OBJECTIVE: The aim of this study was 2-fold: (1) to examine the relationships between psychophysiological responses and locomotor demands with variations in technical performance during 2v2 and 4v4 conditioned games and (2) to compare psychophysiological and locomotor responses among players exhibiting higher and lower technical performance levels during the conditioned games.
METHODS: Twenty-four male youth soccer players (16.3 ± 0.8 y old) participating at the trained/developmental level underwent monitoring for psychophysiological responses (including heart rate, rating of perceived exertion, and visual analog scale), locomotor demands (such as distance covered), and technical performance variables (including successful and unsuccessful passes and shots, as well as lost balls) across 2v2 and 4v4 formats. These formats were applied 4 times within a single session and were replicated twice over 2 weeks.
RESULTS: Large correlations between the number of lost balls per minute and mean heart rate were found in both the 2v2 and 4v4 games (r = .586 and r = .665, respectively). Successful shots were inversely and largely correlated with mean heart rate (r = -.518) in 4v4 games. The number of interceptions per minute was inversely and significantly correlated with the visual analog scale in 2v2 and 4v4 games (r = -.455 and r = -.710, respectively). The frequency of lost balls was significantly higher among players who attained a higher mean heart rate (2v2: +42.9%, P = .031, d = -0.965; 4v4: +57.1%, P < .001, d = -2.072).
CONCLUSIONS: Coaches should be aware that highly psychophysiologically demanding scenarios may significantly impair technical performance. Therefore, prioritizing technical performance by deliberately adjusting the intensity should be considered.

Technological development has boosted the use of multi-sensor devices to monitor athletes\' performance, but the location and connectivity between devices have been shown to affect data reliability. This preliminary study aimed to determine whether the placement of a multi-sensor device (WIMU PROTM) could affect the heart rate signal reception (GARMINTM chest strap) and, therefore, data accuracy. Thirty-two physical education students (20 men and 12 women) performed 20 min of exercise in a cycle ergometer based on the warm-up of the Function Threshold Power 20 test in laboratory conditions, carrying two WIMU PROTM devices (Back: inter-scapula; Bicycle: bicycle\'s handlebar-20 cm from the chest) and two GARMINTM chest straps. A one-dimensional statistical parametric mapping test found full agreement between the two situations (inter-scapula vs. bicycle\'s handlebar). Excellent intra-class correlation values were obtained during the warm-up (ICC = 0.99, [1.00-1.00], p < 0.001), the time trial test (ICC = 0.99, [1.00-1.00], p < 0.001) and the cool-down (ICC = 0.99, [1.00-1.00], p < 0.001). The Bland-Altman plots confirmed the total agreement with a bias value of 0.00 ± 0.1 bpm. The interscapular back placement of the WIMU PROTM device does not affect heart rate measurement accuracy with a GARMINTM chest strap during cycling exercise in laboratory conditions.

This study aimed to compare training load parameters, delayed onset muscle soreness (DOMS), and fatigue status between season periods (1st and 2nd halves) in U14 soccer players and to analyze the relationships between training load parameters based on season periods (1st and 2nd halves) with peak height velocity (PHV), DOMS, and fatigue status in under-14 (U14) young elite soccer players. Additionally, it was intended to analyze if fatigue, DOMS and PHV could explain training load parameters across the season.
Twenty U14 players that competed in the national league participated in this study. The players were monitored during the whole season (26 weeks), and evaluations were carried out at the end of the in-season. Anthropometric and body composition parameters and the maturity offset of each player were utilized to compute each player\'s age at PHV. Players reported their levels of DOMS and fatigue status using Hooper index questionnaires. The internal load was monitored using the rating of perceived exertion (RPE). Acute weekly internal load (AW), chronic weekly internal load (CW), acute: chronic workload ratio (ACWR), training monotony (TM), and training strain (TS) were also obtained.
The main results showed that TM was higher in the 2nd half, while CW, AW and DOMS were higher in the 1st half of the season. Moreover, the main correlations showed a positive correlation between PHV and TS (2nd half of the season) and between fatigue and TM (1st half of the season).
In conclusion, variations in well-being status and PHV cannot explain the variations in internal training loads in elite U14 soccer players. In addition, internal training load indices during the first half of the competitive season can promote a fundamental base for progression loads during the second period of the competitive season.

In order to study the load-bearing failure characteristics of a RPCCP under internal load, a field prototype test was designed, and a finite element model was established. An internal load was applied up to 2.0 MPa step by step and the force variation law of each part was obtained. During the production of the RPCCP, by wrapping prestressed steel bars around the concrete core with a cylinder, the core was subjected to an initial precompression stress. In the loading process, the protective cover cracked first, from where the concrete core gradually changed from the initial compression state to a tension state, finally cracking from the inner and outer diameter. The stresses of the cylinder and steel bars increased steadily with the internal load and did not yield. The finite element calculation results were in good agreement with the test results, and the influence characteristics of the tension control stress of the steel bar and the concrete strength on the failure of the RPCCP under internal load were discussed. The results showed that the internal load of the protective cover was independent of the tension control stress, but decreases with a decrease in concrete strength, while the load corresponding to the concrete core entering plasticity is related to the tension control stress and the concrete strength, and the relationships were basically linear.

UNASSIGNED: The aim of this study was to analyze the effect of the length of the microcycle (ie, training period from the day after the match to the following match) on the daily external load and perceived wellness of professional soccer players (Spanish LaLiga Smartbank).
UNASSIGNED: The length of the microcycle has a significant effect on the daily external load and perceived wellness.
UNASSIGNED: Longitudinal study.
UNASSIGNED: Level 3.
UNASSIGNED: Data were collected daily during a full season using perceived wellness questionnaires and electronic performance and tracking systems.
UNASSIGNED: The length of the microcycle had a significant effect on volume- and intensity-related external load variables. There were differences between short, regular, and long microcycles depending on the day of the microcycle. These differences were observed in all external load variables. However, no significant differences between short, regular, or long microcycles were found on match day for any external load variable, except for high-intensity decelerations. Regarding the perceived wellness, the length of the microcycle had no effect on these variables, and there were no significant interactions between the length and the day of the microcycle.
UNASSIGNED: The length of the microcycle had a significant effect on volume- and intensity-related external load variables, but no significant effect on perceived wellness was observed.
UNASSIGNED: These data may help strength and conditioning coaches understand that workload periodization should take this contextual variable into account, especially for external training load. In addition, this study may serve as a guide for practitioners to know the physical requirements of professional soccer players in Spanish LaLiga Smartbank, because the weekly external load profile and perceived wellness have been reported for different lengths of the microcycles. Thus, these data may be used for player load management.

BACKGROUND: The aim of this study was to describe and compare the in-season variations of acute: chronic workload ratio (ACWR) coupled, uncoupled, and exponentially weighted moving average (EWMA) through session rating of perceived exertion (s-RPE), total distance (TD), high-speed running distance (HSRD) and sprint distance (SPRINT) in three different periods of an elite soccer season according to player positions.
METHODS: Twenty male elite players (age: 29.4 ± 4.4) from an Asian First League team were daily monitored for twenty consecutive weeks during the 2017-2018 in-season. Forty-seven trainings and twenty matches were monitored using global positioning system units (GPS) to collect TD, HSRD and SPRINT. Through the collection of s-RPE, TD, HSRD, and SPRINT by ACWR and EWMA were calculated for each training session.
RESULTS: The results revealed that according to different periods of the season, workload measures observed in mid-season were meaningfully higher compared with early-season (g = ranging from 0.53 to 4.98) except for EWMASPRINT. In general, wingers and strikers tended to have greater scores in workload measures compared to the defenders and midfielders (g = ranging from 0.41 to 5.42).
CONCLUSIONS: These findings may provide detailed information for coaches and sports scientists regarding the variations of acute and chronic workload ratio and external loading in-season and between player positions in an elite soccer team.

BACKGROUND: The main purpose of the current study was to compare the within-season variations of workload, training duration, acute/chronic workload ratio (ACWR), training monotony ™, and training strain (TS) through session rating perceived exertion (s-RPE) between starters and non-starters.
METHODS: Seventeen under-17 European male soccer players (age, 16.2 ± 0.3 y, height, 1.8 ± 0.1 m; body mass, 66.5 ± 4.0 kg) divided in two groups: nine starters and eight non-starters, were evaluated over 50 weeks throughout the season.
RESULTS: In general, there were load variations for all players during the full-season. RPE tended to decrease during in-season and RPE, training duration and s-RPE did not present significant differences between starters and non-starters. TM and TS presented lower values for starters in mesocycle (M) 4 and M11 compared to non-starters. TS presented lower values for starters in M4 and M11 compared to non-starters, while in M10 a higher value was found for starters when compared to non-starters. ACWR showed differences between starters and non-starters in two of the mesocycles.
CONCLUSIONS: This study showed that some mesocycles provided higher load for non-starters. This information can alert coaches that non-starter players are likely to try too hard in training to demonstrate their abilities, leading to non-functional overreaching, overtraining syndrome, and then poor performance.

Purpose: The current study compared metabolic profiles and movement patterns between different player positions and explored relationships between indicators of internal and external loads during elite male basketball games. Methods: Five main players from 14 basketball teams (n = 70) were selected as subjects and defined as backcourt (positions 1-3) or frontcourt (positions 4-5) players. Video-based time motion analysis (VBTMA) was performed based on players\' individual maximal speeds. Movements were classified into high and low intensity running with and without ball, high and low intensity shuffling, static effort and jumps. Saliva samples were collected before and after 40-min basketball games with metabolomics data being analyzed by multivariate statistics. Independent t-tests were used to compare VBTMA. Results: Frequency, duration, and distance of high and low intensity running and -shuffling were higher in backcourt players, whereas static effort duration and frequency as well as jump frequency were higher in frontcourt players (all p ≤ 0.05). The levels of taurine, succinic acid, citric acid, pyruvate, glycerol, acetoacetic acid, acetone, and hypoxanthine were higher in backcourt players, while lactate, alanine, 3-methylhistidine were higher and methionine was lower in frontcourt players (all p < 0.05). High intensity running with ball was significantly associated by acetylecholine, hopoxanthine, histidine, lactic acid and leucine in backcourt players (p < 0.05). Conclusion: We demonstrate different metabolic profiles of backcourt and frontcourt players during elite male basketball games; while aerobic metabolic changes are more present in backcourt players, frontcourt players showed lager changes in anaerobic metabolic pathways due to more static movements.

The objective of this manuscript was to examine the periodization strategy of an international Rugby-7s team during an Olympic season. Training load data were collected in 14 elite male players over a 48-week period during the 2015-2016 Olympic season. The season consisted of 3 macrocycles including: preseason (12-weak duration), in-season (25-weak) fragmented into four 4-7 weeks mesocycles (In-1-4) and the final preparation for the Rio 2016 Olympic Games (Olympic preparation, 11-weak). External training load (TL) such as the total distance (TD), the high-intensity distance (HID) and the number of accelerations performed, was monitored in training and competition over the entire duration of the season using a global positioning system (GPS) devices. The rating of perceived exertion (RPE) was multiplied by the session duration (min) to provide an internal TL (session-RPE) value for all training sessions and competitions. The Olympic preparation may enable planning of higher external TL compared to the preseason (TD, 21 ± 13%, moderate; total accelerations, 27 ± 4%, moderate) whereas no difference was observed for internal TL values between these two periods. High-intensity distance (HID) and internal TL (session-RPE) were lower (-11.0 ± 7.8%, small and -38 ± 3%, moderate, respectively) during the in-season compared to preseason. Internal TL, TD as well as HID were lower in the third in-season mesocycle (In-3) compared with the first in-season mesocycle (In-1) (-25 ± 12%, moderate; -32 ± 4%, moderate; -49 ± 8%, moderate, respectively). The staff managed the workload considering the in-season as the main part of the \"Road to Rio.\" The strategy to reduce the workload at the middle of the season and to induce weeks of regeneration at the end of the in-season was highlighted by the training availability of 100% of the squad at the beginning of the Olympic preparation. The workload periodization strategy of an Olympic season differs from the strategy previously described during a non-Olympic season.

This study described the weekly variations of acute (wAL), chronic (wCL), acute:chronic workload ratio (wACWR), training monotony (wTM), and training strain (wTS) of perceived load, such as wellness indicators over a competitive season. In addition, we analyzed the associations between training load metrics and weekly reports. Twenty-nine under 16 years old elite players were daily monitored for 20 consecutive weeks during the season by individual observations. Training and match load were obtained using the session rating of perceived exertion. Well-being status relative to stress, fatigue, delayed onset muscle soreness (DOMS), and sleep quality/disorders were daily monitored using the Hooper index method. The results revealed that the highest values of wAL, wCL, and wTS were verified in the mid-season and the lowest values in the start-season. The highest values of accumulated weekly fatigue, stress, and DOMS were observed in the end-season, and the lowest values of sleep and stress in the start-season while the lowest values of fatigue and DOMS were observed in the mid-season. Regarding the load variability, the results showed the highest values between-week variations to wTS (15%; week-8 to 9) and the lowest reduction to wACWR (-19%; week-9 to 10). The highest within-week variations were verified to wACWR (coefficient of variation =19%; week-18) and the lowest to wCL (coefficient of variation =6%, week-19). Wellness indicators were moderate-large related to acute load, monotony and strain (r = 0.46-0.67). Overall Hooper index was the best predictor of the acute load (R2 = 0.45). These results provide new insights for coaches and practitioners about perceived loads and well-being variations over a season in elite youth level.