Big data and data analytics are becoming widely popular terms in today's technologically dominant landscape. Numerous organisations and sectors are embracing these emerging technologies to make fruitful use of data. The sports industry is also leveraging big data analytics to revolutionise sports.
Data analytics and sports might seem completely unrelated. But, data analytics has proven useful in improving game quality, fan experience and player safety. Nowadays, sports analytics are taken very seriously by professional teams, managers, coaches and players.
Data analytics jobs are in huge demand these days. These jobs pay well and provide several opportunities to aspiring data scientists. If you are a sports fan, you can now have a rewarding career as a data analyst. Sports analytics is the perfect career choice for you, allowing you to pursue your love for sports. However, since data analytics is a technical field, you need to have proper data analyst training.
How is sports analytics changing the game?
It helps coaches make decisions regarding the recruitment of athletes.
Player recruitment is an important part of any sport, particularly at the professional level.
Many modern sports franchises are leveraging data analytics to recruit the right players for their teams.
Data is being used to identify and hire talented but undervalued players.
Universities are also using data analytics to discover potential upcoming athletes. This allows them to understand where to invest their time and efforts.
It helps broadcasters create a better viewing experience for fans.
Sports commentary makes watching a sport more fun. The broadcasters provide stats and facts for viewers to understand the importance of each event. This makes the viewing experience more compelling. This is made possible by big data analytics.
Big data is also being used to increase live attendance in stadiums by satisfying fans and enhancing their overall experience of watching a game live. This can be done by analysing which games have better chances of selling swiftly and prompting frequent audiences to buy tickets.
Another way to compel audiences to watch games live is to improve the supply of items that are in high demand. This can include merchandise, eatables, etc., which can improve the viewer experience.
Big data can also be useful in tackling the factors which affect the viewer experience negatively. For instance, it can save viewers from the struggle of finding a parking spot by carrying out traffic analysis.
It is used to create better sporting strategies.
Strategy plays a significant role to win a game. Be it an individual sport or a team sport, players cannot compete without a strategy in mind.
Coaches make use of big data to create personalised winning strategies for each player and the team as a whole. For example, Liverpool FC’s coach used data analytics to compete against opponents and emerge as winners of the Premier League.
It helps in live data collection.
Data like speed, distance, mileage, etc. is difficult to gather manually. However, with wearable devices operated using artificial intelligence and machine learning technologies, vital data can be collected in real-time.
The devices are worn by players or attached to their clothes to keep track of player performance and fitness variables like heartbeat, speed, etc.
This data can help coaches in preparing an ideal fitness plan for players and improve their safety.
RFID tags are also attached to players or their sports equipment to collect crucial data.
It allows better judgment.
Many times, a situation occurs where the referees might find it challenging to take a decision. Thus, they might end up taking the wrong decision. This impacts the whole game and demoralises the players.
With big data and analytics, sports authorities now make use of devices that can track data which is difficult to be observed by the human eye. For example, it can give information on a strike or a ball hit that could be missed by referees.
Sports analytics is a relatively new field and the sports industry is still in the process of optimising its applications. Thus, it has a huge scope for research and development.
However, data analyst training is necessary to enter this job market. Our team at Imarticus Learning has designed an data Analytics and Machine Learning course to kickstart your data analyst career. Our Postgraduate Program in Data Analytics and Machine Learning comes with guaranteed interview opportunities and extensive career services. Graduates and professionals (with up to 5 years of experience) having a technical background are eligible to apply.
Sports analytics is an upcoming and interesting area of work. Join the big data revolution to make sports more fair, entertaining and competitive.
