Application of Data Mining in Technical and Tactical Analysis of Volleyball Match

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Application of Data Mining in Technical and Tactical Analysis of Volleyball Match Jiang Haiyan 1, Feng Jianqiang 2,* 1 Sichuan University, Chengdou 610064, Sichuan, China 2 Xi an University of Technology, Xi an 710048, Shaanxi, China *Corresponding author(feng Jianqiang, E-mail: fengjianqiangsc@163.com) Abstract Combined with the application of competitive volleyball data mining system, this paper analyzes the status quo of competitive volleyball data mining system, system design principles and functional structure of the system. Competitive volleyball data mining system has the function of complex, data sharing, the module is simple, easy to operate and so on. We can use this system to analyse tactics in volleyball matches. In data collection, we look for frequent scripts to improve data collection speed, to meet the real-time requirements of the spot collection. In the data pre-processing, we tackle the issue of data ambiguity caused by volleyball matches by using data mining algorithms. Design experiment shows the correctness and feasibility of the program. Key words: Data mining, Volleyball game technique, Tactical analysis, Application 1. INTRODUCTION At present, the sports powers pay more and more attention to the improvement of their competitive sports level, and constantly increase their manpower, material and financial resources. With the continuous development of computer multimedia technology and artificial intelligence technology, computer video diagnosis system, computer technology and tactics analysis, auxiliary training and competition support system have gradually penetrated into the netting type of ball netting competition and have been paid more and more attention by all countries. At the same time for the technical and tactical analysis of the game, you can make the coaches, athletes know what to do, ready for the game and the command of the spot. From the domestic point of view, the high level of volleyball training in our country, the level of high-tech means used in the competition is not high, coaches, athletes and managers need to strengthen the scientific training awareness, although some volleyball coaches have begun to attach importance to technical statistics in guiding volleyball The role of athletes in training and competition, but basically the usual technical statistics on the spot. Conventional volleyball statistics are mostly done manually by statisticians. There are many shortcomings such as many participants, long time consuming and single feedback, which have obvious hysteresis in athlete's competition information feedback. The coaches, athletes in major competitions should be promptly opponent tactical tactics feedback, timely transformation tactics, adjust the play, and ultimately win. Therefore, based on the volleyball technical and tactical video capture platform, the development of volleyball data mining system is of great practical significance for enriching our country volleyball technical and tactical analysis theory, promoting elite sports teams to prepare for the major competitions and promoting the development of competitive sports in our country. In the volleyball game, the spot technical and tactical data analysis result is an important basis for the coaches to carry out strategic deployment. Therefore, the acquisition of field technical and tactical data, statistics and analysis has become a key decision coaching decisions. Therefore, this article discusses the data mining algorithm used in the tactical analysis of volleyball matches. In volleyball competitions, athletes, through their personal and collective questions, use the rhythms of strength and weakness displayed during the tactics to show the unique rhythm pattern of volleyball. Quick pace of the game means less time-consuming fast, slow pace means that the use of time-consuming, slow speed. The pace of volleyball basically reflected in the tactics and the space, the rhythm of the game can be divided into technical rhythm and tactical rhythm. The influence points can be as follows. Athletes to participate in the mission is to win the game, the game activities, in the process of the body to then withstand extremely nervous, all sorts of subjective and objective conditions change, war frequent ups and downs of the game, in the prosperity and adversity swaps, and basic audience with the different attitudes and tendency, and the reality of these complex is highly stressed and athletes physical and psychological activities together, athletes psychological activity changes directly affect the effect of movement, and then affect the rhythm of the game. A good tactical athlete can timely and correctly predict and predict his opponent's tactical purpose and intention, and also take the opportunity to take reasonable measures to adjust his tactical behavior so that the game can be carried out in an orderly way. 327

The two basic elements of volleyball are physical ability and skill, which need to combine these two different elements. The use of technique and tactics must be based on good physical ability, and the use of techniques and tactics in fierce battle will be converted into a winning score directly. If it is a skilled athlete or a sports team that cannot win, it is often because of physical deficiency, especially when the level is close. Fig. 1 Volleyball Match Comprehensive technology, offensive speed, offensive and defensive conversion fast, fast serve, largescale height, bouncing height, the flexibility of players, tactical and flexible use. The technical requirements and tactical changes of the hidden pass, as accuracy, pass accuracy defensive position and so on set a new height for the physical training of volleyball today. From a single force, the barbell entered a new concept. Special abilities such as special explosive force, small muscle group, core area training, deep muscle strength, coordination ability, speed and other special abilities have mentioned a whole new height. The volleyball skill and the tactical characteristics are the players into the large scale, serve as the first offense. Online competition is more intense, jumping, jumping and changing tactics into three-dimensional attacks. The characteristics of the five points of attack, the rapid application of the development, the specific quality of physical fitness are the direction and trend of development. The use of computers for statistical analysis is a way to solve this problem. But there are also several problems. Data collection. Because volleyball changes the score on a round basis, and during each turn, there are two teams of 12 athletes in the arena at the same time. The volleyball needs a lot of speed, which makes the scorer must be in a very short period of time Record the situation on the court, including a number of players, the ball's landing area, technical and tactical a series of data, demanding real-time. Data analysis. Due to the many tactical changes and contingencies in volleyball, there is a need to prevent the possible emergence of incorrect analytical results based on small amounts of data. The system's ability to analyze data has high requirements. It is more and more necessary to apply the data mining algorithm to the technical and tactical analysis of volleyball matches. This article will propose a program based on Markov process data mining algorithm for the key elements of the victory of the volleyball game. According to the two application difficulties mentioned above, the solutions to meet the real-time requirements in the data acquisition process and the ambiguous solutions to the data pre-processing process will be given respectively. The correctness and feasibility of the scheme will be demonstrated experimentally. 2.Data Mining Algorithm 2.1.Data mining The idea of data mining algorithm based on Markov process is that the mining object is regarded as a system composed of multiple states, the transition process between states conforms to semi-markov process, and the state transition probability matrix is obtained through statistics. The matrix calculates the system reliability, then sets the increment, calculates the system reliability difference, and analyzes the sensitivity of the reliability to the transfer rate. The method of calculating system reliability is as follows. 328

C1n Q11, Q12,..., Q1n C1n C2n Q21, Q22,..., Q2n C2n......... Cnn Qn1, Qn2,..., Qnn Cnn (1) C1n is obtained from the initial state to the success of the system reliability. The system reliability difference is calculated by adding a small increment to each of the state transition probability matrices after calculating the system reliability and then recalculating the system using the state transition probability matrix after adding the increments Reliability, the difference between the reliability of the system before and after the system reliability is the difference, the greater the difference, indicating that the state transition process corresponding to the value of the state transition probability changes the greater the impact on system reliability. When applying this algorithm to a volleyball game, you can think of a series of moves from serve to score and their conversion as a system, with each action related only to the previous one. Think of every action as a state, and the transition between actions as a state transition. According to the principle of the algorithm, the change of state transfer rate can affect the change of system reliability, so the state transition rate of each group of motion can be judged by the sensitivity analysis of the system reliability to each state transition rate. For the last The size of the impact of the results, in order to determine the results of the key action leading to the conversion process. If you set the system failure state is C0, the possibility of system failure is as follows: F10 Y11, Y12,..., Y1n F10 F20 Y 21, Y 22,..., Y 2n F20...... Fn0 Yn1, Yn2,..., Ynn... Fn0 Yij( t) Pij * fi ( t) Where f 1 i R i 2.2.Data collection In order to collect the data needed to implement the data mining algorithm, the recording of the execution of each technical action in the volleyball game is required. As the athletes in the game more changes in tactical and tactical, and various actions in an instant to complete, so the process of recording the game is challenging. In order to solve this problem, Data Volleyball designed by Data Project Company of Italy has designed a process-based script description language. The language uses the mnemonic method to encode the basic technical movements in a volleyball game. However, this script description language is designed in such a way that the recorder records a series of information including player number, technical movement, type of technique, starting area and ending area under the fast changing situation in the competition, which makes the workload of the recorder very hard Big. 2.3.Ambiguous Problems and Solutions We apply the data mining algorithm based on the Markov process to volleyball matches and we must solve the problem of the ambiguity of the action conversion process. The problem arises because of the rules of the volleyball game. Since up to three consecutive actions can be performed at each half-time in the volleyball game, this creates ambiguity in describing the action transition process. (2) (3) (4) Fig 2. Ambiguous generation 329

Fig 3. Detailed Steps for the Generation When the two pass - spike this process occurs, there may be two completely different situations, which is due to the success of the passman to pass the decision, the two possibilities represent different meanings, the path of the ball is also different. This problem will be solved during the preprocessing of collected data. The solution is as follows. 1) Set a threshold. Threshold setting method is: due to the characteristics of volleyball competition, some of the action conversion process occurs frequently, and some of the action conversion process appears only in the race several times. According to the state transition rate of the collected action combination, take a value that can divide the value combination of the state transition rate into two intervals, where the interval containing the state transition rate of the larger value is A interval and contains a smaller value The interval of the state transition rate is the B interval and approaches the maximum threshold of the B interval. 2) For a combination of actions whose state transition rate is greater than the threshold (A interval element), the original meaning is maintained and a reasonable action transition is performed. 3) Ignore action combinations (B-range elements) whose state transition rates are less than or equal to the threshold, or incorporate their values into a combination of actions that are similar in their meaning. 2.4.Representative sampling method Sampling is a classic statistical technique that has been studied for more than a century, and especially random sampling techniques. There are many basic principles (such as the central limit theorem, Chernoff, Hoeffing, Chebyshev, etc.) that describe the effectiveness of random sampling In the field of data management, sampling takes a small subset of data that captures the basic characteristics of the data to represent the total data set, obtains approximate query results based on the sample set, or performs data mining based on the sample set. 3.Data Analysis Fig. 4 Classification of representative sampling methods on data mining 330

According to the above application, the algorithm is implemented. The source of the experimental data is the Athens Olympic Games (2004) women's volleyball final: the Chinese women's volleyball VS Russian women's volleyball team. First, the data in the system running database is integrated and classified to form a new small data warehouse, and then ambiguous elimination of the ambiguous action combination according to the algorithm 1 is performed. Table 1 shows the state transition matrix obtained after data preprocessing. Table 1. State transition rate matrix Action Catch the ball Stalemate Attack Defense Control Success Mistakes Serve 98.2323 0.47 1.31 Serve the ball 23.21 43.19 4.10 12.89 2.39 14.22 Stalemate 12.77 56.22 6.04 24.97 Attack 32.05 11.79 17.31 Defense 38.85 32.05 11.79 17.31 Control 20.21 62.09 1.72 15.98 As can be seen from Table 1, the highest difference is from the spike-defense process. And hanging ball related to several lower. This shows that in this game, the other side of the fierce attack on the effective defense is the key to score, and lob play a small role in this game. Therefore, the suggestions shall be concluded from the following paragraphs. Today's colleges and universities are not only shouldering the responsibility of training comprehensive talents, but they are also important places for scientific research in our country. One of the important purposes for the state to build colleges and universities is to enable colleges and universities to provide technical support and guarantee for the development of various undertakings in our country. Colleges and universities have many professional and the technical research personnel, with many advanced research equipment. However, the current college volleyball research on the development of men's volleyball in our country has far failed to achieve the desired goal. In the volleyball technical and tactical papers, the vast majority did not apply flexibly to volleyball practice. The innovation of the man 's volleyball tactics and tactics in our country must firmly grasp the level of scientific research and comprehensively promote the innovative contribution of university volleyball research to technology and tactics. Therefore, we shall focus on the following features of the activities. The technical comprehensiveness, the rules stipulate, each member must undertake position rotation, not only want to the front row to smash the ball and block, also need to turn back to defend and receive. Which requires the volleyball players must master a variety of the techniques and tactics, such as blocking, pass, spiking, ball, etc., the volleyball players can suitable for any roles in volleyball match, and give full play to the role of the defense and offense. This is an indirect explanation of the overall character of the tactics and tactics of volleyball. Fierce competition, in volleyball competition, in order to then win the competition, both sides will fight fiercely in the competition, compete for every minute and second, and score as much as possible. In such a fierce competition, the use of technology and tactics is then often strong antagonistic, so that we can more effectively attack and defend, and create the conditions for winning games. To ensure the stability of ball catching and serve can effectively improve the quality of a tapping, so it can be said that the stability of ball catching and serve can promote the use of tactics. In practice, the men's volleyball catch and serve should be based on the characteristics of the team and the style of players to make the appropriate adjustments, in order to ensure that each player can play their own advantages and enhance the team's cooperation effect: and to ensure that catch and The main purpose of service quality is to ensure that the team can achieve efficient attack, therefore. We must also constantly improve each defender's own ability and skills, and actively create opportunities to improve the effectiveness of the offensive. In addition, the number of people who catch the ball and serve, it should be based on the actual situation to choose and adjust to improve the actual effect. 4.Conclusion The data mining method proposed in this paper can not only be used for technical and tactical analysis of table tennis matches, but also for technical and tactical analysis of other ball games such as volleyball, badminton, tennis and so on. As long as the system behavior to meet the conditions of the Markov process can be. The experimental results show that this scheme can mine the data of the great significance, and can excavate the key action transformation process. This scheme has a certain effect on the mining technical and tactical information of volleyball matches. In the future, we will validate the proposed methodology. 331

Acknowledgement General Project Funded by National Social Science: A Study on the Cultural Mission and Orientation of Physical Education from the Perspective of Core Values, Project No.: 16BTY070. References Silva, M., Lacerda, D. and João, P.V., 2014. Match analysis of discrimination skills according to the setter defence zone position in high level volleyball. International Journal of Performance Analysis in Sport, 14(2), pp.463-472. Peña, J., Rodríguez-Guerra, J. and Serra, N., 2013. Which skills and factors better predict winning and losing in highlevel men's volleyball?. The Journal of Strength & Conditioning Research, 27(9), pp.2487-2493. Gao, X. and Tang, X., 2002. Unsupervised video-shot segmentation and model-free anchorperson detection for news video story parsing. IEEE Transactions on Circuits and Systems for Video Technology, 12(9), pp.765-776. Moreira, A., Freitas, C.G., Nakamura, F.Y., Drago, G., Drago, M. and Aoki, M.S., 2013. Effect of match importance on salivary cortisol and immunoglobulin A responses in elite young volleyball players. The Journal of Strength & Conditioning Research, 27(1), pp.202-207. Wang, H. and Wang, J., 2014, November. An effective image representation method using kernel classification. In Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on (pp. 853-858). IEEE. Hank, M., Zahalka, F. and Maly, T., 2015. Comparison of spikers' distance covered in elite female volleyball. Sport Science, 8(2), pp.102-106. Viskin, D., Rosso, R., Havakuk, O., Yankelson, L. and Viskin, S., 2017. Attempts to prevent tongue swallowing may well be the main obstacle for successful bystander resuscitation of athletes with cardiac arrest. Heart rhythm, 14(11), pp.1729-1734. Ye, C. and Liu, Y., 2016, March. Research on the influence factors of volleyball passing technique based on AHP. In Measuring Technology and Mechatronics Automation (ICMTMA), 2016 Eighth International Conference on (pp. 556-559). IEEE. Jiao, J., Venkat, K., Han, Y. and Weissman, T., 2015. Minimax estimation of functionals of discrete distributions. IEEE Transactions on Information Theory, 61(5), pp.2835-2885. Laporta, L., Nikolaidis, P., Thomas, L. and Afonso, J., 2015. Attack Coverage in High-Level Men s Volleyball: Organization on the Edge of Chaos?. Journal of human kinetics, 47(1), pp.249-257. Medeiros, A.I., Mesquita, M.I., Marcelino, O.R. and Palao, J.M., 2014. Effects of technique, age and player s role on serve and attack efficacy in high level beach volleyball players. International Journal of Performance Analysis in Sport, 14(3), pp.680-691. YIN, H.M., SUN, P., ZHANG, M., LIANG, Z.J., YUAN, F., GU, S. and CHEN, H.W., 2015. Core Elements of Physical Fitness Specific Training for Volleyball Players. Journal of Beijing Sport University, 11, p.020. Gao, X., Xiao, B., Tao, D. and Li, X., 2010. A survey of graph edit distance. Pattern Analysis and applications, 13(1), pp.113-129. de Aquino Leal, A.V. and Ferreira, D.J., 2016. Learning programming patterns using games. International Journal of Information and Communication Technology Education (IJICTE), 12(2), pp.23-34. Hodge, C., Pederson, J.A. and Walker, M., 2015. How do you like my style? Examining how communication style influences Facebook behaviors. International Journal of Sport Communication, 8(3), pp.276-292 332