk of injuries and increase player availability by analysing player biomechanics and health data.

Esports Analytics: Esports, or competitive video gaming, has experienced rapid expansion, and analytics is essential to comprehending player performance and tactics in this young industry.

Regulatory Changes: The adoption of analytics systems is impacted by regulatory changes in sports leagues, such as the use of player monitoring technology in-game. Leagues are adopting data-driven insights more frequently to improve fairness and competition.

Global Expansion: New markets and audiences have been produced as a result of sports' globalisation. Organisations can better understand and serve their various fan bases' interests and behaviours by using analytics.

COVID-19 epidemic: The epidemic messed with sporting events and made businesses reconsider their fan engagement strategies. Analytics, such as remote player monitoring and virtual fan experiences, helped organisations respond to these developments.

Privacy and data security have grown in importance as a result of the increased gathering and usage of personal data in sports analytics. Regulations governing data protection must be followed.

AI and Machine Learning: By combining artificial intelligence (AI) and machine learning with sports analytics, new predictive and prescriptive insights are made possible, improving a variety of sports-related decisions.

Innovation in sports analytics is being fueled by startups, which are offering cutting-edge tools and methods that are upending the market's established competitors.

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