Abstract
udy was to assess the relationship between the countermove- ment jump (CMJ) and sprint performance of professional football players, and to determine which strength and speed elements assessed by the CMJ translate into effective
Education and Sport, 80-336 Gda ´nsk, Poland; pawel.wolanski@awf.gda.pl 11 Football Club, Academy Lechia Gda ´nsk, 80-560 Gda ´nsk, Poland *Correspondence: anna.mika@awf.krakow.pl Abstract: Objectives:The aim of this study was to assess the relationship between the countermove- ment jump (CMJ) and sprint performance of professional football players, and to determine which strength and speed elements assessed by the CMJ translate into effective running.Methods:The research sample comprised 87 male professional football players (age 23.7±4.20 years; body mass 82.33±6.56 kg; body height 1.86±0.05 m) who performed the CMJ on a dual-force platform, as well as the 30 m sprint test. The time and velocity of the run were recorded by photocells at 0, 5, 10, and 30 m of the distance.Results:No significant differences were noted in the time or velocity of the sprint over the initial 5 m between the groups of football players with a higher and lower braking rate of force development (RFD) in the CMJ (p> 0.05). However, at subsequent intervals (5–10 m and 10–30 m), players with a higher braking RFD achieved significantly better time and velocity than those with a lower RFD. Significant correlations in the group with a lower braking RFD between the CMJ and sprint variables occurred in the propulsion phase of the CMJ and most of them were in the first interval (0–5 m). In the group with a higher braking RFD, significant relationships were visible in both the propulsion (concentric) and braking (eccentric) phases of the CMJ, mainly during the second and third intervals of the sprint test.Conclusions:The noted observations may suggest that the relationship between strength and running performance is more complex than previously indicated, and that higher strength in the CMJ does not fully correlate with better sprinting. Therefore, it has been hypothesized that training aimed at generally increasing strength may not always be fully beneficial for running performance in football players and hence specific training guidelines are suggested for targeted strengthening of the required muscle performance characteristics. This may possibly contribute to reducing the unnecessary muscle overload during both training and matches, thereby preventing sports-related injuries. Keywords:countermovement jump; sprint test; football players;
that training aimed at generally increasing strength may not always be fully beneficial for running performance in football players and hence specific training guidelines are suggested for targeted strengthening of the required muscle performance characteristics. This may possibly contribute to reducing the unnecessary muscle overload during both training and matches, thereby preventing sports-related injuries. Keywords:countermovement jump; sprint test; football players; performance; training; injury risk J. Clin. Med.2024,13, 4581.
J. Clin. Med.2024,13, 4581 2 of 14 1. Introduction In elite football, it has been found that a sprint bout occurs approximately every 90 s, with each sprint lasting 2 to 4 s, corresponding to 0.5–3.0% of the effective playing time. Moreover, above 90% of sprint bouts during a game are shorter than 30 m, with 49% being less than 10 m [1]. Therefore, rapid acceleration over short distances is crucial for these athletes [2–4]. In research on the subject, it has been indicated that greater muscular strength enhances performance in fundamental sports skills such as jumping, sprinting, and change of direction tasks, all essential components of football [1,2]. In previous studies, the rate of force development (RFD) has been defined as the rate of the rise in force over time, which is crucial across various sporting events [2,5,6]. In some studies, it has been suggested that sprint performance may be limited by the ability to produce a high RFD over brief contacts rather than absolute force application [2,7]. It has been demonstrated that professional sprinters generate higher vertical forces in the initial stance phase, highlighting the importance of the RFD in terms of sprinting ability [2,8]. It is widely assumed that foot contact during sprint running shares physio- mechanical similarities with movements such as the countermovement jump (CMJ) [9]. The effectiveness of a football player on the pitch largely depends on the ability to develop maximum running speed during the first few seconds, and this requires specific muscle performance in generating high acceleration [10]. However, despite numerous studies in this area, the relationship between lower limb strength and running speed in football players still involves many unexplained issues. Tillin et al. [11] have shown that elite rugby players with a high RFD demonstrated substantially faster sprint times compared to those with a lower RFD, underscoring the importance of explosive strength in athletic performance. In previous investigations among elite and sub-elite sprinters, as well as in runners and elite football players [1], signifi- cant relationships were demonstrated between vertical jumping ability and sprint per- formance [12,13]. It was observed that
a high RFD demonstrated substantially faster sprint times compared to those with a lower RFD, underscoring the importance of explosive strength in athletic performance. In previous investigations among elite and sub-elite sprinters, as well as in runners and elite football players [1], signifi- cant relationships were demonstrated between vertical jumping ability and sprint per- formance [12,13]. It was observed that stronger athletes tend to achieve faster sprinting performance compared to weaker subjects [1,9,14,15], although no significant difference between strong and weak athletes was confirmed in other studies [16,17]. Katja et al. [18] noted that the maximal velocity measured during the 60 m sprint, as well as the velocities at different intervals (0 to 10, 10 to 20 and 20 to 30 m), was correlated with the CMJ. Other authors have shown that greater power and strength in jumps may have beneficial effects on sprint performance [9]. However, it is not known whether this relationship is consistent across all athletes. Interestingly, Wisloff et al. [1] have indicated substantial time differences between football players for the 30 m sprint test. In particular, even if two of the players had similarly timed performances regarding the overall test, significant differences were observed between how they ran the first and last parts of the test. Therefore, it can be hypothesized that the total time of the running test may probably not be the best indicator of running performance among football players. The specificity of running during a match is based on short sprints and sudden accelerations; therefore, the running performance of a given player may be better demonstrated by the ability to accelerate in the first few seconds of the sprint. Thus, in the present research, the relationship between the force indicators from the CMJ and the running parameters in three intervals of the 30 m running test was analyzed. Optimal adjustment of training methods to the specific demands of a given sport is a key element in both athletic performance and the prevention of sports-related injuries [19,20]. In prior research, it has been shown that factors such as insufficient or excessive muscle strength, or
and the running parameters in three intervals of the 30 m running test was analyzed. Optimal adjustment of training methods to the specific demands of a given sport is a key element in both athletic performance and the prevention of sports-related injuries [19,20]. In prior research, it has been shown that factors such as insufficient or excessive muscle strength, or improper contraction speed and type, can lead to impaired motor control during movement. This, in turn, can cause overloads and injuries [21]. This study for the first time analyzed the relationship between CMJ and sprint perfor- mance when football players were divided into those with a higher and lower braking RFD measured during the CMJ, whereas other authors analyzed the general RFD without distinguishing its specific components. We have hypothesized that this approach may allow for a much deeper analysis of the sprint and jump performance and an evaluation of the
J. Clin. Med.2024,13, 4581 3 of 14 nature of this relationship, which may imply further modifications to the training of football players. It may also be hypothesized that determining the detailed relationship between the CMJ variables and sprinting performance may be useful for modifying the training routines of football players in order to specifically strengthen those features allowing for more effective sprinting. Therefore, the aim of this study was to evaluate the relationship between the results obtained by football players in the CMJ jump and the performed sprint, and to determine which strength and speed elements assessed by the CMJ translate into effective running. 2. Materials and Methods 2.1. Participants This study included 87 male football players aged 18–31 years, all belonging to first league professional teams (age 23.7±4.20 years; body mass 82.33±6.56 kg; body height 1.86±0.05 m; training experience 10±3 years). The inclusion criteria were as follows: no history of musculoskeletal injuries or being cleared to play by a medical specialist in the case of sustaining injuries in the past, playing professional football for at least 5 years, and no comorbidities that may influence the study results. The evaluation was conducted after obtaining agreement from the coaching staff. The data collection was preceded by a detailed conversation with the coach, who, based on the inclusion criteria, excluded players with injuries. Qualification for the study was managed by the coaching staff. The study participants were informed in detail about the research protocol and provided their written informed consent to participate in the study. Approval from the Ethical Committee of Regional Medical Chamber in Kraków was obtained for this study (35/KBL/OIL/2024). All the procedures were performed in accordance with the 1964 Declaration of Helsinki and its later amendments. 2.2. Procedures The football players were asked to abstain from unaccustomed strenuous exercise for at least 24 h prior to testing. The protocol consisted of a single testing session during which anthropometric and demographic data (height, mass, age) were measured. A five-minute warm-up that included general dynamic exercises involving the entire body, such as light running, bends, lunges, and elements of dynamic stretching,
football players were asked to abstain from unaccustomed strenuous exercise for at least 24 h prior to testing. The protocol consisted of a single testing session during which anthropometric and demographic data (height, mass, age) were measured. A five-minute warm-up that included general dynamic exercises involving the entire body, such as light running, bends, lunges, and elements of dynamic stretching, was performed. The players knew the test protocol very well as they were routinely tested. However, to ensure that they were familiar and comfortable with the test protocol, they were allowed to practice it. For each test, a total of two successful trials were recorded, and the mean was used for further analysis. 2.2.1. Countermovement Jump (CMJ) Following the warm-up, participants performed the CMJ on the dual-force Hawkin Dynamics platform, which measured three-dimensional kinetic data bilaterally at a sam- pling rate of 1000 Hz (Hawkin Dynamics, Westbrook, ME, USA). The subjects started from an upright position, performing a rapid downward movement followed by dynamic com- plete extension of the lower-limb joints. To avoid undesirable changes in jump coordination, the athletes freely determined the amplitude of the countermovement. During the CMJ, participants were required to keep their hands on their hips throughout the full range of the movement. Each trial began with the participants standing still, with each foot placed on a force platform. Upon initiating the countermovement, participants attempted to jump vertically as high as possible. They were instructed to lower themselves as quickly as possible, jump as high as possible, and return to a standing position after landing [22]. The subjects performed two attempts at the CMJ, with a 10 s rest interval between jumps. The following variables were analyzed: •Peak Propulsive Velocity (m/s); •Peak Relative Propulsive Power (W/Kg); •Peak Relative Propulsive Force (%);
J. Clin. Med.2024,13, 4581 4 of 14 •Relative Propulsive Net Impulse (Newton Second per Kilo (N.s/Kg); •Peak Braking Velocity (m/s); •Peak Relative Braking Power (W/Kg); •Peak Relative Braking Force (%); •Relative Braking Net Impulse (Newton Second per Kilo (N.s/Kg); •Braking RFD (N/s); •Time to Take-Off (s); •Take-Off velocity (m/s); •Impulse Ratio (Unitless; Propulsive Net Impulse/Braking Net Impulse); •Jump Height (m). 2.2.2. Sprint Test The sprint test consisted of a maximal running effort over a distance of 30 m The time and velocity of the run were recorded using the VALD Performance photocell system (VALD Performance Pty Ltd., Brisbane, Australia) located at the start (0 m), 5th, 10th meter and at the end (30th meter) of the distance. The system measures running and reaction times to the nearest 0.001 s. The time and velocity were measured for three intervals of the distance: •Between 0 and 5 m; •Between 5 and 10 m; •Between 10 and 30 m. Based on the analysis of the receiver operating characteristic curve (ROC), the sub- groups were distinguished. The Youden Index was calculated from the ROC curve. The analyses were conducted based on the division into stronger and weaker groups (using the variable braking RFD) and into faster and slower groups (using the sprint variable velocity 0–5 m). The braking RFD from the CMJ represents the RFD from the eccentric phase, which is a crucial element in force generation during the stretch-shortening cycle. The second variable, the velocity 0–5 m, represents the speed in the first phase of the sprint. The participants classification with ROC methods involved the following steps (this process involved the following steps separately for the variable braking RFD and for the velocity 0–5 m): 1. Determining the threshold value: To classify participants into two groups, a thresh- old value for the continuous variables (braking RFD or velocity 0–5) was identified. This value was selected based on the ROC curve analysis, which allowed for the assessment of the point at which this variable best differentiates the two classes. 2. Calculating the ROC curve parameters: For each possible threshold value, the sensitivity and specificity
into two groups, a thresh- old value for the continuous variables (braking RFD or velocity 0–5) was identified. This value was selected based on the ROC curve analysis, which allowed for the assessment of the point at which this variable best differentiates the two classes. 2. Calculating the ROC curve parameters: For each possible threshold value, the sensitivity and specificity were calculated. The ROC curve was created by plotting the sensitivity against (1—specificity) for various threshold values. 3. Optimal threshold value: The point on the ROC curve closest to the upper left corner of the plot (the point with the highest sensitivity and specificity) was considered the optimal threshold value. This allowed for maximal discrimination between the participants. 4. Classifying participants: After determining the optimal threshold value, participants were classified as belonging to one of the two groups. It was found that for the velocity 0–5 m variable, the optimal threshold value (cutoff point) on the ROC curve equal to 4.81 m/s was the most sensitive and specific measure separating individuals with a higher braking RFD (stronger) from those with a lower braking RFD (weaker). Subsequently, the value of the braking RFD equal to 7077 N/s (determined from the ROC curve), which most sensitively and specifically separated faster individuals from slower ones, was identified. In further analyses, the following grouping variables were used: •Velocity 0–5 m (4.81 m/s): Group 1a—faster, Group 2a—slower; • Braking RFD (7077 N/s): Group 1b—higher braking RFD, Group 2b—lower braking RFD.
J. Clin. Med.2024,13, 4581 5 of 14 2.3. Statistical Analysis STATISTICA 13.0 software was used for the statistical analysis. Data normality was tested with the Shapiro–Wilk test. Thet-test was used to determine the differences between groups. The effect size (ES) was calculated using Cohen’s d and interpreted as small (0.2–0.3), medium (0.5) or large (>0.8) [23]. The variability within each dataset was described using the arithmetic mean and standard deviation (SD), coefficient of variation (CV) and standard error of measurement (SEM). The bias between two means (higher braking RFD vs. lower braking RFD group) was examined using the Bland–Altman method [24]. Additionally, Pearson’s linear correlation coefficient (r) was calculated. The sensitivity, specificity and receiver operator characteristic (ROC) curve were calculated. ROC curves plot the true-positive rate (sensitivity) against the false-positive rate (1 minus the specificity) for the possible cut-off score [25]. Differences were considered statistically significant at the level ofp< 0.05. Power analysis determined that at least 35 subjects were required to obtain a power of 0.8 at a two-sided level of 0.05 with an effect size ofd= 0.8. This analysis was based on data derived from the previous literature [1,13–15]. To ensure the better validity of this study, more participants were included. 3. Results 3.1. Comparison of Participants’ Basic Information No significant difference was found for any variable concerning the participants’ basic information (Table) Table 1.Basic information differences of participants in the subgroups. Outcome Measure Group Velocity 0–5 m Mean±SD p Group Braking RFD Mean±SD p Body height (m) 1a 1.79 ±0.04 1b 1.89 ±0.03 2a 1.88 ±0.05 0.87 2b 1.80 ±0.06 0.97 Body mass (kg) 1a 80.21 ±5.54 1b 83.30 ±5.21 2a 82.83 ±6.01 0.97 2b 79.45 ±6.02 0.75 Age (years) 1a 22.3 ±5.32 1b 23.1 ±3.25 2a 24.7 ±3.40 0.86 2b 24.3 ±3.30 0.92 SD—standard deviation;p—pvalue; Group 1a = faster; Group 2a = slower; Group 1b = higher braking RFD; Group 2b = lower braking RFD. 3.2.Comparison of Sprint Test Variables between Football Players with Higher and Lower Braking RFD There were no significant differences in the time or velocity of the sprint over the initial 5
24.7 ±3.40 0.86 2b 24.3 ±3.30 0.92 SD—standard deviation;p—pvalue; Group 1a = faster; Group 2a = slower; Group 1b = higher braking RFD; Group 2b = lower braking RFD. 3.2.Comparison of Sprint Test Variables between Football Players with Higher and Lower Braking RFD There were no significant differences in the time or velocity of the sprint over the initial 5 m interval between the group of football players with a higher and those with a lower braking RFD. However, in the second (5–10 m) and third intervals (10–30 m), players with a higher braking RFD achieved a significantly better time and velocity than the group with a lower braking RFD. This means that athletes generating a higher braking RFD run faster, but not at the very beginning of the sprint (during 0–5 m interval). The football players with a higher braking RFD were slower during the first 5 m (they accelerated more slowly). However, in the subsequent intervals (5–10 m and 10–30 m), they achieved significantly better results than the players with a lower braking RFD (Table). For the sprint time, the results of the Bland–Altman plot have shown bias between players with a higher and lower braking RFD. The mean difference for time 0–5 m was 0.0006 s (limit of agreement from−0.135 to 0.136); for time 5–10 m, the mean difference was 0.015 s (limit of agreement from−0.088 to 0.120); and for time 10–30 m, the mean difference was 0.025 s (limit of agreement from−0.209 to 0.261) (Figure).
Description
This research evaluates how strength elements from CMJ relate to sprinting in football players.