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Article

Effects of Congested Matches and Training Schedules on Salivary Markers in Elite Futsal Players

by
Alejandro Soler-López
1,2,
Carlos D. Gómez-Carmona
1,3,*,
Adrián Moreno-Villanueva
1,4,
Ana M. Gutiérrez
1,5 and
José Pino-Ortega
1,2
1
BioVetMed & SportSci Research Group, University of Murcia, 30100 Murcia, Spain
2
Department of Physical Activity and Sport, Faculty of Sport Sciences, University of Murcia, 30720 San Javier, Spain
3
Research Group in Optimization of Training and Sports Performance (GOERD), Department of Didactics of Music Plastic and Body Expression, Faculty of Sport Science, University of Extremadura, 10003 Caceres, Spain
4
Faculty of Health Sciences, Isabel I University, 09003 Burgos, Spain
5
Department of Animal Medicine and Surgery, Veterinary School, CEIR Campus Mare Nostrum (CMN), University of Murcia, 30100 Espinardo, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(12), 4968; https://doi.org/10.3390/app14124968
Submission received: 14 May 2024 / Revised: 4 June 2024 / Accepted: 5 June 2024 / Published: 7 June 2024
(This article belongs to the Section Applied Biosciences and Bioengineering)
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Abstract

:

Featured Application

Monitoring salivary biomarkers demonstrates a potential application to assess the internal training load and recovery status of elite futsal players during congested competition periods, especially total protein and salivary immunoglobulin A. Tracking biomarker changes provides a practical tool for coaching staff to guide adjustments to training loads, nutrition, and recovery protocols to mitigate risks and optimize athlete performance and health.

Abstract

A congested match and training schedule could alter internal load, and this could be reflected in biomarkers of stress and immunity in elite futsal players. The aim of this study was to analyze the effects of a congested match and training schedule on internal load and levels of total protein, total oxidant status (TOS), total antioxidant capacity (TAC), oxidative stress index, and the concentrations of salivary immunoglobulin A (SIgA) in 17 professional players from the same Portuguese elite futsal club (age: 23.07 ± 6.76 years old; height: 1.75 ± 0.06 m; body mass: 75.47 ± 7.47 kg; experience in playing in elite: 5.38 ± 2.03 years) who performed 5 matches and 16 training sessions in a period of 27 days. The salivary content of total protein, TOS, TAC, oxidative stress index, and SIgA were calculated before and after the training sessions and the unofficial matches under study. Saliva sampling was conducted 10 min before each match or training session and 40 min after (post-match and post-training). The MANOVA of repeated measures showed a significant difference for total protein and SIgA (p < 0.01). Total protein (sphericity = 0.007; statistical power = 0.818) and SIgA (sphericity = 0.018; statistical power = 0.693) are highly correlated with the time factor. The main findings revealed several key points: (a) There was a significant increase in total protein, SIgA, and TAC during acute load (pre- vs. post-session) in both training and match contexts. Specifically, total protein and SIgA displayed notable increments in both training and match settings, while TAC exhibited significant increases exclusively during matches. (b) No changes in TOS and oxidative stress index were observed during acute load in either training or match contexts. (c) A positive trend was noted between the chronic load during a congested week of the precompetitive season and the decrease in total protein and SIgA levels. (d) Additionally, a positive correlation between internal training loads and oxidative/antioxidant responses was found, as expressed by the oxidative stress index, without significant differences (p-value > 0.05) in acute and chronic loads during congested matches and training schedules.

1. Introduction

In recent decades, the physiological demands of futsal have undergone significant alterations. This can be attributed to the escalation in the number of high-level futsal games being played and the increased intensity of such games on average [1,2]. When the fixture list becomes congested, with players compelled to participate in two matches each week for several weeks, the gap between subsequent matches shrinks to just 2–3 days. This limited recovery time may prove insufficient for complete player recuperation, resulting in acute and chronic fatigue, as well as potentially leading to underperformance, heightened levels of fatigue, and an elevated risk of injury [3,4,5]. The issue of congested periods has been extensively discussed in the literature on football match analysis [6,7]. However, only a few studies have assessed the effects of futsal games during a short congested schedule, which makes it difficult to draw any definitive conclusions. Therefore, it is crucial to register the workload suffered by futsal players during congested match periods in training and competition to manage fatigue, reduce injury risk, and determine player readiness for performance [8].
Players’ workload has been categorized into two types: internal and external. External load pertains to the physical exertion experienced by players, which refers to the stimulus applied. Meanwhile, internal load pertains to the biochemical, physiological, and psychological reactions triggered by training sessions or matches [9,10]. The enhanced accessibility of contemporary technological tools for monitoring external loads (e.g., the Global Positioning System or Local Positioning Systems) has led to a decrease in focus on internal loads or actual psychophysiological responses [11]. Nevertheless, the significance of registering the internal responses to the applied stimuli has been recently stressed in order to obtain a comprehensive understanding of an athlete’s condition [11]. From this perspective, a positive correlation has been established between physical stress and neuroimmune–endocrine responses in elite athletes [12,13]. Several studies have been conducted to explore the connection between different neuroimmune–endocrine responses and training stress [14,15,16,17]. However, we have not discovered any articles that have investigated the relationship between neuroimmune–endocrine system responses in top-level futsal players during a congested schedule.
Immunoglobulin A (IgA) secretion patterns are widely acknowledged as a crucial marker of immune responses. Salivary immunoglobulin A (SIgA) acts as a vital immunological barrier, neutralizing and preventing viral pathogens from infiltrating the body through mucosal surfaces [18]. Numerous studies have proposed a correlation between the risk of upper respiratory tract infections and SIgA levels, particularly when combined with other antimicrobial proteins present in the saliva, such as amylase, defensins, lysozyme, and lactoferrin [19]. For athletes, contracting upper respiratory tract infections can have detrimental effects on their training regimens and performance capabilities [20,21]. Some scientific studies have investigated how acute exercise stress influenced the mucosal immune system, finding a temporary decrease in the level of SIgA after a session of intense exercise [20,22,23,24,25]. The decrease in SIgA levels has been associated with compromised immune function and an elevated susceptibility to upper respiratory tract infections. For instance, Mortatti et al. [26] documented a reduction in SIgA concentration accompanied by a higher incidence of upper respiratory tract infections among elite under-19 soccer players who were monitored during a series of seven matches over a 20-day period. Nonetheless, there remains ambiguity surrounding the relationship between exercise training and the SIgA response, as some researchers have not reported any changes [27,28] and have even observed an increase in SIgA following acute exercise [29].
While the corpus of literature examining salivary biomarkers has experienced a considerable expansion over the past decade [13,15,17,20,22,28,30,31,32,33], very few studies investigated TOS, TAC, or fluctuations of total protein levels [16,34,35]. Typically, total protein concentrations can serve as potential indicators of overall hydration levels in humans. The findings reported by Walsh et al. [35] indicate a strong correlation between salivary osmolality, urinary osmolality, salivary total protein concentration, and plasma osmolality in dehydrated subjects. Additionally, their study revealed an increase in salivary total protein levels from pre-exercise to post-exercise conditions during a trial involving prolonged exercise without fluid intake. However, despite its relationship with the hydration status of the athlete, we have not found studies that analyze whether total protein can be a sensitive biomarker to detect fatigue in elite futsal players.
According to the evidence that participation in futsal competitions can lead to decreased SIgA levels and increased internal load during training and competition periods, there are currently no studies investigating immune and endocrine responses during a congested competitive period among elite futsal players. Therefore, the present study aimed to analyze the effects of a congested match and training schedule on levels of total protein, TOS, TAC, oxidative stress index, and the concentrations of SIgA in elite futsal players, clarifying whether these biomarkers are sensitive to detecting acute fatigue in elite futsal players. The hypothesis was that all the biomarkers analyzed in this manuscript would be sensitive to detecting both acute and chronic loads in elite futsal players during a congested period of matches and training sessions.

2. Materials and Methods

2.1. Experimental Approach to the Problem

This investigation aimed to examine the responses of various salivary biomarkers (total protein, SIgA, TAC, TOS, and oxidative stress index) and their relationships with training and match loads in elite futsal players during a congested period in the precompetitive season. The participants provided resting saliva samples approximately 10 min before the pre-session warm-up (PRE), while post-session saliva samples were collected within 40 min after the conclusion of the session (POST). The elite futsal players performed a total of twenty-one sessions during the study period, comprising sixteen training sessions and five unofficial matches. The designated training sessions incorporated a combination of tactical technical training (TT) and physical training (PT) throughout the preseason period. The PT was integrated with the TT on the court, with an average training duration of approximately 100–120 min per day, excluding the time allocated for warm-up and cool-down periods. The volume and intensity of TT and PT remained relatively consistent across all training sessions. However, the number of training sessions conducted per week varied between preseason weeks (see Table 1). It is important to note that this investigation occurred during the pre-season period, and no official matches were held during the 4-week duration of this study.

2.2. Subjects

This study employed a convenience sampling approach, recruiting 17 players from the same elite Portuguese futsal club (age: 23.07 ± 6.76 years; height: 1.75 ± 0.06 m; body mass: 75.47 ± 7.47 kg; experience in elite-level play: 5.38 ± 2.03 years). Prior to the commencement of this study, all participating players were familiarized with the aims, procedures, requirements, potential risks, and benefits of the research. The athletes volunteered to participate and were informed about the research protocol, subsequently providing their written informed consent. The exclusion criteria included the following: (i) any recent injury requiring medical attention; and (ii) consumption of anti-inflammatory drugs or antioxidant supplements during the study period. This study received approval from the institute’s research ethics committee (ID: 3495/2021) and adhered to the ethical recommendations for research involving human participants, as outlined in the Declaration of Helsinki (2013).

2.3. Saliva Collection

The participants were instructed to abstain from consuming food and caffeine products for a minimum of 2 h prior to the pre-collection of saliva samples. Initially, they were required to rinse their mouths with distilled water to eliminate potential contaminants that could influence salivary IgA levels. Participants maintained a seated position with eyes open and head slightly tilted forward, and they were instructed to chew on a sponge for a period of 1 min before expelling the saliva into sterile tubes. To minimize the influence of diurnal variation, all training sessions took place in the afternoon, commencing at 7 pm, with ambient temperatures ranging between 24 and 27 °C. Saliva samples were collected using synthetic fiber swabs and specific tubes (Salivette Cortisol tubes, Sarstedt AG & Co., KG, Nümbrecht, Germany). The collected saliva samples were stored at −80 °C until further analysis.

2.4. Assays

2.4.1. Salivary Immunoglobulin A

The concentrations of SIgA were quantified using an Enzyme-Linked Immunosorbent Assay (ELISA) kit (Salivary Secretory IgA indirect Enzyme immunoassay Kit, Salimetrics, State College, PA, USA). The saliva samples underwent a meticulous analytical process: Initially, reagents were prepared according to the manufacturer’s instructions, and the plate layout was arranged for duplicate assays of the saliva samples. The required strips were retained in the holder, while the remaining strips were stored at 2–8 °C. Subsequently, 3 mL of 1X SIgA diluent was pipetted into a tube, adjusting the volume when not using the full plate. For sample preparation, tubes were labeled for each sample, and 100 μL of diluent was added, followed by 25 μL of saliva and vortexing. In separate 5 mL tubes, 4 mL of diluent was added, and 10 μL of standards, controls, and diluted saliva samples were pipetted, along with 10 μL of diluent to the zero tube. The antibody enzyme conjugate was diluted 1:120, and 50 μL was added to each tube, followed by a 90 min incubation. After incubation, 50 μL from each tube was transferred to designated plate wells, with 50 μL of diluent added to blank wells. The plate was mixed for 90 min, washed 6 times with 1X wash buffer, and then 50 μL of TMB substrate solution was added to each well, followed by a 40 min incubation in darkness. Finally, 50 μL of stop solution was added to each well, ensuring color change, and optical density was read at 450 nm within 10 min. A secondary filter correction at 490 to 492 nm was considered for accuracy.

2.4.2. Oxidative Stress Biomarker Quantifications

Since antioxidants reduce oxidants, the TAC method is based on the measurement of the reducing ability of the antioxidants in the sample compared to a control antioxidant, Trolox, which is used as a calibrator. Specifically, the method FRAP (ferric reducing antioxidant power) measures the reduction of the ferric tripyridyltriazine complex of the reagent used to the ferrous (FeII) at low pH. This reaction produces color, with an absorption maximum at 593 nm [36]. The optimized assay protocol (FRAP) involved combining 36 μL of the saliva sample with 270 μL of the ferric reducing power reagent. Antioxidant activity was determined by interpolating the measured absorbance of the samples at 593 nm on a calibration curve generated with Trolox at concentrations ranging from 100 to 1.56 μM/L, employing a linear regression curve fit. The coefficients of variation were consistently below 15%, and the limit of detection was established at 0.432 μM/L Trolox equivalents.
For the assessment of oxidant status, the commercially available Pierce™ Quantitative Peroxide assay (Thermo Fisher Scientific Inc., Waltham, MA, USA) was utilized. Saliva samples were diluted 1:2 for analysis, and the reaction consisted of 150 μL of standard or saliva sample and 70 μL of working buffer. The levels of oxidants in the saliva samples were calculated by interpolating the measured absorbances at 595 nm using a 4-parameter curve fit with a calibration curve constructed with hydrogen peroxide at concentrations ranging from 31.25 to 0.97 μM/L. The coefficients of variation were determined to be below 11%, and the detection limit for peroxidase equivalents was established at 0.5 μM/L of peroxidase equivalents. The oxidative stress index was calculated as the ratio of TOS to TAC, following established methodologies [37].

2.4.3. Total Protein Content Determination

The total protein content of saliva samples was assessed following established protocols [38]. Saliva samples were diluted (1:40) for analysis, and the concentrations were calculated by interpolating the absorbances of the samples obtained at 590 nm in a calibration curve of 5–100 ng/mL of bovine serum albumin (Sigma-Aldrich, Darmstadt, Germany) using a linear curve fit.

2.5. Statistical Analysis

Firstly, the sample characterization of the biochemical response of the futsal players during the mesocycle was conducted by means and standard deviations. Normal data distribution and homoscedasticity were confirmed by the Kolmogorov–Smirnov and Levene tests [39]. To evaluate the acute effect of fatigue, two analyses were performed: (1) a repeated measures t-test to evaluate the result of training and match workload in the levels of total protein, SIgA, TAC, TOS, and oxidative stress index previous and before the events; and (2) an independent measures t-test to evaluate whether training and matches produce different effects using new calculated variables as the difference between post- and pre-values. To evaluate the chronic effect of fatigue, a MANOVA of repeated measures was conducted to identify the mean of differences between the session throughout the congested period. Two-by-two comparisons were performed by Bonferroni correction [39]. The statistical power calculation, based on a F-test for within-group factors with two levels (training vs. match) and two time points (pre vs. post), determined that a sample of 17 participants would provide 95.5% power to detect differences with a p < 0.05 and effect size of 0.65, using G-Power [40]. In addition, partial omega-squared (ωp2) was calculated to evaluate the magnitude of the differences for MANOVA and interpreted following Cohen [41]: <0.01 as trivial, 0.01–0.06 as small, 0.06–0.14 as medium, and >0.14 as large. Instead, Cohen’s d was used to interpret 2-by-2 comparisons using the classification of Hopkins et al. [42]: trivial (<0.2), low (0.2–0.5), moderate (0.5–0.8), and high (>0.8). Statistical analyses were conducted by SPSS v24.0 software (SPSS, Inc., Chicago, IL, USA), and graphics were created using GraphPad Prism v9.0 software (GraphPad Software, La Jolla, CA, USA). Statistical significance was established at p < 0.05.

3. Results

3.1. Acute Load

Figure 1 shows the effect of training and matches in pre- and post-values in the biochemical variables evaluated during the congested-fixture period. Higher values after sessions were found in total protein with moderate effect in both contexts (training: t = −6.85, p < 0.01, d = 0.73; match: t = −4.15, p < 0.01, d = 0.52) and in SIgA with high effect in matches (t = −3.09, p < 0.01, d = 1.09) and moderate effect in training (t = −2.95, p < 0.01, d = 0.52). In addition, a low effect with high after-match values were found in TAC (t = −3.67, p < 0.01, d = 0.46). No effect was found in TAC during training sessions and in TOS and oxidative stress index in both scenarios.
The differences of acute effects between training and match contexts in biochemical markers are shown in Table 2. Higher acute fatigue in the match context was found with a moderate effect in SIgA and a low effect in TAC and TOS. No effect was found in the total protein and oxidative stress index between session contexts.

3.2. Chronic Load

Figure 2 shows the dynamics of biochemical markers throughout a week during the congested fixture period at four moments: (1) pre-match; (2) post-match; (3) 48 h after the match; and (4) 120 h after the match. Statistical differences with a large effect size were found in total protein (F = 47.02; p < 0.01; ωp2 = 0.81) and SIgA variables (F = 14.69; p < 0.01; ωp2 = 0.56). TOS, TAC, and oxidative stress index did not present differences among assessment moments (F < 0.77; p > 0.52; ωp2 < 0.01).
Regarding total protein, higher values were found in the post-match condition in comparison with the rest of assessment moments with a large effect size (p < 0.01; vs. pre-: d = 1.25, vs. 48-h: d = 1.80, vs. 120-h: d = 1.63). As well as higher values being found in the pre-match condition versus the 48-h condition (p < 0.01; d = 0.84 large), SIgA also presented higher values in the post-match condition with a large effect size (p < 0.01; vs. pre-: d = 1.61, vs. 48 h: d = 1.69, vs. 120-h: d = 1.82).

4. Discussion

This study examined the changes in total protein, SIgA, TAC, TOS, and oxidative stress index and their relationships with training loads during a congested match and training schedule period in elite futsal players, conducted in the precompetitive season. The main findings were (a) a significant increase in total protein, SIgA, and TAC were observed in acute load (pre- vs. post-session) in training and match contexts, specifically, total protein and SIgA showed notable increments in both training and match settings, while TAC exhibited significant increases exclusively during matches; (b) no changes in TOS and oxidative stress index were detected in acute load during training and match contexts; (c) a positive trend was observed between the chronic load during a congested week of the precompetitive season and the decrease in total protein and SIgA levels; and (d) a positive relationship was found between internal training loads and oxidative/antioxidant responses, as expressed by a oxidative stress index without significant differences (p-value > 0.05) in acute and chronic loads during a congested match and training schedule.

4.1. Acute Load

Regarding the relative changes in SIgA in acute load, previous studies involving elite athletes within their regular training regimens or competitive settings have shown that intense endurance exercise typically leads to reduced levels of SIgA post-exercise [43]. This consensus is supported by numerous studies illustrating declines in SIgA levels following intense physical exertion [20,23,24,25,44,45]. However, the present study did not find evidence to support the hypothesis that a congested period of matches and training sessions during the futsal preseason would transiently suppress mucosal immune function in elite players, as assessed by SIgA levels. Notably, increases in SIgA, as observed in the players (see Figure 1), have been similarly reported in prior investigations [27,46,47,48]. These discrepancies in the scientific literature may be attributed to the variability in the SIgA measurement employed in the studies to elucidate the findings. The ratio of SIgA to total protein (SIgA/Pro ratio) has been investigated and discussed in previous exercise immunology research papers. Tomasi et al. [49] reported a higher percentage of SIgA depletion when this variable was expressed relative to the concentration of total proteins. However, it has been suggested that utilizing the ratio of SIgA to total protein concentration can lead to misinterpretation due to the fact that the total protein content of saliva is considerably more variable due to the high concentrations of enzymes such as amylase, which are induced by flow rate stimulation. It may be more appropriate to express salivary IgA concentration as a ratio to albumin, as albumin is less influenced by flow rate and is not actively secreted across the epithelial membrane [46,50].
Regarding total protein, the results of the present study also show that there was a significant increase in total protein from PRE (1.49 ± 0.79 mg/mL−1) to POST (2.25 ± 1.40 mg/mL−1) training and PRE (1.31 ± 0.77 mg/mL−1) to POST (1.81 ± 1.22 mg/mL−1) match. These findings support the results found in other studies [46], which showed increases in total protein concentrations (0.48 ± 0.10 mg/mL−1 to 1.80 ± 0.38 mg/mL−1). The role of total protein in immunological studies and the changes in protein levels under different physiological conditions are still poorly understood. These limitations are extensive for most of the salivary protein functions [51]. In addition, between matches and training sessions, during acute loads, total protein seems to be a less sensitive variable for determining the acute effect on elite futsal players compared to SIgA; these changes appear to be largely due to stimulation of amylase secretion by increased sympathetic nervous activity, which appears to have a greater effect on SIgA levels [52].
Concerning the relative changes in TOS, TAC, and oxidative stress index under acute loading conditions, the present study did not observe statistically significant differences (p > 0.05) in all variables, except for TAC. This discrepancy could be attributed to a intrasubject coefficient of variation (33.45%). Oxidative responses to workload are inherent to the body’s physiological processes. However, to ascertain the body’s oxidative load tolerance, it is imperative to scrutinize its antioxidant response. Therefore, the TOS/TAC ratio serves as an indicator of the oxidative stress index. Furthermore, as demonstrated in Table 2, match-related loads elicit a significant increase in both TOS and TAC variables (p-value < 0.02 and p-value < 0.01, respectively) compared to training sessions. Nevertheless, no distinctions are evident in the oxidative stress index, suggesting that the antioxidant defense mechanism adequately counteracts the oxidative demands. These findings imply that subjects in this study did not exhibit oxidative stress in response to acute loads during the congested match and training schedule.

4.2. Chronic Load

Regarding chronic load, a congested week of preseason was analyzed to observe if there were significant changes in the variables total protein, SIgA, TAC, TOS, and oxidative stress index at three time points (see Figure 2) compared to PRE levels. The findings did not show significant differences in any of the evaluated variables beyond the results shown in the acute load mentioned earlier. However, there appears to be a positive trend between the chronic load during a congested week of the precompetitive season and the decrease in total protein and SIgA levels, and a positive relationship was found between internal training loads and oxidative/antioxidant responses.
Total protein and SIgA levels did not show significantly altered values at 48 h or 120 h, indicating that the subjects included in this study do not show a risk of contracting upper respiratory tract infections (URTIs) due to a decreased immune reaction, as shown in other studies [13,53,54,55] where a significant depletion of SIgA was found with the progression of workloads supported by athletes. The findings may be due to the large interindividual variability of the variables (total protein and SIgA), as well as the small sample size. Additionally, the time of measurement of the mentioned variables appears to be a determining factor for their determination; most articles that have analyzed this variable show highly heterogeneous measurement times [20,23,24,25,27,44,45,46,47,48,49], making it difficult to determine the most suitable time to measure this variable, as we can find in other variables such as lactate, of which we know that its optimal measurement time is around 3–5 min after activity [56]. The values of TAC, TOS, and oxidative stress index remained unchanged (see Figure 2), indicating that the chronic load supported by elite futsal athletes during the evaluated week in the preseason showed no signs of oxidative stress. The TOS and TAC variables behaved similarly, resulting in an unchanged oxidative stress index. The loads induced on these athletes during this period were optimally assimilated at the oxidative level by all elite players, showing no signs of a high oxidative stress index.
The present findings indicate that after a congested period of matches and training during the competitive preseason in elite futsal players, total protein and SIgA variables have proven to be sensitive in detecting physiological changes in athletes under acute load. Additionally, SIgA emerges as a more sensitive variable than total protein in distinguishing between training and matches, partly explained by the influence of sympathetic nervous system activity. This study suggests that chronic load does not appear to diminish SIgA levels. However, this does not imply that SIgA should be disregarded as a potential mechanism that could render athletes more susceptible to infection, especially during periods of overreaching or overtraining. Moreover, given the nature of team sports and their distinct demands compared to endurance exercises, the likelihood of different effects should be considered. Regarding the oxidative stress index, players did not exhibit signs of oxidative stress under acute and chronic loads, indicating optimal assimilation of the load during congested matches and training schedules.

5. Conclusions

The presented data indicate that monitoring the training process can assist coaches and scientists in comprehending the immune and oxidative responses to training. Indeed, this study revealed that SIgA and total protein may serve as valuable markers of match intensity in elite futsal players during periods of intensified training. Furthermore, they could be utilized to mitigate the risk of URTIs during the in-season phase, with the monitoring of the SIgA as routine analysis. However, the variability in responses among players suggests the necessity for individual analysis of results in team sports settings. Additionally, evaluating oxidative and antioxidant responses through the oxidative stress index can aid coaches and trainers in determining whether athletes exhibit a negative balance in the oxidative stress index and consequently adjust or adapt training loads or nutritional strategies accordingly. Indeed, meticulous monitoring and control of training using these practical tools may enhance athlete health and availability for selection. Further research into the role of acute post-exercise changes in SIgA expression in elite professional soccer players is needed.

Author Contributions

Conceptualization, A.S.-L., A.M.G. and J.P.-O.; methodology, A.S.-L., A.M.-V. and A.M.G.; software, C.D.G.-C. and J.P.-O.; validation, A.M.-V., A.M.G. and J.P.-O.; formal analysis, A.S.-L. and C.D.G.-C.; investigation, A.S.-L. and A.M.-V.; resources, A.M.G. and J.P.-O.; data curation, A.S.-L. and C.D.G.-C.; writing—original draft preparation, A.S.-L. and C.D.G.-C.; writing—review and editing, A.M.-V., A.M.G. and J.P.-O.; visualization, C.D.G.-C. and A.M.-V.; supervision, A.M.G. and J.P.-O.; project administration, A.M.G. and J.P.-O. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University of Murcia (ID: 3495/2021).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the Organic Law 3/2018, of 5 December, on the Protection of Personal Data and Guarantee of Digital Rights of the Government of Spain, which requires that this information must be in custody.

Conflicts of Interest

The authors declare no conflicts of interest.

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Disclaimer/Publisher’s Note: The statements, opinions, and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions, or products referred to in the content.
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Figure 1. Acute fatigue (pre- vs. post-session) in training and match contexts in immunological and oxidative variables. Notes: SIgA: salivary immunoglobulin A; TOS: total oxidant status; TAC: total antioxidant capacity. * indicates statistical significance set at a p-value of ≤ 0.05. Cohen’s d is interpreted by the authors as: * small (d = 0.2 to 0.49), ** medium (d = 0.5 to 0.79), and *** large (d ≥ 0.8).
Figure 1. Acute fatigue (pre- vs. post-session) in training and match contexts in immunological and oxidative variables. Notes: SIgA: salivary immunoglobulin A; TOS: total oxidant status; TAC: total antioxidant capacity. * indicates statistical significance set at a p-value of ≤ 0.05. Cohen’s d is interpreted by the authors as: * small (d = 0.2 to 0.49), ** medium (d = 0.5 to 0.79), and *** large (d ≥ 0.8).
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Figure 2. Immunological and oxidative marker dynamics in four moments throughout the congested fixture period (pre-: pre-match; post-: post-match; 48 h: 48-h after the match; 120 h: 120-h after the match). Notes: SIgA: salivary immunoglobulin A; TOS: total oxidant status; TAC: total antioxidant capacity. α: Statistical differences from the pre-match condition (p < 0.05); β: Statistical differences from the post-match condition (p < 0.05); γ: Statistical differences 48-h after match condition (p < 0.05); δ: Statistical differences 120-h after match condition (p < 0.05).
Figure 2. Immunological and oxidative marker dynamics in four moments throughout the congested fixture period (pre-: pre-match; post-: post-match; 48 h: 48-h after the match; 120 h: 120-h after the match). Notes: SIgA: salivary immunoglobulin A; TOS: total oxidant status; TAC: total antioxidant capacity. α: Statistical differences from the pre-match condition (p < 0.05); β: Statistical differences from the post-match condition (p < 0.05); γ: Statistical differences 48-h after match condition (p < 0.05); δ: Statistical differences 120-h after match condition (p < 0.05).
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Table 1. Training, a match-congested schedule, and saliva sampling during the preseason.
Table 1. Training, a match-congested schedule, and saliva sampling during the preseason.
WeekMondayTuesdayWednesdayThursdayFridaySaturdaySunday
1Session 1Session 2Session 3Session 4Session 5 -
TT//PTTT//PTTT//PTTT//PTTT//PT
2Session 6 Session 7Session 8Session 9Session 10Session 11-
TT//PT
SS1		TT//PTTT//PTTT//PT
SS2		TT
FM
SS3
3Session 12Session 13Session 14Session 15 -Session 16 -
TT//PT
SS4		TT//PTTT//PTTT//PT
SS5		 FM
SS6
4Session 17Session 18 Session 19 Session 20-Session 21 -
FM
SS7		TT//PT
SS8		FM
SS9		TT//PT
SS10		 FM
SS11
Notes: PT = physical training; SS = salivary sample; TT = tactical technical training; FM = friendly match.
Table 2. Independent measures t-test to evaluate the differences in acute effect between training and match contexts.
Table 2. Independent measures t-test to evaluate the differences in acute effect between training and match contexts.
Training
M ± SD		Match
M ± SD		tp-ValueCohen’s d (Effect)
Total Protein0.76 ± 1.040.50 ± 0.971.550.130.15 (trivial)
SIgA63.81 ± 122.46162.73 ± 149.01−1.960.040.77 (moderate)
TAC0.09 ± 4.732.37 ± 5.12−2.84<0.010.47 (low)
TOS−0.85 ± 3.371.37 ± 5.66−2.370.020.49 (low)
TOS/TAC ratio−0.04 ± 0.200.03 ± 0.32−1.180.240.13 (trivial)
Notes: SIgA: salivary immunoglobulin A; TOS: total oxidant status; TAC: total antioxidant capacity. t = t-statistic; p = p-value. Bold indicates statistical significance set at a p-value of ≤0.05. Cohen’s d is interpreted by the authors as (d = 0.2 to 0.49) small, (d = 0.5 to 0.79) medium, and (d ≥ 0.8) large.
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MDPI and ACS Style

Soler-López, A.; Gómez-Carmona, C.D.; Moreno-Villanueva, A.; Gutiérrez, A.M.; Pino-Ortega, J. Effects of Congested Matches and Training Schedules on Salivary Markers in Elite Futsal Players. Appl. Sci. 2024, 14, 4968. https://doi.org/10.3390/app14124968

AMA Style

Soler-López A, Gómez-Carmona CD, Moreno-Villanueva A, Gutiérrez AM, Pino-Ortega J. Effects of Congested Matches and Training Schedules on Salivary Markers in Elite Futsal Players. Applied Sciences. 2024; 14(12):4968. https://doi.org/10.3390/app14124968

Chicago/Turabian Style

Soler-López, Alejandro, Carlos D. Gómez-Carmona, Adrián Moreno-Villanueva, Ana M. Gutiérrez, and José Pino-Ortega. 2024. "Effects of Congested Matches and Training Schedules on Salivary Markers in Elite Futsal Players" Applied Sciences 14, no. 12: 4968. https://doi.org/10.3390/app14124968

APA Style

Soler-López, A., Gómez-Carmona, C. D., Moreno-Villanueva, A., Gutiérrez, A. M., & Pino-Ortega, J. (2024). Effects of Congested Matches and Training Schedules on Salivary Markers in Elite Futsal Players. Applied Sciences, 14(12), 4968. https://doi.org/10.3390/app14124968

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