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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. [ABSTRACT FROM AUTHOR]

In this study, we tested the theory of angles that was proposed almost a century ago by the tennis player Henri Cochet. This theory proposes that expert tennis players should position themselves on the bisector of the angle of the opponent's possibilities in order to optimize shot return, suggesting a geometric occupation of the court relative to the opponent's affordances; namely what he/she is capable of doing. We tested this hypothesis by analysing player and ball positioning data from professional tennis matches recorded with a Hawk-Eye system. We compared this hypothesis with two alternative computational and probabilistic hypotheses which would consist in positioning oneself on the average or the median of the shots usually played from a given location. The results show that expert tennis players apply the principles of the theory of angles and thus confirm Henri Cochet's intuition. That is, for lateral court positioning, a geometric strategy is deemed optimal by expert players. It also appears that the more experienced the players are, the more precise their application of this strategy becomes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The relative age effect (RAE) has been the subject of many studies, but no relevant literature has discussed the phenomenon of RAE in Chinese tennis. Numerous studies have demonstrated that RAE significantly contributes to brain drain and other occurrences that create inequity. This paper analyzes the birth dates and year-end rankings of all male players (N = 2697) who participated in China's junior tennis tournaments (U12, U14, U16) between 2014 and 2019 and who were selected for China's National Junior Team in 2019 and 2020; the paper classifies the birth dates into quarters and semesters. One of the research objectives of this study is to analyze whether RAE exists in Chinese junior men's tennis and whether RAE exerts an effect on athletes' performance. Differences between the observed and expected birthdate distributions were tested using chi-square statistics, and subsequent calculations were tested using odds ratios. The study found that RAE was present in all Chinese junior male tennis sports groups (p<0.001). The percentages of athletes born in the first half of the year were 56.4% (U12), 60.4% (U14), and 60.4% (U16), and the percentages of those born in the first quarter were 34.1% (U12), 36.4% (U14), and 37.1% (U16). Athletes with birth dates closer to the beginning of the year had a higher probability of achieving excellent athletic performance as a result of RAE, whereas those who were born near the end of the year had a more difficult time achieving strong athletic performance. [ABSTRACT FROM AUTHOR]

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 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. [ABSTRACT FROM AUTHOR]

The use of statistical tools for predicting the winner in tennis matches has enjoyed an increase in popularity over the last two decades and, currently, a variety of methods are available. In particular, paired comparison approaches make use of latent ability estimates or rating calculations to determine the probability that a player will win a match. In this paper, we extend this latter class of models by using network indicators for the predictions. We propose a measure based on eigenvector centrality. Unlike what happens for the standard paired comparisons class (where the rates or latent abilities only change at time t for those players involved in the matches at time t), the use of a centrality measure allows the ratings of the whole set of players to vary every time there is a new match. The resulting ratings are then used as a covariate in a simple logit model. Evaluating the proposed approach with respect to some popular competing specifications, we find that the centrality-based approach largely and consistently outperforms all the alternative models considered in terms of the prediction accuracy. Finally, the proposed method also achieves positive betting results. [ABSTRACT FROM AUTHOR]

Simple Summary: The precompetitive anxiety should be controlled in athletes to optimize their performance. In this regard, heart rate variability (HRV) is a non-invasive tool to assess the autonomic nervous system balance. Therefore, this study aims to investigate the HRV response of elite international junior tennis players during an international tournament. Eleven players participate in this study, with a mean age of 15.36 (0.67) years old. The HRV of tennis players are assessed 24 h before the event, and immediately before the first and the second match of the ITF Junior Davis Cup event. Each of the registers lasted 5 min and the time domain, frequency domain, and non-linear variables were extracted. Results show that elite tennis players did not decrease the HRV between the baseline and the first match. However, the HRV response significantly differed between the baseline and the second match. Nevertheless, anxiety was higher before the first match than before the second match. Coaches and physical trainers could use HRV to control and manage the precompetitive anxiety of junior tennis players. The experience in international tournaments and the familiarization with the environment in the second match could explain these results. The aim of the present study was to investigate the evolution of the HRV during an international team tennis tournament in elite junior tennis players. A total of 11 tennis players, with a mean age of 15.36 (0.67) from six nationalities, participated in this cross-sectional study. Participants were measured one day before the event, before the first match, and before the second match of the ITF Junior Davis Cup event. Each of the registers lasted 5 min and the time domain, frequency domain and non-linear variables were extracted. The tournament took place in Valencia (Spain). Results showed that there was not a significant decrease in the heart rate variability (HRV) induced by precompetitive stress. However, significant differences (p-value < 0.05) were found between baseline and second match pre-competition HRV values in low frequency (LFNu) (p-value = 0.008) and high frequency (HFNu) power (p-value = 0.008), LF/HF ratio (p-value = 0.008) and Sample Entropy (SampEn) (p-value = 0.033) variables. Furthermore, cognitive anxiety (measured by CSAI-2r) (p-value = 0.017) and anxiety (measured by STAI-S) (p-value = 0.042) were higher before the first match than before the second match. Coaches and physical trainers could use HRV to control and manage the precompetitive anxiety of junior tennis players. The experience in international tournaments and the familiarization with the environment in the second match could explain these results. [ABSTRACT FROM AUTHOR]

With the continuous development of voice coil motors, it has also been widely used in today's sports competitions. For example, the Hawk-Eye system in tennis matches uses voice coil motors to focus on the camera to capture the trajectory of the tennis ball. Therefore, in order to better solve the problem of dynamic parameter uncertainty, external load disturbance, and tracking control of the voice coil motor servo system in motion, this paper proposes for the first time the strategy of using L1 adaptive control algorithm to control the voice coil motor servo system. First, it briefly analyzes the working principle and control method of the voice coil motor, and then constructs the uncertain parameter model according to the mathematical model of the voice coil motor. The closed-loop system of voice coil motor is simulated and analyzed by L1 adaptive controller. The results show that the L1 adaptive control method effectively suppresses the high-frequency interference caused by the voice coil motor in operation, can control the tracking error to gradually converge and so the tracking effect is better, and has strong robustness to the perturbation of system parameters. It can be applied to voice coil motor servo control. [ABSTRACT FROM AUTHOR]

Single-elimination (knockout) tournaments are the standard paradigm for both main tennis professional associations, WTA and ATP. Schedules are generated by allocating first seeded and then unseeded players with seeds prevented from encountering each other early in the competition. Besides, the distribution of pairings in the first round between unseeded players and seeds for a yearly season may be strongly unbalanced. This provides often a great disadvantage to some "unlucky" unseeded players in terms of money prizes. Also, a fair distribution of matches during a season would benefit from limiting in first rounds the presence of Head-to-Head (H2H) matches between players that met in the recent past. We propose a tournament generation approach in order to reduce in the first round unlucky pairings and also replays of H2H matches. The approach consists in a clustering optimization problem inducing a consequent draw within each cluster. A Non-Linear Mathematical Programming (NLMP) model is proposed for the clustering problem so as to reach a fair schedule. The solution reached by a commercial NLMP solver on the model is compared to the one reached by a faster hybrid algorithm based on multi-start local search. The approach is successfully tested on historical records from the recent Grand Slams tournaments. [ABSTRACT FROM AUTHOR]

Topspin is one of the most widely used hitting techniques in a tennis match and it is an effective tool to win over the opponent. Hence, flight path simulation of a spinning ball can be a tremendous analysis tool to help tennis players perfect their game. This article proposes a fuzzy logic model based on the principles of kinematics and mechanics. This study analyzes the physical characteristics of a spinning ball during the flight process, which are divided into two categories: the characteristics of the ball on impact (including the floating and rotating it causes) and the landing rebound characteristics. These two characteristics are considered as the constraints of the flight path simulation and the inputs of the fuzzy logic model. Fuzzy logic is used to fuzzify the impact and landing rebound information of the ball based on the knowledge base, solve the problem, and finally defuzzify the results into crisp outputs, that is, accurate flight trajectory. The simulation results show that the estimation error of the proposed model is lower than 3.7 cm/s and 0.9°, and the success rate of accurate topspin execution is 100%, indicating that the proposed model is effective to train tennis players. [ABSTRACT FROM AUTHOR]

The purpose of this article is to present the use of a previously validated wearable sensor device, Armbeep, in a real-life application, to enhance a tennis player's training by monitoring and analysis of the time, physiological, movement, and tennis-specific workload and recovery indicators, based on fused sensor data acquired by the wearable sensor—a miniature wearable sensor device, designed to be worn on a wrist, that can detect and record movement and biometric information, where the basic signal processing is performed directly on the device, while the more complex signal analysis is performed in the cloud. The inertial measurements and pulse-rate detection of the wearable device were validated previously, showing acceptability for monitoring workload and recovery during tennis practice and matches. This study is one of the first attempts to monitor the daily workload and recovery of tennis players under real conditions. Based on these data, we can instruct the coach and the player to adjust the daily workload. This optimizes the level of an athlete's training load, increases the effectiveness of training, enables an individual approach, and reduces the possibility of overuse or injuries. This study is a practical example of the use of modern technology in the return of injured athletes to normal training and competition. This information will help tennis coaches and players to objectify their workloads during training and competitions, as this is usually only an intuitive assessment. [ABSTRACT FROM AUTHOR]

The aim of the study was to explore the service round technical-tactical performance indicators of three phases discriminating the match result and the two match forms. The statistics of 72 professional men's singles matches of the 2018 international competitions were collected. A chi-square test was used to assess the relationship between match form, match outcome and service round result. Afterwards, a two-way ANOVA was performed to evaluate 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 results displayed that: (1) there was a weak relationship between the service round outcome and match form for both the winning and losing players (p<0.001, ES=0.12); (2) the winners outperformed the defeated players by a higher technical effectiveness in all three phases with small to moderate effects (p<0.05, ES:0.50-1.00) at both match forms; (3) the usage rate of performance indicators of the first four strokes phase and six strokes above phase distinguished the SHM matches from the OHM matches by small to large effects (p<0.05, ES:0.50-1.26). This study offers insights for practitioners to comprehend the technical-tactical aspects that are deciding for performance when competing against different types of opponents and to make effective training plans and match strategies. [ABSTRACT FROM AUTHOR]

Tennis is a popular sport, and professional tennis matches are probably the most watched games globally. Many studies consider statistical or machine learning models to predict the results of professional tennis matches. In this study, we propose a statistical approach for predicting the match outcomes of Grand Slam tournaments, in addition to applying exploratory data analysis (EDA) to explore variables related to match results. The proposed approach introduces new variables via the Glicko rating model, a Bayesian method commonly used in professional chess. We use EDA tools to determine important variables and apply classification models (e.g., logistic regression, support vector machine, neural network and light gradient boosting machine) to evaluate the classification results through cross-validation. The empirical study is based on men's and women's single matches of Grand Slam tournaments (2000–2019). Our analysis results show that professional tennis ranking is the most important variable and that the accuracy of the proposed Glicko model is slightly higher than that of other models. [ABSTRACT FROM AUTHOR]

Forecasting has been playing an important role in different fields of life, i.e., in decision-making activities of management, to predict uncertain events within an organization, in weather forecasting, in flood forecasting, etc. Stakeholders involved in betting market take advantage of tennis forecasting directly or indirectly. Winning probability calculated using forecasting models helps the bettors in deciding whether to place a bet or not. Keeping in view the importance of tennis forecasting, the Bradley-Terry model is used to model men's professional tennis for predicting match outcomes in tennis matches of men's singles. Model coefficients are estimated using data from January 2019 to September 2020 of 3439 matches. Ratings for each player are calculated using model coefficients. Player rankings are then calculated using these ratings. Comparison of model rankings with ATP rankings has shown satisfactory results. Winning probability for each player is calculated using model coefficients and ratings. These probability predictions are evaluated against four measures of performance. The results reveal that surface on which a game is played on contributes significantly towards a player's performance. Due to this impact of the surface, our model has produced superior player rankings for certain players who had been ranked very low in official ATP rankings. According to most of the performance measures, the model has shown good results for clay court data which are closely followed by hard court data. To calculate return on investment, model results are compared with the bookmakers' average odds and best available odds. It has been found that return on investment for a fitted model is highest in the case of clay court data in comparison to bookmaker's average odds and best odds. [ABSTRACT FROM AUTHOR]

This paper uses data mining technology to mathematically model the training movements of tennis players, establish a three-dimensional data information database of athletes utilizing depth imaging, analyze the data with data mining algorithms, and derive the results after comparative evaluation and analysis with a database of movement characteristics of tennis dribblers. This paper uses video observation and mathematical modeling to construct a tennis player training action evaluation model, which provides a reference basis for tennis players to improve and enhance their tactical level; it can also provide a reference for the development of sports training special theory of tennis projects and enrich the tactical diagnosis method of tennis matches. To improve the accuracy of 3D human pose estimation, this paper adopts a 3D skeleton point extraction method based on RGBD images; for the action alignment problem, this paper uses a dynamic time warping (DTW) algorithm; for the similarity measure, this paper gives a Pearson correlation coefficient method based on the joint point features of human parts. This paper aims to conduct a systematic theoretical analysis of tennis players' training movements based on theories and methods such as system science theory and social network analysis. On this basis, the characteristics of tennis training technology development are analyzed from a combination of qualitative and quantitative perspectives, while the development of tennis player training is explored based on tracking observations of tennis player movement training, and finally, the attack and service characteristics of tennis training are analyzed to better provide some reference for the sustainable development of tennis. [ABSTRACT FROM AUTHOR]

This research was conducted to determine the reasons and expectations of tennis players participating in the Eastern League organized by the tennis federation, preferring this sports branch. The research group consists of 138 athletes (53 women and 85 men) participating in the Eastern League Tennis Tournament. The scanning method was used in the research. As a data collection tool, a personal information form prepared by taking expert opinions and a scale form determining the reasons for preferring the tennis branch were used. SPSS statistical package program was used to analyze the data, and the significance was accepted as p<0.05. According to the results of the research, the research group; 73.9% are students, 39.9% are undergraduates, 56.5% are members of a club other than a tennis club, 55.8% do their training at Provincial Directorates of Youth and Sports, and 60%, It has been determined that 1 of them has a provincial championship. In addition, most of the athletes stated that the materials in the sports facilities were insufficient. It was seen that the friends, easy access to the facilities and prevalence, family and TV, cinema, and press-broadcasting were effective in preferring the tennis branch of the research group, respectively. [ABSTRACT FROM AUTHOR]

Wearable sensor systems are a emerging tools for the evaluation of the sport's activity and can be used to quantify the external workload of the athlete. The main goal of this paper was to evaluate the validity and reliability of the "Armbeep inertial measurement unit" (IMU) sensor both in a closed tennis exercise and in open matchplay. Twentyfour junior tennis players performed a baseline drill and played matches, during which they wore a combined accelerometer and gyroscope sensor. Video footage was concomitantly recorded using a digital video camera. The agreement between the measurements was assessed with the intraclass correlation coefficient (ICC) and the standard error of measurement (SEM). A simple linear regression was used to predict the number of shots registered from the video and from the Armbeep IMU sensor's data. The number of total forehand and backhand shots during the drill repetitions showed an excellent test and re-test reproducibility (ICC≥0.90). There was a significant relationship between the Armbeep IMU sensor's number of contacts and the total number of shots (R2 = 0.938) which indicated the excellent reliability of the tested Armbeep IMU sensor for those parameters. Considering the accuracy of the total tennis shots and the small magnitude of error for wrist speed and acceleration, the Armbeep IMU sensor appears to be an appropriate on-court tool that can be used to monitor the hitting load during tennis practice and matches. [ABSTRACT FROM AUTHOR]

Grand Slam tennis tournaments are played on different surfaces. The aims of the present study were to analyse the technical differences in the Grand Slam tournaments (Australian Open or AO, Roland Garros or RG, Wimbledon or W, and the United States Open or US), as well as to establish differences between winning and losing players. A total of 580 sets in 248 matches played in Grand Slams between 2017 and 2018 were analysed. To observe differences between the tournaments, a one-way analysis of variance (Kruskal Wallis) with the Bonferroni post-hoc test was performed. Univariate (Wilcoxon test) analysis of data was carried out to show the differences between the winning and losing performances of sets. Players who had more aces, points won on the 1st serve, winning shots and net points won more matches in the AO, W and US than in the RG (p<.05). However, in RG, players won more receiving points (43.56% of the points played) with chances to break the opponents' service game. The results also showed that the winning players were superior in both service and receiving, and the most influential variables on the outcome of the match were percentage of receiving points won, break points won, and percentage of points won on the first serve. Such knowledge may have implications for the design of appropriate game strategies and specific training sessions to improve performance in professional women's tennis. [ABSTRACT FROM AUTHOR]

The famous Bradley-Terry model for pairwise comparisons is widely used for ranking objects and is often applied to sports data. In this paper we extend the Bradley-Terry model by allowing time-varying latent strengths of compared objects. The time component is modelled with barycentric rational interpolation and Gaussian processes. We also allow for the inclusion of additional information in the form of outcome probabilities. Our models are evaluated and compared on toy data set and real sports data from ATP tennis matches and NBA games. We demonstrated that using Gaussian processes is advantageous compared to barycentric rational interpolation as they are more flexible to model discontinuities and are less sensitive to initial parameters settings. However, all investigated models proved to be robust to over-fitting and perform well with situations of volatile and of constant latent strengths. When using barycentric rational interpolation it has turned out that applying Bayesian approach gives better results than by using MLE. Performance of the models is further improved by incorporating the outcome probabilities. [ABSTRACT FROM AUTHOR]

We study the gender differences in aversion to COVID-19 exposure using a natural experiment of the 2020 US Open. It was the first major tennis tournament after the season had been paused for six months, held with the same rules and prize money for men and women. We analyze the gender gap in the propensity to voluntarily withdraw because of COVID-19 concerns among players who were eligible and fit to play. We find that female players were significantly more likely than male players to have withdrawn from the 2020 US Open. While players from countries characterized by relatively high levels of trust and patience and relatively low levels of risk-taking were more likely to have withdrawn than their counterparts from other countries, female players exhibited significantly higher levels of aversion to pandemic exposure than male players even after cross-country differences in preferences are accounted for. About 15% of the probability of withdrawing that is explained by our model can be attributed to gender. [ABSTRACT FROM AUTHOR]

With the development of Internet of things technology, the combination of Internet of things technology and sports competition parameter collection technology, so as to carry out rapid and accurate retrieval and positioning of technology and tactics, has innovation in the current research field. In the high-level table tennis competition, the use of technology and tactics is closely related to the gain and loss of points. At present, the traditional table tennis video mining algorithm has some problems such as low efficiency and poor performance of optimization classification. Based on this, this article introduces the big data platform of the wireless sensor networks to construct the table tennis match database, realizing the real-time updating of table tennis match parameters and the call of historical data at any time. Then establishing a data mining model to realize the data and dynamic analysis of table tennis matches. Finally, based on this strategic analysis system, the data collected from two table tennis competitions are simulated, and the tactical recommendation of theoretical analysis is obtained, which provides a theoretical basis for the digitization of table tennis sports. [ABSTRACT FROM AUTHOR]

This paper aims to highlight the importance of coordinative abilities in the training plan of 10-12 year old tennis players, and whether through the methods and means chosen for this experiment an optimisation of tennis specific movements is observed. The ability to combine different forms of movement allows the player to better and faster adapt to the different surfaces they have to play on. In most cases, tennis movement is the combined result of and is constantly conditioned by the court area, technical processes and the player's experience. The results of this study show that the development of coordinative abilities positively influences the player's ability to combine the different types of movements specific to tennis matches. [ABSTRACT FROM AUTHOR]

Table tennis is a popular sport in China. It has a low barrier to entry and also has difficult techniques. In order to improve the skills of table tennis match between players, this paper introduced the dynamic analysis of ping pong ball in flight after being hit. The main content was the stress analysis in the flight of ping pong ball. Moreover, the Magnus force caused by rotation was considered. The dynamic model of ping pong ball flight was built, the flight track of top spinning ball at 0, 30, 60, 90 and 120 r/s were simulated using Java software. The actual flight track of ping pong ball under the same conditions was obtained using the table tennis serving machine and highspeed camera to verify the effectiveness of the dynamic model. The results showed that the track obtained by the dynamic model basically coincided with the actual track, which verified the validity of the dynamic model; the maximum height and drop point distance of ping pong ball decreased with the increase of spinning speed of top spinning ball; the flight time of ping pong ball decreased with the increase of spinning speed of top spinning ball. To sum up, players can reduce the flight height, drop point distance and flight time of ping pong ball by increasing the top spinning speed, so as to improve the opponent's counterattack difficulty. [ABSTRACT FROM AUTHOR]

Objective: The present study investigates skill transfer from Virtual Reality (VR) sports training to the real world, using the fast-paced sport of table tennis. Background: A key assumption of VR training is that the learned skills and experiences transfer to the real world. Yet, in certain application areas, such as VR sports training, the research testing this assumption is sparse. Design: Real-world table tennis performance was assessed using a mixed-model analysis of variance. The analysis comprised a between-subjects (VR training group vs control group) and a within-subjects (pre- and post-training) factor. Method: Fifty-seven participants (23 females) were either assigned to a VR training group (n = 29) or no-training control group (n = 28). During VR training, participants were immersed in competitive table tennis matches against an artificial intelligence opponent. An expert table tennis coach evaluated participants on real-world table tennis playing before and after the training phase. Blinded regarding participant's group assignment, the expert assessed participants’ backhand, forehand and serving on quantitative aspects (e.g. count of rallies without errors) and quality of skill aspects (e.g. technique and consistency). Results: VR training significantly improved participants’ real-world table tennis performance compared to a no-training control group in both quantitative (p < .001, Cohen’s d = 1.08) and quality of skill assessments (p < .001, Cohen’s d = 1.10). Conclusions: This study adds to a sparse yet expanding literature, demonstrating real-world skill transfer from Virtual Reality in an athletic task. [ABSTRACT FROM AUTHOR]

In many sports contests, the equilibrium requires players to randomize across repeated rounds, i.e., exhibit no temporal predictability. Such sports data present a window into the (in)efficiency of random sequence generation in a natural competitive environment, where the decision makers (tennis players) are both highly experienced and incentivized compared to laboratory studies. I resolve a long-standing debate about whether professional players' tennis serve directions are serially independent (Hsu, Huang & Tang, 2007) or not (Walker & Wooders, 2001) using a new dataset that is two orders of magnitude larger than those studies. I examine both between- and within-player determinants of the degree of serial (in)dependence. Evidence of the existence of significant serial dependence across serves is presented, even among players ranked Number 1 in the world. Furthermore, significant heterogeneity was found with respect to the strength of serial dependence and also its sign. A novel finding is that Number 1 and Number 2 ranked players tend to under-alternate on average, whereas in line with previous findings, the lower-ranked the players, the greater their tendency to over-alternate. Within-player analyses show that high-ranked players do not condition their randomization behavior on their opponent's ranking. However, the under-alternation of top players would be consistent with a best-response to beliefs that the population of opponents over-alternates on average. Finally, the degree of observed serial dependence is not systematically related to other match variables proxying for match difficulty, fatigue, and psychological pressure. [ABSTRACT FROM AUTHOR]

Team Tennis competitions produce aggregate scores for teams, and thus team rankings, based on head-to-head matchups of individual team members. Similar scoring rules can be used to rank any two groups that must be compared on the basis of paired elements. We explore such rules in terms of their strategic and social choice characteristics, with particular emphasis on the role of cycles. We first show that cycles play an important role in promoting competitive balance, and show that cycles allow for a maximum range of competitive balance within a league of competing teams. We also illustrate the impact that strategic behavior can have on the unpredictability of competition outcomes, and show for a general class of team tennis scoring rules that a rule is strategy-proof if and only if it is acyclic (dictatorial) and manipulable otherwise. Given the benefits of cycles and their relationship with manipulability, a league valuing competitive balance may invite such social choice violations when choosing a scoring rule. [ABSTRACT FROM AUTHOR]

We propose a logistic regression model to predict the win probability in a tennis match in the context of the betting market. The variables included in the model are ATP points and rankings, the players' ages, the home factor and the information derived from bookmaker odds. The model is estimated using data related to 2012 tournaments, and it is then used in an out-ofsample betting experiment where the odds implied by the model are used, following a specific procedure, for betting against bookmakers. The algorithm is applied to all matches of the four Grand Slam Championships 2013, and the whole procedure is evaluated with respect to the global return of the strategy. After 501 matches, the total cumulative return is 16.3%. [ABSTRACT FROM AUTHOR]

The aim of this study was to compare activity patterns between male and female wheelchair tennis (WT) matches. Sixteen singles international WT matches (eight male and eight female) were analysed. Each match was recorded and analysed according to the following variables: total match time (minutes), total set time (minutes), effective playing time (%), total resting time (%), working timetresting time ratio (W:R), resting time between points (seconds), rally duration (seconds), points per set, shots per set, shots per rally, bounces per point, and time between shots (seconds). Mann-Whitney U test was used to compare between the genders and Wilcoxon test was used to compare variables with the type of point (non-game point opportunity-NGO, and game point opportunity - GO). Female matches showed higher values (p<.05) in rally duration, bounces per point, and frequency of shots than male matches. Both genders spent more time between points in GO than in NGO situation. The findings indicate that male and female players play in a different way, and these differences should be taken into consideration by the WT coaches. [ABSTRACT FROM AUTHOR]