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Effect of Small-Sided Games and Repeated Shuffle Sprint Training on Physical Performance in Elite Handball Players

Dello Iacono, Antonio; Ardigò, Luca P.; Meckel, Yoav; Padulo, Johnny

The Journal of Strength & Conditioning Research: March 2016 - Volume 30 - Issue 3 - p 830–840
doi: 10.1519/JSC.0000000000001139
Original Research
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Dello Iacono, A, Ardigò, LP, Meckel, Y, and Padulo, J. Effect of small-sided games and repeated shuffle sprint training on physical performance in elite handball players. J Strength Cond Res 30(3): 830–840, 2016—This study was designed to compare the effects of small-sided games (SSGs) and repeated shuffle sprint (RSS) training on repeated sprint ability (RSA) and countermovement jump (CMJ) tests performances of elite handball players. Eighteen highly trained players (24.8 ± 4.4 years) were assigned to either SSG or RSS group training protocols twice a week for 8 weeks. The SSG training consisted of 5 small-sided handball games with 3-a-side teams excluding goalkeepers. The RSS consisted of 2 sets of 14–17 of 20-m shuttle sprints and 9-m jump shots interspersed by 20-second recoveries. Before and after training, the following performance variables were assessed: speed on 10-m and 20-m sprint time, agility and RSA time, CMJ height, standing throw, and jump shot speed. Significant pre-to-post treatment improvements were found in all the assessed variables following both training protocols (multivariate analysis of variance, p ≤ 0.05). There was a significantly greater improvement on 10-m sprint, CMJ, and jump shooting, after the RSS in comparison with SSG training (+4.4% vs. +2.4%, +8.6% vs. +5.6%, and +5.5% vs. +2.7%, respectively). Conversely, agility and standing throwing showed lower improvements after RSS in comparison with SSG (+1.0% vs. +7.8% and +1.6% vs. +9.0%, respectively). These results indicate that these training methods are effective for fitness development among elite adult handball players during the last period of the competitive season. Specifically, SSG seems to be more effective in improving agility and standing throw, whereas RSS seems preferable in improving 10-m sprint, CMJ, and jump shot.

1Science Life, Orde Wingate Institute for Physical Education and Sports, Netanya, Israel;

2Department of Neurological and Movement Sciences, School of Exercise and Sport Science, University of Verona, Italy;

3University eCampus, Novedrate, Italy; and

4Tunisian Research Laboratory “Sports Performance Optimization,” National Center of Medicine and Science in Sports, Tunis, Tunisia

Address correspondence to Luca P. Ardigò, luca.ardigo@univr.it.

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Introduction

Sport coaches and scientists usually build specific performance models starting from the physiological and mechanical demands resulting from sport training and competition investigation. Then, such models become ready-to-use for athletes and coaches for their daily sport activity. Therefore, development of models should account for both the different required sport abilities and the seasonal periodization, i.e., the trainings and competitions succession.

Modern handball has been previously defined as a strenuous contact team sport that involves high-intensity short-duration activities such as sprinting, jumping, turning, pushing, blocking, and throwing (10,13,40). The physiological responses of official handball matches emphasize the predominant involvement of both phosphagens and glycolytic energy systems (10,29,39,40). Accordingly, Povoas et al. (39) reported that during the average 73 minutes of match time, 825 activity changes of very short duration (2–6 seconds) were performed with 6-second intervals and with energy supplies mostly provided by ATP-CP and glycolytic pathways (29). These results suggest that handball players spend a considerable amount of energy in acceleration and deceleration movements and illustrate the intermittent nature of their efforts—a common trait in team sports (21,28,39).

Considering this background, interpretation of such data could be of great importance for optimal periodization of the physical and sport-specific conditioning programs aimed at improving overall handball performance (22). In elite male players, physical fitness has been reported to improve generally during the first part of the season, with a tendency to plateau or even decrease slightly by the end of the season when the most crucial official matches are usually played (13). Moreover, the increase in the number of training sessions related to the competitions (28) is likely to have consequences on the in-season fitness level of the handball players because of the limited amount of time that can be devoted specifically to structured conditioning programs. In this scenario, the daily handball practice itself has a direct effect on most of the determinant qualities in the game (22). Nevertheless, performing additional handball-specific training based on strength, power, speed, agility, and high-intensity aerobic intermittent activity is highly recommended (5,13). Therefore, during the last phase of the season, it becomes particularly necessary to optimize the training to cope with the needs of keeping at high level both neuromuscular quality and tactical skill. To date, most studies in team sport players have investigated the effect of either high-intensity “aerobic training” (3,5), “mixed,” i.e., repeated shuffle sprints (RSSs) (1,8,22), or game-based, i.e., small-sided games (SSGs) (3,11,16–18,22) programs. Repeated shuffle sprint is commonly used to improve neuromuscular qualities. Indeed, RSS is used to improve maximal sprinting speed and muscle explosive power for athletic performance, given that a combination of speed and explosive strength training is needed to improve peak running speed and jump height. Moreover, this training method contributes to the reproduction of the specific intermittent nature of the handball play, while also requiring players to train according to the typical physiological demands and mechanical outputs, i.e., acceleration, deceleration, change of direction, jump and throw, that are handball related (40). The use of SSG as a training method has recently become the focus of scientific research because of its ability to develop physical capacities together with sport-specific tactical and technical skills (3,4,21,33). The primary benefits of SSG are that the game can replicate the movement patterns, as well as the physiological demands and technical requirements of competitive match play (11,33), while also requiring players to make decisions under conditions of pressure and fatigue. In addition, compared with traditional fitness training sessions, SSG training is thought to increase player compliance and motivation, because it is perceived to be a sport-specific exercise that maximizes the training time spent with the ball (3). The reported results seem encouraging because both methods have been shown to significantly improve the physical qualities associated with the handball performance. However, there is no consensus on the most appropriate regimen, and concerns remain about which conditioning training would provide more advantages for improving the sport-specific physical components. At present, no data are available regarding the long-term effects of RSS vs. SSG training on the fitness of elite adult handball players during the last phase of the in-season period. Given that handball requirements include both high neuromuscular quality, i.e., RSS-improvable, and tactical skill, i.e., SGG-improvable, we believe that the 2 training modes deserve to be investigated about their effect on specific abilities.

Therefore, the purpose of this study was to compare RSS with SSG training in improving selected fitness variables of elite male handball players. We hypothesized that 8 weeks of either RSS or SSG training performed twice a week would enhance handball-specific activities outcomes (repeated sprint ability [RSA], short sprints, agility, jumps, and throwing performances), and we aimed to determine which of the 2 programs would be most effective.

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Methods

Experimental Approach to the Problem

This study adopted a counterbalanced fully controlled research design with randomized allocation of training intervention and pre-post assessments. Accordingly, participants were divided into 2 training groups that performed either SSG (n = 9) or RSS (n = 9) in addition to their normal handball training sessions. We acknowledge that this study design could have been more powerful with a nonintervention control group. However, the population from which well-trained handball players can be drawn, belonging to the same team and with a common conditioning background, is limited and, therefore this dictated the approach we used. The 2 training interventions reflected what handball coaches and fitness trainers usually implement during the competitive season. As a consequence, such a methodological strategy promoted the ecological validity of the possible outcomes of this investigation. The study was conducted during the last part of the handball in-season period (February–April). Overall, the study lasted 10 weeks and consisted of 1 week of pretesting, 8 weeks of specific training, and 1 week of posttesting. To isolate the effect of the 2 training protocols, the additional fitness training sessions, e.g., technical, tactical, and strength, during the 8 weeks of training were identical for both groups. Overall, we acknowledge that such additional fitness training sessions could potentially bias the effect on the considered variables by the 2 specific training interventions. Nevertheless, coaches and fitness trainers were already fully aware of the impact of the additional fitness training sessions. In addition to that, we wanted to keep our approach as much ecological as possible. Including the additional fitness training sessions, all the subjects performed approximately the same number of jumps and standing throws/jump shots during the study duration. Tests included RSA (6), 20-m sprints, a countermovement jump (CMJ) test, standing throw, and jump shot tests.

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Subjects

The sample size was estimated using acceptable precision and confidence intervals (CIs) a priori (G*Power software, version 3.0.10, Heinrich-Heine-Universität Düsseldorf, Germany) and using the approach developed for magnitude-based inferences (23). Based on the assumption that a between-group difference in the mean RSA time of 1.2 ± 1.1% is meaningful (3), and considering a within-subject SD (typical error) of 0.8% (24), a sample size of >7 participants per group would provide maximal chances of 0.5 and 25% of type I and type II errors, respectively. Eighteen male elite handball players (age: 24.8 ± 4.4 years, range 20–29 years; body height: 188.1 ± 6.8 cm; body mass: 90.6 ± 9.0 kg; body fat: 11.8 ± 2.3%), members of a top team of the national league, were recruited to participate in the study. All players had at least 8 years of competitive experience at the national or international level. Six of the players were included in the national handball team squad at the time of data collection. All players trained 6 times per week (∼12 hours) and competed during the weekend over the entire intervention period.

The participants were fully informed about the procedures, the nature, and the associated risks and benefits involved in this study, and gave voluntary written consent to participate. They were all free of cardiovascular and pulmonary disease and were not taking any medications. This study, which was approved by the institute's Research Ethics Committee, conformed to the recommendations of the Declaration of Helsinki.

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Procedures

Testing Schedule

According to the testing schedule, subjects performed 3 similar sets of tests. The first set was conducted 2 weeks before the initiation of the study, with the participants performing familiarization sessions to become acquainted with the testing procedures. Additionally, all tests were administrated with the aim of assessing the test-retest reliability of the measures. On the same occasion, a Yo-Yo intermittent recovery level 1 (YYIRTL1) was performed with the aim of assessing the maximal heart rate (HR) values for each player. The latter were determined as the peak HR observed during the YYIRTL1 and were further used for the calculation of the HR responses during both training interventions. The second and third sets of tests were conducted during the week before and after the 8-week training period, respectively. All sets of tests were administered on 3 nonconsecutive days using the same procedures by 2 technicians, who were masked to the training group affiliation. On the first test day, RSA was performed, followed by the anthropometric assessment. On the second day, CMJ test and sprint performance were assessed. On the third day, the ball throwing speed for the standing throw and jump shots were determined. All tests were performed on the same regular indoor court, at the same time of the day (5:00 PM/7:00 PM) and in similar ambient conditions of temperature (20.5 ± 0.5° C) and relative humidity (60 ± 4.5%), which maintains test validity and reliability with regard to any influence of circadian rhythms and diurnal variation (12). To prevent unnecessary fatigue effect, players and coaches were instructed to avoid intense training 24 hours before each day of testing. Participants were also asked to fast at least 3 hours before each testing session.

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Day 1

Repeated Sprint Ability Test

Repeated sprint ability involved 6 repetitions of maximal 2 × 12.5-m shuttle sprints (∼6 seconds) departing every 20 seconds as previously described (6). During the approximately 14-second recovery between sprints, subjects were required to stand passively. Two seconds before starting each sprint, the subjects were asked to assume the start position, with the front foot placed 5 cm before the first timing gate and await the start signal for the next sprint. Strong verbal encouragement was provided to each subject during all sprints. Time was recorded using photocell gates (Timing-Radio Controlled; TT-Sport, San Marino, Italy) placed at the start-finish point and on the 10-m lines, approximately 0.5 m above the ground, and with an accuracy of 0.001 second. Three scores were calculated for RSA: the best sprint time (RSAbest, s), the mean sprint time (RSAmean, s), and the percent sprint decrement (%Decr, %), calculated as follows:

In addition, averages were calculated for 10 m (the first linear 10 m from the start point) and agility performance times (the time for the 2 × 2.5-m turnaround, between the 10-m and 15-m lines crossing, respectively). To balance the legs' physical effort during the change of direction, participants were asked to alternate the legs' use during each sprint (36).

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Anthropometry

Anthropometric variables of height (m), body mass (kg), and body fat (%) were measured 3 times for each participant, and the mean of each measure set was calculated. Height and body mass measurements were made on a leveled platform scale (model 284; SECA, Hamburg, Germany) with an accuracy of 0.001 m and 0.05 kg, respectively. Percentage of body fat was calculated from measurements of 7 skinfold thickness according to the equations of Jackson and Pollock (25).

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Day 2

Jump Test

Lower limb explosive power was assessed by a CMJ test according to the protocol of Bosco et al. (2). Participants were instructed to keep their hands on their hips to prevent the influence of arm movements. The starting position was stationary, erect, with knees fully extended. The participants then squatted down to approximately ∼90° of knee flexion before starting a powerful upward motion (37). Subjects were instructed to jump as high as possible, and verbal encouragement was provided to each subject before each trial. Each athlete performed 3 trials with passive recovery of 45 seconds between jumps, and the best result was recorded. The height of each jump (in centimeters) was assessed with the Optojump apparatus (Optojump; Microgate, Bolzano, Italy).

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Sprint Tests

Sprint ability was evaluated by a 20-m standing-start all-out run. The subjects were asked to assume the start position, as already detailed for RSA, and await the start signal. Strong verbal encouragement was provided to each subject during all sprints. For time measurement, the test was conducted using the same equipment as in RSA. The 20-m sprint was performed 3 times, separated by at least 2 minutes of passive recovery. The best performance was recorded and used for further analysis.

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Day 3

Handball throwing speed test

Specific explosive strength in handball was evaluated on an indoor handball court during an overarm throw and in 2 situations: a standing throw (penalty throw) (17) and a jump shot (19). Both throwing tests were undertaken after a 15-minute standardized warm-up (5 minutes of jogging, 5 minutes of dynamic stretching exercises, jumping drills, and some handball passes and free shots). The subjects were instructed to throw a standard handball (mass 480 g, circumference 58 cm) with one hand and as fast as possible thorough a standard goal, using their own technique. To simulate a typical handball action, the players were allowed to put resin on their hands, and they were told to throw with maximal speed toward the upper right corner of the goal. The coaches supervised both tests closely to ensure that the required techniques were followed. In the standing throw, one of the feet had to be in contact with the floor behind the line 7 m from the goal, i.e., behind the penalty mark. In the jump shot, players made a preparatory 3-step run before jumping vertically and releasing the ball while still in the air and from behind a line 9 m from the goal. Throw times were recorded from the ball release to the goal line crossing by a digital video camera (Casio Exilim FH100, High-speed, 240 fps; Casio, Tokyo, Japan), positioned on a tripod 3-m above and parallel to the player (34). A validated open-source software (Kinovea, http://www.kinovea.org/) converted measures of throw times (in seconds) and ball displacements (in meters) to speeds (in meter per second, 0.027 m·s−1 accuracy related to standard calibration). For each type of throw, subjects performed 5 trials with a 2-minute rest elapsed between throws. Throws with the greatest average speed were selected for further analysis.

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Training Intervention

Training started 1 week after baseline testing and consisted of 2 sessions per week (on Sundays and Wednesdays) of either SSG or RSS performed over a period of 8 consecutive weeks. Both training programs were structured according to a gradual progress plan that included a 7-day tapering period, i.e., total training volume was reduced by 30%, with the aim of maximizing the final performance (Table 1). The SSG training program consisted of five 2.25–3.10-minute bouts of small-sided handball games with a passive recovery of 1 minute between bouts (Table 1), according to the protocol described by Dello Iacono et al. (11). Thus, SSG was organized in 3-a-side teams excluding goalkeepers on a playing court delimited by an area of 20 × 20 m (half regular handball court), wherein the players had to score in 2 minigoals (1.2 × 0.9 m). Some playing rules were created to avoid game breaks, thus ensuring continuity of the games and consequently maintaining high exercise intensity. For instance, walking and dribbling were not allowed, defense stops as for those achieved by regular fouls were sanctioned with ball turnover, and the maximal time to complete an attack before losing ball possession was preset at 20 seconds. Penalty throws were kept. Repeated shuffle sprint training consisted of 2 sets of 14–17 of 20-m shuttle sprints and 9-m jump shots, interspersed with 20 seconds of active recovery (∼2 m·s−1) between repetitions and 4 minutes of passive recovery between sets. An example of the RSS exercise pattern is presented in Figure 1. Small-sided game and RSS were matched for activity and recovery time at each training session. In addition, to isolate the effect of the current 2 training protocols, other fitness training sessions, e.g., technical, tactical, and strength, were conducted identically in both groups during the 8 weeks of the study. Specifically, the average total training time for each group was ∼12 hours per week, including similar technical, tactical strength, and basic skills' drills. Strength training included 2 sessions per week of upper and lower limb exercises (bench press, shoulder press, pullover, half squat, deadlift, and lunge), with an average load of 50% of 1RM, 3 sets for each exercise with 2 minutes of passive recovery in-between (8–10 fast repetitions, “<1 second”), recovery between repetitions (2 seconds), and work-to-rest ratio = 1:3 (35).

Table 1

Table 1

Figure 1

Figure 1

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Heart Rate Responses

Heart rate responses were continuously monitored during all the SSG and RSS training sessions to provide the mean HR percentage (%HRmean) and the percentage of maximal HR (%HRmax) reached during each conditioning intervention. Heart rate responses were recorded by a telemetry system (Hosand Technologies Srl, Verbania, Italy) at 5-second intervals by means of an electrode transmitter belt (T31; Polar Electro, Kempele, Finland) fitted to the participant's chest as instructed by the manufacturer. The maximum HR was determined as the peak HR observed during the YYIRTL1.

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Statistical Analyses

All data are presented as mean ± SD. The Shapiro-Wilk test was used to ensure normal distribution of the results. The intraclass correlation coefficient (ICC) with 95% CI was used to determine the test-retest reliability of the measures. As for the intratest reliability, the spreadsheet of Hopkins' (20) was also used to determine the typical error of measurement, expressed as a coefficient of variation (CV, %) with 95% CI. The effect size (η2) was calculated for all variables between each condition. Multivariate analysis of variance (MANOVA) with repeated measures was used to examine the data for intergroup differences at the preintervention and postintervention time points, to determine the main and interactive effects of training. The independent variables included 1 within-subjects factor (time), with 2 levels (pretest and posttest), and 1 between-subjects factor (treatment) with 2 levels (SSG vs. RSS). Finally, the Pearson product-moment correlation coefficient was computed to assess the relationships between all the assessed variables at preintervention and postintervention time points. The alpha test level for statistical significance level was set at p ≤ 0.05. Statistical analysis was performed using SPSS Statistics 21 software (SPSS, Inc., Chicago, IL, USA).

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Results

Raw values for all performance variables are shown in Table 2. The 95% ICCs between the test-retest measurements ranged from 0.844 to 0.996 for all the measures (Table 3) indicating good to excellent agreement between trials. At pretest and posttest intervention points, all the measured variables showed highly intratest-reliable data, with CVs ranging from 0.88 to 3.47% (Table 3). Between-groups MANOVA showed no significant baseline anthropometric or performance differences between the groups for all measurements with all p > 0.05.

Table 2

Table 2

Table 3

Table 3

Within-subjects MANOVA of the 3 RSAs scores showed significant differences as effect of time with F(1,16) = 110.841 and p < 0.001 (η2 = 0.874), F(1,16) = 156.911 and p < 0.001 (η2 = 0.907), and F(1,16) = 62.752 and p < 0.001 (η2 = 0.797), for RSAbest, RSAmean, and %Decr, respectively. However, no significant differences were found between the 2 training conditions as effect of treatment (time × treatment interaction) with regard to the 3 RSA scores (p > 0.05) (Table 2).

Within-subjects MANOVA of the 10-m performance time showed significant differences as effect of time with F(1,16) = 84.345 and p < 0.001 (η2 = 0.841). Additionally, between-groups MANOVA showed significant differences as effect of treatment (time × treatment interaction) with F(1,16) = 7.161 and p = 0.017 (η2 = 0.309). Specifically, the RSS group showed improvements in 10-m linear sprinting time (−4.5%), with results significantly higher than those in the SSG (−2.5%) (Figure 2A).

Figure 2

Figure 2

The agility performance was significantly different between tests as effect of time and between groups as effect of training interaction with F(1,16) = 91.627 and p < 0.001 (η2 = 0.851), and F(1,16) = 54.725 and p < 0.001 (η2 = 0.774), respectively. Significantly higher improvements in agility performance time were found in the SSG (−7.8%) compared with the RSS (−1.0%) (Figure 2B).

Within-subjects MANOVA of the CMJ height showed significant differences as effect of time with F(1,16) = 215.509 and p < 0.001 (η2 = 0.931). Additionally, between-groups MANOVA showed significant differences as effect of treatment with F(1,16) = 10.977 and p = 0.004 (η2 = 0.407) (greater increases in the jump height in the RSS; Figure 2C).

Standing throw and jump shot speeds were significantly different between tests: standing throw speed F(1,16) = 344.474 and p < 0.001 (η2 = 0.956) and jump shot speed F(1,16) = 318.760 and p < 0.001 (η2 = 0.952) (Table 2). In addition, between-groups MANOVA showed significant differences as effect of training intervention. Small-sided game achieved greater improvements in standing throw speed at the posttest point with F(1,16) = 159.770 and p < 0.001 (η2 = 0.909), whereas RSS showed higher throw speed in jump shot as compared with SSG with F(1,16) = 34.702 and p < 0.001 (η2 = 0.684) (Figures 3A, B).

Figure 3

Figure 3

Finally, significant strong positive correlations were found between 10-m sprint times and RSAbest at preintervention and postintervention points, both for SSG and for RSS (r = 0.98 and 0.95, 0.99 and 0.99, respectively) (Figure 4). In addition, agility times and %Decr results were positively correlated from poor to moderate levels (r = 0.11 and 0.56) after the 8-week intervention for SSG group, while strongly negatively correlated both at preintervention and postintervention points for RSS (r = −0.83 and −0.87) (Figure 4).

Figure 4

Figure 4

The %HRmean during the training sessions in the SSG training group ranged between 90.4 ± 1.7% and 92.3 ± 0.8 of %HRmax. Training sessions' SSG %HRmean was not significantly different (p > 0.05) from the corresponding RSS group values (90.6 ± 1.1% and 92.5 ± 0.9% HRmax). The %HRmax reached during SSG was 94.2 ± 0.4%, similar to that recorded by the RSS group (94.1 ± 0.6%).

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Discussion

This study is the first to use specific field assessment and a controlled study design to compare the effectiveness of 2 distinct training methodologies, i.e., SSG and RSS, on RSA and explosive power performances in elite adult handball players during the last phase of the competitive period. First, the results indicated that both training approaches led to significant improvements in all the performance variables after an 8-week intervention. Second, our outcomes show different and specific adaptations to each training regimen. Greater improvements in short linear sprint (10 m) speed, CMJ height, and jump shot speed were observed after RSS, whereas agility and standing throw speed improved more after SSG.

As expected, both training interventions significantly improved the RSA-related scores highlighting the enhanced ability of the player to repeatedly produce maximal sprint efforts. Such conclusions are reflected by the better results in the RSAmean time (sprint average time) and the reduction in the difference between the best and the worst sprint as expressed by the %Decr (Table 2). Although this study is the first to determine the effect of conditioning methodologies on RSA in elite adult handball players during the late phase of competitive period, the current results are in agreement with those of previous investigations reporting designing similar type of training designed for adult handball players (11), young basketball (1), and soccer players (15), which had reported beneficial effects on agility, maximal sprinting, and jumping performance, respectively. These adaptations are likely a consequence of increases in leg muscle explosive power, because of improvements in motor unit synchronization, stretch-shortening cycle efficiency, or musculotendinous stiffness (2), as supported by parallel improvements in linear sprint performances (10 and 20 m times) and vertical jump (CMJ) heights. This is not surprising because it confirms the known relation between the vertical jump height and short-duration sprint time in elite adults (7) and is in agreement with those biomechanical analyses of sprinting, which report that short-distance sprint is highly dependent on the subject's ability to generate powerful extensions of the knee extensors, hip extensor, and plantar-flexors muscles (30). However, it is worth nothing that although no intergroup differences were observed in the RSA scores after the 8-week intervention, significant interaction effects (time × intervention) leading to increased maximal sprinting speed (10 m) and greater agility ability were directly attributable to RSS and SSG, respectively (Figures 2A, B). As previously reported, a strong correlation exists between RSA and sprint qualities (38). Our results are in agreement with these findings, as this study demonstrates that intervariable correlations between RSAbest and 10-m sprint times changed as a factor of the specific training typology to which the athletes were assigned (Figure 4). Consequently, it is possible that players performing RSS benefitted from the favorable effect of specific shuffle sprint and jumping training on leg power and maximal sprinting speed when performing RSA. An additional possible explanation for the improved performance on 10 m after RSS training may be the evident presence of training exercise specificity between this exercise and RSA. This speculation is further supported by the evidence that concurrent greater changes in the CMJ height were observed in RSS than in SSG (Figure 2C). From a methodological perspective, the main characteristic differentiating the 2 training protocols designed in our study was that in RSS the conditioning stimulus was both horizontal and vertical in nature, whereas in SSG, players played only with ground-feet-contact motion patterns. As a consequence, performing the shuffle sprint and the jump shot repeatedly may have increased the chances for the RSS group to make greater adaptations, considering the importance of both horizontal and vertical force production and its application in sprint and jumping performance, respectively (30,31).

Another finding of this study was the significantly greater improvement in agility performance after SSG training compared with RSS training (Figure 2B). Our results are in agreement with those of Dello Iacono et al. (11), which showed that a similar SSG training protocol resulted in a significant improvement in specific agility performance of adult male handball players. Agility is a complex ability that depends on several factors, such as muscle strength, balance, flexibility, and speed (9,42). The advantage of the SSG training over the RSS group in agility improvement may have resulted from the recurring “one-on-one” situations, which forced players to withstand and to overcome an opponent who was attempting either to score or to avoid goals. We speculate that such situations might have stimulated enough the biarticulate muscles of the lower limbs, i.e., biceps femoris, rectus femoris (long head), sartorius, gracilis, and gastrocnemius, which are known to be determinant for multijoint movements that involve deceleration, acceleration, and change of direction (26,42). As previously suggested, to improve athletic performance in highly trained athletes, it is almost obligatory to stress the athletic quality of interest (41). Indeed, using SSG may provide a sufficient stimulus to promote functional relevant adaptations in the agility-related fitness variables, as supported by our results. Moreover, our results highlight the importance of the improvements in agility abilities for achieving greater capability to repeatedly perform shuffle sprints as expressed by %Decr scores. In fact, agility times and %Decr in the SSG group correlated more after the 8-week intervention than at the pretime point, with r values increasing from 0.11 (weak correlation) to 0.56 (moderate correlation). Conversely, agility abilities and %Decr measured in the RSS group were significantly and negatively correlated both at the preintervention and postintervention points (r = −0.83 and −0.87, respectively) (Figure 4).

Outcomes from this study also revealed significant improved values of overarm throwing speeds in both groups after the training period (Table 2). Yet, there was a significant “training type” interaction, suggesting 2 interesting points: the superiority of SSG training over RSS to enhance the standing throw performance and an opposite trend concerning the jump shot results, with the RSS showing greater improvements when compared with SSG (Figures 3A, B). Although it is difficult to compare our findings with previous studies of handball players because of differences in study design, age, body mass, skill level, throwing technique (standing, 3-step running throw, jump shot), and modality of training, there is absolute agreement between coaches and scientists in considering throwing as a fundamental handball skill (14,28). One of the basic factors that influence the efficiency of shots is the throwing speed. The faster the ball is thrown, the less time defenders and goalkeeper have to save the shot. Practitioners seem to agree that the main determinants of throwing speed are the technique, the coupling time of movement in consecutive body segments, and the strength and power of both the upper and lower limbs (14,43). However, there is no consensus about the type and the optimal overload that are most likely to enhance strength, power, and consequently throwing speed. Several studies investigating the overarm throwing biomechanics indicated that the elbow extension and shoulder internal rotation torques were the main mechanical contributors for the development of the total ball release speed during standing throw (32,43). The high occurrence of actions such as hitting, blocking, pushing, and holding and the greater frequency of physical contacts between players in the SSG could have created a cumulative training stimulus for such musculature. The physiological explanation of our results relies on the findings of Johnston et al. (27), who showed that the addition of physical contact to noncontact SSG results in upper body neuromuscular fatigue, as well as marked and longer-lasting increases in creatine kinase, compared with no physical contact. Therefore, the chronic application and the cumulative effect of this training stimulus might have been effective in improving the neuromuscular properties of upper body and throw-related muscles, thus producing significant gains in throw performance. In contrast to the last finding, jump shot speeds resulted in higher improvements after RSS training than after SSG training. From a mechanical perspective, the jump shot recognizes 3 critical factors for its successful performance: high whole-body horizontal acceleration and speed aiming to develop linear momentum, a high lower limb impulse for momentum conservation before the airborne phase, and optimal transfer of the whole-body momentum to the upper body and then to the ball until its release (32). As direct consequence, it seems reasonable that players who trained according to the RSS protocol have achieved greater improvements. The parallel better performances on CMJ and 10-m linear sprint may have produced physical advantages for such improved throws. In addition, the exercise used in the RSS protocol provided a neuromuscular overload in a manner that is task related. In fact, it is assumed that identical motor and mechanical demands were required from players when performing either RSS or the specific jump shooting test. Such similarities, in terms of exercise specificity, could have contributed to these significantly better results. In other words, the standing throw, reasonably an almost purely technical sport action, may have benefited from the more tactical skill-oriented SSG. Differently, the more neuromuscular quality–oriented RSS improved both short sprint speed and jumping capability, 2 main specific determinants of jump shot effectiveness. Although these concepts have not yet been specifically demonstrated through research, they can provide coaches with a commonsense approach to strategically select exercises in athlete's overall training program.

In conclusion, both the training methods seem to be generally effective for handball-specific fitness maintenance and improvement in elite adult players during the last phase of the season. Specifically, SSG shows to be more effective in conditioning the tactical skill-related abilities of agility and standing throw. Differently, RSS results to be more effective in conditioning the neuromuscular quality–related abilities of short sprint speed, CMJ, and jump shot.

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Practical Applications

This study demonstrated that an 8-week period intervention, including either SSG or RSS training sessions twice a week, could improve RSA and jumping performances of elite adult handball players during the last period of the competitive season. Coaches and athletes are strongly encouraged to integrate these conditioning methodologies into the planning of regular handball training, given that the latter both SSG and RSS represent a viable means for achieving peak performance levels before the most crucial matches such as playoffs, tournaments, and national/international competitions. In addition, both SSG and RSS may be used as specific training methods for attempting long-term adaptations oriented to handball agility, jumping capability, and short sprint performances. These outcomes provide practitioners with training tools that, when applied as chronic interventions, could help athletes in developing certain physical abilities according to the specific discipline, the handball performance model, and related playing demands.

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Acknowledgments

The authors thank all the players who volunteered within this study. The authors thank Mrs. Dinah Olswang for English correction. The results of this study do not constitute endorsement of the product by the authors or the NSCA.

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Keywords:

agility; explosiveness; peak performance; power; team sport

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