Because of the requirement profiles of different team sports, the conditional properties of strength and speed are important for the performance of their respective sports (9,10,17). For example, the requirement profile of soccer shows the importance of strength and speed-strength abilities in addition to other conditional characteristics. During a game, for example, a soccer player completes many strength and speed-strength actions (34). This is also true for football, tennis, rugby, etc. Strength and speed-strength actions are movements limited by the expression of strength and speed. These actions are important for scoring, winning, or losing duels or even in determining the outcome of the game (29). Thus, sprinting is a performance-limiting factor in the mentioned sports. For example, in soccer, most of the sprints reach distances of up to 30 m, whereas approximately 50% of all sprints are <10 m (34). The time to run these sprint distances is determined by the ability of strength and speed strength. This is illustrated in various studies that have found a medium-to-high correlation between strength and sprint performance measurements (3,8,18,21,24,30,35,39–41). These studies show a clear influence of strength, depending on the strength measurement, and the sprint performance during the acceleration phase. Further, investigations have shown that strength training leads to faster sprint times in distances up to 30 m (31,37). In addition to the linear sprint (LS), in many sports, athletes must perform sprints with changes in direction (change-of-direction sprint [COD]). The COD performance is often measured using agility tests. It should be noted that there are a large number of different agility tests, and some of these tests do not necessarily reflect the demands of a sport (33). The tests differ, considerably in some cases, in terms of the total duration and the number and degree of the COD. Regarding correlations between strength and speed-strength parameters for the COD relevant findings in the literature are inconsistent (2,19,23,26,28,42,43). The findings in the literature range from no correlations to strong correlations. This inconsistency is partly a result of the different test designs and different strength and strength-speed parameters.
Longitudinal studies also show differing results. Hoffmann and Kang (16) found that 15 weeks of strength training with weightlifting exercises in football players resulted in no significant improvements in performance in the T-test. Additionally, Tricoli et al. (36) and Fry et al. (13) found that 8 weeks of strength training with weightlifting exercises resulted in no significant improvements in the COD. Additionally, Harris et al. found no improvements in the COD after 9 weeks of strength training. The study with the longest intervention period (9 months of periodized strength training on machines) did not result in improvements in the COD (19). Only 1 study by McBride et al. (25) found significant improvements in sprint times of the COD after 8 weeks of squat jump training with 30 and 80% of 1 repetition maximum (1RM).
Therefore, this study aims to clarify the extent to which there is a strength training effect on sprint time with changes of direction and to analyze the possible correlations between the 1RM in the squat and the COD.
Experimental Approach to the Problem
The primary objective of this study was to show the effect of 2 years of periodized strength training on the COD performance. Further, potential correlations between the COD and the 1RM relative to body weight (SREL) were evaluated. To accomplish these objectives, 112 elite youth soccer players were enrolled in the study. Thirty-six professional soccer players were also selected as a performance standard for the youth soccer players. The elite youth soccer players were divided into 2 groups. One group performed periodized strength training in addition to their regular soccer training (strength training group [STG]), and the other group performed their regular soccer training alone (control group [CG]). Further, both groups were divided into subgroups based on the ages of the subjects. Performance in the COD (5 m with turning left [L5], R5, L10, and R10) and the strength test were designated as dependent variables, and the STG and CG were designated as the independent variables. The dependent variables were analyzed for group differences with time for the strength measures and the parameters of COD. All participants were familiarized with the tests by making them perform a pretest 1 week before testing. The first testing protocol for the youth soccer players was conducted in July 2009 (T1) at the beginning of the season. The second testing protocol was in May 2011, 2–3 weeks after the last match of the season. In addition, 34 professional soccer players (PRO) from first and second division clubs in Germany were analyzed with respect to the parameters of the COD in June 2011 at the beginning of the season to standardize the performance of young players. No subject participated in a fatiguing training session for a minimum of 2 days before testing or reported an injury at the time of testing. Anthropometric and performance measurements were collected by the same researchers at the same time on the testing day, and all the participants were asked to wear the same clothing and footwear. All the participants were asked to eat and drink sufficiently until 1 hour before testing.
Approval for this study was obtained from the institutional review board of Johann Wolfgang Goethe-University, Frankfurt, Germany. The investigators informed all the subjects of the objectives of the investigation and all the aspects of the research. All the participants gave written informed consent to participate. Informed consent was obtained from the participants' parents for those under the age of 18 years and directly from the participants aged 18 years and above.
For the study, 112 young soccer players were recruited from the training centers of 2 professional clubs. These players were divided into 2 groups. One group (STG) added strength training twice per week to their regular soccer training 3–4 times per week. The second group (CG) participated in their regular soccer training 3–4 times a week. Further, the subjects under the ages of (a) 19 years, (b) 17 years, and (c) 15 years were divided into subgroups. The anthropometric data are depicted in Table 1.
The professional soccer players were from first and second division clubs in Germany. The mean height and weight of this group were 183.8 ± 6.9 cm and 77.7 ± 6.5 kg, respectively.
The STG completed 2 strength sessions per week in addition to 3 or 4 soccer workouts. During the strength training sessions, the parallel back and front squat exercises were each completed once a week. Additionally, the players in these cohorts performed bench presses, deadlifts, neck presses, and exercises for the trunk muscles and the standing row. The subjects were trained to use the appropriate squat technique during the first 4 weeks, and squat strength training was then periodized. During the following 8 weeks, the subjects performed hypertrophy training consisting of 5 sets of 10 repetitions, with a 3-minute rest between sets. The third training block consisted of 5 sets of 6 repetitions and a 3-minute rest between sets; this was followed by another training block including 5 sets of 4 repetitions and a 5-minute rest period between sets. Faigenbaum et al. (11) showed that this training protocol is appropriate for youth (4). The amount of weight to lift during the training sessions was determined by individual ability, and the subjects lifted their maximum weight using the correct technique (4RM, 6RM, or 10RM). The weight was increased during the next training session if the subject could lift the given weight with the proper technique in the respective squat variant. The training for the trunk muscles and the upper extremities always consisted of 3–5 sets of 10 repetitions and a rest period of 3 minutes between sets. The subjects performed a rotation of 3 of the previously mentioned exercises for the upper body and 1 exercise for the trunk muscles, in addition to the squat exercise, during every training session. The described periodization was repeated twice during the season. The comparative group (CG) completed 3 or 4 soccer workouts per week, whereas the PRO completed five to six 90-minute soccer-training sessions per week.
The COD performance was measured using 3 double light barriers (system produced by Refitronic, Schmitten, Germany). The COD was designed as an equilateral triangle (60° angles) illustrated in Figure 1. Each side of the triangle was 5 m. To determine the time for a COD, the subjects sprinted 2.5 m, then changed direction. After sprinting another 5 m, a second change of direction was required. Then, another 2.5 m was sprinted through the final light barrier. The total running distance was 10 m with 2 changes of direction. The timer started after the subject passed the first light barrier. After the activation of the light barrier, the subjects independently decided when to start. The reaction time was therefore excluded from the measurement. The starting point was set 0.75 m in front of the light barrier to avoid an early release that could occur inadvertently by a hand movement or by bending the upper body forward at the start. The starting point was placed 0.75 m before the start light barrier. The subjects were required to pass through closely spaced pylons to emphasize the changes of direction and to prevent breaking from the circuit. The subjects sprinted to both the right and the left. The intracorrelation classes for the COD parameters are 0.88–0.91 (p < 0.05; n < 500).
This test design was chosen because the traditionally used COD tests, such as the T-test or the Illinois agility test, do not differentiate between other parameters (i.e., forward vs. backward, left vs. right, slalom vs. 180° COD are mixed within these tests). The test used in this study was designed to differentiate changes of direction (i.e., moving left and right) and to focus the COD using short sprint tracks.
The players completed a 10-minute, standardized warm-up to the COD.
A 1RM in the front and back squats was used to determine the maximum strength of the lower extremities in the soccer players. In both exercises, the parallel (60° knee angle) version of the squat was performed. The intracorrelation classes were r = 0.97 (p < 0.05) for the front squat and r = 0.99 (p < 0.05) for the back squat. The warm-up was standardized and consisted of 2 sets of squats with 6–8 repetitions using a submaximal weight. The strength tests were evaluated in a maximum of 5 trials. The maximum strength of the front squat was measured first, followed by the back squat. The soccer players participated in technique training for the squat variants twice a week for 2 weeks before they were tested. In many sports, the body must move quickly during sprints and jumps. Therefore, instead of primarily recording absolute strength values, strength performance in relation to body weight (SREL) should also be evaluated. Therefore, the SREL was calculated (SREL = 1RM/bodymass).
The data were analyzed using the Kolmogorov-Smirnov test for normal distribution. In addition, the data were tested for homogeneity of variance. A possible existing difference in performance between the 2 groups at baseline was controlled by the analysis of variance and is reported in the results. For the analysis of the performance development within a group and pairwise comparisons between 2 groups, an analysis of variance with repeated measures was calculated with the factors group and time. The significance level was set at p < 0.05. To rate the results of young people, an analysis of variance of the parameters of the COD of T2 data of the PRO, the CG, and the STG was performed. The significance level was set at p ≤ 0.05. The effect sizes were calculated using the variable d
. In general, effect sizes defined as d > 0.5 can be interpreted as large effects. Similarly, effect sizes ranging from 0.5 to 0.3 are considered to be moderate, effect sizes from 0.3 to 0.1 are considered to be small, and those defined as d < 0.1 are considered trivial (5). Relationships between the COD and SREL were calculated for the normal distributed data using a plurality of bivariate correlations by Pearson. The significance level was set at p < 0.05. The data are presented as the mean ± SD.
The data showed no significant differences for any parameter in the Kolmogorov-Smirnov test, which can be expected from a normal distribution of data. Similarly, one can assume homogeneity of variance because of the lack of significance using Levene's test. The strength test data can be found in Table 2. At T1, significant differences (p < 0.05) only occurred in the B-cohort. The effect size for this purpose is d = 0.4.
The C-cohort, reported at the beginning of the study, revealed no significant differences in all parameters of the COD. The STG reported in T1 times of 1.858 ± 0.095 seconds in L5, 1.846 ± 0.079 seconds in R5, and 3.501 ± 0.166 seconds to 3.481 ± 0.130 seconds in L10 and R10, respectively. The CG achieved intermediate times of 1.860 ± 0.092 seconds in L5 and R5 of 1.852 ± 0.084 seconds and end times of 3.496 ± 0.183 in L10 seconds and 3.453 ± 0.190 seconds in R10. The absolute time changes can be found in Figure 2. The effect sizes of group differences in the absolute amount of time changes are 0.5 < d > 0.8.
In T2, the STG had intermediate times of 1.692 ± 0.068 seconds (L5), 1.720 ± 0.114 seconds (R5), and 3.217 ± 0.144 of end times (L10) and 3.224 ± 0.190 (R10). The CG showed T2 intermediate times of 1.779 ± 0.09 seconds (L5) and 1.807 ± 0.093 seconds (R5). End times of 3.401 ± 0.159 seconds (L10) and 3.455 ± 0.148 seconds (R10) were measured. Additionally, the test day factor showed significant (p < 0.05) differences in analyses of repeated measurements for both the groups.
In T1, the STG demonstrated times of 1.777 ± 0.049 in L5, 1.778 ± 0.073 seconds in R5, 3.306 ± 0.117 in L10 and 3.377 ± 0.113 seconds in R10. The CG achieved intermediate times of 1.675 ± 0.057 seconds in L5 and 1.691 ± 0.059 seconds in R5 and end times of 3.149 ± 0.098 seconds in L10 and 3.204 ± 0.114 seconds in R10. The B-cohort showed a significant (p < 0.05) difference in all COD variables in T1. The effect sizes for the differences in T1 are high. The absolute time changes can be found in Figure 3. The effect sizes of group differences in the absolute amount of time changes were d > 1.5.
In T2, the STG had intermediate times of 1.674 ± 0.089 seconds (L5) and 1.694 ± 0.072 seconds (R5) and end times of 3.177 ± 0.151 seconds (L10) and 3.188 ± 0.115 seconds (R10). In T2, the CG demonstrated intermediate times of 1.727 ± 0.072 seconds (L5) and 1.733 ± 0.073 seconds (R5) and end times of 3.283 ± 0.122 seconds in L10 and 3.338 ± 0.106 seconds in R10. Additionally, for the test day factor, significant (p < 0.05) differences in analyses of repeated measurements existed for both the groups.
In T1, the STG recorded times of 1.738 ± 0.082 seconds in L5, 1.712 ± 0.047 seconds in R5, 3.240 ± 0.091seconds in L10, and 3.27 ± 0.071 seconds in R10. The CG achieved intermediate times of 1.675 ± 0.056 seconds in L5 and 1.652 ± 0.039 seconds in R5 and end times of 3.165 ± 0.108 seconds in L10 and 3.144 ± 0.077 seconds in R10. The A-cohort showed no significant (p < 0.05) group difference in T1 only for the parameter L10. The effect sizes for the differences in T1 are high. The absolute time changes can be found in Figure 4. The effect sizes of group differences in the absolute amount of time changes are d > 1.
In T2, the STG had intermediate times of 1.606 ± 0.014 seconds (L5) and 1.636 ± 0.066 seconds (R5) and end times of 3.066 ± 0.084 in L10 and 3.076 ± 0.12 in R10. In T2, the CG showed intermediate times of 1.658 ± 0.055 seconds (L5) and 1.694 ± 0.053 seconds (R5) and end times of 3.165 ± 0.081 seconds in L10 and 3.223 ± 0.108 seconds in R10. Additionally, significant (p < 0.05) differences in analyses of repeated measurements for the factor test day existed for both the groups.
The professionals reached intermediate times of 1.698 ± 0.058 seconds in L5 and 1.695 ± 0.045 seconds in R5 and end times of 3.188 ± 0.096 seconds in L10 and 3.215 ± 0.083 seconds in R10. Analysis of variance of the parameters of COD in T2 of the A-cohort showed no significant (p < 0.05) differences in the CG compared with the values of PRO, but the STG in all parameters of COD was significantly (p < 0.05) faster than the PRO. Compared with the youth of the B-cohort, PRO showed significantly (p < 0.05) faster times in L10 and R10 than the CG did. However, the CG showed no significant (p < 0.05) differences in R5 and L5 compared with that shown by the PRO. The STG showed no significant (p < 0.05) differences in the B-cohort compared with that of the PRO. In the C-cohort, there was a significant (p < 0.05) difference between the PRO and the CG at all levels of the COD variables, favoring the PRO. However, no significant (p < 0.05) differences were observed between the STG and the PRO.
The correlations between the SREL in the front and back squats and COD are depicted in Table 3.
This study found that additional strength training has a positive effect on the performance in the COD and maximum strength in the front and back squats relative to body weight. Furthermore, this study shows that moderate to high significant correlations exist between the relative maximum strength and the parameters of the COD. The PRO values represent reference values, which represent “good performances” in the COD. Subgroup A of the CG shows a good performance in the COD; however, there are no significant differences in T2 to determine the PRO. The younger cohorts of the CG, however, showed significant differences compared with that of the PRO. No significant differences were observed between the C- and B-youth and the PRO in the STG, whereas the A-cohort was significantly faster than the PRO cohort.
The development of the times of COD in this study showed significant group differences in favor of the STG in almost all variables of the COD. The high effect sizes of the group differences support the effectiveness of the additional strength training on COD performance. Data from longitudinal studies could not corroborate most of the significant improvements of COD in this study after a strength training intervention (13,14,20,36). Previous studies report shorter intervention periods of 8–15 weeks (13,14,36). It appears that a 9-month strength training intervention is insufficient to achieve significant improvements in the COD (19). Strength training interventions lasting >1 year in youth soccer were not found in the literature.
Referring to the results of this study, we can see that the high SD may be the result of the variance of R5 in subgroup C. It should be noted, however, that the CG started with lower sprint times in some parameters of the COD in the A- and B-cohorts in T1 in this study. It is possible that the strength gains and neuromuscular adaptations achieved during this period were insufficient to gain improved performance in the COD. This is explained by the fact that the increased SREL by strength training cannot be harnessed 1:1 in the target motion. The central nervous system must learn to transfer the improved performance of the neuromuscular system in a complex task. The more complex the target task, the lower the chance of transfer. However, after a 2-year strength training intervention, it is possible that the increased maximum strength is transferred to the target movement. Although while playing soccer various CODs are performed, the increased transfer of strength may be augmented. Specifically, it is conceivable that improved acceleration contributed to improvements in the COD. It is possible that longer interventions result in further improvements of the target movement. Additionally, gains in deceleration (i.e., high eccentric load) can have a positive effect on shorter sprint times in COD. In the literature, moderate to high correlations were found between the eccentric and dynamic maximum strength (34). Thus, it is possible that a higher maximum strength level is a contributing factor in faster COD times and deceleration. The slower COD times in A and B juniors in T2 cannot be explained by the present data. It is possible that developmental changes (e.g., growth) are responsible. Perhaps the smaller increases of strength gains compared with that of the STG do not parallel the developmental changes and compromised coordination. It is also possible that the stage of the season results in fatigue (i.e., preseason vs. postseason). Perhaps the substantial changes in the SREL in the STG have an additive effect resulting in better performance when compared with those in the CG where the changes in the SREL were too low, and fatigue limited performance to a greater extent. This suggests that additional resistance training brings an important performance advantage to the players of the STG. This increased capacity in the COD could potentially facilitate the elite junior athlete’s entry to a professional athlete.
The results of the maximum strength measurements show highly significant differences between both groups (STG, CG) and in all of the subgroups over time. The literature provides data for SREL in adults; the SREL values for football players are between 1.7 and 1.9 in the parallel back squat (1,24) and between 1.1 and 1.3 in the parallel front squat (27). Wisloff et al. (40) found SREL values of 2.2 for soccer players in the half squat. Reference values for youth could not be found in a review of the literature. The training group in T2 demonstrated values in the front and back squats that were similar to the values for adults. This investigation shows that SREL increases regardless of strength training at the junior level. The increase in the maximum strength without regular strength training appears to be limited. An investigation conducted by Ronnestad et al. (32) evaluated adult soccer players over a period of 22 weeks with strength training sessions performed either once per week or every other week. After the training period, the soccer players performed similarly in 1RM in the squat compared with what they did during the pretest. The group, which just completed a biweekly strength training session, showed even worse results after 22 weeks. The results reported by Christou et al. (7) determined after 4 months that strength trained soccer players aged 12–15 years increased their 1RM in the leg press when compared with soccer players without strength training and a CG. The high effect sizes for repeated measurements in this investigation are consistent in the literature. Christou et al. (7) determined that after 4 months of strength training, the effect size was d = 2.77 compared with soccer training alone, where the effect size was d = 1.7 in the 1RM. Chelly et al. (6) found increases in 1RM by 25% after 8 weeks of strength training in 17-year-old soccer players. In contrast, Hetzler et al. (15) explain that growth rates of 42% occur after 12 weeks of strength training in 13-year-olds. Additionally, Blimkie (4) explains that growth rates increase up to 52% in adolescents. In this study, growth rates exceed that of the strength trained soccer players compared with previously reported data. The differences between these data and the present data can be explained by the duration of the training intervention; the maximum duration of training interventions in the previous studies was only 20 weeks. The group difference between the STG and CG occur in the changes in the SREL between pretest and posttest, which are significantly (p < 0.05) different in all subgroups. These data show that an additional strength training session in soccer using squat exercises over a 2-year period is superior to soccer training alone in the development of the SREL. The SREL performance gains in the CG could potentially result from the effect of soccer training and developmental factors in youth. Assuming that developmental factors also contribute to the development of STG performance in the SREL, an interaction effect between weight training and development is possible. In the CG, the SREL increased, but other factors (i.e., growth, or playing soccer) could also explain this increase. This investigation shows that an intervention of >1 additional training session seems to be effective in increasing 1RM to a greater extent. It was found that the strength training of STG shows high strength gains, which is consistent with or exceeds those in the literature (11,12,16).
This study shows that moderate to high significant correlations exist between the relative maximum strength and the parameters of the COD. The literature review shows that Negrete and Brophy (26) found significant moderate correlations between strength parameters and COD. Jones et al. (19) also found significant moderate correlations among different power parameters, COD and LS. Young et al. (43), however, found no correlations between the COD and isokinetic strength measurements, but they did find a correlation between COD and a Drop Jump (DJ) test. Young et al. (42) found no relationship among COD, DJ, and a Counter Movement Jump (CMJ). Barnes et al. (2) found a significant moderate correlation between CMJ and COD. Only 2 studies have examined the relationship between maximum dynamic strength measurements and COD. Markovic et al. (23) found a weak correlation (r = −0.17 to −0.31) between the 1RM in a Smith machine and 3 COD tests. Peterson et al. (28) found weak to moderate correlations between the 1RM in the squat and the T-agility test; however, moderate to high correlations after the 1RM of squat were calculated relative to the body weight (men: r = −0.33, women: r = −0.633). The moderate to high significant correlation between the 2 SREL front and back squats and COD is consistent with the results reported by Peterson et al. (28). The investigators found a significant (p < 0.05) correlation of r = −0.805 between the T-test and the SREL in the back squat. Markovic et al. (23), however, found weak correlations in the performance of different COD tests (i.e., lateral stepping, 20-yd shuttle run, and slalom run) and the 1RM strength using a Smith machine in 76 student athletes. Perhaps the different correlations resulted from the different test protocols or by calculating 1RM relative to body weight. Isolating the subcomponents of COD (i.e., deceleration, change of direction, acceleration) assumes that a connection between a sprint with direction changes and the SREL exists. There are various studies that show a moderate-to-high correlation between maximal sprint acceleration and force measurements (22,24). It is also assumed that a high maximum strength level is related to deceleration, possibly because of the effect of the high eccentric load of this movement. In the literature, there are high correlations between the eccentric and dynamic maximum strengths (38). As such, 2 of the subcomponents of the COD are correlated with the maximum strength. Therefore, it can be concluded that the full COD movement is correlated with maximum strength, although the relationship may be weaker. This is because of the complexity of the movement. This notion is consistent with the significant moderate-to-high correlations of the COD parameters and SREL in the front and back squats. The parameters R5 and L5 have in comparison with the L10 and R10 lower significant correlations with SREL. Perhaps, this is because of the higher eccentric load of the second change of direction. Here, the subjects are at a higher speed compared with the first change of direction (just 2.5 m for acceleration).
In summary, this study found that an additional 2-year strength training regimen has a positive effect on the performance of COD and SREL in the front and back squats. This improvement can be observed across different ages. Furthermore, this study shows significant moderate-to-high correlations between the SREL and the COD.
Long-term strength training is an appropriate means to improve COD performance for both professional and young athletes. This provides an opportunity for young players to reach the PRO level of strength and speed performance at an earlier age. The net effect of strength training for the PRO results from the positive influence of additional periodized strength training on the development of the strength and speed-strength parameters. Therefore, additional periodized strength training programs are recommended not only in soccer but also in other sports (e.g., volleyball, tennis, football, and rugby) where CODs may be a performance-limiting factor. The data from this study show an increase in the efficiency of the COD following a long-term strength training intervention. Rather, only long-term periodized resistance training is recommended. It is conceivable that athletes aged 6–7 years will benefit from strength training interventions in addition to the sport-specific training sessions. At this point, the focus should be on introducing the techniques of complex lifts. Progression in strength training volume and intensity should increase gradually with age, focusing on the perfection of the techniques. Young athletes aged 14–16 years will have an advantage after years of strength training. Consequently, the additional strength training sessions at the age of 14–16 years could begin at a much higher level than that currently employed, suggesting another potential positive benefit in adjusting the performance of speed-strength parameters.
This research was not supported by any funding source.
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