In modern technology, big data is gradually penetrating into the field of sports, big data technology in the world's number one sport soccer is widely used. The big data is used in the world's most popular sport, and it's used in a variety of ways, including the introduction of the Lunar New Year's Big Data Backstage and the training and competition related content, and the introduction of the big data of how the medical record of the players' injuries and how to take measures to prevent the players' future injuries and illnesses.
If talent determines whether a player can go on to a professional soccer career, then injuries will determine how far a player can go. There are too many talented players because of injuries and failed to reach the height of people's expectations, "Alien" Ronaldo, 20 years old on the title of World Football Champion, no injuries, he may be Pele, Maradona, after another king of the ball; Van Basten, the Dutch Three Musketeers dancers on the front line, no injuries, he may lead the Dutch Van Basten, the Dutch Three Musketeers dancer on the front line, without injury, he may lead the Netherlands to completely remove the "uncrowned king" hat; Kaka, the last Ballon d'Or winner before the era of Melo, no injuries may become a triad of the Jade Warriors. How to make the youth training stage of the players away from injuries, the smooth growth of a professional player, medical support is also one of the important role of the background of big data.
Application of big data in healthcare
Soccer players may suffer from a variety of injuries on the field and training ground, including a variety of muscle and soft tissue injuries caused by frequent running, as well as broken bones and even concussions caused by scrambling, and so on. Injury categorization in the first interface of personal big data health care, athletes almost all common conditions through the human musculoskeletal diagram is divided into categories, players injured team doctors will be the player's injury type and diagnosis of different categories into the system. The big data system will automatically record the player's injury time (the team doctor will mark the player as healed, the injury record will automatically stop, and the injury time will be reflected in the player's attendance time), and the relevant team doctor will record the player's treatment plan and related processes in the process of the injury into the big data system. For more serious injuries, such as broken bones and torn ligaments, players can go to hospitals in China that have specialized sports medicine departments for treatment, and the player's image data will also be recorded in the big data background, and the player will also be able to view his own injury records and the team doctor's treatment plan as well as dietary and recovery training recommendations through his personal big data background account. With the help of both the professional hospital and the school's athletic rehabilitation center, players will be able to recover from their injuries faster by following the doctor's instructions and exercising actively.
Big Data creates an injury catalog for every team and player in Luneng Youth Training. It assists in the management of injuries and the healing process, and it enhances the efficiency of athlete treatment by recording data on each athlete to help physiotherapists monitor key health data. The Catapult's wearable device, which we mentioned in the training section, is equipped with gyroscopes, accelerometers, and other sensors, and is able to monitor running distance, speed, change of direction, acceleration, deceleration, bouncing, heart rate, and a number of other data, which is actually not only helpful for improving the quality of training, but also for transmitting the data to the big data backend, while allowing the team doctor and the athletes themselves to see how much exercise is being done for each player, and to know the impact of exercise on the player's performance. The data will then be transferred to a big data backend, allowing team doctors and athletes to see for themselves how much each person is doing, and how the exercise is affecting the players' health.
Big data has a lot to live up to in healthcare
Exercise monitors can help to identify changes in an athlete's performance at an early stage, and big data can help to visualize them by organizing the data from the monitors to show, to some extent, trends in health and increases in the risk of injury. But excessive exercise is also a significant cause of injury, and the line between raising an athlete's exercise threshold and excess leading to injury is not clear.
The current data research service for sports injury prevention is still in the exploratory phase, and the subjective willingness of players and the empirical judgment of coaches are still the main indicators of injury prevention and recruitment. In the introduction of Henderson's transfer operation, Ferguson because of his running posture problems and rejected the deal, and later Henderson suffered plantar fasciitis also proved the vision of Lord Ferguson, but let everyone did not expect to later change the way of playing Henderson, but to lead the Liverpool to get the Gerard period did not take the Premier League title, and then look at the United's current midfielders, to give up the introduction of the Henderson is right or wrong, whether it's a personal decision or big data, I'm afraid no one can say.
Former Manchester City captain Vincent Kompany was out for six weeks in the 2015/16 season with a muscle strain, and after coming on as a substitute for a few minutes on Boxing Day, he immediately left the field with a muscle strain, which was a huge disruption to the team. Kompany belongs to the habitual muscle strain players, Manchester City staff combined all the data of Kompany's injuries in the past 5 years, after repeated analysis, it is believed that he needs to be allowed to participate in a few stable low confrontation matches, in order to adapt to the rhythm of the official game, so as to avoid repeated injuries. In a similar vein our big data plays the role of a place to provide experience, where the team manager can better determine the type of injury a player has by looking at the player's injury history in the big data backend and determining whether the player can come on in a key game and contribute to the team's victory by how they perform in training.
The core of the application of big data in sports training is prediction, which is essentially finding patterns in the data and improving cognitive abilities to make predictions and guide decisions. The traditional manual recording of players' training performance is susceptible to subjective factors, excessive workload, inaccurate statistics, and data retention is not easy, etc. The big data system we are using now is more capable of instantly and comprehensively generating a sufficient volume of data with training guidance value.
We believe that in the future, more professional technicians will be able to analyze large amounts of historical and real-time data to accurately predict, track, and calculate injury risk, and professional sports medicine teams will be able to help players take timely intervention and treatment measures.