Big Data is a priori concept that refers to an increasingly wide range of tools that gather the information that can be analyzed, sold, and licensed (for profit) to third parties.

 

According to George Arabatlian - the head of FeedConstruct, big data and artificial intelligence are revolutionizing professional sports. Leagues and sports organizations are increasingly hiring machine learning experts to help optimize each ounce of collected data from player evaluation to fan engagement and enhanced betting experience. 

 

To take advantage of the available analytics, federations and leagues often turn to sports data businesses like FeedConstruct and BetConstruct – companies that can tailor programs and services to meet individual needs.

 

This article will showcase some of the state-of-the-art solutions for a range of critical challenges in the emerging area of sports analytics.

 

How Are Big Data And Analytics Impacting Sports?

 

Data and sports go hand in hand. Thanks to technological advances, particularly in player tracking, more advanced analytics are possible.

Players, team managers, coaches, and fans rely on sports analytics for making decisions or developing strategies to win games.

 

Data science isn’t just used in sports to fuel competition between professional players; it also plays an essential role in improving game quality, fan experience, and player safety. 

 

Sports analytics include statistics of players, weather conditions, the team's recent wins/losses, etc. With this data, sports organizations can create predictive machine learning models to make informed decisions on behalf of the management. Moreover, sports analytics can be used for the following purposes: 

 

Explore the Impact of Analytics 

 

Data analysis helps sports in many different ways. It changes the way sports management personnel approaches business not only on the field but also around the office and even in the medical tent.

 

On-Field Performance 

 

Athletes use data to track their performance on the field and discover which type of play is best to run in certain situations. Soccer teams could use data analytics and advanced camera systems to track the movements of every player on the pitch, determining who uses their movements most efficiently, who’s completing the best passes, and who has the most positive impact on possession.

 

Healthcare and Rehabilitation

 

Healthcare, athletics, and technology are all intersecting. Several devices help monitor athlete health and vital statistics, as well as programs that compile all those data points and identify areas of concern. 

 

Leveraging The Power Of Big Data In Sports Betting

 

Big Data algorithms use powerful analytics to predict the possibilities of future events with absolute accuracy, becoming hugely important for the betting industry. 

 

The methods associated with big data are changing the sports betting industry by creating partnerships between professional sports leagues, sports data providers, and betting operators. All while enhancing experiences for users and simultaneously protecting the integrity of national and international sports betting.

 

Moreover, many bettors are attracted to sports gambling because of the vast amount of information and analytics at their disposal when making decisions.

Technology And Sports Analytics

 

To enhance technological advancement in collecting big data from sports and distributing it across various sports organizations with various goals, FeedConstruct has innovated data collecting technologies. 

 

To showcase the effort put into those technologies, it is mandatory to acknowledge 2 of them: DeePro and AJNA.

 

 

DeePro is a data-collection software developed in collaboration with basketball insiders with the specific aim of meeting the demands of the modern age of sports data. Driven by the growing demand for real-time facts and figures in a range of fields, DeePro quickly and efficiently collects crucial player and match data. This valuable information is then immediately curated, analyzed, and used for internal and external purposes.

 

The sports data collected by DeePro includes:

 

• Match-related data (venue location, crowd size, names of the referees, etc)

• Time-related data (Match start/end, quarter start/end, etc) 

• Full live data per team and each player

• Classification of shots, including rebounds

• Coordination of shots - on and off-target

 

DeePro is the perfect tool to create new betting markets and even improve sports analytics for making decisions. 

 

 

AJNA is the most advanced scouting tool that uses Artificial Intelligence to deliver post-game statistics. With an 8k ultra wide-angle view, time-lapse recording, multi-cam input, and advanced player tracking it can fix tiny details and fast actions on the field. It is different from any other camera because it provides real-time biodata of each player with no external computation unit or operators.

 

To meet the needs of big data in sports betting, the technology was built with three aims:

 

• To develop statistical information for teams and coaches for tactical analysis

• To create augmented information and add more information to live streams

• To collect individual statistics and create additional opportunities in sports betting

  

Conclusion

 

Data is the world’s most valuable resource. In sports, big data can help determine future player and team performance, fuel the betting industry, and boost technological advancement. Enhanced Artificial Intelligence and improved machine learning models have boosted the capacity for updating the performance of the teams and are the future of sports analytics.