The Application of Data Mining in Sports Events

Abstract

In recent years, data mining has played a more and more important role in all fields and had an increasingly greater influence. By using association analysis of data mining and classification algorithm, this paper analyzes the result data of volleyball games, which were held in a university’s volleyball venue during 2010 Guangzhou Asian Games. It studies the correlation between different competing countries, competition time and audience number and make correlation analysis between the competition results and athletes’ physical qualities. These results may be significant for scientific game guidance and athlete selection. With the development of China’s competitive sports and the constant improvement of athletes’ competitive levels, a higher request was also put forward towards sports training and competition efficiency. Today, in the age of Internet and technology, both the training of competitive sports and the selection of athletes need a more scientific prediction, management and program. However, the data management of our country’s competitive sports is largely at a state of disorder at present: modern information technology and various data of country’s competitive sports development, which was accumulated for years, have not been fully used; regularities and modes other than objective experience have not been mined efficiently neither. In these 10 years, the skill of data mining and analysis becomes increasingly mature. If it is applied to the training and the competing process of athletic competition, they will be more scientific and standardized. Data mining is defined as mining the hidden, unknown but potentially useful information from plenty of actually applied data, which is massive, incomplete, noisy, ambiguous and random. These hidden, unknown, but potentially useful information can be presented in various forms such as concept, rule, mode and law. Simply put, data mining is a deep-level data analysis approach. That is: data mining is a kind of information technology which is not limited to search and access, but find potential links between different data. This paper analyses the result data of volleyball games, which was held in a volleyball venue of a university during 2010 Guangzhou Asian Games, using Apriori algorithm and ID3 algorithm. It studies the correlation between different competing countries, competition time and audience number and the correlation between competition results and athletes’ physical qualities respectively. These results may be significant for scientific game guidance and athlete selection. 2. The application of data mining in the data analysis of Asian Games’ volleyball matches 2.1 Experimental data