Psychophysiological Stress Markers During Preseason Among Elite Female Soccer Players

Prevalence of Specific Mood Profile Clusters among Elite and Youth Athletes at a Brazilian Sports Club

Those responsible for elite and youth athletes are increasingly aware of the need to balance the quest for superior performance with the need to protect the physical and psychological wellbeing of athletes. As a result, regular assessment of risks to mental health is a common feature in sports organisations. In the present study, the Brazil Mood Scale (BRAMS) was administered to 898 athletes (387 female, 511 male, age range: 12-44 years) at a leading sports club in Rio de Janeiro using either "past week" or "right now" response timeframes. Using seeded k-means cluster analysis, six distinct mood profile clusters were identified, referred to as the iceberg, surface, submerged, shark fin, inverse iceberg, and inverse Everest profiles. The latter three profiles, which are associated with varying degrees of increased risk to mental health, were reported by 238 athletes (26.5%). The prevalence of these three mood clusters varied according to the response timeframe (past week > right now) and the sex of the athletes (female > male). The prevalence of the iceberg profile varied by athlete sex (male > female), and age (12-17 years > 18+ years). Findings supported use of the BRAMS as a screening tool for the risk of psychological issues among athletes in Brazilian sports organisations.

Effects of a Preseason Neuromuscular Training Program vs. an Endurance-Dominated Program on Physical Fitness and Injury Prevention in Female Soccer Players

BACKGROUND

The pre-season preparatory period is considered key for optimizing the physical fitness levels needed to withstand congested match periods and preventing injuries during the regular soccer season. This study contrasted the effects s of neuromuscular training (NMT) versus an endurance-dominated training (ET) program conducted during the preseason on measures of physical fitness and injury occurrence in female soccer players.

METHODS

Twenty-four female soccer players aged 17.0 ± 1.3 years from a professional soccer club participated in this study. Players were randomly assigned to NMT (n = 12) or ET (n = 12) groups according to their playing position. The preseason intervention program lasted six weeks, with three weekly sessions with a duration of 45-60 min per session. Exercises in the NMT group included muscle strengthening exercises, plyometrics, agility and dynamic stability exercises, while the ET group practiced a traditional pre-season training program consisting of running and sprinting exercises, fartlek, and high-intensity interval training. The training volumes were similar in the two study groups. Anthropometric measurements, physical fitness tests (i.e., linear and change-of-direction speed, muscle strength and power tests) and the overall injury rate per 1000 h of exposure (training, match) were recorded throughout the season.

RESULTS

No between group differences were found at pre (T1). Significant group-by-time interactions were observed for the 5, 10, and 30-m linear sprint speed tests (p < 0.001, 2.16 < d < 2.58), the T-test (p = 0.024, d = 1.03), the squat (p < 0.001, d = 4.04), and the countermovement jump test (p < 0.001, d = 2.21), the Loughborough soccer passing test (LSPT) (p = 0.019, d = 1.08), and the 1-RM back squat test (p < 0.001, d = 2.53). Post-hoc tests indicated that NMT provided larger improvements for SJ, CMJ, 1-RM back squat, the 5-m sprint, 10-m sprint, 30-m sprint, T-test and LSPT compared to ET (1.07 > d > 2.77). The injury rate across the season was significantly lower in the NMT (5.1/1000 h exposure) compared to ET (11.8/1000 h exposure) (p = 0.014).

CONCLUSIONS

The findings support that six-weeks of preseason NMT versus ET induced larger performance improvements, and significantly reduced injury occurrence in elite female soccer players.

Can a Psychologic Profile Predict Successful Return to Full Duty After a Musculoskeletal Injury?

BACKGROUND

Psychologic variables have been shown to have a strong relationship with recovery from injury and return to work or sports. The extent to which psychologic variables predict successful return to work in military settings is unknown.

QUESTIONS/PURPOSES

In a population of active duty soldiers, (1) can a psychologic profile determine the risk of injury after return to full duty? (2) Do psychologic profiles differ between soldiers sustaining injuries in the spine (thoracic or lumbar) and those with injuries to the lower extremities?

METHODS

Psychologic variables were assessed in soldiers returning to full, unrestricted duty after a recent musculoskeletal injury. Most of these were noncombat injuries from work-related physical activity. Between February 2016 and September 2017, 480 service members who were cleared to return to duty after musculoskeletal injuries (excluding those with high-velocity collisions, pregnancy, or amputation) were enrolled in a study that tracked subsequent injuries over the following year. Of those, we considered individuals with complete 12-month follow-up data as potentially eligible for analysis. Based on that, approximately 2% (8 of 480) were excluded because they did not complete baseline surveys, approximately 2% (11 of 480) were separated from the military during the follow-up period and had incomplete injury data, 1% (3 of 480) were excluded for not serving in the Army branch of the military, and approximately 2% (8 of 480) were excluded because they were not cleared to return to full duty. This resulted in 450 soldiers analyzed. Individuals were 86% (385 of 450) men; 74% (331 of 450) had lower extremity injuries and 26% (119 of 450) had spinal injuries, including soft tissue aches and pains (for example, strains and sprains), fractures, and disc herniations. Time-loss injury within 1 year was the primary outcome. While creating and validating a new prediction model using only psychological variables, 19 variables were assessed for nonlinearity, further factor selection was performed through elastic net, and models were internally validated through 2000 bootstrap iterations. Performance was deciphered through calibration, discrimination (area under the curve [AUC]), R 2 , and calibration in the large. Calibration assesses predicted versus actual risk by plotting the x and y intersection of these values; the more similar predicted risk values are to actual ones, the closer the slope of the line formed by the intersection points of all subjects is to equaling "1" (optimal calibration). Likewise, perfect discrimination (predicted injured versus actual injured) presents as an AUC of 1. Perfect calibration in the large would equal 0 because it represents the average predicted risk versus the actual outcome rate. Sensitivity analyses stratified groups by prior injury region (thoracic or lumbar spine and lower extremity) as well as the severity of injury by days of limited duty (moderate [7-27 days] and severe [28 + days]).

RESULTS

A model comprising primarily psychologic variables including depression, anxiety, kinesiophobia, fear avoidance beliefs, and mood did not adequately determine the risk of subsequent injury. The derived logistic prediction model had 18 variables: R 2 = 0.03, calibration = 0.63 (95% confidence interval [CI] 0.30 to 0.97), AUC = 0.62 (95% CI 0.52 to 0.72), and calibration in the large = -0.17. Baseline psychologic profiles between body regions differed only for depression severity (mean difference 1 [95% CI 0 to 1]; p = 0.04), with greater mean scores for spine injuries than for lower extremity injuries. Performance was poor for those with prior spine injuries compared with those with lower extremity injuries (AUC 0.50 [95% CI 0.42 to 0.58] and 0.63 [95% CI 0.57 to 0.69], respectively) and moderate versus severe injury during the 1-year follow-up (AUC 0.61 [95% CI 0.51 to 0.71] versus 0.64 [95% CI 0.64 to 0.74], respectively).

CONCLUSION

The psychologically based model poorly predicted subsequent injury. This study does not minimize the value of assessing the psychologic profiles of injured athletes, but rather suggests that models looking to identify injury risk should consider a multifactorial approach that also includes other nonpsychologic factors such as injury history. Future studies should refine the most important psychologic constructs that can add the most value and precision to multifactorial models aimed at identifying the risk of injury.

LEVEL OF EVIDENCE

Level III, prognostic study.

Physiological, anthropometric and athletic performance adaptations from completing a 1-month pre-season period. A two-year longitudinal study in female collegiate soccer players

Introduction

Collegiate coaches and integrative support staff often utilize pre-season as a brief and intense training period to prepare athletes technically, tactically, and physiologically, to meet the demands of competition during a soccer season. This study sought to examine the dose-response from performing on-field soccer activities during a four-week pre-season period in female collegiate soccer players, and if the magnitude in response was associated with accumulated exercise stress.

Methods

A total of twenty-seven healthy female soccer players training as part of a collegiate soccer program volunteered to participate in this two-year longitudinal study. Data collection commenced prior to the start of each pre-season period, at the beginning of August, and was completed at the beginning of September, when pre-season ended. Data collection periods were separated by a 31-day period. Indices of cardiovascular function, anthropometry, and athletic performance were examined during each data collection period. Internal and external measures of accumulated exercise stress were recorded using the Polar Team Pro® system.

Results

When comparing the beginning to the end of pre-season, significant improvements were observed in body fat (%) [24.2 ± 6.0 "vs." 23.3 ± 5.6, p = 0.001], heart rate variability (rMSSD) [51.8 ± 25.1 "vs." 67.9 ± 34.6 ms, p = 0.002], resting heart (bpm) [73.8 ± 12.1 "vs." 64.3 ± 8.8, p = 0.001] and cardiorespiratory performance (YoYo IRTL-1) [925.8 ± 272.8 "vs." 1,062.6 ± 223.3 m, p = 0.001]. Significant reductions in musculoskeletal performance were observed through vertical jump height (cm) [24.9 ± 23.7, p = 0.04]. Change in the end of pre-season body weight (kg) was significantly associated with accumulated accelerations and decelerations [r ≥ 0.49, p = 0.01]. End of pre-season change in cardiorespiratory performance was significantly associated with both accumulated training load (au) and TRIMP (au) [r ≥ 0.63, p = 0.01].

Discussion

In conclusion, performing a four-week pre-season period, involving only on-field training, can promote positive and significant adaptations in anthropometry, cardiovascular function, and athletic performance measures in female collegiate soccer players. The magnitudes of these adaptations were associated with both internal and external measures of accumulated exercise stress.

Effects of 8 weeks pre-season training on physical fitness, heart rate variability and cognition in women soccer players

The aim of this study was to explore the variations (pre-post) of (i) Anthropometric measures: weight, body mass index, lean and muscle mass, (ii) Physical fitness: countermovement jump (CMJ) and VO2max, (iii) heart rate variability (HRV) (recumbent and sitting): mean RR, RMSSD, NN50 and NN50 %, (iv) Psychomotor Vigilance Task, and v) SART: ACC Go, ACC NoGo and reaction times in semi-professional women soccer players from the second division of the Spanish League. The analysis indicated that lean mass improved after the observation period (p = .05, d = -0.38), while no other significant changes in anthropometric measures were observed. Additionally, CMJ and aerobic power were also improved (p<.01, d>0.50). The RMSSD [recumbent (d = -0.73) and sitting (d = -0.52)] and NN50 [recumbent (d = -0.69) and sitting (d = -0.70)] increased after the period of observation (p < .05). Reaction time also significantly improved after the period of observation [PVT (d = 0.42) and SART (d = -0.89)]. Correlations performed between measures revealed that smaller body mass and body mass index were largely associated with greater NN50 (r < 0.83, p = .001). Additionally, greater CMJ and aerobic fitness were associated with greater HRV [recumbent (r = -51, p = .001) and sitting (r = -0.60, p = .01). The main findings of this study were that there was no relationship between cognitive performance and physical fitness, but HRV was related to body composition and physical fitness during the pre-season in women soccer players.

Monitoring mood state to improve performance in soccer players: A brief review

Introduction

Psychological aspects of sport are key in maintaining athlete motivation and make a difference in competitive outcomes. Adjustments to training may be necessary according to athletes' emotional state. Therefore, it is important to assess and quantify mood states throughout the season in team sports, including among soccer players. The Profile of Mood States (POMS) is a widely used questionnaire that assesses emotional states characterized by positive or negative feelings and can be administered repeatedly to assess changes in mood state. This review aims to assess and summarize the current literature on mood state variation in soccer players with a specific focus on training loads, training modalities, and competitive performance.

Methods

A literature search was systematically conducted and resulted in 156 records. After removing duplicates, items with irrelevant titles and abstracts were screened out, and full texts were then screened for relevance and compared with inclusion and exclusion criteria. The remaining 37 articles were included in the final qualitative synthesis.

Results

POMS scores were related to variability in training load, intensity of the training period, modality of training exercises, competitive performance and time of day in soccer players. Common recommendations include monitoring the mood state of soccer players during training sessions, matches, and throughout training periods to detect early signs of psychological disturbance and aid in optimizing high-level training performance.

Conclusion

The POMS allows for monitoring of players' psychological state, providing coaches with data to aid in adjusting acute program variables according to players' psychological states and improve performance. Results offer practical support for the use of a simple POMS measurement as part of an overall program to monitor the players' psychological states. Results also highlight how training choices (i.e., load and exercise modality) and competitive performance are related to mood states (i.e., tension, anger, confusion, depression, fatigue, and vigor).

Biomarkers of post-match recovery in semi-professional and professional football (soccer)

High-level football (soccer) players face intense physical demands that result in acute and residual fatigue, impairing their physical performance in subsequent matches. Further, top-class players are frequently exposed to match-congested periods where sufficient recovery times are not achievable. To evaluate training and recovery strategies, the monitoring of players' recovery profiles is crucial. Along with performance and neuro-mechanical impairments, match-induced fatigue causes metabolic disturbances denoted by changes in chemical analytes that can be quantified in different body fluids such as blood, saliva, and urine, thus acting as biomarkers. The monitoring of these molecules might supplement performance, neuromuscular and cognitive measurements to guide coaches and trainers during the recovery period. The present narrative review aims to comprehensively review the scientific literature on biomarkers of post-match recovery in semi-professional and professional football players as well as provide an outlook on the role that metabolomic studies might play in this field of research. Overall, no single gold-standard biomarker of match-induced fatigue exists, and a range of metabolites are available to assess different aspects of post-match recovery. The use of biomarker panels might be suitable to simultaneously monitoring these broad physiological processes, yet further research on fluctuations of different analytes throughout post-match recovery is warranted. Although important efforts have been made to address the high interindividual heterogeneity of available markers, limitations inherent to these markers might compromise the information they provide to guide recovery protocols. Further research on metabolomics might benefit from evaluating the long-term recovery period from a high-level football match to shed light upon new biomarkers of post-match recovery.

Effect of Intensified Training Camp on Psychometric Status, Mood State, and Hematological Markers in Youth Soccer Players

During training camps, training load is purposefully intensified. Intensified training loads (TL) are associated with psychological variations, increased fatigue, insufficient recovery, decreased muscular performance, and biological changes in adult athletes, but whether these changes occur during training camps in youth athletes has not been established. The aim of this study was to assess changes in psychometric status, vertical jump performance (i.e., height), and hematological markers before and after an intensive training camp in youth soccer players. In this case, 15male youth soccer players (mean ± SD: age: 14.8 ± 0.4 years; height: 172.0 ± 6.9 cm, body mass: 60.8 ± 7.9 kg; training experience: 5.2 ± 0.7 years) completed a 2-week training program consisting of 1 week of moderate TL (MT) and 1 week of intensive training camp (TC). Rate of perceived exertion (RPE), TL, monotony, strain, and psychometric status (total quality of recovery (TQR) and well-being indices (sleep, stress, fatigue, and muscle soreness) were monitored before each first daily training session across two weeks. The profile of mood states (POMS), countermovement jump (CMJ) height, and blood markers (complete blood count, urea, and creatinine) were assessed before and after TC. TL (d = 5.39, large), monotony (d = 3.03, large), strain (d = 4.38, large), and well-being index (d = 7.5, large) scores increased and TQR (d = 4.6, large) decreased during TC. The TC increased tension, fatigue, and total mood disturbance and decreased vigor (all p <0.01). CMJ performance p < 0.01, d = 0.52, moderate), creatinine (p < 0.01, d = 1.29, large), and leukocyte concentration (p < 0.01, d = 1.4, large) and granulocyte concentration (p < 0.01, d = 1.93, large) increased after TC. Percentage of lymphocytes (p < 0.05, d = 1.17, large) and monocytes (p < 0.01, d = 1.05, large) decreased while the percentage of granulocytes (p < 0.05, d = 0.86, large) increased significantly. Well-being, quality of recovery, mood, granulocyte concentration, and creatinine were all altered during the week-long intensified training camp. These results may provide coaches with valuable information about psychometric status and physiological fatigue and recovery of youth soccer players to better prescribe and adjust training loads during intensive training periods.

Relationships between Fitness Status and Blood Biomarkers in Professional Soccer Players

Background

Physical conditions are recognized to be optimal after the pre-season (PS) phase in professional sports. Given that blood measures may also reveal variations, which in turn, may present associations with fitness changes.

Objective

The aim of this study is to test the changes of blood markers and physical fitness outcomes at the beginning and following the PS phase. Additionally, we aimed also to analyze the associations of training adaptations between blood markers and the physical fitness measures. Methodology. 25 professional male soccer players (28.1 ± 4.6 years old, 2.0 ± 7.8 kg, and 176.7 ± 4.9 cm) were assessed for hematological and biochemical parameters, and physical fitness measures in the baseline and after the phase of PS.

Results

Increases in platelets were observed after the PS phase (p = 0.001, η2 = 0.39). Regarding the biochemical parameters, significant increases between PS were found for creatinine (Cre) (p = 0.001, η2 = 0.66), alkaline phosphatase (ALP) (p = 0.001, η2 = 0.79), C-Reactive Protein (CRP) (p = 0.001, η2 = 0.74), cortisol (C) (p = 0.001, η2 = 0.63), and testosterone (T) (p = 0.001, η2 = 0.76), whereas significant decreases were found for albumin (Alb) (p = 0.004, η2 = 0.29), and calcium corrected (Ca Corr.) (p = 0.002, η2 = 0.32). Moderate correlations were found between albumin and the 5-meter linear sprint split (r = -0.44 (95%CI: -0.71; -0.05)) and CRP (r = -0.48 (95%CI: -0.74; -0.10)). Moderate correlations were found between VAMEVAL and hemoglobin (r = 0.44 (95%CI: 0.05; 0.71)).

Conclusions

The overall physical fitness measures improved after the PS phase. Also, significant variations (decreases/increases) were observed for the case of biomchemical and hematological outcomes. Coaches should carefully consider the adaptative changes observed in blood parameters as the changes in whole organism and metabolism after specific critical phases as the PS in professional players. Thus, optimal management of stimulus/recovery can be warranted to minimize illness and injury rate and to follow the direction and dynamics of adaptative changes.

Blood Biomarkers Variations across the Pre-Season and Interactions with Training Load: A Study in Professional Soccer Players

Background: Pre-season training in soccer can induce changes in biological markers in the circulation. However, relationships between chosen hematological and biochemical blood parameters and training load have not been measured. Objective: Analyze the blood measures changes and their relationships with training loads changes after pre-season training. Methodology: Twenty-five professional soccer players were assessed by training load measures (derived from rate of perceived exertion- known as RPE) during the pre-season period. Additionally, blood samples were collected for hematological and biochemical analyses. Results: For hematological parameters, significant increases were found for platelets (PLT) (dif: 6.42; p = 0.006; d = -0.36), while significant decreases were found for absolute neutrophils count (ANC) (dif: -3.98; p = 0.006; d = 0.11), and absolute monocytes count (AMC) (dif: -16.98; p = 0.001; d = 0.78) after the pre-season period. For biochemical parameters, there were significant increases in creatinine (dif: 5.15; p = 0.001; d = -0.46), alkaline phosphatase (ALP) (dif: 12.55; p = 0.001; d = -0.84), C-reactive protein (CRP) (dif: 15.15; p = 0.001; d = -0.67), cortisol (dif: 2.85; p = 0.001; d = -0.28), and testosterone (dif: 5.38; p = 0.001; d = -0.52), whereas there were significant decreases in calcium (dif: -1.31; p = 0.007; d =0.49) and calcium corrected (dif: -2.18; p = 0.015; d = 0.82) after the pre-season period. Moreover, the Hooper Index (dif: 13.22; p = 0.01; d = 0.78), and all derived RPE measures increased after pre-season period. Moderate-to-very large positive and negative correlations (r range: 0.50-0.73) were found between the training load and hematological measures percentage of changes. Moderate-to-large positive and negative correlations (r range: 0.50-0.60) were found between training load and biochemical measures percentage of changes. Conclusions: The results indicated heavy physical loads during the pre-season, leading to a decrease in immune functions. Given the significant relationships between blood and training load measures, monitoring hematological and biochemical measures allow coaches to minimize injury risk, overreaching, and overtraining.