Last season the Portland Trail Blazers achieved great results in the NBA. They may not have won the ring, but they surprised everyone by employing a very good technical strategy that won them several matches. What were the keys to their success? First, they had a great team; second, they had something nobody else had: data.
Technical decisions such as throwing, passing or going for a certain move were predicted on a board and tablet. This device collected all court data and turned it into useful information to make decisions in real time.
Show time is now big data time
Without doubt, technology is also now part of sports. For instance, soccer has pioneered systems for better refereeing work. The NBA approaches this in a different way: they want to use information from each match to improve the game and design better tactics.
Portland’s case should be studied: replays and player information were used to better analyze moves and determine how to attack, who to pair for defense purposes, etc.
If we think about all the information generated from a basketball match (ball possession, shooting ratio, areas where the ball is shot from), when a group of assistants processed it in real time, the team had a competitive advantage.
But theirs was not a technical break-through. They simply used existing technology and applied it to a very clear purpose: to find out more about what was in front of their eyes and use it. A lot of teams followed their example and it is increasingly common to see how a tablet is as important as a board.
This technology is clearly focused on the athletes, and shows that Big Data can adapt to different situations. But it can be used in other ways – the NBA has closed agreements with technology giants such as SAP to provide this information to users.
BBVA has been part of this transformation for a while now. Using beacons, stadia try to customize user experience even more; also, with information from each supporter, their phone can receive potentially interesting information.
Sports fans are always eager for information and they can now have access to more real-time information. Even though they will not be able to maximize this information as much as coaches, they are still clearly interested in Big Data, in extracting information and ultimately using and applying it.
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