Follow-Up Weekly Training Distribution and Accumulated Internal Load Effects on Young Football Players' Well-Being, Physical Fitness, and Technical Performance.

This study aimed to quantify the relationships among internal training load, wellness, physiological, isokinetic profile, and technical performance and assessed changes before and after a six-week pre-season structured combining physical fitness, small-sided-game and skill-based training program in young soccer players. Forty-five national-level young male soccer players (16.8 ± 0.9 years) were evaluated. There were no significant correlations between the wellness index and the physiological, isokinetic, or specific soccer skill parameters. Moderate correlations were observed between fatigue and stress (r = 0.47, moderate, p < 0.01), fatigue and average muscle soreness (r = 0.38, moderate, p = 0.01), and a large correlation between average stress and muscle soreness (r = 0.53, large, p < 0.01) were presented. All physiological, isokinetic, and technical parameters improved after a six-week pre-season training program (0.1 to -61.0%). Significant alterations in the physiological domain were observed after a six-week period, particularly in the fatigue index of the Bangsbo sprint test, YO-YO IR1 performance, and YO-YO peak La- (p < 0.01; -61.0%, 25.3%, and -19.8%, respectively). As such, the implementation of structured training and the monitoring of stress responses can lead to appropriate adaptation and balancing in the psychological and physical well-being of young national-level soccer players, particularly in the pre-season period.

Monitoring of the Training Load and Well-Being of Elite Rhythmic Gymnastics Athletes in 25 Weeks: A Comparison between Starters and Reserves.

The objective of this study was to monitor the training loads (TL) and well-being of elite rhythmic gymnastics (RG) athletes, as well as compare these variables between starters and reserve gymnasts during 25 weeks of training. Ten athletes from the Brazilian national RG team (17.4 ± 1.1 y of age) were monitored during the general preparatory period (GPP), specific preparatory period (SPP), and pre-competitive period (PCP). The internal TL was quantified with the use of sessional ratings of perceived exertion (sRPE). We assessed well-being daily with a well-being scale. The TL, duration, monotony, and strain were calculated weekly. We found that the internal TL and session durations were 9242 ± 2511 AU and 2014 ± 450 min, respectively. The internal TL, strain, and monotony were greater in the PCP than in the GPP and SPP for starters. In the SPP, there were statistical differences in internal TL (p = 0.036) and strain (p = 0.027) between starters and reserves. In the PCP, there were also statistical differences between starters vs. reserves athletes regarding internal TL (p = 0.027) and strain (p = 0.05). There was no statistically significant difference in well-being between the periods assessed. In conclusion, RG athletes display a higher TL magnitude during the PCP, whereas only reporting non-significant minor variations in well-being. In addition, there is a discrepancy in the TL between starters and reserves.

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.

Session Rating of Perceived Exertion Is a Superior Method to Monitor Internal Training Loads of Functional Fitness Training Sessions Performed at Different Intensities When Compared to Training Impulse.

Despite its increase in popularity, little is known about how to best quantify internal training loads from functional fitness training (FFT) sessions. The purpose of this study was to assess which method [training impulse (TRIMP) or session rating of perceived exertion (sRPE)] is more accurate to monitor training loads in FFT. Eight trained males (age 28.1 ± 6.0 years) performed an ALL-OUT FFT session and an intensity-controlled session (RPE of six out of 10). Internal load was determined via Edward's TRIMP (eTRIMP), Bannister's TRIMP (bTRIMP), and sRPE. Heart rate was measured continuously during the session, while blood lactate and rate of perceived exertion were measured at baseline, and immediately and 30 min after the sessions. ALL-OUT blood lactate and RPE were significantly higher immediately and 30 min after the session compared to the RPE6 condition. ALL-OUT training load was significantly different between conditions using bTRIMP (61.1 ± 10.6 vs. 55.7 ± 12.4 AU) and sRPE (91.7 ± 30.4 vs. 42.6 ± 14.9 AU), with sRPE being more sensitive to such differences [p = 0.045, effect size (ES) = 0.76 and p = 0.002, ES = 1.82, respectively]. No differences in the training loads of the different sessions were found using eTRIMP (93.1 ± 9.5 vs. 84.9 ± 13.7 AU, p = 0.085). Only sRPE showed a significant correlation with lactate 30 min post session (p = 0.015; p = 0.596, large). sRPE was more accurate than both TRIMP methods to represent the overall training load of the FFT sessions. While the use of sRPE is advised, further research is necessary to establish its ability to reflect changes in fitness, fatigue, and performance during a period of training.

Combined Small-Sided Game and High-Intensity Interval Training in Soccer Players: The Effect of Exercise Order.

The aim of the present study was to compare combined small-sided game (SSG) and high-intensity interval training (HIT) with different order. Twenty-one semi-professional soccer players were divided into two groups: SSG+HIT (n = 10) and HIT+SSG (n = 11), and underwent similar four-week training programs. Players completed the 30-15 Intermittent Fitness Test (30-15IFT) before and after the experiment; maximum speed (VIFT) was recorded. During the experiment, seven sessions of SSG (3 vs 3) and HIT (15"-15" with 95-100% VIFT) were implemented. Weekly accumulated training loads for both groups during the experiment were similar. Moderate improvements in VIFT were observed in both SSG+HIT (+6.2%, 90% confidence limits, [CL] 4.6; 7.7 and Effect Size, [ES] +0.96) and HIT+SSG (+6.9%, 90% CL 4.6; 9.3 and ES +0.97) groups. Between-group difference in changes of VIFT was trivial (+0.7%, 90% CL -1.8; 3.3 and ES +0.11). Combining SSG and HIT in different order elicited the same enhancement in high-intensity intermittent performance in soccer players.

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.

Test-retest reliability of TRIMP in collegiate ice hockey players.

The utility of the heart rate derived variable TRaining IMPulse (TRIMP) for assessing internal training load in ice hockey players is not clear. Having a reliable measure of internal training load during on-ice training sessions would help coaches program exercise training. This study determined the reliability of TRIMP during on-ice training sessions in ice hockey players. Twelve Division I collegiate male ice hockey players (aged 18-23 years) had their heart rate (HR) data recorded during two on-ice practice sessions separated by two weeks. TRIMP and other descriptive HR variables were compared between sessions. TRIMP demonstrated moderate reliability during on-ice sessions. Systematic error, quantified as standardized change in means was negligible (-0.19); random error quantified as the percent typical error (%TE) was moderate (12.2%); and, test-retest correlation was very strong (0.75). TRIMP is suitable for quantifying training load during intermittent work in hockey athletes. The results from our study can be used to determine the threshold for meaningful change in TRIMP, which may aid in informing decisions by coaches and strength training staff regarding on-ice training session difficulty and composition.

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.

Session-RPE for quantifying the load of different youth basketball training sessions.

The aim of the study was to evaluate youth basketball training, verifying the reliability of the session-RPE method in relation to session duration (< and ≥ 80 minutes) and workout typology (reduced and high warm-up, conditioning, technical, tactical, game portions within a single session) categories. Six male youth basketball players (age, 16.5±0.5 years; height, 195.5±6.75 cm; body mass, 93.9±10.9 kg; and body mass index, 23.6±2.8 kg.m-2) were monitored (HR, type and duration of workouts) during 15 (66 individual) training sessions (80±26 minutes). Edwards' HR method was used as a reference measure of internal training load (ITL); the CR-10 RPE scale was administered 30 minutes after the end of each session. The results obtained showed that all comparisons between different session durations and workout portions revealed effects in term of Edwards' ITLs except for warm-up portions. Moderate to strong relationships between Edwards' and session- RPE methods emerged for all sessions (r = .85, P < .001), player's sessions (r range = .79 - .95, P < .001), session durations (< 80 minutes: r = .67, P < .001; ≥ 80 minutes: r = .75, P < .001), and workout portions (r range = .78 - .89, P range = .002 - < .001). The findings indicated that coaches of youth basketball players can successfully use session-RPE to monitor the ITL, regardless of session durations and workout portions.

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.

Prediction of Functional Overreaching From Subjective Fatigue and Readiness to Train After Only 3 Days of Cycling.

PURPOSE: To investigate whether monitoring of easily measurable stressors and symptoms can be used to distinguish early between acute fatigue (AF) and functional overreaching (FOR). METHODS: The study included 30 subjects (11 female, 19 male; age 40.8 ± 10.8 y, VO2max 51.8 ± 6.3 mL · kg-1 · min-1) who participated in an 8-d cycling event over 1300 km with 18,500 climbing meters. Performance was measured before and after the event using a maximal incremental test. Subjects with decreased performance after the event were classified as FOR, others as AF. Mental and physical well-being, internal training load, resting heart rate, temperature, and mood were measured daily during the event. Differences between AF and FOR were analyzed using mixed-model ANOVAs. Logistic regression was used to determine the best predictors of FOR after 3 and 6 d of cycling. RESULTS: Fifteen subjects were classified as FOR and 14 as AF (1 excluded). Although total group changes were observed during the event, no differences between AF and FOR were found for individual monitoring parameters. The combination of questionnaire-based changes in fatigue and readiness to train after 3 d cycling correctly predicted 78% of the subjects as AF or FOR (sensitivity = 79%, specificity = 77%). CONCLUSIONS: Monitoring changes in fatigue and readiness to train, using simple visual analog scales, can be used to identify subjects likely to become FOR after only 3 d of cycling. Hence, we encourage athlete support staff to monitor not only fatigue but also the subjective integrated mental and physical readiness to perform.

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.

Carga interna de treinamento em diferentes aulas pré formatadas do sistema Les Mills® / Internal training load in different pre standardized workouts of Les Mills® system

O objetivo do presente estudo foi quantificar a carga interna de treinamento imposta em diferentes aulas pré-formatadas do sistema Les Mills® e comparar a percepção de esforço planejada pelo instrutor com a percebida pelas alunas. A amostra foi constituída por 20 mulheres jovens. Foram monitoradas 10 aulas, em duas semanas consecutivas. A carga interna foi determinada pelo método da percepção subjetiva do esforço da sessão (PSE-sessão). Os valores da PSE-sessão não diferiram significativamente da 1ª para a 2ª semana (Body Combat© = 252 ± 36 vs. 258 ± 39 UA – p=0,64; Body Pump© (terça-feira) = 171 ± 35 vs. 177 ± 30 UA – p=0,33; Body Step© = 246 ± 51 vs. 252 ± 46 UA– p=0,43; Body Pump© (quinta-feira) = 183 ± 30 vs. 225 ± 38 UA– p=0,06; Power Jump© = 291 ± 44 vs. 315 ± 42 UA– p=0,06). Houve diferença em 50% das aulas no tocante à intensidade planejada pelo instrutor e a experimentada pelas alunas: Body Combat© (Instrutor: 3 vs. Alunas: 4,2 ± 0,6 – p<0,01), Body Pump© (terça-feira) (Instrutor: 2 vs. Alunas: 2,8 ± 0,6 – p<0,01) e Power Jump© (Instrutor: 6 vs. Alunas: 4,8 ± 0,7 – p<0,01) ministradas na 1ª semana e nas aulas de Body Step© (Instrutor: 5 vs. Alunas: 4,2 ± 0,7 – p<0,01) e Power Jump© (Instrutor: 6 vs. Alunas: 5,2 ± 0,5 – p<0,01) ministradas na 2ª semana. Os resultados sugerem que as aulas analisadas mantiveram o mesmo padrão de carga interna quando repetidas em semanas distintas. Entretanto, houve discrepância entre a intensidade planejada pelo instrutor e a experimentada pelas alunas. Estes resultados apontam a importância do monitoramento das cargas de treinamento em aulas pré-formatadas, especialmente no contexto do fitness.

The aim of this study was to quantify internal training loadimposed on different pre-formatted classes Les Mills® system and compare the perception ofeffort planned by the instructor with perceived by the students. The sample consisted of 20young women. 10 lessons were monitored for two consecutive weeks. The internal loadwas determined by the perceived exertion of the session (session-PSE) method. thevalues of PSE-session did not differ significantly from the 1st to 2nd week (Body Combat ©= 252 ± 36 vs. UA 258 ± 39 - p = 0.64; © Body Pump (Tuesday) = 171 ± 35 vs. 177 ± 30AU - p = 0.33; Body Step © = 246 ± 51 vs. UA- 252 ± 46 p = 0.43; © Body Pump (Thursday)= 183 ± 30 vs. 225 ± 38 UA- p = 0.06; Power Jump © = 291 ± 44 vs. UA- 315 ± 42 p = 0.06).Was no difference in 50% of lessons regarding the intensity planned by the instructor and theexperienced by the students: Body Combat © (Instructor: Students vs. 3: 4.2 ± 0.6 - p <0.01), Body© Pump (Tuesday) (Instructor: Students vs. 2: 2.8 ± 0.6 - p <0.01) and Power Jump © (Instructor: 6vs. Students: 4.8 ± 0.7 - p <0.01) in the 1st week and taught classes in Body Step © (Instructor:5 vs. Students: 4.2 ± 0.7 - p <0.01) and Power Jump © (Instructor: Students vs. 6: 5.2 ± 0.5 - p <0.01)held in the 2nd week. The results suggest that the classes analyzed maintained the samestandard internal load when repeated in different weeks. However, there was a discrepancybetween the intensity planned by the instructor and experienced by the students. these resultsindicate the importance of monitoring training loads at pre-formatted classes,especially in the context of fitness.

Relação entre métodos de quantificação de cargas de treinamento baseados em percepção de esforço e frequência cardíaca em jogadores jovens de futsal / Relationship between methods of training load quantification based on perception of effort and heart rate in young futsal players

Os objetivos do estudo foram verificar a associação entre os métodos de quantificação da carga de treinamento, PSE da sessão e impulso de treinamento proposto por Lucía (LuciaTRIMP) e descrever a distribuição da intensidade de treinamento no futsal semiprofissional da categoria sub 18. Quinze jogadores (média e DP; idade: 17 ± 1 ano; massa corporal: 70,4 ± 6,5 kg; estatura: 175 ± 4 cm e IMC 23 ± 2 kg.m-2) foram submetidos a um teste de corrida incremental para determinar o limiar ventilatório (LVmax), o ponto de compensação respiratória (PCR) e o consumo máximo de oxigênio (VO2max). Apenas oito atletas foram monitorados por meio dos métodos PSE da sessão e LuciaTRIMP durante 78 sessões de treinamento antes da principal competição da temporada. Foram encontradas correlações individuais de magnitudes alta a quase perfeita (r = 0,64 - 0,91) entre os métodos PSE da sessão e LuciaTRIMP. O padrão de distribuição da intensidade de treinamento foi 76, 18 e 6% do tempo abaixo do LV (zona 1), entre LV e PCR (zona 2) e acima do PCR (zona 3), respectivamente. O método PSE da sessão se mostrou altamente relacionado com um método objetivo de quantificação da carga de treinamento. Além disso, as sessões de treinamento de uma equipe de futsal semiprofissional da categoria sub 18 apresentaram um padrão decrescente de distribuição das intensidades de treinamento.

The aims of this study were to verify the association between the methods of training load quantification session-RPE and training impulse -proposed by Lucia (LuciaTRIMP) -and to describe the training intensity distribution in under-18 semi-professional futsal. Fifteen male players (mean and SD; age: 17 ± 1 years; body mass: 70.4 ± 6.5 kg; height: 175 ± 4 cm and BMI 23 ± 2 kg.m²) performed an incremental treadmill test to determine the ventilatory threshold (VT), respiratory compensation point (RCP), and maximal oxygen consumption (VO2max). Only eight athletes had their training loads quantified by means of session-RPE and Lucia methods over a total of 78 training sessions before the main competition of the season. High to almost perfect correlations (r = 0.64 - 0.91) were found between session-RPE and LuciaTRIMP methods. The distribution of the training intensity was, respectively, 76, 18 e 6% of training duration below VT (zone 1), between VT and RCP (zone 2), and above RCP (zone 3). The session-RPE method was highly associated with an objective method of training load quantification. Furthermore, the training sessions of a semi-professional under-18 futsal team showed a decreasing training intensity distribution.

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.

Monitoring training loads in elite tennis / Monitoring training loads in elite tennis

Training load (TL) is influenced by both training volume and training intensity. A precise understanding of the TLs completed during training is crucial to achieve desirable training outcomes and to avoid overtraining. TL can be monitored in many different ways; however, we recommend the session-rate of perceived exertion (session-RPE) method for quantifying TL because of its low cost and because it is easy to understand and relatively simple to implement. In this report, we provide data regarding TLs collected during the 2008 Roland Garros Tournament. Our experience in tennis suggests the session-RPE method to be a valuable tool that can be used to control training and to avoid excessive TLs. We alsobelieve that accurate monitoring of TL will enable the coach to better understand of the sports training process, ultimately leading to the improvement of performance.

A carga de treinamento (CT) é influenciada pelo volume e pela intensidade. A determinação precisa das CTs utilizadas durante o treinamento é crucial para atingir as adaptações desejadas e evitar o overtraining. A CT pode ser monitorada de diversas maneiras. Entretanto, nós recomendamos o método da percepção subjetiva de esforço da sessão (PSE da sessão) para quantificar a CT pelo seu baixo custo, pela sua fácil compreensão e a pela sua relativa simplicidade de implementação. Neste relato, nós apresentamos dados relacionados às CTs coletados durante o Torneio de Roland Garros em 2008. Nossa experiência no tênis sugere que o método da PSE da sessão é uma ferramenta valiosa que pode ser usada para controlar o treinamento e evitar CTs excessivas. Nós também acreditamos que o monitoramento preciso da CT proporcionará ao técnico o melhor entendimento do processo de treinamento desportivo, em última instância,levando ao aumento de desempenho.