Hard Court Research Articles

Core Temperature and Sweat Responses in Professional Women's Tennis Players During Tournament Play in the Heat

Tennis is often played in hot, humid environments, intensifying the thermoregulatory strain placed on the athletes. As a safety measure, some tennis organizations allow for a 10-minute break in play between the second and third sets when environmental conditions are extreme. However, the actual effect of these breaks in reducing core temperature is unknown. To determine change in core temperature after a 10-minute break in play and assess fluid balance in professional female tennis players during tournament matches in the heat. Cross-sectional study. A Women's Tennis Association Tour-sanctioned outdoor tournament on hard courts under hot conditions (30.3°C ± 2.3°C). Seven professional tennis players. Change in core temperature after a 10-minute break in tournament play, fluid intake, and sweat losses during match play. Core temperature was reduced from 38.92°C to 38.67°C (change of -0.25°C ± 0.20°C) when a break was taken (P = .02). Mean sweat rate during match play was 2.0 ± 0.5 L/h. During that time, mean fluid intake was 1.5 ± 0.5 L/h, resulting in a 1.2% ± 1.0% reduction in body mass. Female professional tennis players are subjected to high heat loads during match play in hot environments. However, a 10-minute break in play decreased core temperature in 6 of 7 players by an average of 0.25°C, indicating that the break provides practical benefits in the field. Furthermore, although mean sweat rate in this group of female tennis players was high, most athletes were still able to minimize mass loss to less than 2% of their prematch weight.

The Effect of Playing Surface on Injury Rate

Synthetic playing surfaces are widely used for field and court sports. Artificial turf surfaces are commonly used as an alternative to natural grass, while outdoor surfaces like clay and acrylic are also prevalent. The effect of these synthetic surfaces on injury rates has not been clearly established. The available literature is largely limited to football and soccer data and the majority of studies are short-term. Confounding variables such as climate, player position and footwear, as well as varying definitions of injury, also make it difficult to draw firm conclusions about the general effect of artificial playing surfaces on injury rates. Many peer-reviewed studies cite a higher overall rate of injury on first- and second-generation artificial turf surfaces compared with natural grass. Despite differences in injury type, the rate of injury on third-generation and natural grass surfaces appears to be comparable. It also appears that clay is significantly safer than either grass or hard court tennis surfaces, but this is a conclusion drawn with limited data. Further research investigating overall injury trends as well as sport-specific data is needed to draw more definitive conclusions regarding the effect of artificial playing surfaces on injury rates.

Monte Carlo Tennis: A Stochastic Markov Chain Model

We develop a stochastic Markov chain model to obtain the probability density function (pdf) for a player to win a match in tennis. By analyzing both individual player and 'field' data (all players lumped together) obtained from the 2007 Men's Association of Tennis Professionals (ATP) circuit, we show that a player's probability of winning a point on serve and while receiving serve varies from match to match and can be modeled as Gaussian distributed random variables. Hence, our model uses four input parameters for each player. The first two are the sample means associated with each player's probability of winning a point on serve and while receiving serve. The third and fourth parameter for each player are the standard deviations around the mean, which measure a player's consistency from match to match and from one surface to another (e.g. grass, hard courts, clay). Based on these Gaussian distributed input variables, we use Monte Carlo simulations to determine the probability density functions for each of the players to win a match. By using input data for each of the players vs. the entire field, we describe the outcome of simulations based on head-to-head matches focusing on four top players currently on the men's ATP circuit. We also run full tournament simulations of the four Grand Slam events and gather statistics for each of these four player's frequency of winning each of the events and we describe how to use the results as the basis for ranking methods with natural probabilistic interpretations.

Evaluation of Tennis Match Data - New Acquisition Model

Evaluation of Tennis Match Data - New Acquisition Model The purpose of this research was to analyze and interpret the latent (factor) area of a tennis match. The entities in this research make 128 tennis matches played at the 2007 and 2008 Grand Slams hard court surfaces. The variables were created by use of the official statistics kept by the IBM Software - IBM DB2 Universal Database. The original variables were standardized to the number of sets in a match. A factor analysis under a component model was conducted. The number of factors retained, which was determined by the G-K criterion, explained 83.38 % of the total variance. Five significant factors substantiated the hypothesis established in this paper. The first factor named Match Successfulness is determined by the total number of break points; break points won and received points. The second factor named First Serve Significance is determined by the total number of first serves and winning points after the first serve. The third factor named Serve Speed is determined by the average speed of the serve and the fastest serve. The fourth factor named Net Play is determined by the total net approaches as well as the winning points after net approaches which are directly dependent on the total number of serves. The fifth factor named Play Errors is determined by unforced and double-fault errors. Winning matches differentiate from the lost matches by a smaller number of unforced and double-fault errors; considerably better results of the first serve, maximum serve speed and the number of aces scored, high score of total break points and break points won. The facts that do not differentiate winning matches from the lost ones are: first serves total, first serve throw-in, winning points after the first serve, number of net approaches and winning points after net approaches. The classification results show that with a system of 15 variables it is possible to recognize 96.0% of lost and 96.9% of winning matches. The achieved results indicate that the official match statistics with a modified system of 15 selected variables can properly interpret and predict match successfulness. This enables creators of a match observation system to valorize and enhance it with new indices.

Tennis physics, anyone?

After a tennis ball lands on the court, it slows down, spins up, and squashes. Friction on the ball can even reverse direction, pushing it forward.

Experimental designs in sport implement research: Application to the tension loss in tennis strings

The aim of this study was to quantify the influence of five experimental variables (style of play, sheath and central structure of synthetic strings, racket frame, and game court) on the tension loss in tennis strings in field situations, using experimental design methodology. Sixteen experiments were defined using a fractional factorial design 2(5–1). The tension loss in tennis strings was calculated by the difference between the tension measured just before and just after one hour of play. Multiple linear regression was performed to express the tension loss as a function of the five experimental variables and their first‐order interactions. The results showed that the tension loss was influenced by three main experimental variables: game court, racket frame, and string‐sheath, and by four two‐factor interactions, including the style of play and string central structure interaction term. The tension loss in tennis strings was minimal when playing with an 18‐main‐string racket frame strung with an S1‐coated string on a hard court. This work suggested that experimental designs could help researchers to highlight the sport implements’ behaviour in field situations.

Caffeine, Carbohydrate, and Cooling Use During Prolonged Simulated Tennis

To determine the effects of prolonged simulated tennis on performance and the ergogenic potential of caffeine, carbohydrates, and cooling. Twelve highly trained male tennis players (age 18.3 +/- 3.0 y, height 178.8 +/- 8.5 cm, body mass 73.95 +/- 12.30 kg, mean +/- SD) performed 4 simulated matches (2 h 40 min) against a ball machine on an indoor hard court. The counterbalanced experimental trials involved caffeine supplementation (3 mg/kg), carbohydrate supplementation (6% solution), precooling and intermittent cooling, and placebo control. Physiological markers (core temperature, heart rate, blood lactate, and blood glucose), subjective responses (ratings of perceived exertion and thermal sensation), stroke velocity and accuracy, serve kinematics, and tennis-specific perceptual skill quantified the efficacy of interventions. Significant effects of time (P < .01) reflected increased physiological demand, reduced serve velocity and ground-stroke velocity and accuracy, and a slowing of the serve racket-arm acceleration phase. Caffeine increased serve velocity (165 +/- 15 km/h) in the final set of the match (P = .014) compared with placebo (159 +/- 15 km/h, P = .008) and carbohydrate (158 +/- 13 km/h, P = .001) conditions. Carbohydrate and cooling conditions afforded physiological advantage (increased blood glucose, P < .01, and reduced preexercise thermal sensation, P < .01) but did not affect performance relative to the placebo condition. Prolonged simulated tennis induced significant decrements in tennis skills. Caffeine supplementation partly attenuated the effects of fatigue and increased serve velocity. In contrast, carbohydrate and cooling strategies had little ergogenic effect on tennis performance.

An integrated physiological and performance profile of professional tennis

Objective: To describe the physiological responses to tournament tennis in relation to prevailing environmental conditions, match notation, and skills that underpin performance. Design: 14 male professional tennis players (mean (SD)...

Walking Stride Variability On Different Walking Surfaces

Measurements of the fractal scaling index of gait (α) provide an estimate of gait stability and risk of falling. Little attention has been given to the effects of walking surface on this measurement. PURPOSE: This investigation compared stride-to-stride variability for healthy subjects walking on two different surfaces. METHODS: Seven healthy subjects (ages 20–56) performed 20–25 minute, self-paced walks (1100–1300 strides) on two different surfaces (tennis hard court and an all-weather rubberized running track). An oval walking route was used to minimize the effects of turns on stride-to-stride variability. Surface roughness was estimated from the standard deviation of the vertical accelerations (SDa) made by a remote control vehicle as it traveled over the surfaces at the same average speed as the walkers. Each subject wore a shoe constructed from wool felt. Three force-sensing resistors were placed in the sole of the shoe worn by the dominant foot (usually the left): at the heel and at the head of the first and fifth metatarsals. A recorder carried in a fanny pack digitized the output of the sensors (256 Hz, 12-bit A/D) after it was passed through a signal-conditioning preamp and the stride times extracted. Stride-to-stride variability was estimated from the standard deviation (SDw) and the coefficient of variation (CV). Detrended fluctuation analysis was used to estimate α. RESULTS: The fractal scaling index was significantly higher (i.e. risk of falling smaller) for walking on the rougher surface (P < 0.0001; Wilcoxon rank sum test): running track (SDa = 0.28 m/sec2): α ∼0.96 (range .88-1.10); tennis court (SDa = 0.09 m/sec2): α ∼ 0.83 (.76-.89). The fractal scaling index for shuffled gait stride data was similar to that for uncorrelated white noise (α ∼ 0.5). No significant difference between the two surfaces was observed for the SDw and CV of the gait strides (P > 0.4). CONCLUSIONS: Changes in walking surface roughness over a range typically encountered during activities of daily living affect α, but not other measurements of gait variability. In particular walking surfaces that are slightly rougher than those typically encountered in residential and clinical settings (e.g. SDa ∼0.1 m/sec2) may offer advantages for minimizing risk of falling.

The importance of the International Tennis Federation's junior boys' circuit in the development of professional tennis players

The relationship between junior boys' tennis success, as measured by a top 20 International Tennis Federation's Junior Circuit (ITFJC) ranking, and subsequent ranking accomplishments in professional men's tennis is discussed. The names, countries, and birthdates of all players to achieve a top 20 ITFJC boys' year-end ranking from 1992 to 1998 were recorded. The progress of these players through the professional ranks was then tracked to the end of 2004. Results indicate that 91% of top 20-ranked boys achieved a professional men's ranking, while a stepwise regression analysis revealed junior ranking (JR) to be a predictor of future, professional ranking (β = 0.232, r 2 = 0.054, p < 0.05). A regression equation [predicted professional rank = 78.17 + 6.31*(JR)] accounted for a significant amount of variance in professional ranking. For male players, therefore, the achievement of a top 20 junior ranking appears to be a reasonable yardstick for future, professional success. The type of surface upon which junior players develop their games was also shown to influence professional ranking highs, with play on clay courts or a combination of clay and hard courts helping to produce higher, professionally ranked players than hard court play alone (p≤ 0.01).

METABOLIC AND FUNCTIONAL RESPONSES PLAYING TENNIS ON DIFFERENT SURFACES

The purpose of this study was to compare various metabolic and functional responses while playing tennis on clay and hard courts. Twelve 90-minute matches were played (6 on clay courts and 6 on hard courts) by 4 nationally ranked players. During the on-court tests, oxygen uptake (VO2) and heart rate (HR) were measured using portable systems. Capillary blood lactate concentration (LA) was measured every 10 minutes. Additionally, distance ran, playing time, resting time, and exercise to rest ratio were monitored by time-motion analysis. The statistical analysis showed that playing time was higher on clay courts than on hard courts (p < 0.05), and resting time on clay courts and hard courts was not statistically different (p > 0.05). The exercise to rest ratio was affected by the interaction between playing time and resting time, showing a longer recovery time per unit of exercise on hard courts than on clay courts (p < 0.05). Distance ran, mean HR, and mean LA were significantly higher on clay courts than on hard courts (p < 0.05). There was less fluctuation of the VO2 response on clay courts than on hard courts. Therefore, it is suggested that conditioning programs should be adjusted according to the playing surface to account for the longer playing time, greater exercise to rest ratio, increased HR and LA, and a more steady pattern of VO2 seen on clay courts.

The relationship between court surface and tactics in tennis using a computerized scorebook.

The purpose of this study was to use a newly developed computerised scorebook for tennis in order to clarify the characteristics of tennis tactics used on specific court surfaces. The authors developed a computerised scorebook for tennis that calculates the time duration of shots, points, and the time between points. Data were collected from matches played by male Japanese intercollegiate players. A total of 97 points were observed. Two observers (A, B) were recruited for recording matches using the scorebook. The mean error of observer A was 0.003±0.05 s, while the mean error of observer B was 0.02±0.10 s.The computerised scorebook for tennis was used to collect data for clarifying the characteristics of tennis tactics used on specific court surfaces. Forty-one matches from the Grand Slam tournaments held in 2003 and 2004 were analyzed. The scorebook recorded the final shot of each point, the result of each point, and the time duration of each shot. The final shots were categorised into the following 5 groups: service, return of serve, ground strokes, attacking strokes, and defending strokes. The time between the impact of the serve and the impact of the return of serve determined the duration of service. The time duration of ground strokes was calculated as the time between the impact of one player and the impact of the other player. A chi-square test was used to compare the distribution of the final shots on each surface. An ANOVA test was conducted in order to compare the time duration on each surface and a Tukey’s HSD test was used for multiple comparisons. For the last shot of each point, significant differences were observed between the court surface and the distribution of the type of stroke. The percentage of ground strokes was high on clay while the percentages for attacking and defending strokes were high on grass. Furthermore, the rate of service strokes was high on hard courts. The shot time duration of the 1st service was 0.91 s on clay, 0.71 s on grass, and 0.73 s on hard courts. The time duration of service on clay was significantly longer than the time durations observed on other surfaces. The time duration of ground strokes was 1.36 s on clay, 1.34 s on grass, and 1.35 s on hard courts. The time duration of ground strokes on clay was significantly longer than time durations observed on grass; however, the difference was only 2/100 of a second. Service and return of service strokes were important to the tactics used on grass and hard courts as players must react more quickly than on clay. Ground strokes were important on clay and hard courts, and the average time duration of ground strokes was equal on these surfaces.

Tennis specific limitations in players with an ACL deficient knee

Background: Complete rupture of the anterior cruciate ligament (ACL) causes significant alteration of knee joint kinematics. Untreated patients often develop joint instability, chronic articular degeneration, and knee dysfunction. Demands on...

INJURIES DURING AN INTERNATIONAL PROFESSIONAL BEACH VOLLEYBALL TOURNAMENT

The purpose of this project was to evaluate injury patterns during an international, Olympic qualifier professional beach volleyball tournament. Similar previous analyses have generally focused on indoor, hard court volleyball players. In these studies, the most common injuries generally reported included ankle and thumb sprains, overuse injuries of the knee and shoulder, suprascapular neuropathy, and low back injury. In this 7-day tournament, a total of 35 injuries were recorded. The most common injuries were cervical and low back strains, accounting for 7 (20%) of the injuries. There were also 2 quadriceps strains, 2 iliotibial band syndromes, 2 lateral ankle sprains, 1 supraspinatus strain, and 1 biceps tendonitis. Foot injuries accounted for 5 (14%) of the injuries. Two toe lacerations, 1 sesamoiditis, 1 toenail avulsion, and 1 puncture wound from a nail were noted. Despite a concern about heat injury, mild heat exhaustion occurred in only 1 individual. One anterior shoulder dislocation occurred in an athlete during a jump serve. It appears that the injury pattern does differ between hard court and sand volleyball players. Sand volleyball may be associated with less overuse injuries to the knee, but with an increased risk of traumatic foot injury. Health care personnel covering such events should be prepared for a different injury pattern than is seen in the indoor, hard court game.

INJURIES IN PROFESSIONAL BEACH VOLLEYBALL - A PROSPECTIVE ANALYSIS OF INJURIES DURING THE 1995 AVP PRO BEACH VOLLEYBALL TOUR 1066

Although previous prospective studies have addressed common injuries among indoor volleyball players, there have been no published reports which specificly involved professional beach volleyball players. The physical demands of the beach volleyball athlete are extremely rigorous and unique to this rapidly growing sport, thus suggesting that the injury rate and prevalence may be high. The athletes studied were members of the Association of Volleyball Professionals and participated in the 1995 AVP Pro Beach Volleyball Tour. Injury data was collected from June through August 1995 during five different three day tournaments, and included anatomical site, injury type, maneuver performed, and treatment required. A total of 56 injuries were recorded. The most common involved the spine (27), followed by the lower extremity (17), and the upper extremity (6). In addition, an injury which appears to be completely flexion injury to the metatarsophalangeal joint of the great toe, was prevalent. Overall most of the injuries occurred during a defensive dive (or dig) or during a jump serve. The differences in the composition of the playing surface (sand vs. hard court) and the total court area covered in beach volleyball by 2 players vs. the area ccvered in indoor volleyball by 6 players probably are significant factors in the type and rate of injury. In summary, the injuries sustained in beach volleyball athletes have not previously been documented and include injuries that are unique to the sport. Treatment and prevention of these injuries should be sport-specific.