Big Data is a very simplified concept that refers to an ensemble of data that cannot be stored in traditional databases because of their complexity, speed, and most of all, the volume of information. The amount of data known as big data needs other types of storage that are mostly organized in cloud services and other platforms of storage. A common mistake is thinking about Big Data as a generic tool that serves an objective. It’s rather an array of tools and platforms that are based on Big Data principles.
Big data now has a long history of applications in different industries and most of them boast of an immense quantity of data points that can be exploited.
But the sports industry is still young in the world of Big Data. And this doesn’t mean that a sports discipline doesn’t produce big volumes of data (a single Formula 1 race can produce millions of data items), but rather, sports institutions haven’t yet exploited all the capabilities that the data they gather has to offer them. Some teams and associations don’t even collect data on their activity.
Today we will be reviewing the different implementations that sports entities (clubs, franchises, and actors in the sports industry) are exploiting for their activities.
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Big Data to gain a competitive edge
The physical capabilities of the human being are being tested with time and soon we will reach a limit in terms of the boundaries where athletes can improve their bodies. This can be seen in professional sports as teams and individuals are each time more equal in terms of their performances.
This is why sports are looking into Big Data to produce that aggregate value that would take a team that centimeter farther that will tip the balance in their favor.
GPS tracking, performance analysis, rival scouting, and evaluation of game plans, are all being analyzed by “data analysts” and “data engineers”. These are new positions that sporting institutions are bringing into their teams to manage all the “eventing” data, meaning all the data points that can be extracted from a determined sport.
In the context of collective sports like baseball, basketball, or football, Big Data is being used extensively for player scouting. Looking into large sets of data for individual players to determine characteristics and information that interest the team in question. This reduces the uncertainty risks of buying a player that won’t perform in a determined tactical context or who won’t have chemistry with the rest of the team.
Companies like Statsbomb and Opta have been precursors in the collection of eventing in sports like football and now work with clubs all around the world, providing data sets and information upon request.
Big Data for commercial interests
At the same time, Big Data can be very useful for sporting organizations in the consecution of bigger sponsorship deals as well to better understand the consumption preferences of their fans, who are in the end their main clients.
One of the most popular teams in the world, FC Barcelona, has developed a fan membership that costs around 50 euros per year. The membership grants discount ticket prices, exclusive access to content from their team and other advantages.
The idea behind the membership is to collect data from their fans, to better understand them, to know what they want to consume in order to produce compelling content and products for them.
Sources from the Catalan club mention that only a 3% of their total fans will ever have the chance to go to their stadium and watch a game live in the Camp Nou. This means that they must find ways to capitalize on the 97% remaining and Big Data will help in this mission.
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And what about other industries?
There are many “side actors” in the world of sports that have Big Data as their main component in the development of their work.
Sports betting platforms are the perfect example of how Big Data can have a profound impact in an industry that’s strictly related to sports.
Years before Big Data, bookmakers would have to fixate on external factors like the win ratio, the physical traits of athletes or other criteria that very often isn’t 100% reliable.
Now, the information and data they manage allows betting platforms to produce complex algorithm models to offer their clients the best possible odds without jeopardizing their business.
And now users can even find specialized betting platforms such as SBO that recommend the best betting sites for every person depending on what they’re looking for. You can find betting platforms specialized in result forecasting and others on football transfers for example. Plus, sites like SBO offer sites with free bets, bonuses, and advice on how to bet effectively and safely.
Big Data has provided an array of tools to improve most businesses and even if sports haven’t got to the levels of telecoms or financial companies, the way is paved to continue to exploit the data in profitable ways for both organization and fans.
