Simulative analysis in competitive sports can provide prospective insights, which can help improve the performance of players in future matches. However, adequately simulating the complex competition process and effectively explaining the simulation result to domain experts are typically challenging. This work presents a design study to address these challenges in table tennis. We propose a well-established hybrid second-order Markov chain model to characterize and simulate the competition process in table tennis. Compared with existing methods, our approach is the first to support the effective simulation of tactics, which represent high-level competition strategies in table tennis. Furthermore, we introduce a visual analytics system called Tac-Simur based on the proposed model for simulative visual analytics. Tac-Simur enables users to easily navigate different players and their tactics based on their respective performance in matches to identify the player and the tactics of interest for further analysis. Then, users can utilize the system to interactively explore diverse simulation tasks and visually explain the simulation results. The effectiveness and usefulness of this work are demonstrated by two case studies, in which domain experts utilize Tac-Simur to find interesting and valuable insights. The domain experts also provide positive feedback on the usability of Tac-Simur. Our work can be extended to other similar sports such as tennis and badminton.

To analyse the technical strength of elite table tennis players more accurately, a model of stroke performance relevance (SPR) was proposed in this study, and 40 matches between Chinese male elite players and players from other countries were selected as samples. Compared with other match analysis methods in table tennis, the main advantage of the SPR model is that a) the calculating the performance relevance of each stroke can more completely reflect the technical and tactical advantage or disadvantage of both players than can the traditional analysis methods. b) In addition to the contribution (score) and responsibility (loss) information, the SPR value includes information on the orders of stroke and scores, which can better reflect the role of various game actions in different game periods. This is the most important difference between the SPR model and traditional match analysis methods. In addition, the SPR analysis showed that the first three strokes, the three techniques (“topspin + attack”, touch short, twist), and the three placements (long backhand, long forehand, long middle) in a table tennis match had an important impact on the game results. The technical strength of Chinese players was significantly better than that of players from other countries.

Tactics are one of the winning factors in table tennis matches because they can reflect the technical strength and strategies of players. However, the current evaluation method of tactics is relatively simple, and it can be difficult to distinguish the pros and cons of different tactics. To solve these issues, this study used information from 60 matches played by top-25 men’s right-handed shake-hand offensive players as samples and proposed a tactical benefit algorithm and a visible evaluation model to analyse tactical performance. The model could help coaches and players find meaningful tactics quickly and easily and make reasonable comparisons between them. The results showed that 1) the numbers of tactics based on the tactical association-mining model and the L-shaped curve were 37 in the first six strokes. Among them, there were 9 selected tactics in the first to third strokes, the third to fifth strokes, and the second to fourth strokes, respectively, and 10 selected tactics in the fourth to sixth strokes. 2) The visible evaluation model of tactical benefit can determine the difference between the frequency, scoring rate, and benefit of different tactics as mapped into the model as well as quickly and effectively discover the distribution of tactics and measure the advantages and disadvantages of tactics from multiple dimensions.

Conventional racket sports training highly relies on coaches' knowledge and experience, leading to biases in the guidance. To solve this problem, smart wearable devices based on Internet of Things technology (IoT) have been extensively investigated to support data-driven training. Considerable studies introduced methods to extract valuable information from the sensor data collected by IoT devices. However, the information cannot provide actionable insights for coaches due to the large data volume and high data dimensions. We proposed an IoT + VA framework, Tac-Trainer, to integrate the sensor data, the information, and coaches' knowledge to facilitate racket sports training. Tac-Trainer consists of four components: device configuration, data interpretation, training optimization, and result visualization. These components collect trainees' kinematic data through IoT devices, transform the data into attributes and indicators, generate training suggestions, and provide an interactive visualization interface for exploration, respectively. We further discuss new research opportunities and challenges inspired by our work from two perspectives, VA for IoT and IoT for VA.

Currently, technical and tactical analysis has become an indispensable task for sport in many countries. Many studies analysed players’ specific technical and tactical factors, but it is rare to quantitatively analyse the importance of table tennis players’ shot effectiveness. This is the first study to propose the new concept of “shot effectiveness model”, and the purpose of this study is to explore the structure of the shot effectiveness model for elite table tennis, including the importance degree of shot effectiveness, and the relationship between them. 258 matches were selected between the top 50 players in the world from 2019 to 2021 as samples. Multiple regression analysis was used to obtain the standard regression coefficients and game simulation, and the total decision coefficient (TDC) was used to evaluate the importance degrees of shot effectiveness (SE) on match results. (1) There was little difference in the importance degree of each shot effectiveness between men and women players. (2) The importance degree of the first and third shots (SE₁), the second and fourth shots (SE₂), the fifth and after shots (SE₃), and the sixth and after shots (SE₄) for both men and women players account for approximately 25%, 35%, 22%, and 16% respectively. (3) There was little difference in the importance degree of each shot effectiveness between Chinese women players and women players from other countries and regions with the same importance order of SE₂ > SE₁ > SE₃ > SE₄. However, the structure of the shot effectiveness model for men players was quite different from that for women players. (4) There is a compensation effect between shot effectiveness of table tennis players, and the total evaluation score of 12 and 13 is the dividing line for success or failure in both men and women matches. TDC could well reflect the important degrees of each shot effectiveness in various ways on winning probability in table tennis matches. And this study compared the importance of several types of players’ performance on the probability of winning a match. In addition, we found that there is a compensation effect between shot effectiveness of table tennis players, and the magnitude of this effect will vary according to the type and level of shot effectiveness.