Relationship between sprinting, jumping, dynamic balance with change of direction on the performance of young footballers

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Ninety-four highly skilled elite young male footballers from the same top-flight academy agreed to participate in the study with at least 3 years of competitive experience in the regional category and stayed for one season complete at the academy. All participants were aware of the assessments carried out. In addition, I completed 9 hours of soccer practice plus 1 competitive game per week. All parents and participants were informed of the purpose of the study and signed informed consent prior to the start of the study, detailing the possible benefits and risks of the research. In this sense, the inclusion criteria were the following i) previous experience of ≥ 5 years ii) Participants who had not suffered any type of traumatic, musculotendinous or neural injury in the 3 months preceding the performance of the tests were excluded from the study; iii) belong to the academy for a full season; iv) participate in ≥ 80% of the training sessions, from July to April 2020/2021, and v) participate in all the tests offered and v) give consent.

The groups have been divided into two categories under 16 (U16) [(n = 27); age: 14.8 ± 0.4 years; height: 170.6 ± 5.6 cm; body mass: 64.7 ± 8.4 kg)] or under 19 (U19) [(n = 67); age: 16.6 ± 1.3 years; height: 173.7 ± 7.2 cm; body mass: 66.7 ± 8.0 kg)]. Regarding the sample size, the following equation was used: Sample size=Z2 × (p) × (1 − p)/ C2 where Z = confidence level (95%); p= 0.05 andVS= margin of error 0.05. Participants were treated according to American Psychological Association (APA) guidelines, which guaranteed the anonymity of participant responses. In addition, the study was conducted in accordance with the ethical principles of the Declaration of Helsinki for Human Research and was approved by the Research Ethics Committee of the Pontifical University of Comillas (internal project no: 2021 /65).

Experimental design

Participants completed three test sessions, 7 days apart, as you can see in Figure 1. During each session, data from a CMY, a cross-jump test, a 10 m sprint test, 505 COD tests and 90° COD test were collected. During test session 1, anthropometric data was also measured and included. Participants knew all of the tests from their regular fitness test battery. To account for circadian variability, both test sessions were performed at the same time of day and during the participants’ usual training hours. This study was conducted in April of the 2020/2021 season on day 4 (Wednesday), allowing a rest of 72 hours before the match and within the usual training time (3:30 p.m.-6:00 p.m.). The evaluations were carried out under climatic conditions (29°C and 50% humidity). The tests were carried out on a 3rd generation synthetic grass playing surface with a height between 35 and 70 mm and with a distance between them allowing the incorporation of padding.

Figure 1

Schematic representation of a test day (see text for full description).

Procedure

Before performing tests, participants performed a standardized warm-up taking into account the protocols of Fletcher and Monte-Colombo26. Thus, they performed aerobic activity (continuous running), dynamic stretching, progressive sprints and submaximal pre-planned changes of direction, lasting 10 min, football players are familiar with all the exercises . After the standardized warm-up, participants received verbal instructions and demonstrations from the research team immediately before proceeding with 2 familiarization attempts for each test. Recovery intervals between attempts were standardized to three minutes for each test. For the selection of the dominant leg, players were asked which leg they prefer to use to control, pass and throw the ball regardless of playing position27. All the evaluations were carried out at the same time and in the same space, before the training session, with the footballer’s usual outfit, the specific shoes and supervised by the same technical specialists.

Variables measured

Anthropometric characteristics

Anthropometric measurements were taken before the physical tests. First, body composition (BC) was assessed in the morning (8:00 a.m.) during the first day of assessment without breakfast and wearing only shorts and removing all metal and jewelry prior to assessment28. For BC assessment, the Bioelectrical Impedance Analysis (BIA) method was used with a TANITA® (MC-980MA PLUS, Arlington Heights, IL). BIA is a widely used method for estimating LM and offers a cost-effective, non-invasive method to assess the fluid distribution and BC of young soccer players. Secondly, height was measured with a stadiometer (Seca® 206, Hamburg, Germany).

Jump in countermovement

The CMJ was evaluated using the Chronojump-Boscosystem® (Barcelona, ​​Spain) which has an intraclass correlation between 0.821 and 0.949 for measuring high jump29. This system was connected to a MacBook Pro (macOS On 11.1). The values ​​were analyzed with a chronopic and recorded by Chronojump version 2.0.2. After a warm-up, participants performed the CMY test three times on a contact platform at each load jump, with 20 s (sec) recovery between attempts to minimize the effect of fatigue and three minutes between attempts. different load jumps30. The best jump in centimeters (cm) was considered the final result. They were asked to jump as high as possible after reaching a knee angle of approximately 90°. Participants were also instructed to keep their hands on their hips during the CMJ and to land with their legs extended with maximum plantar flexion of the feet. If one of these conditions was not met, the test was repeated.

Cross jump test

For the cross jump test, the participant performed three consecutive jumps on a 15 cm line that had been drawn on the ground (Fig. 2). The test consists of performing three jumps in monopodal support and landing with the same leg with which your impulse31. Subjects had to place their hands on their hips and hold the landing position for 3 s, without loss of balance or performing any additional movements involving the free limb. The distance reached was measured in cm from the take-off line to the heel in the final position32. They made two attempts and the best one was selected.

Figure 2
Figure 2

Get ready for the cross jump test.

10m sprint event

Three sprint tests (10 m) were performed with 2 min recovery between sprints. The times for each sprint were taken in seconds. The evaluation system was carried out via FitLight Trainer® sensors (Ontario, Canada). The timing gates were adjusted to an appropriate hip height according to the average size of the sample group. The time recorded for each of the players was stored in a portable tablet with an Android system and its subsequent analysis in Microsoft Windows® Excel program (Redmond, Washington, USA). For data analysis, average the three attempts made in each run for further analysis. For the evaluation, 2 Led sensors were placed on a bar 1 m high and in a straight line at distances of 10 m. At the light signal, the player sprints in a straight line on a corridor of 80 cm from the sensor.

505 COD test

Methodology for 505-COD was consistent with originally established methods33, see Fig. 3. It is therefore a 10m linear sprint from a static start, a 180° turn on a predetermined turn stage (right/left) ensuring contact with a designated line, and a 5 m return sprint via an identified finish line. The time taken to complete the last 5 meters of the 10m linear sprint, the turn and the 5m return sprint was recorded34. For the speed assessment, 2 attempts were made with a recovery time of 2 min between repetitions and an average of the two repetitions for later analysis. Times were measured in seconds. As happened in the 10m sprint test, the rating system was done through FitLight Trainer® sensors. The timing gates were adjusted to an appropriate hip height according to the average size of the sample group. The time recorded for each of the players was stored in a portable tablet with an Android system and its subsequent analysis in Microsoft Windows® Excel program (Redmond, Washington, USA).

picture 3
picture 3

Get ready for the 505 COD test.

90° COD test

Finally, they performed three COD tests at 90° (right/left) (10 m) with 90° (COD) m, see Fig. 4. The times of each repetition were taken in sec. For data analysis, the average of the two attempts made in each series with 2 min of recovery among them was chosen. For evaluation, 2 Led FitLight Trainer® sensors were placed, one at the start and the other at the end of the course. The timing gates were adjusted to an appropriate hip height according to the average size of the sample group.

Figure 4
number 4

Prepared for COD test at 90°.

statistical analyzes

The mean and the standard deviation were calculated for each variable. For descriptive purposes, partial point clouds were also calculated between the CMJ, the Crossover Hop Test, the 10m sprint test and the change of direction tests (505 COD tests and the 90° COD test) . Before any parametric statistical analysis, the assumption of normality was tested with the Kolmogorov-Smirnov test on each variable (the results of this test are included in Supplementary Table 1). The relationship between the result of jump tests (CMJ), dynamic balance (cross-over hop test) and speed (10 m sprint) and the result of agility tests (505 test and 90° COD test) was analyzed with multiple regressions, including each of the tests and age category as an independent variable (regression p-values ​​and adjusted R-values ​​were calculated). In addition, a multiple linear regression equation was calculated, including the results of the jump height in the CMJ, the time in the dynamic balance test, the time in the 10 m sprint (continuous) and the category age (in category) as independent variables and the result of the change of direction test as the dependent variable. Variance inflation factors were calculated to verify that collinearity was not a serious problem.

Statistical analysis was performed with Origin Lab software (based on the toolGeneral linear regressionthat allow for the inclusion of continuous and categorical variables) and the significant p-value for the regressions was set at 0.05. Effect size was assessed using Evan’s Scale35: i) 0–0.019, very low; ii) ≤ 0.20–0.39, low; iii) ≤ 0.40–0.59, moderate; iv) ≤ 0.60–0.79, strong, and v) ≤ 0.80–1.00, very strong.

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