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Comparative movement analysis of winning and losing players in men's elite squash

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... The resultant digital images were of a resolution of 384 )576 pixels at 25 frames per second but subsequent processing was undertaken at half the vertical resolution (384)288 pixels) to avoid video interlacing problems. Digital images were processed by the SAGIT/Squash tracking system (Perš et al., 2001), which enabled both players' movements to be tracked automatically, albeit with operator supervision using a background subtraction method, as described by Vučković and colleagues (Vučković, Dežman, Erčulj, Kovačič, & Perš, 2003). The principle behind this software is a tracking algorithm that compares each image to a template of the empty court so that a resultant value for each pixel can be compared with a threshold value to determine whether a player had been detected at this coordinate or not (a process known as binarization or thresholding). ...
... The central position of these pixels is then calculated using the procedure outlined by Vučković et al. (2003) to determine a xy coordinate for the player using the following equations: ...
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The velocities and distances covered by players during competition serve as a basis for planning fitness regimes according to the specific demand of the sport. The techniques used to calculate these movement parameters have ranged from human judgements to technological solutions such as GPS and computer vision. This paper evaluates the accuracy of a computerized motion tracking system (SAGIT/Squash) that uses computer vision methods on video captured via a fixed single camera located centrally above the court. Digital images were processed automatically with operator supervision so that any tracking errors could be rectified and manual tagging of all shots added. Four separate experiments were used to assess the error associated with tracking adult players' velocities and positions with respect to the court floor. Experiment 1 involved players standing still in different areas of the court. The tracking software was found to be more accurate when a player was stood in the centre of the court (1.33 m · min error) than in the corners (2.61 m · min error), predominately due to systematic errors (e.g. calibration). Experiment 2 was conducted in the same manner as Experiment 1 except that the players vigorously swung a racket around their body continuously. This resulted in 15 times the error found in Experiment 1 for the distance covered during 1 min. However, this is an unrealistic estimate of the true error when assessing matches, as during matches the racket is only swung approximately 35% of the time. Experiment 3 involved a player running at different speeds around a rectangular path on the court. The resultant trajectory, as captured by the software, was compared using different Gaussian smoothing equations of kernel widths 0.25 s, 0.5 s, and 1 s. The best solution (0.5 s) resulted in the most accurate trajectory, although the difference in distance calculated between the different equations was negligible. Experiment 4 used the 0.5-s smoothing equation to assess the tracking accuracy for a player running at a relatively steady speed in a more realistic circular trajectory. The trajectory of the pixel image was shown to have a smaller radius than the reference trajectory at increased speeds, due to the tendency of the player to lean over when negotiating a circular path. The error associated with the distance covered over 1 min was shown to range between 1.33 and 21 m depending on the nature and position of the player's movements. Values, typically somewhere in this range, are likely to be evident during typical use of this software.
... Other camera angles such as the sidewall and close up secondary cameras do not display both players and are typically used for repetitive shots, usually drop shots or backhands down the wall from the left back corner. However, the movement of the players were cyclical between the T and the corner and deemed to be relatively equal, providing valid results for comparison and aligning with previous studies [17,20,21,24]. Current work is being done to implement autonomous collection of other frame angles of the match. ...
... Game 3 also has the lowest number of frames collected at 76.50% as opposed to the average number of frames collected at 85.65% (without Game 3), supporting the need to filter the raw coordinates. Like previous studies, it appears players travel similar distances as their opponent in each individual game and distances traveled can be correlated to the length of game [20]. ...
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Sports pose a unique challenge for high-speed, unobtrusive, uninterrupted motion tracking due to speed of movement and player occlusion, especially in the fast and competitive sport of squash. The objective of this study is to use video tracking techniques to quantify kinematics in elite-level squash. With the increasing availability and quality of elite tournament matches filmed for entertainment purposes, a new methodology of multi-player tracking for squash that only requires broadcast video as an input is proposed. This paper introduces and evaluates a markerless motion capture technique using an autonomous deep learning based human pose estimation algorithm and computer vision to detect and identify players. Inverse perspective mapping is utilized to convert pixel coordinates to court coordinates and distance traveled, court position, ‘T’ dominance, and average speeds of elite players in squash is determined. The method was validated using results from a previous study using manual tracking where the proposed method (filtered coordinates) displayed an average absolute percent error to the manual approach of 3.73% in total distance traveled, 3.52% and 1.26% in average speeds <9 m/s with and without speeds <1 m/s, respectively. The method has proven to be the most effective in collecting kinematic data of elite players in squash in a timely manner with no special camera setup and limited manual intervention.
... After the serve, the player moves to the T area, which adds certain amount of motion to his overall statistics. Same authors [14] have studied the correlation of various motion intensity indicators and certain properties of the played matches. It has been established that both the motion path length and the duration of the games are highly and statistically significantly correlated with the number of points won by both players. ...
... If only the rally time is taken into the account, the difference between average duration is still large -213 seconds. Considering the results from [14], where high and statistically significant correlation between duration and distance covered by players has been established, the statistically significant differences in path length are expected. However, differences in distance covered are still unexpectedly large. ...
Conference Paper
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In this paper, we present a study on squash player work-rate during the squash matches of two different quality levels. To assess work-rate, the measurement of certain parameters of player motion is needed. The computer vision based software application was used to automatically obtain player motion data from the digitized video recordings of 22 squash matches. The matches were played on two quality levels - international and Slovene national players. We present the results of work-rate comparison between these two groups of players based on game duration and distance covered by the players. We found that the players on the international quality level on average cover significantly larger distances, which is partially caused by longer average game durations.
... The significant differences observed between novice and expert players underline the importance of studying the muscular activity during the backhand stroke. Vukovic et al. [13] measured the trajectory and velocity of movement using a tracking system to determine whether there were significant differences between winners and losers. They analysed the used skills, the time patterns, and the position of the squash players during their performance. ...
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The purpose of this study was to quantify the coordination between agonist and antagonist elbow muscles during squash backhand crosscourt shots in adult female players. Ten right-handed, international-level, female squash players participated in the study. The electrical muscle activity of two right elbow agonist/antagonist muscles, the biceps brachii and triceps brachii, were recorded using a surface EMG system, and processed using the integrated EMG to calculate a co-activation index (CoI) for the preparation phase, the execution phase, and the follow-through phase. A significant effect of the phases on the CoI was observed. Co-activation was significantly different between the follow-through and the execution phase (45.93 ± 6.00% and 30.14 ± 4.11%, p < 0.001), and also between the preparation and the execution phase (44.74 ± 9.88% and 30.14 ± 4.11%, p < 0.01). No significant difference was found between the preparation and the follow-through phase (p = 0.953). In conclusion, the co-activation of the elbow muscles varies within the squash backhand crosscourt shots. The highest level of co-activation was observed in the preparation phase and the lowest level of co-activation was observed during the execution. The co-activation index could be a useful method for the interpretation of elbow muscle co-activity during a squash backhand crosscourt shot.
... Video motion tracking has been used in previous movement analysis studies in different sports such as squash (Eubank and Messenger, 2000;Hughes and Franks, 1994;James and Bradley, 2004;Vuckovic et al., 2003) basketball (Barris, 2008), handball (Pers et al., 2002), soccer (Barros et al., 2006), volleyball (Mauthner et al., 2007) and tennis (Carboch et al., 2014;Carvalho et al., 2013;Martínez-Gallego et al., 2013;Triolet et al., 2013). ...
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The purpose of the study was to determine the timing of a split-step in three categories of tennis players in four groups of strokes. Subjects were divided into three groups: male and female junior, and male professional tennis players. During two tournaments, all matches were recorded with two fixed video cameras. For every stroke, the timing of the split-step between the opponent's impact point when hitting the ball and the player's split-step was measured. A two-way analysis of variance (ANOVA) was used to determine the differences between groups of strokes, players and the interaction Player x Stroke Group. A Tukey post-hoc test was employed to determine specific differences. The results revealed differences between players in detecting the opponent's movement, stroke and ball flight, which were reflected in different split-step timings. Each tennis player has his/her own timing mechanism which they adapt to various game situations. Response times differ significantly depending on the game situation. On average, they are the lowest in the serve, and then gradually rise from the return of the serve to baseline game, reaching the highest values in specific game situations. Players react faster in the first serve than in the second one and in the return of the serve, the response times are lower after the return of the second serve.
... In badminton, it has already been studied the differences between the amount of winners points and unforced errors made by winners and losers of the games (Tong and Hong, 2000;Cabello-Manrique and Gonzalez-Badillo, 2003;Yadav et al., 2007). Similar studies with other racket sports also investigated differences in the frequency of technical skills performed by the winners and losers in squash (Vučković et al., 2003, Vučković andJames, 2010) and tennis matches (Filipčič et al., 2008). However, none of these studies investigated the relationship between point difference established by the players and the game outcome. ...
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The aim of this study was to analyze the point difference established at different phases of the game by the winners and losers in men's singles badminton matches. We analyzed 136 games from matches of the 2015 World Championship. From each game were collected the final result and the maximum point difference established by the players in each phase of the game. We considered from 0 to 7 points the first phase, from 8 to 14 the second phase and 15 to 21 the third phase of the game. We found that in all phases the winners had a superior point difference than the losers and this difference increased significantly over the course of the match. For all the players who were not ahead on the scoreboard in the first phase, 78% have lost the game. We found that one point ahead in the second and third phases was not enough for athletes to win the game. The winners had at least five points of difference to the opponent from the middle to the end of the game. The results presented are important to monitor the athlete's performance during the game and to readjust strategies based on point difference.
... Digital images were processed by the SAGIT/ SQUASH tracking system (Perš, Vu ckovi c, Kova ci c, & Dežman, 2001), which allowed both players' movements to be tracked automatically, albeit with operator supervision using a background subtraction method, as described by Vu cković and colleagues (Vu ckovi c, Dežman, Er culj, Kova ci c, & Perš, 2003). The principle behind this software is a tracking algorithm that compares each image with a template of the empty court so that a resultant value for each pixel can be compared with a threshold value to determine whether a player had been detected at this coordinate (a process known as ''binarization'' or ''thresholding''). ...
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The importance of dominating the T in squash is recognized by coaches and players but there has been little formal investigation of this aspect of tactical play. Consequently, the aim of this research was to analyse player occupancy of a T area, to establish whether there are differences between winners and losers of games at different playing standards. An automated player-tracking system, with operator supervision and intervention, captured players' movements during matches at the World Team Championships (n = 11), the Slovenian National Championships (n = 11), and a local tournament (n = 15). Frequency of occupying the T area at the moment opponents played their shot best discriminated playing standard. Winners spent a greater proportion of total playing time in the T area than losers (P < 0.001), except during closely contested games. The results suggest that time in the T area indicates dominance of rallies. Future studies need to consider both between-group (playing standard) and within-game (individual player standard) differences, as both were shown to influence the time players spent in the T area.
The aim of this study was to examine the effects of the menstrual cycle on vertical jumping, sprint performance and force-velocity profiling in resistance-trained women. A group of resistancetrained eumenorrheic women (n = 9) were tested in three phases over the menstrual cycle: bleeding phase, follicular phase, and luteal phase (i.e., days 1–3, 7–10, and 19–21 of the cycle, respectively). Each testing phase consisted of a battery of jumping tests (i.e., squat jump [SJ], countermovement jump [CMJ], drop jump from a 30 cm box [DJ30], and the reactive strength index) and 30 m sprint running test. Two different applications for smartphone (My Jump 2 and My Sprint) were used to record the jumping and sprinting trials, respectively, at high speed (240 fps). The repeated measures ANOVA reported no significant differences (p � 0.05, ES < 0.25) in CMJ, DJ30, reactive strength index and sprint times between the different phases of the menstrual cycle. A greater SJ height performance was observed during the follicular phase compared to the bleeding phase (p = 0.033, ES = −0.22). No differences (p � 0.05, ES < 0.45) were found in the CMJ and sprint force-velocity profile over the different phases of the menstrual cycle. Vertical jump, sprint performance and the force-velocity profiling remain constant in trained women, regardless of the phase of the menstrual cycle.
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Squash is a sport characterised by complex physical, technical and tactical demands. Despite its increased popularity, there is presently no synthesis of the literature pertaining to the performance requirements of squash. As such, it is difficult to generate evidence-based guidelines for applied practitioners working with squash athletes. The purposes of this review were to a) identify the most important aspects of squash performance with reference to junior and senior athletes, b) identify and discuss the available methods of assessment of squash performance and c) identify areas where further research efforts are needed so that the performance requirements of the squash game are understood. Critical analysis of literature pertaining to movement characteristics and time motion analyses, physiological demands, methods of assessing physical qualities, psychological demands and injury epidemiology were conducted. A summary of the physical characteristics of squash athletes of varying ages and playing standards is presented. Time motion analysis studies present consistent information on the game demands. There are limited data on game demands evolution from youth to senior. There appears to be usable testing protocols available for practitioners supporting squash athletes, although further work is needed to determine the applicability of these measures in junior athletes. Furthermore, better controlled studies are required to establish the injury risks associated with squash.
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No previous research in squash has considered the time between shots or the proximity of the ball to a wall, which are two important variables that influence shot outcomes. The aim of this paper was to analyse shot types to determine the extent to which they are played in different court areas and a more detailed analysis to determine whether the time available had an influence on the shot selected. Ten elite matches, contested by fifteen of the world's top right handed squash players (age 27 ± 3.2, height 1.81 ± 0.06 m, weight 76.3 ± 3.7 kg), at the men's World Team Championships were processed using the SAGIT/Squash tracking system with shot information manually added to the system. Results suggested that shot responses were dependent upon court location and the time between shots. When these factors were considered repeatable performance existed to the extent that one of two shots was typically played when there was limited time to play the shot (< 1.20s). For example, it was clear that when players did not have a lot of time to hit the ball (low time i.e. < 1.06s, and mid time i.e. 1.06 - 1.20s) in the front left corner close to the side wall, the crosscourt lob was used frequently (44.30% and 36.31% respectively) whereas when there was more time this shot was seldom used (13.64%). Consequently variant and invariant behaviour were shown to exist in elite squash although for the first time it was suggested that the availability of time to play a shot contributed to which of these behaviours was evident. This analysis could be extended by adopting a case study approach to see how individual differences in strategy and tactics affect shot selections.
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