Sixteen youth soccer players (13.6 ± 0.5 years; 163.4 ± 5.9 cm; 50.4 ± 7.1 kg; Table 1) from a local first-tier academy were voluntary recruited to participate in this study. All participants had a minimum of 5-year experience with the academy soccer training. They performed 4 training sessions (80–100-min) per week and played an official eleven-a-side match (2 × 35-min) during the weekend on the regular-sized soccer field. Two goalkeepers participated in the SSG, but were not included in the analysis. The players were asked to avoid physical activity for 24-h prior to the experiment and to sleep at least 8-h a night. They were instructed to consume water and light meal 2–3-h before the testing session. Participants were free from neuromuscular injuries or any disorders. Written informed parental consent was obtained before the study. Each participant and his parents agreed to participate in the experiment and were notified about the withdrawal from the study at any time. The procedures followed were in accordance with the ethical standards on human experimentation stated in compliance with the 1964 Helsinki Declaration and its later amendments. The project was approved by the ethics committee of the Faculty of Physical Education and Sport, Comenius University in Bratislava (no. 3/2022, date: 22 September 2022).

This study was constituted as a quasi-experimental investigation without the random assignment of participants to conditions or their order. The pretest-posttest design was used. The dependent variable was measured once before the exercise was implemented and once after it was implemented. Measurements were performed as part of regular in-season training. One week before the experiment, the participants completed an assessment of body height, body mass, acceleration speed in a 10-m sprint, maximal speed obtained from the lowest 10-m split time in a 40-m run, explosive strength in a countermovement jump, and aerobic endurance in a Yo-Yo intermittent recovery test level 1 (Table 1).

Prior to the experiment, the participants underwent a warm-up that included low-intensity running, dynamic stretching, and running drills. No specific exercise with a ball was included. The warm-up and testing of neuromuscular and perceptual-cognitive performance were executed indoors to secure standardized conditions. The participants wore standard indoor soccer footwear. Afterwards they were individually asked to evaluate their subjective perception of fatigue. They changed the footwear to standard football boots and moved to the soccer field located right outside the testing room. The SSGs were performed outdoors on a regular artificial grass soccer field, between 3 and 6 p.m. in temperatures 7 to 10°C (Meteoblue, Basel, Switzerland). After the SSG protocol, the participants immediately moved to the testing room and underwent the same testing procedure within 10-min of its completion. Tests were executed in randomized order. A whole experimental design is shown in Figure 1.

The SSG (4v4 + Goalkeepers) was performed on the outdoor soccer field with artificial grass using formal 11-a-side goals. The size of the pitch 40 × 25-m (length × width) provided a relative field space of 125 m² per player (Calderón Pellegrino et al., 2020). The exercise included six 4-min bouts separated by 1-min passive recoveries (overall game time of 24-min). The players were divided into two teams by the head coach in accordance with his perception of their physical, technical, and tactical skills (Torrents et al., 2016). Standard 11-a-side soccer rules were followed except for the offside rule. Field players were able to pass to goalkeepers. Verbal encouragement from coaches was permitted, but not feedback related to the players’ technical and tactical performance. Several balls were located near the sidelines around the pitch to increase the effective play time (Hill-Haas et al., 2008). The players were familiar with this SSG format as it was used regularly in training.

Data are presented as mean ± SD. The coefficient of variation (CV%) and 90% confidence intervals (CI 90%) were calculated to describe the physiological response of players to the SSG and the kinematic profile in the SSG. The normality of data distribution was determined using the Shapiro-Wilk test. In the case of normal data distribution, the paired-sample t-test was performed. Otherwise, the Wilcoxon signed rank test was performed. Significance was set at p < 0.05 (2-tailed). The smallest worthwhile change was calculated as between subjects’ SD multiplied by 0.2 (Tomczak and Tomczak, 2014). The post hoc statistical power of the sample size was calculated with G*Power (Version 3.1.9.6, Institut für Experimentelle Psychologie, Düsseldorf, Germany). The power for the number of subjects within the study sample was 1 − β = 0.604 with α = 0.05. To compensate for the lower sample size power, additional methods were used. The effect sizes for Hedges’ g were as follows: <0.2 trivial; 0.2–0.5 small; 0.5–0.8 moderate; >0.8 large effect. The Cohens’ r (r_c) for non-parametrical data was as follows: <0.1 small; 0.3–0.5 moderate; >0.5 large effect size. Uncertainties in the true effects of the respective conditions were evaluated by magnitude-based inferences using customized spreadsheets. Magnitudes of clear effect were considered according to the following scale: 25%–75%, possibly; 75%–95% likely; 95%–99%, very likely; >99% most likely (Hopkins, 2007). Differences in the pre- and post-SSG performance variables were expressed as the mean of individual differences (Δ = post-SSG–pre-SSG). Associations between individual performance changes (Δ) and exercise load variables were reported using the Pearson/Spearman correlation coefficient (r/r_s) with lower and upper confidence intervals (90%). The correlation strength was interpreted as follows: r/r_s = <0.1, trivial; 0.1–0.3, small; 0.31–0.49, moderate; 0.5–0.69, large; 0.7–0.89, very large; and 0.9–1, perfect correlation. Additionally, the amount of explained variance (R²) was determined for the parametric data (Hopkins et al., 2009). Statistical analyses were performed using Graph Pad Prism software 9.5.0 (Graph Pad Software, San Diego, CA, United States).

After the SSG, a CMJ height decreased (−6.65% ± 6.23%, p = .014, g = .56, moderate effect, Table 3; Figure 3A), PA time (4.04% ± 2.53%, p = .002, most likely, g = .97, large effect, Table 3; Figure 3B), and RA time increased (6.45% ± 7.37%, p = .003, likely, g = 1.16, large effect, Table 3; Figure 3C). The response time in the GNG task did not change after the SSG (−3.36% ± 8.04%, p = .119, g = .29, small effect, Table 3; Figure 4A), whereas errors of commission increased (87.10% ± 138.99%, p = .023, r_c = .57, moderate effect, Table 3; Figure 4B).

Significant correlations were found between ΔCMJ height and VHSR (r_s = .660, p = .006), ΔCMJ height and MSP (r = .536, p = .032, R² = .286), ΔPA time and HACC (r_s = −.764, p = .002), ΔRA time and VHSR (r_s = −.501, p = .022), and ΔRA time and MSP (r = −.524, p = .037). In addition, ΔGNG errors correlated significantly with absolute and relative TDC (r = −.576, p = .021; r = −.631, p = .009; respectively), and ΔGNG response time with MSR (r = −.596, p = .015, R² = .319). Moderate, large, and very large correlations between performance differences (Δ) and respective exercise load are shown in Table 4.

Neuromuscular performance was affected by SSG in terms of decreased CMJ height and increased PA time. These reductions can be ascribed to players’ high mechanical load in SSGs produced by numerous changes in speed and direction. This requires the eccentric strength of knee extensors to reduce movement velocity in the deceleration phase, and concentric strength in the acceleration phase (Jones et al., 2009). Repeated muscle contractions produce muscle damage which may temporarily decrease players’ force production (Greig and Siegler, 2009; Thorlund et al., 2009). In addition, the fast transition from concentric to the eccentric phase of movement relies on a muscle and tendon complex utilizing a stretch-shortening cycle (Nicol et al., 2006). Fatigue induced by mechanical load alters the neuromuscular activation patterns of human skeletal muscle (Gollhofer et al., 1987). Thus, the observed declines in CMJ height (−6.65%) are in agreement with Rebelo et al. (2016) who reported decreased CMJ height (−9.4%) after two sets of three repetitions of 6-min SSG 4v4. Bujalance-Moreno et al. (2020) applied four 4-min game intervals separated by 2-min passive recoveries between the bouts. Significant changes were observed in the linear 20-m sprint time (1.3%) but not in the 5-m sprint and CMJ height. A different result could be explained by a lower overall work time in the SSG protocol compared to ours.

Furthermore, repeated high-intensity efforts tend to decrease the power generated by hamstring and gluteal muscle groups (Small et al., 2010; Edouard et al., 2018) and affect the change of direction speed by impaired lower-limbs biomechanics (Cortes et al., 2012). These presumptions point to the increments of PA and RA times, which were observed in our study (4.04% and 6.45%; respectively). It is suggested that neuromuscular performance decrease is likely associated with the number of accelerations and decelerations. However, we did not find significant relationships between the number of high-intensity accelerations and decelerations with neither CMJ height nor PA time deterioration. On the other hand, moderate correlations were observed in low to moderate intensity decelerations with ΔCMJ height (r = −.376) and ΔPA time (r = .481). This may be ascribed to 4v4 SSGs’ pitch dimensions which do not allow players to cover enough high-intensity distances and perform high-intensity accelerations and decelerations.

It needs to be stated that SSGs are adjustable in load variables, e.g., number of players, pitch size, rules, or work/rest duration (Sarmento et al., 2018). These factors influence the internal and external load of players (Hill-Haas et al., 2011), resulting in their differential response. Specifically, one study suggested that small formats of SSG (i.e., 1v1 and 3v3) do not have a significant impact on the lower limb power in CMJ. Even though these players surpassed our subjects in the relative distance covered in the game (m/min⁻¹) and the internal load (%HR_max), probably a short exercise duration could not produce a sufficient external load to induce neuromuscular fatigue (Clemente et al., 2017). A lower number of repetitions and longer resting periods compensate for players’ neuromuscular performance decrement. This can also be achieved by reducing the pitch size of SSGs (Castillo et al., 2019). The question remains whether declines in reactive agility and perceptual-cognitive performance can be compensated as well.

A slight decline in players’ response time (−3.36%, n.s.) but a significant increase in errors of commission (87.1%) was observed in the response inhibition task. SSGs engage players’ physical and mental effort in an open-skill and dynamic environment (Owen et al., 2012; Mitrotasios et al., 2021). Therefore, some aspects of cognition are affected by sport-specific exercises as well. Previously, an improved inhibitory control was found in primary school children after the high-intensity SSG (Lind et al., 2019). Exercise-induced arousal improves a choice reaction time (Kashihara and Nakahara, 2005), but it can simultaneously affect object detection in sport-specific tasks (Klatt and Smeeton, 2021). These findings support our results, as youth soccer players react to visual stimuli slightly faster but less accurately after the SSG.

Intermittent exercise induces changes in perceptual-cognitive processes in both high- and low-level soccer players (Casanova et al., 2013). These temporal cognitive declines are often ascribed to the hypothesis of hypofrontality. For the maintenance of motor functions, the brain is limiting its resources to movement centers, causing less activation in centers responsible for higher-order cognitive functions (Dietrich, 2006). However, the lack of advanced neuroimaging tools available for use in sport-specific conditions does not allow us to reveal these changes. More evident is the role of mental fatigue and its impairment of decision-making, the tactical aspect of performance, and the skill execution in elite athletes (Russell et al., 2019). It has been shown that even a 20-min intermittent soccer-specific exercise produces mental fatigue in well-trained soccer players (Bian et al., 2022). However, research needs to shed light on the inducement of mental fatigue by SSGs.

Cognition also plays an important role in reactive agility performance (Young et al., 2015). It is suggested that reactive and planned agility differentiate under fatigue conditions (Ciocca et al., 2022). This may be corroborated by our results with the largest effect size for ΔRA time (6.45%, g = 1.16). Both the Y-shaped reactive agility test and the go/no-go task partly focus on the assessment of decision-making ability. This ability is often evaluated in soccer by the analysis of in-game successful passing (i.e., decision-making index) which tends to decrease with an increasing volume of exercise (Mitrotasios et al., 2021) and additional inducement of mental fatigue before SSG (Fortes et al., 2019; Gantois et al., 2020). Our results confirm that changes in perceptual-cognitive performance occur in response to sport-specific exercise load. However, the current literature deals with the lack of information about the effects of exercise on reactive agility while preferring more conventional methods of planned agility assessments (Marqués-Jiménez et al., 2022; Bilić et al., 2023).

No single robust variable of SSG load was related to neuromuscular nor perceptual-cognitive performance declines in youth soccer players. In the case of external load, only a ΔPA time was moderately correlated with the amount of LMDEC. This resulted in a 23% proportion of variance in ΔPA time increase. It can be assumed that players in our study were not able to cover enough high-intensity distance and perform high-intensity accelerations or decelerations, which would point to these variables as the most contributing to respective performance declines. From the perspective of internal load, time spent in <59% HR_max moderately correlated with ΔRA time by a 19% proportion of variance. The discovered relationships did not fully reveal the contribution of exercise load to the observed declines in neuromuscular and perceptual-cognitive performance.

Previously, a significant association was found between CMJ height decline and high-intensity activities in SSG 4v4 (Rebelo et al., 2016). Similar associations were presented in relation to the amount of external load in soccer matches (Rampinini et al., 2011; Silva et al., 2013; Rowell et al., 2017). Since SSGs 4v4 can relatively overload the mechanical work accumulated in a soccer match (Lacome et al., 2018), similar associations were expected to be found in our case. As mentioned above, we did not confirm these presumptions. Soccer games also include barely detectable high-power actions without a change in the location of players, such as jumping or duels (Dalen et al., 2016). However, our findings can be related to the fact that amateur and professional players’ kinematic profiles in SSGs differ in the amount of high-intensity actions (Dellal et al., 2011). Additionally, no correlation was reported between changes in linear sprint performances and the rate of perceived exertion registered during the four different 5v5 SSG protocols (Castillo et al., 2019). It is also suggested that interindividual differences exist between the perceived effort and the lactate responses of players during SSGs (Köklü et al., 2015). In accordance with our results, the evaluation of youth players’ level of fatigue or the response to exercise should incorporate more than subjective assessment methods.

From the perspective of external load, players who achieved a higher VHSR distance and MSP in SSG tend to show a lesser drop in the ∆CMJ height. Similarly, a correlation of HACC with ∆PA time, and ∆RA time with VHSR was found. A slight compensatory effect occurred in players who were able to achieve very high-speed running and high-intensity accelerations. The same was true for the total distance covered in SSG and the errors in the response inhibition task. In fact, the usage of SSG, usually in warp-ups, can also have positive effects on CMJ and reactive agility performance (Zois et al., 2011). Temporally enhanced performance can be explained by athletes’ physiological response to physical exercise in terms of increased muscle temperature and blood flow, increased neural activation, and improved force-velocity relationship (Binkhorst et al., 1977; Sale, 2002). The lack of correlation in the case of perceptual-cognitive and reactive agility performance with load variables would be attributed to the complexity of SSGs as they engage humans’ motor, sensory, and cognitive systems (Owen et al., 2012; Figueira et al., 2019). Therefore, it seems unlikely to reveal a single variable that would interfere with cognitive performance declines solely from load tracking data or subjective assessment of players.

Nevertheless, this study has some limitations. Heterogeneity in study protocols, the performance level or age of participants makes it difficult to compare our results with the findings of other authors. In addition, there is a variance in the assessment procedures regarding to agility and perceptual-cognitive performance testing. Larger sample sizes and consideration of the growth and maturity levels of players should bring a more profound understanding of the acute effects of SSGs on reactive agility and perceptual-cognitive performance. The novel objective cognitive function evaluation methods could provide evidence to support temporal cognitive changes in response to acute bouts of sport-specific exercises. Since the mental effort of sport-specific tasks is often neglected, research would develop a method that counts physical and psychological exertion of players in these tasks. Practitioners could better estimate the load of sport-specific exercises, players’ level of fatigue, and thereby optimize the exercise load in training microcycles.

We suggest using the SSG 4v4 and its numerous modifications to target players’ agility and decision-making ability. However, practitioners should be aware of subsequent acute performance declines in the planning of the training structure. These declines are hardly detectable by the available load tracking systems and subjective methods. The application of SSGs with a relatively high work-to-rest ratio must be manipulated with caution for youth soccer players.