Monitoring training load, recovery-stress state, immune-endocrine responses, and physical performance in elite female basketball players during a periodized training program

Interrelationships between stress, eating attitudes, and metabolism in endurance athletes across a competitive season

A competitive sport season represents a multidimensional stressor where physical and psychological stress may render an athlete susceptible to energy deficiency (ED). Downstream effects of ED can include a reduction in measured-to-predicted resting metabolic rate (RMRratio), indicating metabolic compensation. A pathway linking stress, eating attitudes, and metabolic compensation has not been explored. To test if sport-specific stress is associated with eating attitudes and metabolism in endurance athletes (18-22 years) at different phases of a competitive season, we assessed two groups of athletes: 26 swimmers (15 female and 11 male) during peak season (PEAK), and 26 runners (female) across pre- (PRE) and off-season (OFF). Stress (RESTQ-52), eating attitudes (cognitive restraint (CR), drive for muscularity (DM), and body dissatisfaction), and metabolism (RMRratio) were assessed. In PRE, sport-specific stress and CR were negatively correlated with RMRratio (R = -0.58; p < 0.05, and R = -0.57; p < 0.05, respectively). In PEAK, sport-specific stress and DM were negatively correlated with RMRratio (R = -0.64; p < 0.05; R = -0.40; p < 0.05, respectively). DM was positively related to sport-specific stress (R = 0.55; p < 0.05). During OFF, there was no relation between RMRratio and sport-specific stress. In runners, there was a change in stress from PRE-to-OFF with highest reported stress during PRE (p < 0.05) versus OFF. Regression analyses revealed that sport-specific stress and CR were significant predictors of RMRratio during PRE and PEAK (p < 0.05), but not OFF (p > 0.05). Associations between stress, eating attitudes, and metabolic compensation in endurance athletes during PRE and PEAK season suggest that during heavier training, metabolic compensation may be linked to upstream eating attitudes associated with sport-stressors.

Training and Game Loads Across Noncongested and Congested Weekly Microcycles During the Regular Season in a Semiprofessional Women's Basketball Team

PURPOSE

To quantify and compare loads encountered in individual training sessions and games during noncongested and congested weeks in semiprofessional women basketball players.

METHODS

Using an observational, longitudinal design, 12 players from the same team had their external (PlayerLoad, relative PlayerLoad, and total and high-intensity inertial movement analysis variables) and internal load (session rating of perceived exertion [sRPE], sRPE-load, percentage of heart rate peak, and modified summated-heart-rate-zones load) monitored across a regular season. Training and game data were categorized into noncongested (0-1 game) and congested weeks (2-3 games). Linear mixed models and Cohen d effect sizes were used for analyses.

RESULTS

Comparisons between training sessions revealed higher (P < .05, d = 1.35-5.33) PlayerLoad, total inertial movement analysis, sRPE, and sRPE-load during training session 1 than training session 2 in congested weeks. Comparisons between training sessions and games revealed higher (P ≤ .001, d = 1.10-1.66) sRPE and sRPE-load during games than training sessions 1 and 2 in noncongested weeks, alongside higher (P ≤ .001, d = 1.87-3.55) sRPE during game 1 than training sessions 1 and 2 in congested weeks. Comparisons between games revealed higher (P < .05, d = 0.57-2.82) loads in game 3 during congested weeks compared with all other games.

CONCLUSIONS

Training appeared to be tapered in congested weeks, likely to account for upcoming increases in game loading, but remained relatively consistent across sessions during noncongested weeks. Individual game loads remained relatively consistent but were noticeably increased when a third game was played in the week.

More than metrics: The role of socio-environmental factors in determining the success of athlete monitoring

The perceived value of athlete monitoring systems (AMS) has recently been questioned. Poor perceptions of AMS are important, because where practitioners lack confidence in monitoring their ability to influence programming, and performance is likely diminished. To address this, researchers have primarily sought to improve factors related to monitoring metrics, e.g., validity rather than socio-environmental factors, e.g., buy-in. Seventy-five practitioners (response rate: n = 30) working with Olympic and Paralympic athletes were invited to take part in a survey about their perceptions of AMS value. Fifty-two per cent (n = 13) was confident in the sensitivity of their athlete self-report measures, but only 64% (n = 16), indicated their monitoring was underpinned by scientific evidence. A scientific base was associated with improved athlete feedback (rS (23) = 0.487, p =0.014*) and feedback correlated with athlete monitoring adherence (rS (22) = 0.675, p =  <0.001**). If athletes did not complete their monitoring, 52% (n = 13) of respondents felt performance might be compromised. However, most respondents 56% (n = 14), had worked with internationally successful athlete(s) who did not complete their monitoring. While AMS can be a useful tool to aid performance optimisation, its potential value is not always realised. Addressing socio-environmental factors alongside metric-factors may improve AMS efficacy.

Recovery in elite youth basketball players: The responsiveness of the psychophysiological measurements and the role of testosterone concentration

This study investigated the recovery responses to the Total Quality Recovery (TQR), Well-Being questionnaire (WBQ), and Heart Rate (HR) responses to Submaximal Running Test (SRT), and the influence of salivary testosterone concentration (TEST) on these responses in 25 elite youth (U15) male basketball players. TQR, WBQ, and HR measurements were assessed after 48 hours of rest (T1), 24 hours after the 1st day of training (T2) and 24 hours after the 2nd day of training (T3). Salivary sampling was conducted at T1 and T3. A significant decrease was observed for TQR (F = 4.06; p = 0.01) and for WBQ (F = 5.37; p = 0.008) from T1 to T3. No difference among the three-time points was observed for HR and HR Recovery, and the TEST concentration did not influence the results. These results show that TQR and WBQ are sensitive to acute transient alterations in training loads (TL) and may be utilized to monitor recovery in elite youth basketball players. The HR related measurements presented limited responsiveness, and the TEST seems not to influence the recovery of these players who are competing at highest performance level.

Weekly Fluctuations in, and Associations Between, Salivary Hormone Responses, Load, and Well-Being During the Pre-season in Professional Male Basketball Players

ABSTRACT

Kamarauskas, P, Scanlan, A, Ferioli, D, and Conte, D. Weekly fluctuations in, and associations between, salivary hormone responses, load, and well-being during the pre-season in professional male basketball players. J Strength Cond Res 38(1): 128-135, 2024-This study aimed to (a) quantify weekly fluctuations in hormonal responses (testosterone [T], cortisol [C], and their ratio [T:C]), external (PlayerLoad [PL] and PL·minute-1) and internal (session rating of perceived exertion load [sRPE-load], summated heart rate zones [SHRZs], and percentage of maximal heart rate [%HRmax]) load measures, and well-being measured using a self-reported questionnaire and (b) determine the associations between weekly changes in hormonal responses and load measures with weekly changes in well-being during the pre-season phase in basketball players. Twenty-one professional male basketball players (age: 26.2 ± 4.9 years) were monitored during a 5-week pre-season phase. Linear mixed models were used to determine weekly differences in each variable and associations between weekly changes in hormonal and load variables with weekly changes in well-being. Findings revealed that T (p < 0.001) and T:C (p = 0.002) increased toward the end of the pre-season phase. Moreover, higher (p < 0.05) external (PL·minute-1) and internal (%HRmax) load intensities were evident during the first 3 weeks of the pre-season, with no significant fluctuations in other load variables. Weekly changes in PL and sRPE-load were negatively associated (p < 0.05) with weekly changes in well-being, albeit weak in magnitudes (R2 = 0.061-0.105). These results highlight that a periodized approach was undertaken across the pre-season predominantly predicated on altering weekly load intensities, which coincided with positive hormonal responses toward the end of the pre-season. In addition, weak relationships were evident between weekly changes in hormonal responses and load measures with well-being, emphasizing that a low commonality may be present between these constructs.

Recovery Methods in Basketball: A Systematic Review

Although different strategies have been implemented to manage recovery-fatigue status in athletes, there is still a lack of consensus on which recovery protocols have the greatest impact and effectiveness when implemented with basketball players, including both physiological and psychological recovery methods. Thus, the purpose of this systematic review is to: (a) determine which recovery methods attain the greatest benefit in restoring the process of attenuating fatigue and (b) provide sports practitioners with guidelines on how some of the most effective recovery strategies can be used to optimize athletes' recovery and ultimately enhance their performance. Using the PRISMA guidelines, a total of 3931 research reports were obtained through four database searches (i.e., PubMed, Scopus, Cochrane, and Web of Science), from which only 25 met the inclusion and exclusion criteria. The recovery protocols analyzed in this systematic review were: sleep, nutrition, hydration, ergogenic aids, cold-water immersion, compression garments, massage, acupuncture, tapering, mindfulness, and red-light irradiation. The results revealed that all recovery strategies are capable of attenuating fatigue and enhancing recovery in basketball players to a certain degree. However, an individualized approach should be promoted, where a combination of proactive recovery modalities appears to result in the most rapid rates of recovery and athletes' ability to maintain high-level performance. Recovery should be programmed as an integral component of training regimens. Also, cooperation and communication between coaches, players, and the rest of the team staff members are essential in minimizing the risk of non-functional overreaching or injury and optimizing basketball players' on-court performance.

Monitoring Internal Load in Women's Basketball via Subjective and Device-Based Methods: A Systematic Review

The monitoring of internal load in basketball can be used to understand the effects and potential physiological adaptations caused by external load. The main aim of this systematic review was to identify the methods and variables used to quantify internal load in female basketball. The studies included different populations and events: youth athletes, elite, and amateur players. Subjective methods included using the rating of perceived exertion (RPE) method, and sensor-based methods included monitoring the cardiac response to exercise, using heart rate (HR) as the primary metric. The results showed that the HRAvg exhibited a wider range of values during training than during competition, and different metrics were used to evaluate internal load, such as HRMax, HRmin, %HRMax, total time and % of time spent in different HR zones (2-8 zones), Banister's TRIMP, and summated HR zones. RPE and HR metrics were the most commonly used methods. However, the use of multiple metrics with little standardization resulted in significant heterogeneity among studies, limiting meaningful comparisons. The review provides a reference for current research on female basketball. Future research could address this limitation by adopting more consistent measurement protocols standardizing the use of metrics.

External and Internal Load Variables Encountered During Training and Games in Female Basketball Players According to Playing Level and Playing Position: A Systematic Review

Background

Despite the growing global participation of females in basketball and number of studies conducted on the topic, no research has summarized the external and internal load variables encountered by female basketball players during training and games.

Objective

To collate existing literature investigating external and internal load variables during training and games in female basketball players according to playing level (club, high-school, representative, collegiate, semi-professional, and professional) and playing position (backcourt and frontcourt players).

Methods

A systematic review of the literature was performed using PubMed, SPORTDiscus, and Web of Science to identify studies published from database inception until June 11, 2021. Studies eligible for inclusion were observational and cross-sectional studies, published in English, reporting external and/or internal load variables during training sessions and/or games. Methodological quality and bias were assessed for each study prior to data extraction using a modified Downs and Black checklist. Weighted means according to playing level and playing position were calculated and compared if a load variable was reported across two or more player samples and were consistent regarding key methodological procedures including the seasonal phase monitored, minimum exposure time set for including player data (playing time during games), approach to measure session duration, and approach to measure session intensity.

Results

The search yielded 5513 studies of which 1541 studies were duplicates. A further 3929 studies were excluded based on title and abstract review, with 11 more studies excluded based on full-text review. Consequently, 32 studies were included in our review. Due to the wide array of methodological approaches utilized across studies for examined variables, comparisons could only be made according to playing level for blood lactate concentration during games, revealing backcourt players experienced higher lactate responses than frontcourt players (5.2 ± 1.9 mmol·L−1 vs. 4.4 ± 1.8 mmol·L−1).

Conclusions

Inconsistencies in the methods utilized to measure common load variables across studies limited our ability to report and compare typical external and internal loads during training and games according to playing level and position in female basketball players. It is essential that standardized methodological approaches are established for including player data as well as measuring session duration (e.g., total time, live time) and intensity (e.g., consistent rating of perceived exertion scales, intensity zone cut points) in future female basketball research to permit meaningful interpretation and comparisons of load monitoring data across studies.

Differences in Weekly Training Load, Well-Being, and Hormonal Responses between European- and National-Level Professional Male Basketball Players during the Pre-Season Phase

This study aimed to compare the weekly fluctuation in training load (sRPE-load), well-being (perceived fatigue, stress, mood, sleep, and muscle soreness), and hormonal responses [testosterone (T) and cortisol (C)] during the pre-season phase in European- and national-level professional male basketball players. Twenty-one professional male basketball players belonging to European-level (n = 11, age: 25.5 ± 3.6 yr; stature: 199.2 ± 7.1 cm; body mass: 94.1 ± 8.5 kg) and national-level (n = 10, age: 23.5 ± 4.7 yr; stature: 198.0 ± 5.6 cm; body mass: 94.0 ± 8.8 kg) teams were monitored during a 5-week pre-season phase. The European-level team showed higher sRPE-load in week 5 compared to week 3 (within-team difference, p = 0.049; ES = -1.44 [-2.38, -0.5], large) and week 1 (p = 0.018; ES = 1.62 [0.64, 2.61], large), week 4 (p = 0.005; ES = 1.79 [0.78, 2.81], large) and week 5 (p = 0.001; ES = 1.96 [0.92, 3.01], large) of the national-level team. The national-level team documented the lowest sRPE-load in week 5, which was statistically different compared to week 2 (p = 0.022; ES = 1.59 [0.61, 2.58], large) and week 4 (p = 0.001; ES = 1.94 [0.9, 2.98], large) of the European-level team. Moreover, higher stress (p < 0.001; ES = 1.94 [0.93, 2.95], large) and better mood (p = 0.003; ES = 1.79 [0.8, 2.78], large) were found in week 1 compared to week 5 within the European-level team. Additionally, higher values of salivary C were found in week 1 for the European-level team compared to week 2 (p = 0.020; ES = 1.6 [0.61, 2.58], large) and week 4 (p = 0.018; ES = 1.66 [0.64, 2.67], large) of the national-level team. Our results can provide reference values for basketball practitioners regarding the fluctuations of weekly load, well-being, and hormones across the pre-season period in professional male teams competing at European and national levels.

Effect of Pre-Season Training on Physiological and Biochemical Indices in Basketball Players—A Systematic Review

The pre-season period in basketball includes all the physiological attributes that the players need to work on and develop, in order to sustain a full season workload. The monitoring of the effectiveness of pre-season training is based on a variety of biochemical and physiological indices; however, it is still unclear how pre-season training affects those markers. Therefore, this study aimed to analyze the effects of pre-season training on biochemical and physiological markers. A search was performed in five large scientific databases (Pubmed (Medline), Scopus, Science-Direct, Sport-Discus (EBSCO), Semantic Scholar) and produced 7081 results, which after removing duplicates and applying inclusion and exclusion criteria, resulted in 28 published scientific articles being included in this review. The most important findings suggested that the majority of the studies used a 6- or an 8-week pre-season training protocol, because these protocols have shown significant positive effects over the years. In addition, the plyometric training protocols that were used by many studies have been found to be beneficial for basketball athletes for many physiological parameters. Furthermore, the evaluation of biochemical markers can be a very useful tool in monitoring and managing fatigue, which is an essential part of modifying the training process, in order to maximize performance.

Physical Persistency across Game Quarters and during Consecutive Games in Elite Junior Basketball Players

Given the intermittent nature of basketball and the different demands that occur during playing time that are specific to every level of competition, the ratio of accelerations/decelerations and the intensity level across quarters were evaluated in female elite junior basketball players (n = 48; age: 16.8 ± 0.7 years; height: 1.76 ± 0.07 cm; body mass: 67.2 ± 6.2 kg). The following variables were analyzed to determine physical persistency across game quarters:(a) total distance covered (m), (b) high-intensity running (HIR) (14–21 km·h⁻¹) distance covered (m), (c) sprint (21–30 km·h⁻¹) distance covered (m), (d) total accelerations (n), (e) total decelerations (n), (f) relative accelerations (n·min⁻¹), (g) relative decelerations (n·min⁻¹), (h) ratio of acceleration/deceleration (A/D), (i) total jumps (j) relative jumps (n·min⁻¹) (k) player load (AU). using the WIMU PRO^® system. Higher but shorter acceleration intensity occurred during the last quarters due to the tight results of the matches. The results suggest that high-intensity efforts such as sprints and HIR seem to increase the A/D ratio (guard and forward positions). Therefore, specific conditioning, as well as eccentric strength training, could be included by practitioners in training programs to improve the performance of these positions during competition, especially as a prior preparation to a game-congested event. Centers seem to have a more variable performance through quarters than do other positions, perhaps highlighting the need for specific conditioning strategies.

Associations between bio-motor ability, endocrine markers and hand-specific anthropometrics in elite female futsal players: a pilot study

BACKGROUND

The second-to-fourth digit ratio (2D:4D) has been calculated for individual athletes and sports, but it has not been investigated in futsal performance. Therefore, the aim of this study was to investigate any relationships between 2D:4D of the dominant and non-dominant hands and physical capacity performances, selected functional variables and hormone concentrations in elite female futsal players.

METHODS

Twenty-four elite female futsal players were measured for 2D:4D in the dominant (2D:4D_D) and non-dominant (2D:4D_ND) hand. The futsal specific performance test (FSPT), hand-grip strength (HGS) and aerobic power were also assessed. In addition, selected circulatory hormones were measured (estradiol, cortisol, growth hormone and insulin like growth factor-1). Pearson's correlation test was used to identify correlational relationships.

RESULTS

Total test-time and performance time (total time + penalty time) for the FSPT showed a significant correlation with 2D:4D_D (r = 0.53, p = 0.005 and r = 0.55, p = 0.003, respectively). HGS_ND also displayed a significant correlation with the 2D:4D_D (r = 0.59, p = 0.002). Aerobic power and time spent running on the treadmill also showed a significant relationship with 2D:4D_ND (both, r = 0.54, p = 0.006). Cortisol showed a significant correlation with 2D:4D_D (- 0.58, p = 0.003) and 2D:4D_ND(- 0.52, p = 0.008).

CONCLUSIONS

The measurement of 2D:4D ratio could be an important factor in determining potential performance attributes and talent identification of elite female futsal players. Further studies are needed in this area to further examine the results presented here.

The underpinning factors of NBA game-play performance: a systematic review (2001-2020)

OBJECTIVE

Recognizing the high stakes associated with winning and losing in the National Basketball Association (NBA), a deep understanding of the underlying mechanisms of NBA game-play performance would provide substantial benefit to all stakeholders involved with preparing NBA players and teams for competitive success. To the best of the authors' knowledge, this systematic review presents the first attempt to systematically amalgamate and appraise the scientific literature published in the XXI Century, following a constraints-led approach (CLA). In particular, two underpinning factors of NBA game-play performance were investigated: (1) NBA player constraints (internal variables) and (2) NBA contextual constraints (external variables).

METHODS

Databases included PubMed (MEDLINE), Web of Science (WOS), ResearchGate, SPORTDiscus, SCOPUS, Google Scholar, and the World Association of Basketball Coaches' database (WABC). This review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) model and the Population, Intervention, Comparison and Outcomes (PICOS) guidelines.

RESULTS

Ultimately, 43 articles met the inclusion criteria (n = 43). Promisingly, the vast majority of studies were published in recent years (>2016; n = 28; 65.1%). Topics related to 'contextual constraints' (n = 25; 58.1%) received more attention than topics related to 'player constraints' (n = 18; 41.9%). Even though the importance of longitudinal-interventional approaches to applied sports science is well-documented, descriptive-observational research emerged as the most popular method of choice (n = 27; 62.8%); interventional studies were absent; and near all researchers merely utilized secondary data sources (n = 37; 86.0%).

CONCLUSIONS

Taking into account the total body of evidence (2001-2020), NBA practitioners may use this systematic review as a baseline reference to enrich their current knowledge about the nature, demands, and dynamics of the modern-day NBA ecosystem. Finally, adoption of an 'Applied Science Research Framework' is encouraged, fostering clearly outlined project incentives; standardizing taxonomies; sequencing follow-up studies; embracing holistic and cross-disciplinary viewpoints; and integrating longitudinal-interventional projects to increase the reproducibility of their findings.

A New Tool for Rapid Assessment of Acute Exercise-Induced Fatigue

Background

There are limited sensitive evaluation methods to distinguish people's symptoms of peripheral fatigue and central fatigue simultaneously. The purpose of this study is to identify and evaluate them after acute exercise with a simple and practical scale.

Methods

The initial scale was built through a literature review, experts and athlete population survey, and a small sample pre-survey. Randomly selected 1,506 students were evaluated with the initial scale after exercise. Subjective fatigue self-assessments (SFSA) were completed at the same time.

Results

The Acute Exercise-Induced Fatigue Scale (AEIFS) was determined after performing a factor analysis. In the exploratory factor analysis, the cumulative variance contribution rate was 65.464%. The factor loadings of the total 8 questions were 0.661-0.816. In the confirmatory factor analysis, χ2/df = 2.529, GFI = 0.985, AGFI = 0.967, NFI = 0.982, IFI = 0.989, CFI = 0.989, and RMSEA = 0.048. The Cronbach's alpha coefficient for the scale was 0.872, and it was 0.833 for peripheral fatigue and 0.818 for central fatigue. The intra-class correlation coefficient for the scale was 0.536, and the intra-class correlation coefficients for peripheral fatigue and central fatigue were 0.421 and 0.548, respectively. The correlation coefficient between the total score of the AEIFS and the SFSA score was 0.592 (p < 0.01).

Conclusion

Our results demonstrate that the AEIFS can distinguish peripheral fatigue and central fatigue and can also reflect their correlation. This scale can be a useful evaluation tool not only for measuring fatigue after acute exercise but also for guiding reasonable exercise, choosing objective testing indicators, and preventing sports injuries resulting from acute exercise-induced fatigue.

Cranial Electrotherapy Stimulation to Improve the Physiology and Psychology Response, Response-Ability, and Sleep Efficiency in Athletes with Poor Sleep Quality

Athletes often have poor sleep quality before a competition. Sleep quality can stabilize mood and improve sports performance. The randomized controlled study explored the effects of cranial electrotherapy stimulation (CES) on the physiology, psychology, response-ability, and sleep quality of athletes who had poor sleep quality before a competition. Athletes who had poor sleep quality (Pittsburgh Sleep Quality Scale score > 5) and had a competition in less than 2 months were recruited. The athletes were grouped into the CES group, which received a 2-week CES treatment (n = 20, age = 21.55 ± 2.26 years), and a placebo group (n = 20, age = 21.05 ± 1.46 years), which received a 2-week sham CES treatment. We performed biochemical analysis, a simple reaction time test, choice reaction time tests, the Profile of Mood States, heart rate variability (HRV), and an Actigraphy activity recorder to measure outcomes before and after the interventions. Our results revealed no significant differences in blood urea nitrogen, creatine phosphate, testosterone, cortisol, and saliva pH between and within groups (p > 0.05). Significant decreases in negative mood states (i.e., anger, tension, and depression) and choice reaction time in the CES group were noted (p < 0.05), moreover, the anger, tension, and depression mood decreased from 0.36 ± 0.45 (95% CI = 0.16–0.55), 1.62 ± 0.97 (95% CI = 1.19–2.04), and 1.67 ± 1.06 (95% CI = 1.20–2.13) to 0.11 ± 0.20 (95% CI = 0.02–0.19, p = 0.03), 1.12 ± 0.74 (95% CI = 0.79–1.44, p = 0.04), and 0.81 ± 0.75 (95% CI = 0.48–1.13, p = 0.001), respectively. Additionally, choice reaction time was decreased from 420.85 ± 41.22 ms (95% CI = 402.78–438.91) to 399.90 ± 36.71 ms (95% CI = 383.81–415.98, p = 0.04) and was also noted in the CES group. For HRV, and Actigraphy activity for sleep measure, the low-frequency (LF)/high-frequency (HF) ratios changed from 1.80 ± 1.39 (95% CI = 1.19–2.40) to 1.21 ± 0.73 (95% CI = 0.89–1.53, p = 0.10), and sleep efficiency decreased from 87.94 ± 6.76% (95% CI = 84.97–90.90) to 81.75 ± 9.62% (95% CI = 77.53–85.96, p = 0.02) in the CES group. The change in LF/HF after the trial were found between CES and placebo groups (p < 0.05). Yet, the decrease in sleep efficiency in the placebo group were noted (p < 0.05). However, we found that the regression line for sleep efficiency was decreased less during the study while using CES. The CES intervention could reduce negative emotions, improve choice reaction times, enhance the parasympathetic and sympathetic nerve activity imbalances, and slow sleep efficiency deterioration. Regardless, small effect sizes of the application of CES on psychology response, response-ability, and sleep efficiency were concluded in athletes with poor sleep quality before a competition.

Internal and External Load Control in Team Sports through a Multivariable Model

Data related to 141 sessions of 10 semi-professional basketball players were analyzed during the competitive period of the 2018-2019 season using a multivariable model to determine possible associations between internal and external load variables and fatigue. Age, height, weight, sessional rate of perceived exertion (sRPE), summated-heart-rate-zones, heart rate variability, total accelerations and decelerations were the covariates, and post-session countermovement jump loss (10% or higher) the response variable. Based on the results observed, a rise in sRPE and accelerations and decelerations could be associated with increased lower-body neuromuscular fatigue. Observing neuromuscular fatigue was 1,008 times higher with each additional sRPE arbitrary unit (AU). Each additional high-intensity effort also increased the probability of significant levels of neuromuscular fatigue by 1,005 times. Fatigue arising from demanding sporting activities is acknowledged as a relevant inciting event leading to injuries. Thus, the methodology used in this study can be used then to monitor neuromuscular fatigue onset, also enhancing proper individual adaptations to training.

Weekly Fluctuations in Salivary Hormone Responses and Their Relationships With Load and Well-Being in Semiprofessional, Male Basketball Players During a Congested In-Season Phase

PURPOSE

To assess weekly fluctuations in hormonal responses and their relationships with load and well-being during a congested in-season phase in basketball players.

METHODS

Ten semiprofessional, male basketball players were monitored during 4 congested in-season phase weeks consisting of 3 weekly matches. Salivary hormone variables (testosterone [T], cortisol [C], and T:C ratio) were measured weekly, and external load (PlayerLoad™ and PlayerLoad per minute), internal load session rating of perceived exertion, percentage of maximum heart rate (HR), summated HR zones, and well-being were assessed for each training session and match.

RESULTS

Significant (P < .05) moderate to large decreases in T were found in the third and fourth weeks compared with the first week. Nonsignificant moderate to large decreases in C were apparent in the last 2 weeks compared with previous weeks. Summated HR zones and perceived sleep significantly (P < .05) decreased in the fourth week compared with the first week; whereas, percentage of maximum HR significantly (P < .05) decreased in the fourth week compared with the second week. No significant relationships were found between weekly changes in hormonal responses and weekly changes in load and overall wellness.

CONCLUSIONS

A congested schedule during the in-season negatively impacted the hormonal responses of players, suggesting that T and C measurements may be useful to detect fluctuations in hormone balance in such scenarios. The nonsignificant relationships between weekly changes in hormonal responses and changes in load and well-being indicate that other factors might induce hormonal changes across congested periods in basketball players.

Training Load Monitoring Considerations for Female Gaelic Team Sports: From Theory to Practice

Athlete monitoring enables sports science practitioners to collect information to determine how athletes respond to training loads (TL) and the demands of competition. To date, recommendations for females are often adapted from their male counterparts. There is currently limited information available on TL monitoring in female Gaelic team sports in Ireland. The collection and analysis of female athlete monitoring data can provide valuable information to support the development of female team sports. Athletic monitoring can also support practitioners to help minimize risk of excessive TL and optimize potential athletic performance. The aims of this narrative review are to provide: (i) an overview of TL athlete monitoring in female team sports, (ii) a discussion of the potential metrics and tools used to monitor external TL and internal TL, (iii) the advantages and disadvantages of TL modalities for use in Gaelic team sports, and (iv) practical considerations on how to monitor TL to aid in the determination of meaningful change with female Gaelic team sports athletes.

Relationship Between Heart Rate Variability and Acute:Chronic Load Ratio Throughout a Season in NCAA D1 Men's Soccer Players

ABSTRACT

Sekiguchi, Y, Huggins, RA, Curtis, RM, Benjamin, CL, Adams, WM, Looney, DP, West, CA, and Casa, DJ. Relationship between heart rate variability and acute:chronic load ratio throughout a season in NCAA D1 men's soccer players. J Strength Cond Res 35(4): 1103-1109, 2021-The purpose of this study was twofold: (a) to examine the relationship between heart rate variability (HRV) and acute:chronic workload ratio (ACWR)-based training load (TL) metrics and (b) to examine relationships across various A:C ratio-based TL metrics. Heart rate variability in 23 male college soccer players (mean ± SD; age, 21 ± 1 years; body mass, 80.3 ± 5.8 kg; height, 181.9 ± 6.5 cm; %body fat, 11.9 ± 2.0%; and V̇o2max, 51.9 ± 5.0 ml·kg-1·min-1) was measured at 5 time points: week(W)1, W3, W7, W12, and W14 during the 2015 NCAA men's soccer season. Heart rate variability was calculated from beat to beat intervals using a heart rate monitor. Players donned a global position satellite-enabled device that measured the following TL metrics: session time (ST), Player Load (PL), PL·min-1, and total distance (TD). Acute:chronic workload ratio was calculated for each TL metric: ACWR-based ST (ACWRST), ACWR-based PL (ACWRPL), ACWR-based PL·min-1 (ACWRPLM), and ACWR-based TD (ACWRTD): ACWR = week average TLs/mo average (30 ± 1 days) TLs. Relationships between HRV and ACWR-based each TL metric were evaluated using mixed effects models. Tukey pairwise comparisons were used to examine differences between types of ACWR-based TL metrics. An increase in ACWRST significantly reduced HRV throughout a season (-7.4 ± 3.6 m·s-1; p = 0.04). There were significant differences between ACWRPLM and ACWRST, ACWRPL and ACWRTD at W1, ACWRPLM and ACWRST at W3 (p < 0.05). In conclusion, ACWRST, ACWRPL, and ACWRTD were significantly different from ACWRPLM. ACWRST was found to significantly predict HRV; higher ACWRST was significantly associated with lower HRV. Therefore, tracking of the ACWR using ST may help to optimize athlete's physiological state throughout a season.

Part I: Relationship among Training Load Management, Salivary Immunoglobulin A, and Upper Respiratory Tract Infection in Team Sport: A Systematic Review

Immunoglobulin A (IgA), which is the first line of defense against upper respiratory tract viruses, has been related with training load management. This article aimed to systematically identify and summarize (1) the studies that have found a relationship between training load and salivary IgA in team sports, and (2) the studies that have highlighted a relationship between IgA and upper respiratory tract infection (URTI) in team sports. A systematic review of relevant articles was carried out using two electronic databases (PubMed and WoK) until 3 October 2020. From a total of 174 studies initially found, 24 were included in the qualitative synthesis. This systematic review confirmed that lower values of IgA occurred after greater training load (intensity/volume) and congested periods. In this scenario, a low level of IgA was correlated with higher URTI, which makes training load management mandatory to healthcare avoiding immunosuppression. Therefore, physical fitness and conditioning coaches should carefully manage training load progression, avoiding high-intensity sessions in two consecutive days. In addition, they should not program high-intensity training sessions during at least the two days following competition.

Monitoring Training Load and Perceived Recovery in Female Basketball: Implications for Training Design

Sansone, P, Tschan, H, Foster, C, and Tessitore, A. Monitoring training load and perceived recovery in female basketball: Implications for training design. J Strength Cond Res 34(10): 2929-2936, 2020-This study investigated the relationship between internal training load and perceived recovery of semi-professional female basketball players during the competitive season. Eleven female players were monitored for 14 weeks during the in-season phase. For each event (training and game), data were collected as follows: (a) Total Quality Recovery (TQR) score before the event (TQRpre); (b) session Rating of Perceived Exertion (sRPE) 20 minutes after completion of the event, to calculate training load (s-TL) of the event; and (c) TQR scores 12 (TQRpost12) and 24 hours (TQRpost24) after the event. Data were analyzed for daily, weekly, and mesocycle (regular season; regional play-off; and national play-off) time frames. Daily analysis showed that: TQRpost12 was lower than TQRpre (p < 0.001) and TQRpost24 (p < 0.001); s-TL had a moderate negative correlation with TQRpost12 (r = -0.48, p = 0.002); the difference between TQRpre and RPE (TS-Δ) had a very large positive correlation with TQRpost12 (r = 0.70, p < 0.001); and TQRpost24 was not significantly correlated with training parameters. Weekly analysis highlighted a very large negative correlation between the acute:chronic workload ratio and TQR collected at the start of the following week (TQRfw) (r = -0.86, p < 0.001). Finally, although weekly TL and TQRfw did not differ between mesocycles, their correlation increased in the later seasonal phases. This study demonstrated negative relationships between training load and recovery of semi-professional female basketball players at daily, weekly, and mesocycle levels. Therefore, concurrently monitoring training and recovery with the sRPE method and TQR scale is recommended for designing training schedules in basketball.

Competitive Recovery-Stress and Mood States in Mexican Youth Athletes

Background

Monitoring recovery–stress balance in sport is becoming more relevant to prevent training maladaptation and reach the optimal performance for each athlete. The use of questionnaires that identify the athlete’s recovery–stress state have much acceptance in sports due to reliability and useful, furthermore for its low cost. Identifying possible differences between sport modalities and sex is important to determine specific needs and possible intervention ways to keep a recovery–stress balance. The aim was to analyze the differences in the recovery–stress state and mood states by sex and sport type during the competitive phase in young Mexican athletes. As a secondary objective, the psychometric properties of the Mexican version of the Recovery–Stress Questionnaire for Athletes (RESTQ-Sport) were analyzed.

Methods

A cross-sectional study was carried on with 461 athletes (61% women and 39% men), 17.95 (±1.2) years old, from six sports disciplines. The RESTQ-Sport and Profile of Mood States (POMS) were applied in a single moment. Differences by sex and sports modality were analyzed. RESTQ-Sport’s confirmatory factor analysis was performed after the stress and recovery theoretical structure of two stress (general and sport) and two recovery (general and sport) dimensions, and last, the concurrent validation with the POMS was carried on.

Results

Significant differences by sex were found in the General Recovery and Sport Stress dimensions of the RESTQ-Sport as well as Vigor factor of the POMS, being higher for men; furthermore, both the Sport Recovery dimension of RESTQ-Sport and Cholera and the Fatigue and Depression factors from POMS also had differences by sport type, showing a less recovery and high stress for individual sport athletes. Goodness-of-fit indexes of the model for the RESTQ-Sport were acceptable. Pearson’s correlation between questionnaires was moderate (p < 0.05).

Conclusion

The recovery–stress state shows differences in the function of sex and sport modality. More special attention is suggested for women and individual sport athletes. The higher punctuation for men compared with women in sport stress dimension did not negatively affect the recovery–stress balance for male athletes. Finally, the Mexican context adaptation of the RESTQ-Sport provides a psychometric instrument suitable to assess the recovery–stress balance in Mexican athletes.

Measuring Physical Demands in Basketball: An Explorative Systematic Review of Practices

BACKGROUND

Measuring the physical work and resultant acute psychobiological responses of basketball can help to better understand and inform physical preparation models and improve overall athlete health and performance. Recent advancements in training load monitoring solutions have coincided with increases in the literature describing the physical demands of basketball, but there are currently no reviews that summarize all the available basketball research. Additionally, a thorough appraisal of the load monitoring methodologies and measures used in basketball is lacking in the current literature. This type of critical analysis would allow for consistent comparison between studies to better understand physical demands across the sport.

OBJECTIVES

The objective of this systematic review was to assess and critically evaluate the methods and technologies used for monitoring physical demands in competitive basketball athletes. We used the term 'training load' to encompass the physical demands of both training and game activities, with the latter assumed to provide a training stimulus as well. This review aimed to critique methodological inconsistencies, establish operational definitions specific to the sport, and make recommendations for basketball training load monitoring practice and reporting within the literature.

METHODS

A systematic review of the literature was performed using EBSCO, PubMed, SCOPUS, and Web of Science to identify studies through March 2020. Electronic databases were searched using terms related to basketball and training load. Records were included if they used a competitive basketball population and incorporated a measure of training load. This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO Registration # CRD42019123603), and approved under the National Basketball Association (NBA) Health Related Research Policy.

RESULTS

Electronic and manual searches identified 122 papers that met the inclusion criteria. These studies reported the physical demands of basketball during training (n = 56), competition (n = 36), and both training and competition (n = 30). Physical demands were quantified with a measure of internal training load (n = 52), external training load (n = 29), or both internal and external measures (n = 41). These studies examined males (n = 76), females (n = 34), both male and female (n = 9), and a combination of youth (i.e. under 18 years, n = 37), adults (i.e. 18 years or older, n = 77), and both adults and youth (n = 4). Inconsistencies related to the reporting of competition level, methodology for recording duration, participant inclusion criteria, and validity of measurement systems were identified as key factors relating to the reporting of physical demands in basketball and summarized for each study.

CONCLUSIONS

This review comprehensively evaluated the current body of literature related to training load monitoring in basketball. Within this literature, there is a clear lack of alignment in applied practices and methodological framework, and with only small data sets and short study periods available at this time, it is not possible to draw definitive conclusions about the true physical demands of basketball. A detailed understanding of modern technologies in basketball is also lacking, and we provide specific guidelines for defining and applying duration measurement methodologies, vetting the validity and reliability of measurement tools, and classifying competition level in basketball to address some of the identified knowledge gaps. Creating alignment in best-practice basketball research methodology, terminology and reporting may lead to a more robust understanding of the physical demands associated with the sport, thereby allowing for exploration of other research areas (e.g. injury, performance), and improved understanding and decision making in applying these methods directly with basketball athletes.

Salivary IgA as a Predictor of Upper Respiratory Tract Infections and Relationship to Training Load in Elite Rugby Union Players

Tiernan, C, Lyons, M, Comyns, T, Nevill, AM, and Warrington, G. Salivary IgA as a predictor of upper respiratory tract infections and relationship to training load in elite rugby union players. J Strength Cond Res 34(3): 782-790, 2020-Upper Respiratory Tract Infections (URTI) are among the most common illnesses reported in athletes. An URTI can result in missed training days, which in turn may lead to performance decrements. The purpose of this study was to investigate the use of salivary immunoglobulin A (sIgA) as a predictor of URTI, while also exploring the relationship to weekly training load in elite rugby union players. Nineteen male elite rugby union players provided morning saliva swabs, biweekly (Monday and Friday), over a 10-week training period. Participants completed an illness log documenting symptoms of URTI. Session Rate of Perceived Exertion (sRPE) was collected to determine training load (sRPE × session duration). Weekly training load was also calculated. Logistic regression was used to analyze the relationship between incidences of URTI with sIgA and training load. Multilevel regression was conducted to compare associations between sIgA and training load. The results found that the likelihood of suffering from an URTI increased when sIgA significantly decreased (p = 0.046). Where sIgA decreased by 65% or more, a player was at a greater risk of contracting an URTI within the following 2 weeks. No association was found between sIgA and training load. In conclusion, sIgA may be a useful predictor for determining the likelihood of players contracting an URTI. This will allow the coach to make informed decisions on training status, helping reduce the risk of players missing training, which may have performance decrements. Coaches will benefit from the fast, easy, and instant results available, to analyze a player's immune function.

Single-Item Self-Report Measures of Team-Sport Athlete Wellbeing and Their Relationship With Training Load: A Systematic Review

BACKGROUND

Single-item athlete self-report measures consist of a single question to assess a dimension of wellbeing. These methods are recommended and frequently used for athlete monitoring, yet their uniformity has not been well assessed, and we have a limited understanding of their relationship with measures of training load.

OBJECTIVE

To investigate the applications and designs of single-item self-report measures used in monitoring team-sport athletes and present the relationship between these measures and measures of training load.

DATA SOURCES

PubMed, Scopus, and SPORTDiscus were searched between inception and March 2019.

STUDY SELECTION

Articles were included if they concerned adult athletes from field- or court-sport domains, if athlete well-being was measured using a single-item self-report, and if the relationship with a measure of modifiable training load was investigated over at least 7 days.

DATA EXTRACTION

Data related to participant characteristics, self-report measures, training load measures, and statistical analysis and outcomes were extracted by 2 authors (C.D. and C.D.).

DATA SYNTHESIS

A total of 21 studies were included in the analysis. A narrative synthesis was conducted. The measures used most frequently were muscle soreness, fatigue, sleep quality, stress, and mood. All measures presented various relationships with metrics of training load from no association to a very large association, and the associations were predominantly trivial to moderate in the studies with the largest numbers of observations. Relationships were largely negative associations.

CONCLUSIONS

The implications of this review should be considered by users in the application and clinical utility of single-item self-report measures in athlete monitoring. Great emphasis has been placed on examining the relationship between subjective and objective measures of training load. Although the relationship is still unclear, such an association may not be expected or useful. Researchers should consider the measurement properties of single-item self-report measures and seek to establish their relationship with clinically meaningful outcomes. As such, further study is required to inform practitioners on the appropriate objective application of data from single-item self-report measures.

Influence of Weekly Workload on Physical, Biochemical and Psychological Characteristics in Professional Rugby Union Players Over a Competitive Season

Dubois, R, Lyons, M, Paillard, T, Maurelli, O, and Prioux, J. Influence of weekly workload on physical, biochemical and psychological characteristics in professional rugby union players over a competitive season. J Strength Cond Res 34(2): 527-545, 2020-This study aimed to (a) quantify the physical workload (P-WL) during training and games throughout the professional rugby season and (b) analyze the influence of the season period and weekly-WL, at short (acute) and moderate (chronic) terms, on physical, biochemical, and psychological responses during the season. Physiological (physical and biochemical) responses to P-WL were analyzed by examining changes in the individual Z score of the Yo-Yo intermittent recovery test (YYIRT), submaximal aerobic tests (5'/5'-test), strength tests, countermovement jump tests, blood sampling, and "recovery-stress" scores (RESTq) in 14 professional players (26.9 ± 1.9 years). Changes throughout the season were analyzed using a linear mixed model to identify changes in P-WL, whereas repeated-measures analysis of variance was used to analyze changes in physiological responses across the season. The relationship between P-WL and physiological responses was analyzed using Pearson's correlation coefficient (r). The results showed that the preseason period comprised the highest level of P-WL compared with all other blocks across the season (p < 0.001). The acute P-WL, acute competitive-WL, and number of impacts seemed to be the WL parameters, which most influenced the physiological responses (changes in testosterone [T], cortisol [C], T/C ratio, IGF-1/C ratio, strength, and RESTq index). The chronic P-WL, particularly conditioning-WL, induced positive changes in fitness characteristics (YYIRT and 5'/5'-test). Finally, this study provides information to players and coaches alike as to the influence of P-WL on as well as adaptations in physiological and psychological indices throughout a playing season. This information can greatly inform the training and preparation of future players in different levels.

Monitoring Workloads of a Professional Female Futsal Team over a Season: A Case Study

The aims of this study were to describe the external and internal workloads in a professional female futsal team during a whole season and to compare workloads during different periods of the season. Ten professional female futsal players (age 22.8 ± 4.3 years; 5.1 ± 2.4 years of experience; weight 61.9 ± 7.1 kg; height 1.66 ± 0.06 m) participated voluntarily in this study during the whole season. The internal workload was measured by the session-Rate of perceived exertion (session-RPE) method, while the external workload was indirectly measured by considering the training and match volume and the type of contents of each session over 43 weeks. Mean sRPE throughout the season was 319.9 ± 127.1 arbitrary units (AU). Higher internal loads (total weekly training load and strain) were reported during the pre-season compared with the in-season mesocycles (p < 0.05); meanwhile, the fifth to eighth mesocycles of the in-season showed an oscillatory pattern. Finally, Monday was the most-demanding session during the in-season period over the Thursday (p < 0.05; effect size: 1.33) followed by match day, meanwhile no statistical differences were reported during different sessions of the pre-season microcycle (p > 0.05). This study suggests that microcycles of pre-season present a stable load pattern, meanwhile workloads during the in-season period report a tapering strategy in a professional female futsal team.

Differences in Weekly Load Distribution Over Two Euroleague Seasons with a Different Head Coach

The weekly training management and competition loads are important aspects to optimize the performance of professional basketball players. The objectives of the study were (a) to describe the weekly external load (EL), as well as the internal response (IR), of elite basketball players over two consecutive seasons with a different head coach and (b) to compare weekly loads of different competitive densities. The data were collected from 27 elite players from the same team competing in the Spanish first division league (ACB) and EuroLeague during 2017–2018 and 2018–2019 seasons. EL was measured using microsensor technology to determine PlayerLoad values, expressed in arbitrary units (AU). Session rating of perceived exertion (sRPE) was used for IR quantification. Comparisons between the two seasons and of weeks with different competitive densities were made. The inter-week load variability was moderate-high for both seasons. The highest EL values were measured during the weeks with three games (W3) (W3 > W0 > W2 > W1), while the most demanding week for players’ IR was observed during weeks with no competition (W0). Additionally, higher EL (d = 0.31) and IR (d = 0.37) values were observed in season 2018–2019 compared to 2017–2018. The results obtained in this study contributed new data on the internal and external load required by professional basketball players in weeks with different number of games and showed that different coaching strategies may demand a different external and internal workload in consecutive seasons. Furthermore, the results highlighted the need to carry out an adequate load management program.

Effects of tapering on neuromuscular and metabolic fitness in team sports: a systematic review and meta-analysis

Purpose: To assess the effects of a taper strategy on neuromuscular and metabolic fitness in team sport athletes, through a systematic review and meta-analysis. Method: To be included in this meta-analysis, studies had to involve competitive team sport athletes and a tapering intervention providing details about the procedures used to decrease the training load, as well as competition or field-based criterion performance and all necessary data to calculate effect sizes. Four databases were searched according to these criteria, which led to the identification of 895 potential studies and the subsequent inclusion of 14 articles. Independent variables were training intensity, volume and frequency, as well as the pattern of taper and its duration. The dependent variable was performance obtained in various neuromuscular and metabolic tests. Results: There was limited evidence of a moderate taper-induced improvement in repeated sprint ability (Standardized Mean Difference (SMD) (95%IC;I²) = 0.41 (0.26-0.55;0%)) and moderate evidence of a moderate increase in maximal power (SMD (95%IC;I²) = 0.44 (0.32-0.56;15%)), change of direction speed (SMD (95%IC;I²) = 0.38 (0.15-0.60;28%)) and maximal oxygen uptake (SMD (95%IC;I²) = 0.76 (0.43-1.09;37%)). Conclusion: Tapering is an effective training strategy to improve maximal power, maximal oxygen uptake, repeated sprint ability and change of direction speed in team sports. However, the literature lacks studies using various tapering strategies to compare their effectiveness and make evidence-based recommendations. Future original studies should focus on this major issue.

Investigating the workload, readiness and physical performance changes during intensified 3-week preparation periods in female national Under18 and Under20 basketball teams

This study aimed to investigate between- and within-team changes in workload [PlayerLoad (PL), training impulse (TRIMP) and session rate of perceived exertion training load (sRPE-TL)], readiness [heart rate variability (HRV)], and physical performance [20-m sprint test (including 10-m split time), countermovement jump (CMJ) and yo-yo intermittent recovery test level 1 (YYIR1)] during 3-week intensified preparation periods in female, national Under18 (n = 12, age = 18.0 ± 0.5y, stature = 180.4 ± 7.5 cm, body mass = 72.7 ± 9.3 kg) and Under20 (n = 12, age = 19.6 ± 0.8y, stature = 178.6 ± 6.4 cm, body mass = 68.0 ± 5.9 kg) basketball teams. Under18 team revealed small-to-moderate statistically significantly higher values in workload [PL: p = 0.010; ES = Small; TRIMP: p = 0.004; ES = Moderate; sRPE-TL: p < 0.001; ES = Moderate] and moderately lower readiness values (p = 0.023; ES = Moderate) compared to Under20. Within-team analysis showed no differences in workload in Under20 and statistically significant reduction (p < 0.05) in Week3 (taper period) in Under18. Pre- and post-preparation changes showed Under18 increasing only YYIR1 performance (p < 0.001; ES = Very large). Differently, Under20 statistically improved in 10-m split time (p = 0.003; ES = Moderate), CMJ (p = 0.025; ES = Moderate) and YYIR1 (p < 0.001; ES = Large). A constant adequate workload positively benefits players' readiness and physical performances during short intensified preparation periods. Conversely, using high workload with periodization strategies encompassing short overload and taper phases induced positive changes on players' aerobic performance, lower readiness values and no changes in anaerobic performances.

Quantification of the Perceived Training Load in Young Female Basketball Players

Otaegi, A and Los Arcos, A. Quantification of the perceived training load in young female basketball players. J Strength Cond Res 34(2): 559-565, 2020-The purposes of this study were (a) to compare training session, match, and weekly perceived training load (TL) between U15 and U16 female basketball players and (b) within the teams, to assess the relationship between perceived TL and the changes in physical fitness performance during an in-season 9-week period. Twenty-one female players from U15 and U16 female teams from the same Spanish club participated in the study. Before and after the study, players were tested to determine physical fitness performance (using Yo-Yo IR1, countermovement jump, T-Test, and 15 m sprint). Each player declared her perceived exertion (PE) for the whole training session and match using Foster's 0-10 scale. Training week perceived TL was higher for the U16 players than the U15 players; U16 players considered the training and matches to be more difficult. In both teams, the perceived TL of the last training session of the week was significantly lower (Effect sizes = large-very large) than the other sessions. Although substantial negative associations (r = 0.52-0.78) were detected between the changes in physical fitness performance and the accumulated volume, sum of PEs and perceived TL in the U15 players, these associations were unclear in the U16 players. The basketball coaches-periodized training goals are to attain the highest session perceived TLs in the middle of the week and to reduce it considerably in the last training session. The U16 and U15 players accumulated perceived TL in different ways. Although the practice volume was similar in both teams, the older players consider the sessions more difficult. The relationship between the perceived TL and the changes in physical fitness performance varied between teams. Based on our findings, we propose that the PE-based dose-response model should be applied with caution in young female basketball players.

Investigation of the Relationship Between Salivary Cortisol, Training Load, and Subjective Markers of Recovery in Elite Rugby Union Players

PURPOSE

Insufficient recovery can lead to a decrease in performance and increase the risk of injury and illness. The aim of this study was to evaluate salivary cortisol as a marker of recovery in elite rugby union players.

METHOD

Over a 10-wk preseason training period, 19 male elite rugby union players provided saliva swabs biweekly (Monday and Friday mornings). Subjective markers of recovery were collected every morning of each training day. Session rating of perceived exertion (sRPE) was taken after every training session, and training load was calculated (sRPE × session duration).

RESULTS

Multilevel analysis found no significant association between salivary cortisol and training load or subjective markers of recovery (all P > .05) over the training period. Compared with baseline (wk 1), Monday salivary cortisol significantly increased in wk 4 (14.94 [7.73] ng/mL; P = .04), wk 8 (16.39 [9.53] ng/mL; P = .01), and wk 9 (15.41 [9.82] ng/mL; P = .02), and Friday salivary cortisol significantly increased in wk 5 (14.81 [8.74] ng/mL; P = .04) and wk 10 (15.36 [11.30] ng/mL; P = .03).

CONCLUSIONS

The significant increase in salivary cortisol on certain Mondays may indicate that players did not physically recover from the previous week of training or match at the weekend. The increased Friday cortisol levels and subjective marker of perceived fatigue indicated increased physiological stress from that week's training. Regular monitoring of salivary cortisol combined with appropriate planning of training load may allow sufficient recovery to optimize training performance.

Heidelberg Risk Sport-Specific Stress Test: A Paradigm to Investigate the Risk Sport-Specific Psycho-Physiological Arousal

In risk sports with medium to high risks of injury (e.g., surfing, free solo climbing, wingsuit flying), athletes frequently find themselves in unexpected and threatening situations. Elevated psycho-physiological stress responses to these situations might have tremendous consequences for their performance as well as for their long-term health. To gain a better understanding of the psycho-physiological response to such events, innovative, externally valid and standardized stress induction protocols are needed. Therefore, the aim of this paper is to introduce and evaluate a risk sport-specific stress protocol, i.e., the Heidelberg Risk Sport-Specific Stress Test (HRSST), which utilizes fear of falling as the stressful event. Climbing novices were asked to climb up a 12 m high wall. Then, participants were requested to “jump into the rope”, leading to a secured fall of about 3 m. This imposed physical danger assumed to elicit psycho-physiological responses. Self-reported state anxiety, salivary cortisol, and heart rate/heart rate variability were measured before, during, and after the HRSST. Results of four independent studies that investigated the psycho-physiological response to the HRSST in 214 participants were analyzed, leading to conclusions about the stressor’s effectiveness. Results showed that self-reported state anxiety consistently increased after the HRSST in all four experiments (moderate to large effects). The results of the physiological indicators were inconclusive. Salivary cortisol significantly increased after the HRSST in one of four experiments (small effect sizes). Although heart rate significantly increased during the “jump in the rope” in experiment 1, heart rate variability significantly decreased after the HRSST in only one of three experiments (small effect sizes). Findings suggest that the HRSST is a valid method to induce risk sport-specific emotional stress, but effects on physiological stress markers were rather minor. To sum up, in case of appropriate sports climbing facilities, the HRSST appears to be a cost-efficient and promising stress induction protocol: It offers the possibility to investigate risk sport-specific stress responses and their underlying mechanisms in climbing novices. These findings may also find application in professions in which individuals are exposed to risky situations, such as police officers, medical first responders, firefighters and military personnel.

Monitoring Workload in Elite Female Basketball Players During the In-Season Phase: Weekly Fluctuations and Effect of Playing Time

PURPOSE

To assess the weekly fluctuations in workload and differences in workload according to playing time in elite female basketball.

METHODS

Twenty-nine female basketball players (mean ± standard deviation, age: 21±5yr; stature: 181±7cm; body mass: 71±7kg; and playing experience: 12±5yr) belonging to the 7 female basketball teams competing in the first division Lithuanian Women's Basketball League (LMKL) were recruited. Individualized training loads (TL) and game loads (GL) were assessed using the session-RPE following each training session and game during the entire in-season phase (24 weeks). Percentage (%) changes in total weekly TL (weekly TL+GL), weekly TL, weekly GL, chronic workload, acute:chronic workload ratio (ACWR), training monotony, and training strain were calculated. Mixed linear models were used to assess differences for each dependent variable, with playing time (low vs high) used as fixed factor and subject, week, and team as random factors.

RESULTS

The highest changes in total weekly TL, weekly TL, and ACWR were evident in week 13 (47%, 120%, and 49% respectively). Chronic workload showed weekly changes ≤10%, while monotony and training strain registered highest fluctuations in weeks 17 (34%) and 15 (59%), respectively. A statistically significant difference in GL was evident between players completing low and high playing times (p=0.026, moderate), while no significant differences (p>0.05) were found for all other dependent variables.

CONCLUSIONS

Coaches of elite female basketball teams should monitor weekly changes in workload during the in-season phase to identify weeks that may predispose players to unwanted spikes and adjust player workload according to playing time.

Training Loads, Wellness and Performance Before and During Tapering for a Water-Polo Tournament

We investigated the effectiveness of a short-duration training period including an overloaded (weeks 1 and 2) and a reduced training load period (weeks 3 and 4) on wellness, swimming performance and a perceived internal training load in eight high-level water-polo players preparing for play-offs. The internal training load was estimated daily using the rating of perceived exertion (RPE) and session duration (session-RPE). Perceived ratings of wellness (fatigue, muscle soreness, sleep quality, stress level and mood) were assessed daily. Swimming performance was evaluated through 400-m and 20-m tests performed before (baseline) and after the end of weeks 2 and 4. In weeks 3 and 4, the internal training load was reduced by 19.0 ± 3.8 and 36.0 ± 4.7%, respectively, compared to week 1 (p = 0.00). Wellness was improved in week 4 (20.4 ± 2.8 AU) compared to week 1 and week 2 by 16.0 ± 2.2 and 17.3 ± 2.9 AU, respectively (p =0.001). At the end of week 4, swimming performance at 400-m and 20-m tests (299.0 ± 10.2 and 10.2 ± 0.3 s) was improved compared to baseline values (301.4 ± 10.9 and 10.4 ± 0.4 s, p < 0.05) and the overloading training period (week 2; 302.9 ± 9.0 and 10.4 ± 0.4 s, p < 0.05). High correlations were observed between the percentage reduction of the internal training load from week 4 to week 1 (-25.3 ± 5.5%) and the respective changes in 20-m time (-2.1 ± 2.2%, r = 0.88, p < 0.01), fatigue perception (39.6 ± 27.1%), muscle soreness (32.5 ± 26.6%), stress levels (25.6 ± 15.1%) and the overall wellness scores (28.6 ± 21.9%, r = 0.74-0.79, p < 0.05). The reduction of the internal training load improved the overall perceived wellness and swimming performance of players. The aforementioned periodization approach may be an effective training strategy in the lead-up to play-off tournaments.

"N-of-1"-Study: A concept of acute and chronic stress research using the example of ballroom dancing

Athletes often report on heightened stress, higher disease susceptibility, and a deterioration in mood and performance throughout periods of high training load and competitions. This paper presents a single-case study combining different research approaches to monitor the dynamic, idiosyncratic responses to competitive stress in elite sports using the example of professional ballroom dancing. Throughout an 8-month period (313 data points), one international-level female dancer provided data on mood, stress, and fatigue. In parallel, she collected saliva samples for the assessment of cortisol (sCort) and alpha-amylase (sAA). A hair strand was collected every 3 months to examine cumulative cortisol secretion. As expected, perceived stress was related to a reduction in well-being. On a daily basis, sCort predicted lower fatigue. In addition, tournaments resulted in a 3-fold and a 2-fold increase in sCort and sAA, respectively, and there was a pronounced drop in hair cortisol in the aftermath of a surgery-related break from dancing. We confirm competitive ballroom dancing to constitute a major stressor with immediate and prolonged consequences for self-reported well-being and biological stress markers. Single-case studies offer much potential for the observation of complex dynamic associations. In a next step, this approach will also become relevant when evaluating the efficacy of preventive and therapeutic interventions on an individual level.

Influence of Different Methods to Determine Maximum Heart Rate on Training Load Outcomes in Basketball Players

Berkelmans, DM, Dalbo, VJ, Fox, JL, Stanton, R, Kean, CO, Giamarelos, KE, Teramoto, M, and Scanlan, AT. Influence of different methods to determine maximum heart rate on training load outcomes in basketball players. J Strength Cond Res 32(11): 3177-3185, 2018-The summated-heart-rate-zones (SHRZ) approach uses heart rate (HR) responses relative to maximum HR (HRmax) to calculate the internal training load (TL). Age-predicted, test-derived, and session-based approaches have all been used to determine HRmax in team sports. The purpose of this study was to determine the effects of using age-predicted, test-derived, and session-based HRmax responses on SHRZ TL in basketball players. Semiprofessional, male basketball players (N = 6) were analyzed during the preparatory training phase. Six age-based approaches were used to predict HRmax including Fox (220 - age); Hossack (206 - [0.567 × age]); Tanaka (208 - [0.7 × age]); Nikolaidis (223 - [1.44 × age]); Nes (211 - [0.64 × age]); and Faff (209.9 - [0.73 × age]). Test-derived HRmax was taken as the highest HR during the Yo-Yo intermittent recovery test (Yo-Yo IRT), whereas session-based HRmax was taken as the higher HR seen during the Yo-Yo IRT or training sessions. Comparisons in SHRZ TL were made at group and individual levels. No significant group differences were evident between SHRZ approaches. Effect size analyses revealed moderate (d = 0.60-0.79) differences between age-predicted, test-derived, and session-based methods across the group and individually in 2 players. The moderate differences between approaches suggest age-predicted, test-derived, and session-based methods to determine HRmax are not interchangeable when calculating SHRZ. Basketball practitioners are encouraged to use individualized HRmax directly measured during field-based tests supplemented with higher HR responses evident during training sessions and games when calculating the SHRZ TL to ensure greatest accuracy.

The effect of block and traditional periodization training models on jump and sprint performance in collegiate basketball players

This study investigated the effect of block periodization (BP) and traditional periodization (TP) approaches on jumping and sprinting performance in collegiate basketball players during an 8-week pre-season period. Ten collegiate male basketball players (mean±SD; age: 21.5±1.7 years; body mass: 83.5±8.9 kg; stature: 192.5±5.4 cm) from the same team were equally assigned to a training group (BP or TP). BP and TP were designed with different numbers of power sessions (BP=8; TP=16) and recovery days (BP=14; TP=8). Counter-movement jump (CMJ) and 20-m sprint performance was measured prior to training commencement (baseline) and every 2 weeks thereafter (week 2, week 4, week 6 and week 8). Within-group, between-group and individual changes were assessed using magnitude-based statistics. Substantially higher (likely positive) CMJ scores were evident in week 8 compared to baseline, week 2 and week 4 with BP training. Substantially higher CMJ values were only observed in week 2 (likely positive) compared to baseline, with TP training. Sprint data showed likely negative differences in week 6 compared to baseline in both TP and BP, with no substantial differences in week 8. The only performance difference between TP and BP training was in CMJ in week 8 (very likely negative). Individual analysis showed that only three athletes demonstrated a negative predicted score (i.e. lower sprinting time) in BP, while all players following the TP model demonstrated positive predicted scores. BP training showed substantially higher jumping performance compared to TP, while no improvement in sprinting performance was observed in either training approach. Basketball coaches should consider using BP training rather than TP to train players' jumping abilities.

The Effect of Training Loads on Performance Measures and Injury Characteristics in Rugby League Players: A Systematic Review

PURPOSE

To conduct a systematic review into the effect of training load (TL) on both performance measures and injury characteristics in rugby league players.

METHODS

Based on PRISMA guidelines, a systematic search of electronic databases was performed from the earliest record to December 2016. Five electronic databases (MEDLINE, SPORTDiscus, CINAHL, Web of Science, and AusSportMed) were searched using keywords within the subcategories of population (rugby league players), intervention (training quantification), and outcomes (performance or injury). Original peer-reviewed published manuscripts were considered if they had a clear quantification of TL (eg, session rating of perceived exertion), clear measures of performance (tests of physiological parameters relative to rugby league players [eg, agility]), and/or injury characteristics (eg, injury incidence).

RESULTS

Twelve studies met the inclusion criteria. The highest TL was observed in preseason training phases. Higher TL elicited greater improvements in maximal aerobic power, vertical jump (in cm), and agility scores (in s). Higher TL was associated with higher incidence of muscular strains and joint sprains, lower-limb injuries, and overexertion and overuse injuries.

CONCLUSIONS

Findings suggest a dose-response relationship between TL, physical performance, and injury characteristics. However, due to study and methodological limitations, the precise nature of this relationship is, as yet, inconclusive. Therefore, the development of uniform TL definition and quantification and further research is warranted.

Heart Rate Monitoring in Basketball: Applications, Player Responses, and Practical Recommendations

Berkelmans, DM, Dalbo, VJ, Kean, CO, Milanović, Z, Stojanović, E, Stojiljković, N, and Scanlan, AT. Heart rate monitoring in basketball: applications, player responses, and practical recommendations. J Strength Cond Res 32(8): 2383-2399, 2018-The aims of this review were to collate the existing literature encompassing heart rate (HR) monitoring in basketball to (a) identify the applications of HR measurement; (b) report HR responses in male and female players during training and game-play; (c) evaluate use of current HR-based training load models; and (d) provide recommendations for future research and best practice approaches for basketball practitioners. Heart rate monitoring in basketball carries 3 primary applications: (a) monitoring exercise intensity; (b) assessing player fatigue status; and (c) quantifying internal training load. When interpreting the available training and game-play HR data in basketball players, key differences have been observed between playing positions and playing levels. Sex- and age-based differences in HR responses during basketball training and game-play are apparent across separate studies; however, further research exploring HR responses in wider player groups is needed, especially in female and junior players. There is also a lack of research directly comparing player HR responses during training and game-play to ascertain the effectiveness of different drills in preparing players for competition. Heart rate-based models have been frequently used to quantify the internal training load in basketball players, including Banister's Training Impulse (TRIMP), Lucia's TRIMP, and Edwards' Summated-Heart-Rate-Zones (SHRZ). The SHRZ model seems to hold practical advantages and better detect changes in player responses across training cycles compared with other approaches. Practical outcomes of this review center on recommendations for position-specific training plans, drills to promote desired cardiovascular stress, analysis of HR outcome measures, and ideal training load monitoring approaches.

Monitoring Training Load and Well-Being During the In-Season Phase in National Collegiate Athletic Association Division I Men's Basketball

PURPOSE

To characterize the weekly training load (TL) and well-being of college basketball players during the in-season phase.

METHODS

Ten (6 guards and 4 forwards) male basketball players (age 20.9 [0.9] y, stature 195.0 [8.2] cm, and body mass 91.3 [11.3] kg) from the same Division I National Collegiate Athletic Association team were recruited to participate in this study. Individualized training and game loads were assessed using the session rating of perceived exertion at the end of each training and game session, and well-being status was collected before each session. Weekly changes (%) in TL, acute-to-chronic workload ratio, and well-being were determined. Differences in TL and well-being between starting and bench players and between 1-game and 2-game weeks were calculated using magnitude-based statistics.

RESULTS

Total weekly TL and acute-to-chronic workload ratio demonstrated high week-to-week variation, with spikes up to 226% and 220%, respectively. Starting players experienced a higher (most likely negative) total weekly TL and similar (unclear) well-being status compared with bench players. Game scheduling influenced TL, with 1-game weeks demonstrating a higher (likely negative) total weekly TL and similar (most likely trivial) well-being status compared with 2-game weeks.

CONCLUSIONS

These findings provide college basketball coaches information to optimize training strategies during the in-season phase. Basketball coaches should concurrently consider the number of weekly games and player status (starting vs bench player) when creating individualized periodization plans, with increases in TL potentially needed in bench players, especially in 2-game weeks.

Perceived training load and jumping responses following nine weeks of a competitive period in young female basketball players

The aims of this study were to describe the session rating of perceived exertion (sRPE), total quality recovery (TQR), and variations in countermovement jump (CMJ) height throughout nine weeks of a competitive period in young female basketball players. In total, 10 young female basketball players (17.2 ± 0.4 years; 71.8 ± 15.0 kg; 177.2 ± 9.5 cm) participated in this study. The sRPE and TQR were assessed in each training session, whereas the CMJ height was assessed prior to the first weekly training session. The magnitude-based inferences method was used to compare the sRPE, TQR, and CMJ height across the nine weeks of training. The training loads accumulated in weeks 1, 2, and 3 were likely to almost certainly be higher than in the following weeks (ES varying from 0.67 to 2.55). The CMJ height in week 1 was very likely to be lower than in weeks 2, 5, 7, and 8 (ES varying from 0.24 to 0.34), while the CMJ height of the 9th week was likely to almost certainly be higher than all previous weeks of training (ES varying from 0.70 to 1.10). Accordingly, it was observed that when higher training loads were accumulated, both CMJ and TQR presented lower values than those presented during periods with lower internal training loads. These results highlight the importance of using a comprehensive and multivariate approach to effectively monitor the physical performance of young athletes.

The Yo-Yo Intermittent Tests: A Systematic Review and Structured Compendium of Test Results

Background: Although Yo-Yo intermittent tests are frequently used in a variety of sports and research studies to determine physical fitness, no structured reference exists for comparison and rating of test results. This systematic review of the most common Yo-Yo tests aimed to provide reference values for test results by statistical aggregation of published data.

Methods: A systematic literature search for articles published until August 2017 was performed in MEDLINE, Web of Science, SPORTDiscus and Google Scholar. Original reports on healthy females and males ≥16 years were eligible for the analysis. Sub-maximal test versions and the Yo-Yo Intermittent Recovery Level 1 Children's test (YYIR1C) were not included.

Results: 248 studies with 9,440 participants were included in the structured analysis. The Yo-Yo test types most frequently used were the Yo-Yo Intermittent Recovery Level 1 (YYIR1, 57.7%), the Yo-Yo Intermittent Recovery Level 2 (YYIR2, 28.0%), the Yo-Yo Intermittent Endurance Level 2 (YYIE2, 11.4%), and the Yo-Yo Intermittent Endurance Level 1 (YYIE1, 2.9%) test. For each separate test, reference values (global means and percentiles) for sports at different levels and both genders were calculated.

Conclusions: Our analysis provides evidence that Yo-Yo intermittent tests reference values differ with respect to the type and level of sport performed.The presented results may be used by practitioners, trainers and athletes to rate Yo-Yo intermittent test performance levels and monitor training effects.

An Integrated, Multifactorial Approach to Periodization for Optimal Performance in Individual and Team Sports

Sports periodization has traditionally focused on the exercise aspect of athletic preparation, while neglecting the integration of other elements that can impact an athlete's readiness for peak competition performances. Integrated periodization allows the coordinated inclusion of multiple training components best suited for a given training phase into an athlete's program. The aim of this article is to review the available evidence underpinning integrated periodization, focusing on exercise training, recovery, nutrition, psychological skills, and skill acquisition as key factors by which athletic preparation can be periodized. The periodization of heat and altitude adaptation, body composition, and physical therapy is also considered. Despite recent criticism, various methods of exercise training periodization can contribute to performance enhancement in a variety of elite individual and team sports, such as soccer. In the latter, both physical and strategic periodization are useful tools for managing the heavy travel schedule, fatigue, and injuries that occur throughout a competitive season. Recovery interventions should be periodized (ie, withheld or emphasized) to influence acute and chronic training adaptation and performance. Nutrient intake and timing in relation to exercise and as part of the periodization of an athlete's training and competition calendar can also promote physiological adaptations and performance capacity. Psychological skills are a central component of athletic performance, and their periodization should cater to each athlete's individual needs and the needs of the team. Skill acquisition can also be integrated into an athlete's periodized training program to make a significant contribution to competition performance.

A Review of Player Monitoring Approaches in Basketball: Current Trends and Future Directions

Fox, JL, Scanlan, AT, and Stanton, R. A review of player monitoring approaches in basketball: current trends and future directions. J Strength Cond Res 31(7): 2021-2029, 2017-Effective monitoring of players in team sports such as basketball requires an understanding of the external demands and internal responses, as they relate to training phases and competition. Monitoring of external demands and internal responses allows coaching staff to determine the dose-response associated with the imposed training load (TL), and subsequently, if players are adequately prepared for competition. This review discusses measures reported in the literature for monitoring the external demands and internal responses of basketball players during training and competition. The external demands of training and competition were primarily monitored using time-motion analysis, with limited use of microtechnology being reported. Internal responses during training were typically measured using hematological markers, heart rate, various TL models, and perceptual responses such as rating of perceived exertion (RPE). Heart rate was the most commonly reported indicator of internal responses during competition with limited reporting of hematological markers or RPE. These findings show a large discrepancy between the reporting of external and internal measures and training and competition demands. Microsensors, however, may be a practical and convenient method of player monitoring in basketball to overcome the limitations associated with current approaches while allowing for external demands and internal responses to be recorded simultaneously. The triaxial accelerometers of microsensors seem well suited for basketball and warrant validation to definitively determine their place in the monitoring of basketball players. Coaching staff should make use of this technology by tracking individual player responses across the annual plan and using real-time monitoring to minimize factors such as fatigue and injury risk.

Effects of a Tapering Period on Physical Condition in Soccer Players

Beltran-Valls, MR, Camarero-López, G, Beltran-Garrido, JV, and Cecilia-Gallego, P. Effects of a tapering period on physical condition in soccer players. J Strength Cond Res 34(4): 1086-1092, 2020-The aim of this research was to analyze the effects of a 2-week step tapering period on lower-limb muscle power, change of direction (COD) and acceleration capacities, and on the stress-recovery state in an amateur soccer team. Twenty-two male players were included in the study. After a 6-week progressive training, the sample was divided into experimental group (EG) (n = 11), which did a 2-week period of taper in which training volume was 50% reduced (intensity was kept high) and control group (CG) (n = 11), which kept on with the training. Muscle power (countermovement jump test), acceleration (10-m sprint test), COD (Illinois test), and stress and recovery perceptions (RESTQ questionnaire) were evaluated before training, at the end of it (pretapering, PRE-TP) and after the tapering period (posttapering, POST-TP). After the taper, the EG in comparison with the CG showed significantly improved power (1,029.71 ± 108.51 W·kg vs. 1,084.21 ± 110.87 W·kg; p ≤ 0.01), acceleration (1.72 ± 0.09 seconds vs. 1.67 ± 0.07 seconds; p ≤ 0.05), and lower stress levels (1.9 ± 0.5 vs. 1.6 ± 0.5; p ≤ 0.01) (PRE-TP vs. POST-TP, respectively). Change of direction did not show significant changes. In conclusion, a 2-week step tapering program was found to be an effective periodization strategy to increase muscle power and acceleration, and to reduce stress perception in soccer amateur players.

Monitoring Training Loads in Professional Basketball Players Engaged in a Periodized Training Program

Aoki, MS, Ronda, LT, Marcelino, PR, Drago, G, Carling, C, Bradley, PS, and Moreira, A. Monitoring training loads in professional basketball players engaged in a periodized training program. J Strength Cond Res 31(2): 348-358, 2017-The aim of this study was to investigate the dynamics of external training load (eTL) and internal training load (iTL) during seasonal periods, and examine the effect of a periodized training program on physical performance in professional basketball players. Repeated measures for 9 players (28 ± 6 years; 199 ± 8 cm; 101 ± 12 kg) were collected from 45 training sessions, over a 6-week preseason phase and a 5-week in-season phase. Physical tests were conducted at baseline (T1), week 4 (T2), and week 9 (T3). Differences in means are presented as % ± confident limits. A very likely difference was observed during in-season compared with preseason for the eTL variables (measured by multivariable monitoring device), mechanical load (13.5 ± 8.8) and peak acceleration (11.0 ± 11.2), respectively. Regarding iTL responses, a very large decrement in TRIMP (most likely difference, -20.6 ± 3.8) and in session rating of perceived exertion training load (very likely difference, -14.2 ± 9.0) was detected from preseason to in-season. Physical performance improved from T1 to T3 for Yo-Yo intermittent recovery test 1 (62.2 ± 34.3, effect size [ES] > 1.2); countermovement jump (8.8 ± 6.1, ES > 0.6); and squat jump (14.8 ± 10.2, ES > 0.8). Heart rate (HR; %HRpeak) exercise responses during a submaximal running test decreased from T1 to T3 (3.2 ± 4.3, ES < 0.6), as well as the HR recovery after the test (14.7 ± 8.8, ES > 1.2). These results provide valuable information to coaches about training loads and physical performance across different seasonal periods. The data demonstrate that both eTL and iTL measures should be monitored in association with physical tests, to provide a comprehensive understanding of the training process.