There are distinct physiological and biomechanical differences associated with exercise on a sand training surface, when compared with a firmer and more conventional training surface such as grass (14,23–25,28). These differences include a significant alteration in kinematics and muscle activation patterns when running on sand (25), contributing to a significantly greater energy expenditure when compared with running on a firmer surface at similar speeds (14,23,25,28). Furthermore, the high absorptive qualities of a sand training surface can reduce ground reaction forces (3,5), and limit maximal movement output in the form of sprinting (3) and jumping performance (5,7,10). Despite these substantial differences, research has shown that training on a sand surface can lead to improvements in firm ground performance (11,12).
Impellizzeri et al. (12) investigated the effect of sand vs. grass training surfaces during 4 weeks of plyometric training in amateur soccer players. They showed a significant improvement in firm ground sprinting and jumping performance at the conclusion of the plyometric training on both sand and grass surfaces, with similar changes seen in both training groups. Furthermore, Gortsila et al. (11) showed that 10 weeks of agility training on a sand surface resulted in a significant improvement in agility tests (T-Test and Illinois test) conducted on both sand and firm surfaces. Along with these apparent benefits to firm ground performance gains, a sand training surface is also associated with significantly lower impact forces that can influence the rate and extent of musculoskeletal loading during exercise (3,12,18). A reduction in loading forces may be particularly useful during high-intensity training such as sprinting, jumping, and agility movements, because significant demands are placed on the leg muscles, tendons, and the muscle-tendon units (12). A reduction in stress through these systems may decrease the risk of injury during exercise (12) and can also lead to lower levels of muscle damage, soreness, and associated negative side effects, such as a reduced performance capacity (12,18). Therefore, the use of a sand training surface may be beneficial in sports that involve a high-intensity training component, such as those encountered during team sport activity.
In Part 1, we compared the use of sand and grass training surfaces during a preseason interval training session in team sport athletes. Results from this study showed that performing a standardized interval training session on sand vs. grass can result in significantly greater training intensities, without any increase in muscle damage, soreness or inflammation that typically arise from an increase in exercise intensity. Furthermore, next-day (24 hours postexercise) performance was also unaffected by the higher intensity training session experienced on the sand surface. Following on from these findings, the aim of this study was to determine whether these differences with sand training were also present during more specific team sport conditioning sessions commonly performed in the later stages of a preseason program. Currently, there is little research to support and quantify the physiological effects of sand (vs. grass) at higher running speeds (i.e., sprinting), and during the other high-intensity components of team sport activity such as jumping and rapid changes of direction. Therefore, the results gained from this study are intended to broaden the application for sand training in team sports, and to determine the value of using sand as an alternative training surface to grass during sport-specific training sessions. It was hypothesized that the completion of such a training session on sand (vs. grass) would result in greater training intensities, without any additional detriment to hematological (muscle damage, inflammation, and hemolysis), perceptual (muscle soreness), or physical (athletic performance) markers of recovery.
Experimental Approach to the Problem
The experimental design used in this study was identical to that of Part 1, with athletes required to complete 5 separate testing sessions in a repeated measures design, including 3 performance trials, and 2 training sessions (one each on SAND and GRASS). However, in comparison to the interval running session examined in Part 1, this study investigated the effect of both training surfaces during a more sport-specific conditioning session in team sport athletes. The training session was designed to replicate the movement patterns common to most team sports, including acceleration, agility, and generic game simulation drills. The same training session was completed on both SAND and GRASS surfaces in consecutive weeks, with each session followed 24 hours later by a performance trial consisting of vertical jump (VJ), a repeated sprint ability (RSA) test, and a 3-km running time trial (RTT). These 24 hours postexercise performance trials were compared with the baseline measures (BASE) of these performance indicators to compare the effect of each surface condition on next-day recovery. The same physiological and perceptual variables (blood lactate [BLa], heart rate [HR], and ratings of perceived exertion [RPEs]) were measured during each testing session, and also throughout the 24 hours postexercise period (muscle damage, inflammation, and hemolysis) for a further comparison between the 2 surfaces. In addition, player movement patterns were also monitored during the sport-specific conditioning sessions via global positioning system (GPS) units. Movement variables such as distance and speed were analyzed from the GPS data to gauge the effect of each surface condition on player movement patterns during the standardized drills and games.
Determination of sample size was attained via a power analysis using a customized computer software program (GPOWER Version 2.0, Department of Psychology, Bonn University, Bonn, Germany). The effect sizes used to generate the sample size estimation were attained from previous investigations exploring variables similar to the proposed research (1,13,21). For this study, a sample size of 9 was recommended to yield a power of 0.85 at a significance level of 0.05. Therefore, 10 well-trained team sport athletes were recruited for participation in this investigation. Eight men (Age: 21.8 ± 2.2 years; Mass: 78.1 ± 6.2 kg; Height: 180.8 ± 5.2 cm) and 2 women (Age: 21.0 ± 1.4 years; Mass: 73.9 ± 17.7 kg; Height: 178.6 ± 13.6 cm) were recruited from the same group of athletes that took part in Part 1. At the time of the investigation, all the athletes were in the general preparation phase of their preseason training cycle (summer season). The participants were informed of the requirements and risks associated with their involvement in this study, before written consent acknowledging these details was obtained. Institutional Review Board (IRB) approval for the use of human subjects during this investigation was granted by The University of Western Australia's Human Research Ethics Committee (IRB # RA/4/1/4373).
The methods used in this study are fully described in Part 1, including the 4-week familiarization period and dietary restrictions, and the methodology for the performance trials, and all variables measured throughout each testing session. The sand (SAND) interval training session was conducted on soft dry beach sand, on a level area of beach removed from the water's edge. The regional characteristics of the beach can be defined as carbonate rich, fine to medium grain sand (ø ∼0.4 mm) (27). The grass (GRASS) interval training session was conducted on a well-maintained sporting ground (Kikuyu grass). The athletes were barefoot during the SAND trial, in comparison with GRASS where they wore running shoes. The mean ambient air temperature and relative humidity recorded during the SAND and GRASS trials were 27.5 ± 1.6° C and 52.4 ± 11.3%, respectively, and were 29.3 ± 1.1° C and 41.8 ± 11.2% during the baseline (BASE), and 24 hours postexercise performance trials. The additional details of the methodology are outlined here; otherwise, the reader is referred to Part 1 for other information.
Sport-Specific Training Session
The training session included 2 blocks of activity separated by a short period of rest (5 minutes). The first block of activity consisted of various sport-specific drills (DRILL) including repeated sprint bouts, agility, and power drills involving rapid changes of direction and speed. All drills were performed at a perceived maximal intensity, with an active recovery between efforts in which athletes made their way back to the same start point. First, athletes completed 5 × 5-second maximal sprints on a 1-minute 20-second departure time. After a 3-minute rest period, an agility drill involving a zig-zag-like movement, followed by a maximal sprint that was completed in a combined effort time of approximately 5 seconds. The zig-zag movement involved running around 5 cones that were placed 2 m apart, and 2 m out to alternating sides of a central line. This drill was repeated for 5 efforts on a 1-minute 20-second departure. After another 3-minute rest, the final drill involving a repeated sprint bout of 6 × 4-second maximal sprints on a 30-second departure time was completed.
The second block of activity consisted of small-sided game (SSG) training, and included 5 × 5-minute games, each separated by 2 minutes of rest. First, athletes were randomly allocated into 2 teams of 5, with 1 of the female athletes placed in each team. Subsequently, the 5 vs. 5 game formats were played out on pitch dimensions of 20 × 30 m. Each of the 5 game formats were possession based (tennis ball), with subtle rule changes between games to encourage maximal involvement and to simulate movement patterns similar to those experienced during competitive team sport activity. Player movement patterns were monitored using portable GPS units that were worn by the athletes over the duration of the session. Heart rate was monitored throughout the entire session, with BLa and RPE taken immediately postexercise, and an additional measurement of RPE was taken in between the 2 activity blocks.
Blood Sampling and Analysis
The reader if referred to Part 1 for a full description of the biochemical procedures used in this study. The only change in blood sampling and analysis procedures from Part 1 was the exclusion of Creatine Kinase as a marker of muscle damage. Therefore, Myoglobin (Mb) was used as the sole marker of muscle damage in this study.
Movement Pattern Analysis
Movement patterns were measured using a portable GPS device (MinimaxX, Catapult Innovations, Australia) that was secured in place between the player's scapulae with a harness. The GPS units sampled with a frequency of 5 Hz over the entire duration of the sport-specific training session, with the rest periods between drills and games excluded from analysis. Data from each GPS unit were downloaded to a laptop computer and analyzed using commercially available software (LoganPlus v.4.7). For the data analysis, the speed zones used were individualized and based on a percentage of each athlete's fastest 20-m sprint pace (meters per second) achieved in the preliminary testing session. From this, 3 speed zones were established: low (0–40%), moderate (40–75%), and high (75–100%). The physical variables extracted from this data were total duration (minutes), total distance covered (meters), and average movement velocity (meters per minute) for each speed zone.
All results are expressed as mean with 95% confidence intervals (±95%CI), or standard error of measurement (SEM) for clarity of figures. The reader is referred to Part 1 for a full description of the statistical analyses run on the dependent variables common to both studies. In addition, the effect of each training surface on movement patterns during the sport-specific training session was analyzed using a repeated measure analysis of variance of the time and trial differences in duration, distance and average velocity in each predefined GPS speed zone on both SAND and GRASS. Post hoc (Fisher's least significant difference), paired samples t-tests were used in the event of a main effect to determine specific differences between the surface trials. The alpha level was set at 0.05. Finally, trends in performance were interpreted using Cohen's d effect sizes. However, only effect sizes >0.50 were reported here. The thresholds for the qualitative descriptors of these effects were set at 0.50–0.79 as ‘moderate,’ and ≥0.80 as ‘large’ (8).
Ground Surface Conditions
Surface stiffness measures showed peak impact deceleration forces recorded on SAND (342.2 ± 68.9 N) were significantly lower (p < 0.001) than for GRASS (1,306.7 ± 163.9 N).
Physiological and Perceptual Responses to Training
A significant time effect (p < 0.001) showed that BLa increased from postwarm-up to posttraining in both SAND and GRASS (p < 0.05; Table 1). No significant trial effect (p = 0.454) or time × trial interaction (p = 0.110) existed between the 2 training surfaces. However, large effect sizes suggested that the postwarm-up BLa values were higher on SAND (d = 1.96), and the relative change in BLa was greater on GRASS (d = 0.82).
Ratings of Perceived Exertion
A significant time effect (p < 0.001) showed that RPE was greater during SSG compared with DRILL, for both SAND and GRASS (p < 0.05; Table 1). A significant trial effect (p = 0.002), but not a time × trial interaction (p = 0.148) existed between the 2 training surfaces. Postwarm-up RPE was higher on SAND (p = 0.012), and moderate to large effect sizes suggested that RPE was higher on SAND for both the DRILL (d = 0.89) and SSG (d = 0.51), with the average RPE recorded for both blocks of activity also significantly higher on SAND (p = 0.034).
A significant time effect (p < 0.001) showed that HR was higher during SSG when compared with DRILL, for both SAND and GRASS (p < 0.05; Table 1). Furthermore, HR for the entire training session (DRILL and SSG) was significantly higher on SAND (p = 0.002). However, examining the activity blocks in isolation, it was found that HR was significantly higher on SAND for DRILL only (p < 0.001), and not SSG alone (p = 0.709).
In addition to average HR for the entirety of the SSG activity block, further analysis was conducted to compare HR from each of the 5 individual games within both trials (Table 2). Here, a significant time effect (p < 0.001) revealed that HR during SSG 1 on SAND was higher than all other games (p < 0.05), and HR during SSG 5 was lower than all other games (p < 0.05). For GRASS, HR during SSG 1 was lower than all other games (p < 0.05), and HR during SSG 5 was higher than all other games (p < 0.05). Also, a significant time × trial interaction (p < 0.001), but not a trial effect (p = 0.709) existed between the 2 training surfaces, showing that HR during SSG 1 was higher on SAND (p < 0.001), whereas HR during SSG 5 was higher on GRASS (p < 0.001).
No significant differences were observed between trials for relative VJ height or leg power (p > 0.05; Table 3).
Repeated Sprint Ability
No significant differences were observed between trials for fastest 20-m sprint time, total sprint time (for all 8 repetitions), or percentage decrement in sprint times (p > 0.05; Table 3). Also, no differences were evident between trials for BLa and HR recorded during RSA (p > 0.05).
Three-Kilometer Running Time Trial
No significant differences were observed between trials for time taken to complete RTT (p > 0.05; Table 3). Furthermore, no differences were observed between trials for BLa (p > 0.05); however, the HR recorded during RTT was significantly greater in SAND (p = 0.001).
Delayed Onset Muscle Soreness
A moderate effect size (d = 0.64) showed that 24 hours postexercise delayed onset muscle soreness (DOMS) rating for the hamstring muscle group was higher after GRASS (5 ± 1) compared with SAND (3 ± 2), and a large effect size (d = 0.81) also showed that DOMS rating for the tibialis anterior/peroneal muscle group was higher after SAND (3 ± 2) compared with GRASS (1 ± 1). However, there were no differences observed in any of the other muscle groups (p > 0.05). Furthermore, no significant differences existed in total DOMS rating between SAND (16 ± 6) and GRASS (14 ± 5) (p > 0.05).
A significant time effect (p < 0.001) showed that Mb increased from pretraining to posttraining in both SAND and GRASS (p < 0.05; Figure 1A). However, no significant trial (p = 0.446) or time × trial interactions (p = 0.970) were recorded between the 2 training surfaces.
A significant time effect (p < 0.001) showed that Haptoglobin (Hp) levels were decreased after exercise in both SAND and GRASS (p < 0.05; Figure 1B). No significant trial (p = 0.660) or time × trial interactions (p = 0.252) existed between the 2 training surfaces, although a moderate effect size (d = 0.75) suggested the change in Hp from pretraining to posttraining was greater on GRASS.
A significant time effect (p = 0.012) revealed that C-reactive protein (CRP) levels were increased from preexercise to 24 hours postexercise in both SAND and GRASS (p < 0.05; Figure 1C). No significant trial (p = 0.105) or time × trial interactions (p = 0.312) were evident between the 2 training surfaces; however, moderate effect sizes suggested that pre (d = 0.50), 24 hours post (d = 0.60), and relative change in CRP (d = 0.51) was higher on SAND.
Movement Pattern Analysis
The number of satellites in position (SAND: 7 ± 0, GRASS: 7 ± 0), and horizontal dilution of precision (SAND: 2.1 ± 0.2, GRASS: 2.1 ± 0.2 H-DOP) were not significantly different between SAND and GRASS (p = 0.713 and p = 0.460, respectively). Maximum velocity was significantly higher (p = 0.044) on GRASS (7.4 ± 0.2 m·s−1) compared with SAND (6.7 ± 0.4 m·s−1).
In the low (0–40%) speed zone, duration was significantly greater on SAND (p < 0.001; Table 4). No significant differences were observed between trials for distance covered (p = 0.967); however, average velocity was significantly greater on GRASS (p = 0.01). In the moderate (40–75%), high (75–100%), and overall (0–100%) speed zones, duration, distance, and average velocity were all significantly greater on GRASS (p < 0.05).
There were significant time effects for duration, distance, and average velocity in this speed zone on both SAND and GRASS (p < 0.05; Table 4). Distance covered in SSG 5 was lower than all other games on SAND (p < 0.05), and lower than SSG 1, SSG 2, and SSG 3 on GRASS (p < 0.05). Also, on SAND, average velocity in SSG 1 was higher than all other games (p < 0.05), whereas average velocity in SSG 5 was significantly lower than all other games (p < 0.05). Significant trial effects (p < 0.05) showed that duration was greater on SAND for all 5 games (p < 0.05), whereas distance covered was only greater on SAND for SSG 1 (p = 0.033). Average velocity was greater on GRASS for SSG 2, SSG 3, and SSG 5 (p < 0.05). Furthermore, an average of all 5 SSG was calculated, showing that duration was greater on SAND, whereas average velocity was greater on GRASS (p < 0.05).
Significant time effects (p < 0.05) showed that duration and distance covered in this speed zone was greater for SSG 5 compared with SSG 2, SSG 3, and SSG 4 on GRASS only (p < 0.05; Table 4). Furthermore, significant trial effects (p < 0.05) showed that duration and distance covered were greater on GRASS for all 5 SSG (p < 0.05), whereas average velocity was also higher on GRASS during SSG 4 and SSG 5. The average of all 5 SSGs revealed that duration, distance, and average velocity were greater on GRASS (p < 0.05).
No significant time effects (p > 0.05) existed; however, there were significant trial effects for duration, distance, and average velocity in this speed zone between the two training surfaces (p < 0.05; Table 4). Duration and distance covered were greater on GRASS during SSG 1, SSG 2, SSG 4, and SSG 5 (p < 0.05), whereas average velocity was greater on GRASS for SSG 5 only (p = 0.044). Furthermore, the average of all 5 SSGs showed that the duration, distance, and average velocity were greater on GRASS (p < 0.05).
No significant time (p = 0.257) or trial effects (p = 0.403) existed for total duration in any of the 5 SSGs between the 2 training surfaces (Table 4). However, a significant time effect (p = 0.007) revealed that distance covered in SSG 5 was lower than all previous games in SAND (p < 0.05), whereras distance and average velocity in SSG 5 were higher than SSG 2, SSG 3, and SSG 4 in GRASS (p < 0.05). Furthermore, significant trial (p < 0.05) and time × trial interactions (p < 0.05) showed that distance covered and average velocity were higher in GRASS for all 5 SSG (p < 0.05).
The results of this study show a significantly higher session average for HR and RPE after a team sport-specific training session conducted on sand vs. grass training surfaces. In addition to the findings from Part 1, this study shows that sand training can result in greater exercise intensities experienced by team sport athletes, not only during preseason conditioning sessions but also for sport-specific sessions encountered toward the end of the preseason and throughout the competitive season. However, it must be recognized that the nature of the physiological response seen on sand is different between these 2 types of team sport training. More specifically, the changes seen in HR and RPE here are of a lower magnitude when compared with the interval training session investigated in Part 1 and therefore suggest a reduced effect of sand surface during sport-specific training. It has been suggested that a smaller difference in the degree of stiffness (peak impact deceleration forces) measured between sand and grass training surfaces can contribute to a reduced physiological response on sand (23,24). That is, the difference in stiffness ratings between sand and grass surfaces appear to be directly related to the energy cost differential observed during exercise. A softer surface will provide less stability and energy return during the stance phase of gait, thereby requiring a greater input from the muscles to achieve the same movement output (14,23,25). That being said, the surface readings taken here indicate a softer sand surface, and a greater difference in stiffness levels between sand and grass surfaces when compared with Part 1. Therefore, it is unlikely that surface conditions are responsible for the blunted physiological responses observed here.
It is more likely that the HR and RPE responses are a reflection of the type of activity performed in the sport-specific training session. It is well documented that the effects of sand are reduced at faster running speeds (13,23–25), possibly because of a lower relative foot contact time with the unstable surface as running speed increases (25). Although a direct comparison of running speeds cannot be made, it is possible that athletes were running at faster speeds in the current investigation, when compared with the interval training session examined previously. This is because the DRILL and SSG components of the sport-specific training session largely consisted of shorter duration sprints (<10 seconds), interspersed with a greater relative recovery ratio, which may have allowed the athletes to work at a higher intensity for each exercise interval. In addition to HR and RPE, the BLa response to exercise seen here was also in contrast to previous sand running investigations (23,24). There was a significant increase in BLa on both sand and grass, but no differences existed between the 2 surfaces. Previous research has reported that BLa accumulation is generally 2–3 times higher on sand because of the higher relative training intensities, and the recruitment of additional musculature to assist in stabilization during the support phase of gait (23,25). Although higher training intensities on sand were evident here, the shorter work intervals and longer recovery times may have counteracted any additional accumulation of lactate on the sand surface. However, it is hard to discern the exact cause of this BLa response, because the posttraining BLa sample was taken after the last of the 5 SSGs, and may not have given a true representation of the BLa levels encountered throughout the session. Therefore, future research should obtain more frequent BLa samples to better understand BLa kinetics during high-intensity intermittent activity on sand.
Upon further examination of the physiological response to exercise, it is apparent that there were different effects of the training surface between the 2 blocks of activity (DRILL and SSG). Although average HR for the entire session was significantly higher on sand, this was elevated as a result of a significantly higher HR in the DRILL activity block only, and not the SSG. This may imply that sand is more effective during the structured workload times encountered in DRILL, in comparison to the self-paced workload of SSG training. It is well known that exercise on sand can result in a significantly greater EC for a given workload time (14,23–25,28); however, this is the first study to show a significant physiological effect of sand during short (≤6 seconds), high-intensity sprint and agility drills. Furthermore, the athletes were running at speeds of up to 6.7 m·s−1 (24.1 km·h−1) during DRILL on sand, which is much higher than the previous top speed at which sand is shown to have a significant physiological effect (11 km·h−1) (23–25). Interestingly, the HR difference evident during DRILL is of a similar magnitude to that observed between sand and grass surfaces in Part 1, despite the potentially faster running speeds. Therefore, although there is a trend for physiological responses (HR, BLa, RPE) between sand and grass surfaces to become more similar as running speed increases (23,24), perhaps there is an upper limit for speed at which the effect of sand does not fall any further. Despite this evidence, it must be noted that the majority of DRILL was spent recovering between efforts in a slow jog and walk back to the start line, and because the effect of sand is greater at these slower speeds (14,23–25,28), this may have inflated the physiological responses seen for the entire DRILL block. Therefore, to gain a true understanding of the energetics of sand running during high-speed sprint and agility drills, future research should aim to look at these efforts in isolation.
In contrast to the findings from DRILL, the average HR for the SSG activity block was not different between surfaces. However, the average velocity and distance covered during SSG was significantly lower on sand, suggesting that a significantly higher intensity would be required for the same movement output when compared with grass. The lack of difference in HR observed between training surfaces may be because of the self-paced nature of SSG training, suggesting that athletes may have consciously (or subconsciously) varied their workload throughout the SSG training, to attain the same physiological outcome on both surfaces (4,19). Recent research has suggested that workload during exercise is ultimately regulated by a ‘central governor,’ which involves the central nervous system integration of feed forward and feedback control mechanisms in the brain and peripheral physiological systems, to maintain cellular homeostasis under all conditions of exercise (19). In this study, average HR on both surfaces for the entire SSG activity block was approximately 90% of maximum (HRmax: 207 − age × 0.7) (9), and similar to HR levels encountered during competitive team sport activity on sand (7) and grass surfaces (26). Therefore, it is possible that the athletes were working at the maximum attainable average HR as regulated by the ‘central governor,, irrespective of the surface trained upon. However, it should also be noted that there are many different formats of SSG training, and factors such as pitch size, number of players and also the number and duration of games can significantly influence the resultant training intensities (20,26). Therefore, future research should aim to investigate the various SSG formats on sand vs. grass training surfaces, because such factors may influence the physiological responses seen.
Despite finishing with the same average HR for all 5 games, an analysis of each individual SSG revealed that athletes were working at a significantly lower HR on grass vs. sand during SSG 1. This difference seen in SSG 1 may be because of the execution of an effective pacing strategy in the grass trial. In support of this, HR during SSG 1 on grass was significantly lower than all other games, and HR during SSG 5 was significantly higher than all other games. Pacing strategies are established preexercise, and involve the conscious (or subconscious) variation of workload based on knowledge of the end point of exercise (4), or in this case, the number of SSG to be completed. In the grass trial, the athletes appear to have reduced their workload in SSG 1, to delay the onset of fatigue and complete SSG 5 at a higher intensity. This is in contrast to the sand trial, in which HR during SSG 1 was significantly higher, and HR during SSG 5 was significantly lower than all other games. These findings may indicate that the athletes worked too hard in SSG 1 on sand, resulting in residual fatigue throughout the remaining 4 games, and a significantly reduced performance in SSG 5. This may suggest that the athletes failed to adjust their pacing strategy to account for the higher EC of exercise on sand (14,23–25,28). Because pacing strategies are influenced by previous experience (i.e., muscular pain and fatigue) of the ensuing activity (2), it is possible that the athletes were not familiarized well enough with the physical demands of SSG training on sand. As a result, future research should aim to investigate whether an increased experience or familiarization to sand training can influence the pacing strategies adopted, and the training intensities used during subsequent sand trials.
In addition to the acute training responses (BLa, HR, and RPE), the blood markers of muscle damage (Mb), inflammation (CRP), and hemolysis (Hp) were not different between surfaces. An increase in exercise intensity is typically associated with an increase in these variables (6,16,21); however, our athletes were able to complete the sport-specific training session on sand at a significantly higher intensity (as indicated by the HR and RPE responses) without a greater magnitude of response. Such an outcome may be explained by the significantly lower degree of stiffness (peak impact deceleration forces) measured on the sand training surface. Previous research has shown that sand can reduce the forces placed on the musculoskeletal system during high-intensity activity, thereby limiting the degree of exercise induced muscle damage (18). Similarly, a reduction in force experienced at heel strike can limit the amount of hemolysis (red blood cell destruction) incurred during exercise (17). Further to this lower impact force, Pinnington (22) suggested that a greater degree of plantar flexion when running on sand could lead to a predominantly mid to forefoot running technique. Consequently, this running technique can negate the impact transient generally experienced at heel strike, and further reduce the magnitude of peak vertical force during the impact period (15). In addition to these hematological markers, there were also no differences between trials in next-day (24 hours) performance recovery or DOMS ratings. Therefore, the findings of this study suggest that the lower impact forces experienced on a sand training surface can allow for higher training intensities to be reached during a sport-specific training session, without affecting the acute (24 hours) recovery profile. However, although this study shows the benefits of sand for an isolated training session, the long-term effect of sand training in a team sport setting remains unknown. Therefore, sand should only be used as an adjunct, or occasional substitute (i.e., 1–2 times per week) to the primary training surface (i.e., competitive playing surface), as opposed to a complete replacement.
The results of this study suggest that performing a sport-specific conditioning session on a sand (vs. grass) training surface can result in a greater physiological response experienced by the athlete to a given training session. However, it appears that sand is more effective during structured running drills, in comparison to the self-paced nature of SSG training. That said, there are no negative effects of completing SSG training on sand, and a manipulation of the SSG format may influence the responses seen. Furthermore, the lower impact force experienced on sand appears to limit the rise muscle damage, muscle soreness, and detriments to performance capacity that might be expected from a higher intensity training session of the same relative work output. As a result, sand can be used as an alternative to the primary training surface in team sports, for sport-specific training sessions encountered toward the end of the preseason and throughout the competitive season.
The findings from this study show that sand can be used as an effective substitute to grass for high-intensity, sport-specific conditioning sessions in a team sport setting. For optimal outcome, sand should be used during structured training sessions with predefined workloads, because this may allow for additional training benefits to be gained over grass. Furthermore, sand should also be considered during periods of intensified training, because this surface may allow for higher training intensities to be achieved without any additional detriment to next-day (24 hours) performance. With this in mind, it is recommended to the coach or sport science practitioner working with team sport athletes, that sand should be used as an adjunct, or occasional substitute (i.e., 1–2 times per week) to the primary training surface for sport-specific conditioning sessions. Despite these recommendations, it is also important that athletes are gradually introduced to sand training (i.e., 5–6 sessions), as familiarization with the training surface may be necessary before consistent benefits are seen.
The authors wish to acknowledge the assistance of David Bell, Michelle Wilkins, and the athletes of the WAIS Hockey and Netball programs. They also wish to thank Jim Crandell (Dr. Baden Clegg Pty Ltd.) and Peter Ruscoe (Sports Turf Technology Pty Ltd.) for their assistance and expertise in dealing with the Clegg impact hammer. This research involves no professional relationships with companies or manufacturers who will benefit from the results presented here. Furthermore, the results of this study do not constitute endorsement by the authors or the National Strength and Conditioning Association.
1. Ascensão A, Rebelo A, Oliveira E, Marques F, Pereira L, Magalhães J. Biochemical impact of a soccer match—Analysis of oxidative stress and muscle damage markers throughout recovery
. Clin Biochem 41: 841–851, 2008.
2. Baron B, Deruelle F, Moullan F, Dalleau G, Verkindt C, Noakes TD. The eccentric muscle loading influences the pacing strategies during repeated downhill sprint intervals. Eur J Appl Physiol 105: 749–757, 2009.
3. Barrett R, Neal R, Roberts L. The dynamic loading responses of surfaces encountered in beach running. J Sci Med Sport 1: 1–11, 1997.
4. Billaut F, Bishop DJ, Schaerz S, Noakes TD. Influence of knowledge of sprint number on pacing during repeated-sprint exercise. Med Sci Sports Exerc 43: 665–672, 2011.
5. Bishop D. A comparison between land and sand
-based tests for beach volleyball assessment. J Sports Med Phys Fitness 43: 418–423, 2003.
6. Brancaccio P, Lippi G, Maffulli N. Biochemical markers of muscular damage. Clin Chem Lab Med 48: 757–767, 2010.
7. Castellano J, Casamichana D. Heart rate
and motion analysis by GPS
in beach soccer. J Sports Sci Med 9: 98–103, 2010.
8. Cohen J. Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum Associates, 1988.
9. Gellish RL, Goslin BR, Olson RE, McDonald A, Russi GD, Moudgil VK. Longitudinal modeling of the relationship between age and maximal heart rate
. Med Sci Sports Exerc 39: 822–829, 2007.
10. Giatsis G, Kolloas I, Panoutsakopoulos V, Papaiakovou G. Biomechanical differences in elite beach-volleyball players in vertical squat jump on rigid and sand
surface. Sports Biomech 3: 145–158, 2004.
11. Gortsila E, Theos A, Smirnioti A, Maridaki M. The effect of sand
-based training in agility of pre-pubescent volleyball players. 16th Annual Congress of the European College of Sport Science. Liverpool, United Kingdom. Book of Abstracts, 2011. pp. 643.
12. Impellizzeri FM, Rampinini E, Castagna C, Martino F, Fiorini S, Wisloff U. Effect of plyometric training on sand
versus grass on muscle soreness and jumping and sprinting ability in soccer players. Br J Sport Med 42: 42–46, 2008.
13. Ingram J, Dawson B, Goodman C, Wallman K, Beilby J Effect of water immersion on post-exercise recovery
for simulated team sport
exercise. J Sci Med Sport 12: 417–421, 2009.
14. Lejeune TM, Willems PA, Heglund NC. Mechanics and energetics of human locomotion on sand
. J Exp Biol 201: 2071–2080, 1998.
15. Lieberman DE, Venkadesan M, Werbel WA, Daoud AI, D'Andrea S, Davis IS, Mang'Eni RO, Pitsiladis Y. Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature 463: 531–535, 2010.
16. Mendham AE, Donges CE, Liberts AE, Duffield R. Effects of mode and intensity on the acute exercise-induced IL-6 and CRP responses in a sedentary, overweight population. Eur J Appl Physiol 111: 1035–1045, 2011.
17. Miller B, Pate RR, Burgess W. Foot impact force and intravascular hemolysis
during distance running. Int J Sports Med 9: 56–60, 1988.
18. Miyama M, Nosaka K. Influence of surface on muscle damage and soreness induced by consecutive drop jumps. J Strength Cond Res 18: 206–211, 2004.
19. Noakes TD, St Clair Gibson A, Lambert EV. From catastrophe to complexity: A novel model of integrative central neural regulation of effort and fatigue during exercise in humans: Summary and conclusions. Brit J Sport Med 39: 120–124, 2005.
20. Owen A, Wong DP, McKenna M, Dellal A. Heart rate
responses and technical comparison between small- vs. large-sided games in elite professional soccer. J Strength Cond Res 25: 2104–2110, 2011.
21. Peeling P, Dawson B, Goodman C, Landers G, Wiegerinck ET, Swinkels DW, Trinder D. Training surface and intensity: Inflammation, hemolysis
, and hepcidin expression. Med Sci Sports Exerc 41: 1138–1145, 2009.
22. Pinnington HC. The Physiological and Biomechanical Aspects of Running on Grass Compared to Soft Dry Sand
. Unpublished doctoral dissertation, University of Western Australia, Perth, 2002.
23. Pinnington HC, Dawson B. The energy cost of running on grass compared to soft dry beach sand
. J Sci Med Sport 4: 416–430, 2001.
24. Pinnington HC, Dawson B. Running economy of elite surf iron men and male runners, on soft dry beach sand
and grass. Eur J Appl Physiol 86: 62–70, 2001.
25. Pinnington HC, Lloyd DG, Besier TF, Dawson B. Kinematic and electromyography analysis of submaximal differences running on a firm surface compared with soft, dry sand
. Eur J Appl Physiol 94: 242–253, 2005.
26. Rampinini E, Impellizzeri FM, Castagna C, Abt G, Chamari K, Sassi A, Marcora SM. Factors influencing physiological responses to small-sided soccer games. J Sports Sci 25: 659–666, 2007.
27. Short AD. Australian beach systems—Nature and distribution. J Coast Res 22: 11–27, 2006.
28. Zamparo P, Perini R, Orizio C, Sacher M, Ferretti G. The energy cost of walking or running on sand
. Eur J Appl Physiol 65: 183–187, 1992.