How to use big data in sports？ The NBA team told you

　　Beijing, February 20 (Reporter Lu Hongqiao) According to the voice of the economy "Tianxia Finance", hot big data is now blooming everywhere, and it has been applied in many industries such as finance, consumption, medical care, transportation and so on, which has exerted great value. In fact, as an inexhaustible "gold mine", big data has many unknown magical uses.

　　NBA teams use big data to train.

　　Anyone who often watches the American men’s basketball professional league, that is, the NBA, knows that the Warriors from California have been doing well in recent years. After the media disclosure, people realized that this team has been training with various big data means. It turned out that the home of the Warriors was near Silicon Valley, and a large number of technology companies took the initiative to find the door and provide black technology to the team. Liu Xiao, vice president of Qianjun Sports, said that although not every team has such conditions, it has become a consensus that big data technology can improve performance. In football, basketball, volleyball and other projects, more and more teams collect big data.

　　Liu Xiao said: "It is mainly collected by two means. The first is wearable devices and various sensors all over wearable devices. The second way to collect data is to use high-speed cameras. "

　　The collected data is very rich, including heart rate, blood pressure, running distance, running route, energy consumption and so on. According to a sports big data industry insider, some teams have collected more than 100 items of data, and they are still increasing. "Data such as what to eat for three meals should be collected. Some teams that pay great attention to science and technology have to fill out a questionnaire before getting up in the morning. How do you feel after getting up? What kind of dream did you have last night? Do you remember, was it a nightmare or a dream? You have to look at these things. These things are the embodiment of your physiological indicators. "

　　Sports big data brings "competition" outside the stadium.

　　Big data is becoming another arena outside the arena. In addition to competing for data collection, each team has to compete in data processing. For example, some teams just focus on a physiological index, and dozens of big data companies provide them with analysis services at the same time. For example, Liu Xiao said that a data analysis result is sometimes a big technical and tactical advantage.

　　Liu Xiao said: "For example, on the basketball court, whether it is better to throw a three-pointer or a two-pointer is better. In an era without data support, everyone relies on experience to make decisions. After the introduction of data, through data analysis, we found that the benefit of voting for three points is greater than that of voting for two points. If you push it back to the training session, you will adjust the players in a targeted manner. Now the whole NBA is playing more and more outside the three-point line. "

　　Industry insiders also told reporters that in addition to helping the team improve its training methods, another major role of big data is to improve predictability and let the team balance its performance and commercial interests. "If a player is injured, he should know how long it will take to recover and how to avoid the least injury. Therefore, many players seem to be good on the court, but they must be replaced because there have been such predictions before, but for other reasons he has to play. "

　　Big data has a broad application prospect in the field of sports.

　　Although there are already many application scenarios, Liu Xiao said that there is still much room for improvement in the application of big data in sports.

　　Liu Xiao said: "Now, in many application fields, firstly, the foundation of our data collection is not solid. Second, we haven’t used data as a tool to guide the whole sport, to guide events and athletes to improve their economic level and state. Therefore, there is a lot of room for improvement in the application of big data in sports. "