Sleep duration is associated with overnight changes in perceived fatigue in elite women soccer players.

The current study aimed to describe sleep habits and analyze the associations between sleep indices, changes in perceived fatigue (Δ Fatigue) and external training load measures in women soccer players during a 7-day training camp. Sixteen elite women soccer players (age: 25.4 ± 3.6 years; mean ± SD) from the Portuguese Women's National Team participated in the study. Sleep indices (sleep duration and efficiency) were measured using a wrist-worn accelerometer. External training loads measures were measured using GPS devices. Players also reported perceived fatigue using a Likert scale (1 - very, very low to 7 - very, very high) before and immediately after sleep. Players' within-subject coefficient of variation for sleep duration was 5.6%, and 4.6% for sleep efficiency. Individually, 8 players (50%) slept less than 7 h per night throughout the training camp, and the same number of athletes had a sleep efficiency lower than 85%. Similar values (p<0.05) were measured for sleep duration and efficiency between training and match days. A moderate negative within-subjects correlation was found between Δ Fatigue and sleep duration (adjusted for pre-sleep fatigue) [r = -0.32; 95% Confidence Interval (-0.51 - -0.08); p = 0.04]. These findings reinforce the importance of sleep in the recovery process of elite women soccer players, showing that more sleep may help to attenuate fatigue.

Predicting Injuries in Football Based on Data Collected from GPS-Based Wearable Sensors.

The growing intensity and frequency of matches in professional football leagues are related to the increasing physical player load. An incorrect training model results in over- or undertraining, which is related to a raised probability of an injury. This research focuses on predicting non-contact lower body injuries coming from over- or undertraining. The purpose of this analysis was to create decision-making models based on data collected during both training and match, which will enable the preparation of a tool to model the load and report the increased risk of injury for a given player in the upcoming microcycle. For this purpose, three decision-making methods were implemented. Rule-based and fuzzy rule-based methods were prepared based on expert understanding. As a machine learning baseline XGBoost algorithm was considered. Taking into account the dataset used containing parameters related to the external load of the player, it is possible to predict the risk of injury with a certain precision, depending on the method used. The most promising results were achieved by the machine learning method XGBoost algorithm (Precision 92.4%, Recall 96.5%, and F1-score 94.4%).

Effect of High-Volume Training on Psychological State and Performance in Competitive Swimmers.

This study aimed to examine the effect of four weeks of aquatic high-volume training (HVT) on the psychological state (somatic, cognitive anxiety, and self-confidence) and sprint swimming performance (50 m front crawl) compared to the standard training program (moderate volume training) in competitive swimmers. Twenty-eight male competitive swimmers participated in this study and were randomly allocated into two groups: HVT group (n = 14; age = 16.4 ± 0.31 years) and control group that underwent the standard training program (n = 14; age = 16.1 ± 0.30 years). All psychological state variables and swimming performance were measured in pre and post-test. Our findings showed a significant increase in anxiety state (34.13% to 45.83%; ES = 3.26 to 3.38) and a significant decrease in self-confidence (18.43%; ES = 2.39) after four weeks of HVT, while all psychological state variables remained unchanged in the control group (p > 0.05). In addition, our results showed no significant enhancement in swimming performance in both groups (p > 0.05). The sudden increase in training mileage negatively affected the anxiety, decreasing the state of self-confidence of the participants. In addition, four weeks of high training volume are insufficient to improve swimming performance. To conclude, gradually increasing the volume of the training load may be an adequate solution to promote adaptation to the effort, thus maintaining the stability of the psychological state of swimmers. In addition, it is recommended to integrate a concurrent mental preparation program with high-volume training to monitor the psychological state of competitive swimmers.

Comparison of Measurements of External Load between Professional Soccer Players.

Background: The excessive and rapid increases in training load (TL) may be responsible for most non-contact injuries in soccer. This study's aims were to describe, week(w)-by-week, the acute (AW), chronic (CW), acute:chronic workload ratio (wACWR), total distance (wTD), duration training (wDT), sprint total distance (wSTD), repeat sprint (wRS), and maximum speed (wMS) between starter and non-starter professional soccer players based on different periods (i.e., pre-, early-, mid-, and end-season) of a full-season (Persian Gulf Pro League, 2019−2020). Methods: Nineteen players were divided according to their starting status: starters (n = 10) or non-starters (n = 9). External workload was monitored for 43 weeks: pre- from w1−w4; early- from w5−w17; mid- from w18−w30, and end-season from w31−w43. Results: In starters, AW, CW, and wACWR were greater than non-starters (p < 0.05) throughout the periods of early- (CW, p ≤ 0.0001), mid- (AW, p = 0.008; CW, p ≤ 0.0001; wACWR, p = 0.043), or end-season (AW, p = 0.035; CW, p = 0.017; wACWR, p = 0.010). Starters had a greater wTD (p ≤ 0.0001), wSTD (p ≤ 0.0001 to 0.003), wDT (p ≤ 0.0001 to 0.023), wRS (p ≤ 0.0001 to 0.018), and wMS (p ≤ 0.0001) than non-starters during early-, mid-, and end-season. Conclusion: Starters experienced more CW and AW during the season than non-starters, which underlines the need to design tailored training programs accounting for the differences between playing status.

Internal Training Load Perceived by Athletes and Planned by Coaches: A Systematic Review and Meta-Analysis.

BACKGROUND: Rating of perceived exertion (RPE) and session RPE (sRPE) has been widely used to verify the internal load in athletes. Understanding the agreement between the training load prescribed by coaches and that perceived by athletes is a topic of great interest in sport science. OBJECTIVE: This systematic review and meta-analysis aimed to investigate differences between the training/competition load perceived by athletes and prescribed/intended/observed by coaches. METHODS: A literature search (September 2020 and updated in November 2021) was conducted using PubMed, Web of Science, Embase, and SPORTDiscus databases. The protocol was registered in the Open Science Framework (osf.io/wna4x). Studies should include athletes and coaches of any sex, age, or level of experience. The studies should present outcomes related to the RPE or sRPE for any scale considering overall training/competition sessions (physical, strength, tactical, technical, games) and/or classified into three effort categories: easy, moderate, and hard. RESULTS: Twenty-seven studies were included in the meta-analysis. No difference was found between coaches and athletes for overall RPE (SMD = 0.19, P = 0.10) and overall sRPE (SMD = 0.05, P = 0.75). There was a difference for easy RPE (SMD = - 0.44, small effect size, P = 0.04) and easy sRPE (SMD = - 0.54, moderate effect size, P = 0.04). No differences were found for moderate RPE (SMD = 0.05, P = 0.74) and hard RPE (SMD = 0.41, P = 0.18). No difference was found for moderate (SMD = -0.15, P = 0.56) and hard (SMD = 0.20, P = 0.43) sRPE. CONCLUSION: There is an agreement between coaches and athletes about overall RPE and sRPE, and RPE and sRPE into two effort categories (moderate and hard). However, there were disagreements in RPE and sRPE for easy effort category. Thus, despite a small disagreement, the use of these tools seems to be adequate for training monitoring.

Influence of contextual factors on physical demands and technical-tactical actions regarding playing position in professional soccer players.

BACKGROUND: The aim of this study was to analyse the physical demands and technical-tactical actions for each playing position according to game location and final outcome in professional soccer players. METHODS: A convenience sample was obtained from twenty-one professional male soccer players, belonged to same soccer team of the Spanish Second Division. Players' physical demands were monitored during each match using a portable 18 Hz GPS unit and 600 Hz triaxial accelerometer. These analysed demands were total distance, moderate speed running distance (>14.4 km·h-1), high-speed running distance (>19.8. km·h-1), sprint distance (>25.0 km·h-1), number of accelerations between 2 and 4 m·s-2 and above 4 m·s-2, and number of decelerations between 2 and 4 m·s-2 and above 4 m·s-2. The data related to technical-tactical actions were obtained from WyScout®, a computerized multiple-camera tracking system based on the OPTA® track analysis tool. The obtained indicators were general, defensive and offensive. RESULTS: For all players, higher total distance (p = 0.045; effect size [ES] = 0.24, small effect) was covered and greater deceleration 2-4 m·ss-2 (p = 0.001; ES = 0.68, medium effect) was performed when the team plays at home and lose and for all players, playing at home and winning demanded higher defensive volume (p =0.014; ES = - 1.49, large effect) and nº interceptions (p =0.031; ES = - 1.40, large effect) in comparison to playing at home and losing. CONCLUSIONS: The physical demands and technical-tactical actions vary when contextual game factors (i.e., match location and final outcome) are considered. We can confirm that, although the training of physical demands does not influence the final result of the match, the training of technical tactical actions could help to achieve an optimal performance of the team to win matches.

What Is the Optimal Strength Training Load to Improve Swimming Performance? A Randomized Trial of Male Competitive Swimmers.

This study aimed to compare the effectiveness of high, moderate, and low resistance training volume-load of maximum strength training on muscle strength and swimming performance in competitive swimmers. Thirty-three male swimmers were randomly allocated to high (age = 16.5 ± 0.30 years), moderate (age = 16.1 ± 0.32 years) and a low resistance training volume-load group (age = 15.9 ± 0.31). This study was carried out in mid-season (January to March). Pre and post strength (e.g., repetition maximum [1RM] leg extension and bench press tests), swimming (25, 50 m front-crawl), start (speed, time, distance) and turn (time of turn) performance tests were conducted. Our findings revealed a large main effect of time for 1RM bench press: d = 1.38; 1RM leg extension: d = 1.55, and for 25 (d = 1.12), and 50 m (d = 1.97) front-crawl, similarly for start and turn performance (d = 1.28-1.46). However, no significant Group × Time interactions were shown in all strength swimming performances, start and turn tests (p > 0.05). In conclusion, low training loads have been shown to elicit the same results as moderate, and high training loads protocol. Therefore, this study shows evidence that the addition of low training volume-loads as a regular part of a maximal strength training regime will elicit improvements in strength and swimming performance.

Wearable Inertial Measurement Unit to Accelerometer-Based Training Monotony and Strain during a Soccer Season: A within-Group Study for Starters and Non-Starters.

The purpose of this study was to analyze the intragroup differences in weekly training monotony (TM) and training strain (TS) between starter and non-starter male professional soccer players at accelerometry based variables throughout the periods of a season. TM and TS of different accelerations and decelerations zones for twenty-one players were followed for forty-eight weeks. Regardless of group, players obtained the highest mean TM (starters = 3.3 ± 0.6, non-starters = 2.2 ± 1.1, in arbitrary unit, AU) and TS (starters = 1288.9 ± 265.2, non-starters = 765.4 ± 547.5, AU) scores in the pre-season for accelerations at Zone 1 (<2 m/s2). The results also indicated that both groups exhibited similar TM and TS scores in accelerations at Zones 2 (2 to 4 m/s2) and 3 (>4 m/s2) across the entire season. While the starters showed the highest TM and TS scores at deceleration Zone 1 (<-2 m/s2) in the end-season, the non-starters exhibited the highest scores at the deceleration Zone 1 in pre-season. It seems that in pre-season, coaches applied higher levels of training with greater emphasis on deceleration for non-starters. This tendency was reduced over time for non-starters, while starters presented higher values of deceleration Zone 1. These results highlight the variations in TM and TS across the different periods of a full season according to match starting status among professional soccer players, and the results suggest that non-starter players should receive higher levels of load to compensate for non-participation in matches throughout a soccer season.

Understanding Player Load: Meanings and Limitations.

We present a critical reflection on the mechanical variable Player Load, which is based on acceleration data and commonly used in sports. Our motivation to write this paper came from the difficulties that we encountered in the calculation and interpretation of Player Load using our own data, since we did not use the Catapult Sports equipment, which is a merchandise of the company that proposed this variable. We reviewed existing literature in order to understand Player Load better; we found many inconsistencies in PL calculation methods and in the meanings attached to it. Accordingly, this paper presents a brief discussion on the meanings that have been assigned to Player Load, its limitations, and the lack of clear and complete information about Player Load calculation methods. Moreover, the use of arbitrary units and different practical meanings in the literature has associated Player Load with many physical quantities, thereby resulting in difficulties in determining what Player Load measures within the context of sports. It seems that Player Load is related to the magnitude of changes in acceleration, but not the magnitude of acceleration itself. Therefore, coaches and sports scientists should take this information into account when they use Player Load to prescribe and monitor external loads. We concluded that a deeper discussion of Player Load as a descriptor of external load is warranted in the sports sciences literature.

Internal and External Demands in Basketball Referees during the U-16 European Women's Championship.

(1) Background: The use of advanced technology to study the energy demands of sport participants during actual sport competition is an important current research direction. The purpose of this study was to identify the physiological, internal, and external demands placed on basketball referees using ultra-wideband (UWB) technology, in relation to the period of the game. (2) Methods: The sample was comprised of nine international referees, and the data collection took place during the Women's EuroBasket Sub-16 championship. Internal and external load were assessed through the inertial device WIMU PROTM, using UWB technology in order to quantify the effort exerted by each referee. The internal load was examined in relation to each individual's heart rate (HR). The external load included the kinematic variables accelerations (Acc), decelerations (Dec), Acc/min, Dec/min, distance covered, steps, maximum speed (Vmax), average speed (Vavg), and speed zones, as well as the neuromuscular variables impacts (Imp), PlayerLoadTM (PLTM), PLTM/min, Metabolic Power (PMet), and PMet/min. (3) Results: The results exposed that referees work around 62% HRmax and spend more than 80% of the match at intensities between 0-12 km/h. The first period was the period in which the greatest work demand was experienced in relation to these neuromuscular outcomes (11.92 PL; 3.61 Met; 277 Impacts). The results revealed a diminishment of internal and external demands on the referees over the course of the game. (4) Conclusions: The results highlight the importance of monitoring and quantifying the workload of basketball officials, because doing so would allow for the establishment of individualized performance profiles that could be designed with the purpose of benefiting referee performance during games. The use of inertial devices allows for the objective quantification of referee workload under competitive circumstances.

Comparative Study of Two Intervention Programmes for Teaching Soccer to School-Age Students.

The objective of this study was to design and analyse the differences and/or similarities of two homogeneous intervention programmes (didactic units) based on two different teaching methods, Direct Instruction (DI) and Tactical Games Approach (TGA), for teaching school-age soccer. The sample was composed of 58 tasks, 29 for each intervention programme. The pedagogical and external Training Load (eTL) variables recorded in the Integral System for Training Tasks Analysis (SIATE) were studied. The two intervention programmes were compared using Chi-Square, Mann-Whitney U and the Adjusted Standardized Residuals statistical tests. Likewise, the strength of association of the variables under study was calculated using Cramer's Phi and Cramer's V coefficients. Both intervention programmes had the same number of tasks (n = 29), sessions (n = 12), game phases (x² = 0.000; p = 1.000), specific contents (x² = 5.311; p = 0.968) and didactic objectives, as well as different levels of eTL (U = 145.000; p = 0.000; d = 1.357); which are necessary requirements to be considered similar. The differences and/or similarities between both intervention programmes will offer teachers guidelines to develop different didactic units using the specific DI and TGA methodologies.

Relationships Between Model-Predicted and Actual Match-Play Exercise-Intensity Performance in Professional Australian Footballers During a Preseason Training Macrocycle.

PURPOSE: To assess and compare the validity of internal and external Australian football (AF) training-load measures for predicting preseason variation of match-play exercise intensity (MEI sim/min) using a variable dose-response model. METHODS: A total of 21 professional male AF players completed an 18-wk preseason macrocycle. Preseason internal training load was quntified using the session rating-of-perceived-exertion method (sRPE) and external load from satellite (as distance [Dist] and high-speed distance [HS Dist]) and accelerometer (Player Load [PL]) data. Using a training-impulse (TRIMPs) calculation, external load expressed in arbitrary units was represented as TRIMPsDist, TRIMPsHSDist, and TRIMPsPL. Preseason training load and MEI sim/min data were applied to a variable dose-response model, which provided estimates of MEI sim/min. Model estimates of MEI sim/min were correlated with actual measures from each match-play drill performed during the preseason macrocycle. Magnitude-based inferences (effect size [90% confidence interval]) were calculated to determine practical differences in the precision of MEI sim/min estimates using each of the internal- and external-load inputs. RESULTS: Estimates of MEI sim/min demonstrated very large and large associations with actual MEI sim/min with models constructed from external and internal training inputs (r [90% confidence interval]; TRIMPsDist .73 [.72-.74], TRIMPsPL .72 [.71-.73], and sRPESkills .67 [.56-.78]). There were trivial differences in the precision of MEI sim/min estimates between models constructed from TRIMPsDist and TRIMPsPL and between internal input methods. CONCLUSIONS: Variable dose-response models from multiple training-load inputs can predict the within-individual variation of MEI sim/min across an entire preseason macrocycle. Models informed by external training inputs (TRIMPsDist and TRIMPsPL) exhibited predictive power comparable to those of sRPESkills models.

Relationships Between Model Estimates and Actual Match-Performance Indices in Professional Australian Footballers During an In-Season Macrocycle.

PURPOSE: To assess and compare the validity of internal and external Australian football (AF) training-load measures for predicting match exercise intensity (MEI/min) and player-rank score (PRScore) using a variable dose-response model. METHODS: A cohort of 25 professional AF players (23 ± 3 y, 188.3 ± 7.2 cm, 87.7 ± 8.4 kg) completed a 24-wk in-season macrocycle. In-season internal training and match load were quantified using session rating of perceived exertion (sRPE) and external load from satellite and accelerometer data. Using a training-impulse (TRIMP) calculation, external load (au) was represented as distance (TRIMPDist), distance ≥4.16 m/s (TRIMPHSDist), and PlayerLoad (TRIMPPL). In-season training load, MEI/min, and PRScore were applied to a variable dose-response model, which provided estimates of MEI/min and PRScore. Predicted MEI/min and PRScore were correlated with actual measures from each match. The magnitude of the difference between MEI/min and PRScore estimates for each model input and the difference between the precision of internal and external load measures to predict MEI/min and PRScore were calculated using the effect size ± 90% confidence interval (CI). RESULTS: Estimates of MEI/min demonstrated very large associations with actual MEI/min (r, 90% CI) (eg, TRIMPDist .76 ± .13, and sRPESkills .73 ± .14). Estimates of PRScore demonstrated associations of large magnitude with actual PRScore using the same inputs. Precision of actual MEI/min was lowest using sRPE compared with (ES ± 90% CI) TRIMPDist, -.67 ± .34, and TRIMPPL, -.91 ± .39. There were trivial and unclear differences in the precision of PRScore estimates between TRIMP and sRPE inputs. CONCLUSIONS: Dose-response models from multiple training-load inputs can predict within-individual variation of MEI/min and PRScore. Internal and external training-input methods exhibited comparable predictive power.

Sex difference in the heat shock response to high external load resistance training in older humans.

BACKGROUND: Literature reports on the effects of resistance training on heat shock protein70 (Hsp70) adaptation in older subjects are scarce. Moreover, the optimum training load required to obtain a beneficial adaptation profile is lacking. Therefore, the aim of this study was to determine the effects of resistance training at various external loads on extracellular Hsp70 (eHsp70) resting levels in older humans. METHODS: Fifty-six community-dwelling older (68±5years) volunteers were randomized to 12weeks of resistance training (3×/week) at either high-resistance (HIGH, 8 males, 10 females, 2×10-15 repetitions at 80% 1RM), low resistance (LOW, 9 Males, 10 Females, 1×80-100 repetitions at 20% 1RM), or mixed low resistance (LOW+, 9 Males, 10 Females, 1×60 repetitions at 20% 1RM followed by 1×10-20 repetitions at 40% 1RM). Serum was available from 48 out of the 56 participants at baseline and after 12weeks for determination of eHsp70. Mid-thigh muscle volume (computed tomography), muscle strength (1RM & Biodex dynamometer) and physical functioning (including 6min walk distance [6MWD]) were assessed. RESULTS: There was a sex-related dichotomy in the heat shock response to high external load training. We observed a significant decrease in eHsp70 concentration in the HIGH group for female, but not male, subjects. At baseline, men had a larger muscle volume, leg press and leg extension 1RM compared to women (all p<0.001). Also, the 6MWD was significantly higher in men compared to women at baseline. However, this difference disappeared when correcting for height. Moreover, the overall functional performance and physical activity scores were similar in men and women. None of the participants' characteristics nor any of the outcome variables differed between groups at baseline. There was a significant increase in the strength and physical performance parameters in both men and women post-exercise (all p<0.05). Females in the HIGH group clearly demonstrated a larger gain in leg press 1RM and the isometric knee extensor strength compared to females in the LOW group (p=0.036 and p=0.044, respectively). More so, we found an inverse association between the change in eHsp70 levels and improvement in isometric knee extensor strength and 6MWD (r=-0.443, p=0.002 and r=-0.428, p=0.002; respectively) post exercise. CONCLUSIONS: Our results show that resistance training at high external load decreases the resting levels of eHsp70 in older females. Whether this reflects a better health status requires further investigation.

Monitoring Training Loads: The Past, the Present, and the Future.

Training monitoring is about keeping track of what athletes accomplish in training, for the purpose of improving the interaction between coach and athlete. Over history there have been several basic schemes of training monitoring. In the earliest days training monitoring was about observing the athlete during standard workouts. However, difficulty in standardizing the conditions of training made this process unreliable. With the advent of interval training, monitoring became more systematic. However, imprecision in the measurement of heart rate (HR) evolved interval training toward index workouts, where the main monitored parameter was average time required to complete index workouts. These measures of training load focused on the external training load, what the athlete could actually do. With the advent of interest from the scientific community, the development of the concept of metabolic thresholds and the possibility of trackside measurement of HR, lactate, VO2, and power output, there was greater interest in the internal training load, allowing better titration of training loads in athletes of differing ability. These methods show much promise but often require laboratory testing for calibration and tend to produce too much information, in too slow a time frame, to be optimally useful to coaches. The advent of the TRIMP concept by Banister suggested a strategy to combine intensity and duration elements of training into a single index concept, training load. Although the original TRIMP concept was mathematically complex, the development of the session RPE and similar low-tech methods has demonstrated a way to evaluate training load, along with derived variables, in a simple, responsive way. Recently, there has been interest in using wearable sensors to provide high-resolution data of the external training load. These methods are promising, but problems relative to information overload and turnaround time to coaches remain to be solved.

Pre-training perceived wellness impacts training output in Australian football players.

The impact of perceived wellness on a range of external load parameters, rating of perceived exertion (RPE) and external load:RPE ratios, was explored during skill-based training in Australian footballers. Fifteen training sessions involving 36 participants were analysed. Each morning before any physical training, players completed a customised perceived wellness questionnaire (sleep quality, fatigue, stress, mood and muscle soreness). Microtechnology devices provided external load (average speed, high-speed running distance, player load and player load slow). Players provided RPE using the modified Borg category-ratio 10 RPE scale. Mixed-effect linear models revealed significant effects of wellness Z-score on player load and player load slow. Effects are reported with 95% confidence limits. A wellness Z-score of -1 corresponded to a -4.9 ± 3.1 and -8.6 ± 3.9% reduction in player load and player load slow, respectively, compared to those without reduced wellness. Small significant effects were also seen in the average speed:RPE and player load slow:RPE models. A wellness Z-score of -1 corresponded to a 0.43 ± 0.38 m·min(-1) and -0.02 ± 0.01 au·min(-1) change in the average speed:RPE and player load slow:RPE ratios, respectively. Magnitude-based analysis revealed that the practical size of the effect of a pre-training perceived wellness Z-score of -1 would have on player load slow was likely negative. The results of this study suggests that monitoring pre-training perceived wellness may provide coaches with information about the intensity of output that can be expected from individual players during a training session.

Characteristics impacting on session rating of perceived exertion training load in Australian footballers.

The relationship between external training load and session rating of perceived exertion (s-RPE) training load and the impact that playing experience, playing position and 2-km time-trial performance had on s-RPE training load were explored. From 39 Australian Football players, 6.9 ± 4.6 training sessions were analysed, resulting in 270 samples. Microtechnology devices provided external training load (distance, average speed, high-speed running distance, player load (PL) and player loadslow (PLslow)). The external training load measures had moderate to very large associations (r, 95% CI) with s-RPE training load, average speed (0.45, 0.35-0.54), high-speed running distance (0.51, 0.42-0.59), PLslow (0.80, 0.75-0.84), PL (0.86, 0.83-0.89) and distance (0.88, 0.85-0.90). Differences were described using effect sizes (d ±95% CL). When controlling for external training load, the 4- to 5-year players had higher s-RPE training load than the 0- to 1- (0.44 ± 0.33) and 2- to 3-year players (0.51 ± 0.30), ruckmen had moderately higher s-RPE training load than midfielders (0.82 ± 0.58), and there was a 0.2% increase in s-RPE training load per 1 s increase in time-trial (95% CI: 0.07-0.34). Experience, position and time-trial performance impacted the relationship between external training load and s-RPE training load. This suggests that a given external training load may result in different internal responses between athletes, potentially leaving individuals at risk of overtraining or failing to elicit positive adaptation. It is therefore vital that coaches and trainers give consideration to these mediators of s-RPE training load.

Monitoramento do treinamento no judô: comparação entre a intensidade da carga planejada pelo técnico e a intensidade percebida pelo atleta / Training load monitoring in judo: comparison between the training load intensity planned by the coach and the intensity experienced by the athlete

O objetivo do presente estudo foi comparar a percepção referente à intensidade da carga de treinamento planejada pelos técnicos com a percepção de intensidade reportada pelos atletas de Judô. A amostra foi composta por quatro técnicos e 40 atletas da Seleção Brasileira de Judô. A comparação entre a intensidade planejada e a intensidade experienciada foi realizada através da aplicação do método da percepção subjetiva do esforço (PSE) da sessão durante um training camp. Também foram realizadas coletas de sangue para determinação da concentração de lactato sanguíneo. A intensidade da carga de treinamento reportada pelos atletas superou a intensidade planejada pelos técnicos em todas sessões de treinamento. Com relação à concentração de lactato, houve aumento no período pós-treino em todas as sessões do training camp, não havendo diferença entre as sessões. Os resultados do presente estudo demonstram que, embora o programa de treinamento tenha sido elaborado por técnicos experientes, foi detectada diferença entre a intensidade da carga externa planejada pelo técnico e a intensidade da carga interna percebida pelos atletas. Estes dados reforçam a importância do constante monitoramento do treinamento, a fim de maximizar o desempenho de atletas de elite.

The aim of this study was to compare the perception concerning of the training load intensity of Judo coaches and athletes. The sample consisted of 4 coaches and 40 athletes of the Brazilian National Judo Team. The comparison between the intensity planned by the coach and the intensity experienced by the athletes was determined by the Session RPE method during a "Training camp". In order to assess lactate responses to training, blood samples were collected pre- and post training session. The intensity experienced by athletes was higher than the intensity planned by coaches in all training sessions. Regarding lactate concentration, it was observed an increase at post-training as compared to pre-training in all sessions, with no differences between sessions. The results of this study demonstrate that although the training session has been developed by experienced coaches, significant differences were detected between the intensity of external training load planned by the coach and the intensity of the internal training load experienced by the athletes. These data reinforce the relevance of training monitoring in order to maximize performance of elite athletes.