Table Tennis Matches Research Articles

The development strategies of amateur table tennis matches in China based on the SWOT-AHP model: a case study in Shanghai.

Given the significance of amateur sports matches in health promotion and city culture construction. It is essential to systematically analyze the organizational mode of city amateur matches and propose development strategies. This study aimed to investigate the sustainable development strategies for city amateur matches in China. This study adopted a hybrid model of combined SWOT and the AHP analysis, using the Shanghai City Amateur Table Tennis Matches (ATTM) as a case study. Results showed that 20 factors of the SWOT analysis were included, and the ranking of weights of the SWOT group are Strengths, Opportunities, Weaknesses and Threats, respectively, and the strategic vector (θ, ρ) are (74.21°, 0.5861). ATTM should adopt the S-O pioneering strategy and leverages its advantages and opportunities to promote further development. The findings indicate that ATTM with advanced organizational mode, has good internal strengths and external opportunities, which can enlighten the development of amateur table tennis matches for other regions and countries. Future research should apply the hybrid model to a broader range of events and conduct comparative analyses across countries and regions.

A Semantic Web-Based Approach for Bat Trajectory Reconstruction With Human Keypoint Information

Restoring the trajectory of a bat from a table tennis match video is critical in analyzing a table tennis technique and conducting statistical analysis. However, directly bat location detection in each frame is challenging due to changing shapes caused by varying movement directions and speeds, leading to ambiguity. This paper develops a novel two-stage method. The first stage utilizes YOLO for bat detection in each frame, followed by filtering out erroneous candidate boxes. In the second stage, the authors use a temporal prediction model that integrating human keypoint information and interpolation to reconstruct a complete bat trajectory with minimal errors. The method's effectiveness and performance are evaluated on our video datasets. The evaluation results demonstrate that the proposed method outperforms traditional methods on precision performance metrics. The error screening algorithm improves precision score to nearly 1. In addition, the method has the recall score 22.3% higher than YOLO 's and also 1.4% higher than that of YOLO with cubic spline interpolation.

Spin measurement system for table tennis balls based on asynchronous non-high-speed cameras

Abstract The spin of the ball plays a crucial role in table tennis tactics. However, it has rarely been measured and reported for the broadcast audience to better understand table tennis matches. This paper introduces a system designed to measure the spin of a table tennis ball without using electrically synchronized shutters or high-speed cameras. The system employs multiple unsynchronized cameras to detect the logos printed on the ball and estimates its three-dimensional translational motion to determine the spin rate (rotational velocity expressed in the revolutions per unit time) and spin axis (imaginary line around which the ball rotates). An experimental analysis indicated median errors of 0.78 rps and 12.5° in spin rate and axis, respectively. Additionally, the system exhibited sufficient resolution to analyze the spin rate and axis of a service ball in table tennis, distinguishing between spin axes that differ by 30° with 95.8% confidence. The developed system was used in the Japanese T-League to report the spin of several services after the live streaming of matches. The developed system successfully measured the spins of 92.1% of the served balls, confirming that the system has sufficient capability to feedback spin data immediately after a match.

Optimization of table tennis target detection algorithm guided by multi-scale feature fusion of deep learning.

This paper aims to propose a table tennis target detection (TD) method based on deep learning (DL) and multi-scale feature fusion (MFF) to improve the detection accuracy of the ball in table tennis competition, optimize the training process of athletes, and improve the technical level. In this paper, DL technology is used to improve the accuracy of table tennis TD through MFF guidance. Initially, based on the FAST Region-based Convolutional Neural Network (FAST R-CNN), the TD is carried out in the table tennis match. Then, through the method of MFF guidance, different levels of feature information are fused, which improves the accuracy of TD. Through the experimental verification on the test set, it is found that the mean Average Precision (mAP) value of the target detection algorithm (TDA) proposed here reaches 87.3%, which is obviously superior to other TDAs and has higher robustness. The DL TDA combined with the proposed MFF can be applied to various detection fields and can help the application of TD in real life.

P2ANet: A Large-Scale Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos

While deep learning has been widely used for video analytics, such as video classification and action detection, dense action detection with fast-moving subjects from sports videos is still challenging. In this work, we release yet another sports video benchmarkP2ANetforPingPong-Action detection, which consists of 2,721 video clips collected from the broadcasting videos of professional table tennis matches in World Table Tennis Championships and Olympiads. We work with a crew of table tennis professionals and referees on a specially designed annotation toolbox to obtain fine-grained action labels (in 14 classes) for every ping-pong action that appeared in the dataset, and formulate two sets of action detection problems—action localizationandaction recognition. We evaluate a number of commonly seen action recognition (e.g., TSM, TSN, Video SwinTransformer, and Slowfast) and action localization models (e.g., BSN, BSN++, BMN, TCANet), usingP2ANetfor both problems, under various settings. These models can only achieve 48% area under the AR-AN curve for localization and 82% top-one accuracy for recognition since the ping-pong actions are dense with fast-moving subjects but broadcasting videos are with only 25 FPS. The results confirm thatP2ANetis still a challenging task and can be used as a special benchmark for dense action detection from videos. We invite readers to examine our dataset by visiting the following link:https://github.com/Fred1991/P2ANET.

Research on optimization of table tennis hitting action based on image recognition technology

Abstract In the process of table tennis batting action analysis, the analysis system that relies on modern digital image processing technology plays an increasingly important role. The new GoogleNet model, as a kind of auxiliary means, because of its intuitive, rapid, and other characteristics, can be very good to find out and optimize the drawbacks of batting action in the process of the game and help learners to master the batting essentials quickly. In this paper, the batch regression algorithm is used to transform the images of players’ batting actions during table tennis games, and the AM-Softmax algorithm in the Softmax classifier is used to construct the New GoogleNet model to build the batting action recognition and analysis model that contains both temporal and spatial flows. The main conclusions are as follows: the accuracy of the test results for forehand and left-handed ball attacks based on the New GoogleNet model is as high as 92% and 90%. Forehand and left-handed ball rolling accuracy was 87.5% and 85%, respectively. The optical flow optimization method resulted in a 0.4% and 1.4% increase in the accuracy of the experiments. In the two-stream fusion method with thresholds s=99% and s=1, the accuracy of optimization of the hitting action reached 89.8% and 91.4%, respectively. The accuracy in the averaging method was 95.9% when the optical flow threshold s=1. When the optical flow threshold s = 99% is used in the downscaling method, the accuracy is 93.5%. The results of this paper are of great significance for the recognition of batting movements during table tennis matches and the optimization and improvement of batting movements.

Using complex networks and multiple artificial intelligence algorithms for table tennis match action recognition and technical-tactical analysis

This study developed two action recognition models using the YOLOv8-Alphapose two-stream spatial temporal graph convolutional networks (2s-STGCN), and the networks were used to recognize technical actions in table tennis. This study proposed a novel framework that merges dynamic and static complex network analysis with a community detection algorithm aimed at evaluating table tennis players' techniques, tactical patterns and styles. Two datasets that contain 8015 high-definition action videos of 37 elite players were constructed: a front-facing player technical action dataset (4154 videos) and a backwards-facing player technical action dataset (3861 videos). The results showed that YOLOv8-Alphapose-2s-STGCN achieved better recognition performance than seven other YOLOv8-Alphapose-based artificial intelligence algorithms (transformer, BiGRU, BiLSTM, GRU, LSTM, TCN and RNN algorithms) on both datasets and exhibited robust performance in practical applications. In the case study, multiple indicators were used to measure the importance of nodes (players' techniques) within the serving and receiving networks and within the two-round (winning and losing) networks. Dynamic complex network analysis was adopted to evaluate tactical styles and patterns. Furthermore, this study examined whether players and their opponents exhibit variability or similarity in their tactical patterns, focusing on the player networks and the two-round winning and losing networks. By integrating action recognition with process-focused match analysis, this study explored an innovative and comprehensive way to analyse matches, with implications for the performance analysis of table tennis players and players in related racket sports.

Exploring the structure of the shot effectiveness model for elite table tennis players

BackgroundCurrently, 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.Methods258 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.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.ConclusionsTDC 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.

Using video analysis and artificial neural network to explore association rules and influence scenarios in elite table tennis matches

To become an elite table tennis player, aside from continually practicing, players must know their strengths and weaknesses to plan their strategy beforehand and increase their winning rate. The main problems with previous research were that the data collected were incomplete and imprecise. To address these problems, we established “The Intellectual Tactical System in Competitive Table Tennis”, using video analysis to collect competitive data. Additionally, we proposed a machine learning method using a combination of feature-selection and association rules to discover interesting rules from the data. The international matches of the Taiwanese table tennis single player Yun-Ju Lin were used as research samples by applying 3 S (speed, spin, spot) theory to collect and analyze data. The critical factors and scenarios were analyzed to identify the winning tactical models. The results of this study may provide useful suggestions for Yun-Ju Lin on training and building tactics in competitions. The similar approach may be essential for elite players and coaches to have appropriate tactical analysis.

Elite male table tennis matches diagnosis using SHAP and a hybrid LSTM–BPNN algorithm

This study adopts a new approach, SHapley Additive exPlanation (SHAP), to diagnose the table tennis matches based on a hybrid algorithm, namely Long Short-Term Memory–Back Propagation Neural Network (LSTM–BPNN). 100 male singles competitions (8535 rallies) from 2019 to 2022 are analyzed by a hybrid technical–tactical analysis theory, which hybridizes the double three-phase and four-phase evaluation theories. A k-means cluster analysis is conducted to classify 59 players’ winning rates into three levels (high, medium, and low). The results show that LSTM–BPNN has excellent performance (MSE = 0.000355, MAE = 0.014237, RMSE = 0.018853, and {mathrm{R}}^{2} = 0.988311) compared with six typical artificial intelligence algorithms. Using LSTM–BPNN to calculate the SHAP value of each feature, the global results find that the receive-attack and serve-attack phases of the ending match have essential impacts on the mutual winning probabilities. Finally, case applications show that the SHAP can directly obtain each feature importance on one or more matches, which is more objective and reliable than the traditional simulation method. This research explores an innovative way to understand and analyze matches, and these results have implications for the performance analysis of table tennis and related racket sports.

Tac‐Anticipator: Visual Analytics of Anticipation Behaviors in Table Tennis Matches

AbstractAnticipation skill is important for elite racquet sports players. Successful anticipation allows them to predict the actions of the opponent better and take early actions in matches. Existing studies of anticipation behaviors, largely based on the analysis of in‐lab behaviors, failed to capture the characteristics of in‐situ anticipation behaviors in real matches. This research proposes a data‐driven approach for research on anticipation behaviors to gain more accurate and reliable insight into anticipation skills. Collaborating with domain experts in table tennis, we develop a complete solution that includes data collection, the development of a model to evaluate anticipation behaviors, and the design of a visual analytics system called Tac‐Anticipator. Our case study reveals the strengths and weaknesses of top table tennis players' anticipation behaviors. In a word, our work enriches the research methods and guidelines for visual analytics of anticipation behaviors.

Notational Analysis of Wheelchair Paralympic Table Tennis Matches

Paralympic table tennis is the third largest paralympic sport for the number of players. Performance analysis was conducted for the rally duration and interval and impact of serve, whilst none investigated the shots distribution among classes of physical impairment. Therefore, the purpose of this study was to conduct a notational analysis of international competitions in relation to the wheelchair classes. Five matches for each wheelchair class (C1-to-C5) were evaluated from 20 elite male right-handed players. Both players for each match were analyzed for the following performance indicators: strokes type, the area of ball bouncing, and the shots outcome. Backhand shots were the most used technique for all classes. The most used strokes for C1 players were backhand and forehand drive and backhand lob, while for C5 players they were backhand and forehand push and backhand topspin. Similar shots distribution was registered for C2-to-C5 players. The central and far-from-the-net zone was mainly reached by the serve for all classes. Errors shots were similar in all classes, whilst winning shots were more frequent in C1. The current notational analysis provided a meaningful performance modelling of indicators for coaches and athletes that can be used to design training programs for each class.

Effects of technical-tactical skills on enhancing scoring efficiency when competing with opponents using different handedness in table tennis matchups

Technical-tactical skills are key to determining table tennis match performance. Identifying the skills that can increase scoring probability when competing against opponents with different racket handedness is vital. The aim of this study was to investigate the technical-tactical actions that could significantly improve scoring efficiency in SH (same-handedness) matches and OH (opposite-handedness) matches. The statistics of 72 top-level men's singles matches were collected (40 SH matches and 32 OH matches). An independent samples t-test was performed to evaluate the differences in the scoring efficiency of the point-winning shot. The results showed that the following maneuvers were crucial technical-tactical skills to increase scoring probability: (1) during the mutual-restriction phase, executing a forehand short push to forehand during service round and a backhand long push to backhand during receiving round against SH opponents (p < 0.05, ES: 0.59–0.70), and a backhand short push to middle in receiving round against OH opponents (p < 0.01, ES = 0.66); (2) during the initial-attack-and-counterattack phase, performing an initial forehand flip and a loop (drive) to forehand, a counter backhand loop (drive) to backhand during both types of rounds, and a forehand block (lob) to forehand during service round against SH opponents (p < 0.05, ES: 0.52–1.18), and an initial forehand loop (drive) to backhand and a counter backhand loop (drive) to forehand during both types of rounds, an initial forehand flip and a loop (drive) to backhand during service round, and an initial backhand flip to middle during receiving round against OH opponents (p < 0.05, ES: 0.45–0.99); and (3) during the topspin-exchange phase, hitting a forehand loop (drive) to forehand during service round and a backhand loop (drive) to backhand during both types of rounds against SH opponents (p < 0.05, ES: 0.51–1.32), a forehand loop (drive) to backhand during both types of rounds against OH opponents (p < 0.01, ES: 0.77–0.91). Professionals are recommended to concentrate on the enhancement of the abovementioned key technical-tactical skills to achieve better match performance.

Tennisgame Physio: A tool for amputees physiotherapy based on gamification

The present work aims to develop a computational solution in hardware and software that uses gamification methodologies to help physiotherapy professionals in the rehabilitation sessions of upper and lower limb amputees, who are in the pre-prosthetic and prosthetic stages. Thus, a table tennis match simulator is developed to instigate patients to reach the flow state during the session. Thus, a mobile program is developed to collect data from the smartphone’s gyroscope sensor and, through Bluetooth communication with the Arduino prototyping board, this information is forwarded to the simulator. The data received is used to move the virtual racket in the game. Furthermore, physiotherapists have a tool integrated with the tennis match simulator, to monitor the progress of patients during the sessions. In short, this solution turns out to be effective in helping both patients and physical therapists in physical rehabilitation sessions.

A Visible Analysis Approach for Table Tennis Tactical Benefit.

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.

Stroke performance relevance model for elite table tennis matches

ABSTRACT 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.

Teaching of Backspin Serve in Table Tennis

Backspin serve is a common serve in table tennis matches, and it is also one of the difficult contents for students to master in college table tennis teaching. In order to make students master backspin serve more quickly, the author tries to practice the interest and practicability of serve in the teaching process. This paper expounds and analyzes the feedback information in the concrete implementation and practice in order to further improve the teaching content of physical education in colleges and universities and provide teaching reference for school teaching and sports training.

English

The aim of this study was to compare heart rate variability (HRV) indices before and after a table tennis match, depending in match result. HRV indices were measured before (PRE) and after (POST) match periods to 21 table tennis players (21.86 ± 8.34 yr) in 30 matches. No significant differences were found neither in PRE nor in POST measures comparing winners and losers. A significantly lower value (p &lt; 0.05) was found in mean of RR intervals (mean RR), standard deviation of RR intervals (SDNN), the natural logarithm transform of the root mean square of successive differences between normal heartbeats (LnRMSSD), relative number of successive RR interval pairs that differ more than 50 ms (pNN50), cross (SD1) and longitudinal (SD2) axis of Poincaré plot comparing POST values with PRE values. Nevertheless, low frequency index expressed in absolute power (LF Power) and high frequency indices expressed in absolute power (HF power) and normalised power (HF Power) showed different trends depending on the results (p &lt; 0.05). The obtained results show a HRV decrease after table tennis match regardless the match result, in both time domain and non-linear indices. However, frequency domain indices show a different trend depending on the match outcome.

Explanation and verification of the rules of attack in table tennis tactics

BackgroundThe rules of attack in table tennis tactics have been discovered by the coaches and researchers of the Chinese table tennis team (CTTT) through long-term practice. However, they are only empirical judgements and have not been objectively verified.MethodsThe software "Table Tennis Master" has been used to analyse 200 matches of top players of CTTT against various opponents in recent years to obtain detailed statistics by analysing the effect of attack in the end line (AIEL) and attack out of the end line (AOEL).Results(1) The scoring rate of the players was high after AIEL but very low after AOEL (p < 0.05); (2) the round of service (serve/receive) and level of skills had little influence on the effect of AIEL and AOEL; and (3) the timing of attack had a great influence on the effect of AIEL and AOEL (r > 0.9).ConclusionsIn the high-level table tennis match, the rules of AIEL and AOEL are scientific. In accordance with the rules, the complex tactics can be simplified to the two concepts, AIEL and AOEL.

Effects of match forms and outcomes on the phase-based elite male table tennis match performance

The aim of the study was to explore the service roundtechnical-tactical performance indicators of three phases discriminating thematch result and the two match forms. The statistics of 72 professional men’ssingles matches of the 2018 international competitions were collected. Achi-square test was used to assess the relationship between match form, matchoutcome and service round result. Afterwards, a two-way ANOVA was performed toevaluate the effect of match form (SHM: match between players of the same handedness and OHM: match between players of the opposite handedness) and match result on three evaluation indices of thirteen technical-tactical indicators. The resultsdisplayed that: (1) there was a weak relationship between the service roundoutcome and match form for both the winning and losing players (p&amp;lt;0.001,ES=0.12); (2) the winners outperformed the defeated players by a highertechnical effectiveness in all three phases with small to moderate effects(p&amp;lt;0.05, ES:0.50-1.00) at both match forms; (3) the usage rate ofperformance indicators of the first four strokes phase and six strokes abovephase distinguished the SHM matches from the OHM matches by small to largeeffects (p&amp;lt;0.05, ES:0.50-1.26). This study offers insights for practitionersto comprehend the technical-tactical aspects that are deciding for performancewhen competing against different types of opponents and to make effectivetraining plans and match strategies.