he Relationship between External and Internal Load during Elite Pre-season Friendly Basketball Games.

The aim of this study was to analyse the relationship between External Load (EL) and internal load (IL). Thirteen male basketball players competing at professional level in First Spanish Division (ACB) during six friendly games throughout the 2020/2021 preseason were monitored. The EL variables collected were movement load (ML), movement intensity (MI), box score time (BST), and total duration (TD)] while IL variables monitored were heart rate (HR), respiratory rate (RR), training impulse (TRIMP) and time invested in five HR zones. Very large to almost perfect correlation (r= 0.77-0.91) exists between EL variables except TD. In addition, HR, TRIMP and RR present large to very large correlation (r= 0.55-0.79) with all EL variables except TD. Monitoring HR-based variables would present general information and an estimated prediction of players EL which could allow basketball practitioners to prioritize time invested players internal/external load.

Comparison of Heart Rate Monitoring Accuracy between Chest Strap and Vest during Physical Training and Implications on Training Decisions

Heart rate (HR) and heart rate variability (HRV) based physiological metrics such as Excess Post-exercise Oxygen Consumption (EPOC), Energy Expenditure (EE), and Training Impulse (TRIMP) are widely utilized in coaching to monitor and optimize an athlete’s training load. Chest straps, and recently also dry electrodes integrated to special sports vests, are used to monitor HR during sports. Mechanical design, placement of electrodes, and ergonomics of the sensor affect the measured signal quality and artefacts. To evaluate the impact of the sensor mechanical design on the accuracy of the HR/HRV and further on to estimation of EPOC, EE, and TRIMP, we recorded HR and HRV from a chest strap and a vest with the same ECG sensor during supervised exercise protocol. A 3-lead clinical Holter ECG was used as a reference. Twenty-five healthy subjects (six females) participated. Mean absolute percentage error (MAPE) for HR was 0.76% with chest strap and 3.32% with vest. MAPE was 1.70% vs. 6.73% for EE, 0.38% vs. 8.99% for TRIMP and 3.90% vs. 54.15% for EPOC with chest strap and vest, respectively. Results suggest superior accuracy of chest strap over vest for HR and physiological metrics monitoring during sports.

Changes in Factors Regulating Serum Sodium Homeostasis During Two Ultra-Endurance Mountain Races of Different Distances: 69km vs. 121km

Overdrinking and non-osmotic arginine vasopressin release are the main risk factors for exercise-associated hyponatremia (EAH) in ultra-marathon events. However, particularly during ultra-marathon running in mountainous regions, eccentric exercise and hypoxia, which have been shown to modulate inflammation, hormones regulating fluid homeostasis (hypoxia), and oxidative stress, could contribute to serum sodium changes in a dose-dependent manner. To the best of our knowledge, the contribution of these factors, the extent of which depends on the duration and geographical location of the race, has not been well studied. Twelve male participants (11 finishers) of the short (69km, 4,260m elevation-gain) and 15 male participants (seven finishers) of the long (121km, 7,554m elevation-gain) single-stage Südtirol Ultra Sky-Race took part in this observational field study. Venous blood was drawn immediately before and after the race. Analyses included serum sodium concentration, copeptin (a stable marker for vasopressin), markers of inflammation, muscle damage and oxidative stress. Heart rate was measured during the race and race time was obtained from the race office. During the short and the long competition two and one finishers, respectively showed serum sodium concentrations >145mmol/L. During the long competition, one athlete showed serum sodium concentrations <135mmol/L. Only during the short competition percent changes in serum sodium concentrations of the finishers were related to percent changes in body mass (r=−0.812, p=0.002), total time (r=−0.608, p=0.047) and training impulse (TRIMP) (r=−0.653, p=0.030). Data show a curvilinear (quadratic) relationship between percent changes in serum sodium concentration and body mass with race time when including all runners (short, long, finishers and non-finishers). The observed prevalence of hypo- and hypernatremia is comparable to literature reports, as is the relationship between serum sodium changes and race time, race intensity and body mass changes of the finishers of the short race. The curvilinear relationship indicates that there might be a turning point of changes in serum sodium and body mass changes after a race time of approximately 20h. Since the turning point is represented mainly by non-finishers, regardless of race duration slight decrease in body mass and a slight increase in serum sodium concentration should be targeted to complete the race. Drinking to the dictate of thirst seems an adequate approach to achieve this goal.

Session Rating of Perceived Exertion (sRPE) Load and Training Impulse Are Strongly Correlated to GPS-Derived Measures of External Load in NCAA Division I Women’s Soccer Athletes

Purpose: The purpose of this study was to determine whether session rating of perceived exertion-derived training load (sRPE-TL) correlates with GPS-derived measures of external load in National Collegiate Athletics Association (NCAA) Division I female soccer athletes. Methods: Twenty-one NCAA Division 1 collegiate women’s soccer athletes (11 starters, 10 non-starters; 65.1 ± 7.2 kg, 168.4 ± 7.9 cm, 20.3 ± 1.5 yrs) volunteered to take part in this study. Data for this study were collected over the course of 16 weeks during the 2018 NCAA women’s soccer season. External load and heart rate (HR) data were collected during each training session and match during the season. At least 30 min after the end of an activity (e.g., match or practice), athletes were prompted to complete a questionnaire reporting their perceived exertion for the session. sRPE-TL was calculated at the end of the season by multiplying perceived exertion by the respective session duration. Results: sRPE-TL was very strongly correlated with total distance, distance covered in velocity zones 1–3, the number of accelerations in zones 4 and 5, total PlayerLoad™, and PlayerLoad™. For internal load, sRPE-TL correlated very strongly (0.70 ≤ |r| < 0.90) with Edward’s and Bannister’s TRIMP and strongly (0.50 ≤ |r| < 0.70) with duration spent in in heart rate zones 5 and 6 (80–90% and 90–100% max HR, respectively) while correlations with maximum HR (bpm), mean HR (bpm), and mean HR (%) and sRPE-TL were moderate (0.30 ≤ |r| < 0.50). Conclusions: In NCAA Division I women soccer, sRPE-TL is strongly associated with external measures of workload. These relationships were stronger during match play, with acceleration load and total distance exhibiting the strongest relationship with sRPE-TL.

Internal Load of Female Varsity Ice Hockey Players During Training and Games During a Season

This study quantified internal load, using sessional rating of perceived exertion (sRPE) and heart-rate derived training impulse (TRIMP), of female varsity ice hockey players throughout a season. Twenty-four female (19.8±1.4 yr, 68.0±6.9 kg) varsity ice hockey players participated in this prospective cohort study. Internal load was captured using sRPE and TRIMP for each on-ice session. Internal load was significantly higher (p<0.05) for games (sRPE: 324±202 AU, TRIMP: 95±60 AU) compared to training (sRPE: 248±120 AU, TRIMP: 68±32 AU). Overall, goalies had a higher internal load than forwards (sRPE and TRIMP) and defence (TRIMP), with no differences between forwards and defence. Micro-cycle periodization was present, with training sessions several days prior to game days having the highest internal load (sRPE and TRIMP) and tapering down as subsequent training sessions approached game day. For the meso-cycle assessment, for both training and competition combined, the post-season sRPE was greater than the pre-season (p=0.002) and regular season (p<0.001). Lastly, the association between sRPE and TRIMP, revealed a large, statistically significant relationship (r=0.592, p<0.001). Internal load was greater during competitions, training sessions and subsequent internal loads suggested prioritization around game days, the post-season phase demanded the highest internal load and there was a strong correlation between sRPE and TRIMP.

The integration of training and off-training activities substantially alters training volume and load analysis in elite rowers

Training studies in elite athletes traditionally focus on the relationship between scheduled training (TRAIN) and performance. Here, we added activities outside of scheduled training i.e., off-training (OFF) contributing to total training (TOTAL) to evaluate the contribution of OFF on performance. Eight elite rowers recorded OFF and TRAIN during waking hours for one season (30–45 weeks) with multisensory smartwatches. Changes in performance were assessed via rowing ergometer testing and maximum oxygen uptake ($${\dot{\text{V}}}$$ V ˙ O2max). Based on 1-Hz-sampling of heart rate data during TRAIN and OFF (> 60% maximum heart rate (HRmax), the volume, session count, intensity, training impulse (TRIMP), and training intensity distribution were calculated. OFF altered volume, TRIMP, and session count by 19 ± 13%, 13 ± 9%, and 41 ± 67% (p < 0.001). On an individual level, training intensity distribution changed in 3% of the valid weeks. Athletes exercised 31% of their weekly volume below 60% HRmax. Low to moderate intensities dominated during OFF with 87% (95% CI [79, 95]); however, in some weeks high-intensity activities > 89% HRmax during OFF amounted to 21 min·week−1 (95% CI [4, 45]). No effect of OFF on changes of performance surrogates was found (0.072 > p > 0.604). The integration of OFF substantially altered volume, TRIMP, and session count. However, no effect on performance was found.

Comparison of development of step-kinematics of assisted 60 m sprints with different pulling forces between experienced male and female sprinters

The purpose of this study was to compare step-by-step kinematics of normal and assisted 60 m sprints with different loads in experienced sprinters. Step-by-step kinematics were measured using inertial measuring units (IMU) integrated with a 3-axis gyroscope and a laser gun in 24 national level male and female sprinters during a normal 60 m sprint and sprints with a 3, 4, and 5 kg pulling force. The main findings were that using increasing assisted loads resulted in faster 60 m times, as a result of higher step velocity mainly caused by longer step lengths in both genders and by shorter contact times in women. Men had longer step lengths, longer contact times, and shorter flight times than women. However, the assisted loads had a greater effect on women than on men, as shown by their larger decrease in sprint times. These time differences in gender were the result of more and longer duration increases in maximal step velocity with increasing assisted loads for women (70–80% of distance) than men (65–70% of distance). This was mainly caused by shorter contact times, and by more increased step lengths in women compared to men. In terms of practical application, it is notable that employing this approach, when using assisted loads can help athletes to reach higher step velocities and hold this for longer, which may be a training impulse to move the speed barrier upwards.

Training Load Measures and Biomarker Responses during a 7-Day Training Camp in Young Cyclists—A Pilot Study

Background and Objectives: During intense training periods, there is a high need to monitor the external and especially the internal training load in order to fine-tune the training process and to avoid overreaching or overtraining. However, data on stress reactions, especially of biomarkers, to high training loads in children and youth are rare. Therefore, in this study, we aimed to investigate the training load of youth athletes during a training camp using a multilevel approach. Materials and Methods: Six trained youth male cyclists performed a 7-day preseason training camp. To investigate the internal training load, every morning, minimally invasive “point-of-care testing” (POCT) devices were used to analyze the following biomarkers: creatine kinase (CK), blood urea nitrogen (BUN), albumin (Alb), bilirubin (Bil), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total protein (TP). Additionally, data of training load measures (HR: heart rate, RPE: rating of perceived exertion, sRPE: session-RPE, TRIMP: training impulse, intensity (RPE:HR), and load (sRPE:TRIMP) ratios), self-perception (person’s perceived physical state, questionnaires on muscle soreness, and sleep quality), and measures of the autonomic nervous system (resting heart rate, heart rate variability) were collected. Two days before and after the training camp, subjects performed performance tests (Graded Exercise Test, Wingate Anaerobic Test, Counter Movement Jump). Results: Primarily, the biomarkers CK, BUN, and Alb, as well as the self-perception showed moderate to large load-dependent reactions during the 7-day training camp. The biomarkers returned to baseline values two days after the last training session. Power output at lactate threshold showed a small increase, and no changes were found for other performance parameters. Conclusions: The study suggests that a multilevel approach is suitable to quantify the internal training load and that different parameters can be used to control the training process. The biomarkers CK, BUN, and Alb are suitable for objectively quantifying the internal training load. The self-perception provides additional subjective information about the internal training load.

The Relationship between Training Load Measures and Next-Day Well-Being in Rugby Union Players

The aim of this study is to identify the relationship between different internal and external load measures and next day subjective wellbeing. With institutional ethics approval, ten academy rugby union players (Five forwards, and five backs) with a local National League One club agreed to participate in the study (aged; 18.4 ± 1.0 years, height; 181.3 ± 5.9 cm, body mass 85.9 ± 13.0 kg, VO2max 56.2 ± 6.8 mL·kg−1·min−1). Before the 6-week in-season data collection period, participants completed an incremental treadmill test to determine lactate thresholds at 2 mmol·L−1 (LT) and 4 mmol·L−1 and the heart rate blood lactate (HR-BLa) profile for individualized training impulse (iTRIMP) calculations. Internal training load was quantified using Banister’s TRIMP, Edward’s TRIMP, Lucia’s TRIMP, individualised TRIMP and session-RPE. External training load was reported using total distance, PlayerLoadTM, high-speed distances (HSD) > 18 km∙h−1 and >15 km∙h−1, and individualized high-speed distance (iHSD) based on each player’s velocity at OBLA. On arrival and prior to all training sessions players completed a well-being questionnaire (WB). Bayesian linear mixed model analysis identified that a range of internal and external load measures explained between 30% and 37% of next-day total wellbeing and between 65% and 67% of next-day perceived stress. All other internal and external load measures demonstrated very weak to moderate relationships (R2 = 0.08 to 0.39) with all other wellbeing components. Internal sRPE, iTRIMP and bTRIMP loads alongside external HSD loads provide coaches with the most practical measures to influence players’ perceived wellbeing.