This study aimed to quantify the influence of the playing surface on workload-related variables (i.e., external load, Rate of perceived exertion (RPE), and mental load) in training sessions with a Spanish professional soccer team. Twenty professional male players from the same soccer team were involved. A total of thirty training sessions related to the preseason period were included. All the players completed training sessions on three playing surfaces: natural turf of poor quality, natural turf of high quality, and third-generation artificial turf. Monitoring during sessions involved assessing internal load (i.e., RPE and mental load) via self-reported questionnaires, and external load using Global Positioning System devices. Linear mixed models showed that RPE was significantly higher on natural turf of high quality than on natural turf of poor quality (p < 0.001). Total distance, relative total distance, the number of accelerations, decelerations, and high metabolic load distance were significantly lower on third-generation artificial turf compared to natural turf of poor quality (p < 0.001) and high quality (p < 0.001). In addition, high-speed running, sprint running distances, and the number of sprints reached higher values on third-generation artificial turf compared to the other two playing surfaces. These findings highlight the need for coaches to consider the type of training surface in soccer to optimize training load planning and prevent injuries.

The present study aimed to determine whether neuromuscular fatigue monitored through countermovement jump height was a reliable and helpful marker for monitoring acute (session) and chronic (between sessions/periods of the season) fatigue throughout an entire basketball season. A longitudinal observational study analyzed the neuromuscular performance (i.e., through countermovement jump) during a basketball season. Fourteen semiprofessional male basketball players participated in the study between September 2021 and May 2022 (34 weeks, 102 practices, and 1574 jumps analyzed). Upon waking up, they completed an online wellness questionnaire. Before practices began, players performed three countermovement jumps on a contact platform after a structured warm-up, repeating the protocol at the end of each practice. Ten minutes after finishing such practice, they also reported perceived exertion\'s muscular and cardiovascular ratings. The preseason was the period of the season with the lowest absolute countermovement jump height levels (2.06 to 2.50 cm; d = 1.92 to 2.74, very large, p < 0.02). Average pre-session jumps were very largely higher on Wednesdays (0.62 cm, 95% CI = 0.29 - 0.95, p = 0.0095, d = 2.09) and Fridays (0.62 cm, 95% CI = 0.06 - 0.88, p = 0.06, d = 1.43) compared to Mondays. The countermovement jump is a valuable marker for assessing fatigue in semiprofessional basketball players. Games played on weekends mainly and consistently affected Monday\'s jumping performance, showing the lowest average values. Finally, preseason values were lower than those observed for the rest of the season.

OBJECTIVE: Without appropriate standardization of exercise doses, comparing high- (HI) and low-intensity (LI) training outcomes might become a matter of speculation. In athletic preparation, proper quantification ensures an optimized stress-to-recovery ratio. This review aims to compare HI and LI doses by estimating theoretically the conversion ratio, 1:x, between HI and LI: How many minutes, x, of LI are equivalent to 1 minute of HI using various quantification methods? A scrutinized analysis on how the dose increases in relation to duration and intensity was also made.
METHODS: An estimation was conducted across 4 categories encompassing 10 different approaches: (1) \"arbitrary\" methods, (2) physiological and perceptual measurements during exercise, (3) postexercise measurements, and comparison to (4a) acute and (4b) chronic intensity-related maximum dose. The first 2 categories provide the most conservative estimation for the HI:LI ratio (1:1.5-1:10), and the third, slightly higher (1:4-1:11). The category (4a) provides the highest estimation (1:52+) and (4b) suggests 1:10 to 1:20. The exercise dose in the majority of the approaches increase linearly in relation to duration and exponentially in relation to intensity.
CONCLUSIONS: As dose estimations provide divergent evaluations of the HI:LI ratio, the choice of metric will have a large impact on the research designs, results, and interpretations. Therefore, researchers should familiarize themselves with the foundations and weaknesses of their metrics and justify their choice. Last, the linear relationship between duration and exercise dose is in many cases assumed rather than thoroughly tested, and its use should be subjected to closer scrutiny.

BACKGROUND: Blood flow restriction (BFR) resistance training has demonstrated efficacy in promoting strength gains beneficial for rehabilitation. Yet, the distinct functional advantages of BFR strength training using high-load and low-load protocols remain unclear. This study explored the behavioral and neurophysiological mechanisms that explain the differing effects after volume-matched high-load and low-load BFR training.
METHODS: Twenty-eight healthy participants were randomly assigned to the high-load blood flow restriction (BFR-HL, n = 14) and low-load blood flow restriction (BFR-LL, n = 14) groups. They underwent 3 weeks of BFR training for isometric wrist extension at intensities of 25% or 75% of maximal voluntary contraction (MVC) with matched training volume. Pre- and post-tests included MVC and trapezoidal force-tracking tests (0-75%-0% MVC) with multi-channel surface electromyography (EMG) from the extensor digitorum.
RESULTS: The BFR-HL group exhibited a greater strength gain than that of the BFR-LL group after training (BFR_HL: 26.96 ± 16.33% vs. BFR_LL: 11.16 ± 15.34%)(p = 0.020). However, only the BFR-LL group showed improvement in force steadiness for tracking performance in the post-test (p = 0.004), indicated by a smaller normalized change in force fluctuations compared to the BFR-HL group (p = 0.048). After training, the BFR-HL group activated motor units (MUs) with higher recruitment thresholds (p < 0.001) and longer inter-spike intervals (p = 0.002), contrary to the BFR-LL group, who activated MUs with lower recruitment thresholds (p < 0.001) and shorter inter-spike intervals (p < 0.001) during force-tracking. The discharge variability (p < 0.003) and common drive index (p < 0.002) of MUs were consistently reduced with training for the two groups.
CONCLUSIONS: BFR-HL training led to greater strength gains, while BFR-LL training better improved force precision control due to activation of MUs with lower recruitment thresholds and higher discharge rates.

Purpose: Monitoring players\' training load allows practitioners to enhance physical performance while reducing injury risk. The aim of this study was to identify the key external load indicators in professional U19 soccer. Methods: Twenty-four-professional Italian young (U19) soccer players were monitored by using the rating of perceived exertion (CR-10 RPE scale) and a wearable inertial sensor during the competitive season. Three main components were detected by a Principal Component Analysis (PCA): i) volume metabolic related component, ii) intensity mechanical stimuli component, and iii) intensity metabolic/mechanical component. We hence computed two scores (i.e. Performance [PERF] and total workload [WORK]) permitting to investigate the weekly microcycle. Results: Correlation analysis showed that scores (i.e. PERF and WORK) are low correlated (r = -0.20) suggesting that they were independent. Autocorrelation analysis showed that a weekly microcycle is detectable in all the scores. Two-way ANOVA RM showed a statistical difference between match day (MD) and playing position for the three PCA components and PERF score. Conclusion: We proposed an innovative approach to assess both the players\' physical performance and training load by using a machine learning approach allowing reducing a large dataset in an objective way. This approach may help practitioners to prescribe the training in the microcycle based on the two scores.

UNASSIGNED: Exercise offers substantial health benefits but can induce oxidative stress and inflammation, especially in high-intensity formats such as high-intensity interval exercise (HIIE). Exergaming has become an effective, enjoyable fitness tool for all ages, particularly older adults. Enzyme supplements may enhance exercise performance by improving lactate metabolism and reducing oxidative stress.
UNASSIGNED: This study investigates the efficacy of fruit and vegetable enzyme supplementation in modulating fatigue and enhancing aerobic capacity in older adults following HIIE through exergaming.
UNASSIGNED: The study recruited 16 older adult female participants and allocated them into 2 distinct groups (enzyme and placebo) based on their pretest lactate levels. This division used pairwise grouping to guarantee comparability between the groups, ensuring the integrity of the results. They engaged in HIIE using Nintendo Switch Ring Fit Adventure, performing 8 sets of 20 seconds of maximum effort exercise interspersed with 30 seconds of rest, totaling 370 seconds of exercise. Key metrics assessed included blood lactate levels, heart rate, rating of perceived exertion, and training impulse. Participants in the enzyme group were administered a fruit and vegetable enzyme supplement at a dosage of 30 mL twice daily over a period of 14 days.
UNASSIGNED: The enzyme group showed significantly lower blood lactate levels compared to the placebo group, notably after the fourth (mean 4.29, SD 0.67 vs mean 6.34, SD 1.17 mmol/L; P=.001) and eighth (mean 5.84, SD 0.63 vs mean 8.20, SD 1.15 mmol/L; P<.001) exercise sessions. This trend continued at 5 minutes (mean 6.85, SD 0.82 vs mean 8.60, SD 1.13 mmol/L; P=.003) and 10 minutes (mean 5.91, SD 1.16 vs mean 8.21, SD 1.27 mmol/L; P=.002) after exercise. Although both groups exceeded 85% of their estimated maximum heart rate during the exercise, enzyme supplementation did not markedly affect the perceived intensity or effort.
UNASSIGNED: The study indicates that fruit and vegetable enzyme supplementation can significantly reduce blood lactate levels in older adults following HIIE through exergaming. This suggests a potential role for these enzymes in modulating lactate production or clearance during and after high-intensity exercise. These findings have implications for developing targeted interventions to enhance exercise tolerance and recovery in older adults.

The current study investigated the associations between female football players\' training loads and their sleep variations. The sample included 21 female elite football players from a Norwegian top-league club with a mean age of 24 years (±2.8). Sleep duration, sleep quality, and training load were monitored every day over 273 consecutive days with a Somnofy sleep monitor based on ultra-wideband (IR-UWB) pulse radar and Doppler technology, and a FIFA-approved STATSports APEX 10 Hz GPS tracking system monitoring players\' training loads. A multivariate analysis of variance (MANOVA) was conducted to investigate the relationships between the players\' training loads and sleep. It was revealed that very high training loads were associated with reduced time in bed (p = 0.005), total sleep time (p = 0.044)), and rapid eye movement (p < 0.001). The present findings show that the female football players\' sleep was disrupted when the training load, based on total distance (TDI), was very high. It appears to be a point where their sleep is somewhat consistent through low, medium, and high training loads, but with disrupted sleep when the training load reaches a very high level. Considering the reduced TIB after a very high training load, there should be suggested strategies to improve their sleep, such as extended TIB, to aid in longer TST and improved recovery.

OBJECTIVE: The relationship between external load and creatine-kinase (CK) response at the team/position or individual level using Global Positioning Systems (GPS) has been studied. This study aimed to compare GPS-derived and Football Movement Profile (FMP) -derived CK-prediction models for national-team soccer players. The second aim was to compare the performance of general and individualized CK prediction models.
METHODS: Four hundred forty-four national-team soccer players (under 15 [U15] to senior) were monitored during training sessions and matches using GPS. CK was measured every morning from whole blood. The players had 19.3 (18.1) individual GPS-CK pairs, resulting in a total of 8570 data points. Machine learning models were built using (1) GPS-derived or (2) FMP-based parameters or (3) the combination of the 2 to predict the following days\' CK value. The performance of general and individual-specific prediction models was compared. The performance of the models was described by R2 and the root-mean-square error (RMSE, in units per liter for CK values).
RESULTS: The FMP model (R2 = .60, RMSE = 144.6 U/L) performed similarly to the GPS-based model (R2 = .62, RMSE = 141.2 U/L) and the combination of the 2 (R2 = .62, RMSE = 140.3 U/L). The prediction power of the general model was better on average (R2 = .57 vs R2 = .37) and for 73% of the players than the individualized model.
CONCLUSIONS: The results suggest that FMP-based CK-prediction models perform similarly to those based on GPS-derived metrics. General machine learning models\' prediction power was higher than those of the individual-specific models. These findings can be used to monitor postmatch recovery strategies and to optimize weekly training periodization.

UNASSIGNED: TRIMP and sRPE are both representative indicators of training load(TL), and the correlation between two has been widely demonstrated across various sports. The aim of this study was to investigate the reliability of sRPE-TRIMP correlation across different intensities/duration of training in cross-country skiing, and whether sRPE can serve as an validity supplement to TRIMP data in cases of lost heart rate data.
UNASSIGNED: 10 athletes were used as the experimental objects. The intensity, duration and RPE of 273 different types of training sessions were collected, and statistical methods were used for data analysis.
UNASSIGNED: 1. There was a significant correlation between sRPE and TRIMP (r = 0.68, p < 0.05), but the correlation differs among the LIT, MIT and HIT groups (r = 0.70, 0.46, r = 0.31, p < 0.05) 2. sRPE-TRIMP correlation among three different time duration in the LIT group (0-60 min, 60-120 min and 120-180 min), are all highly significant (r = 0.70, 0.67, 0.69, p < 0.05) and the LRsRPE-TRIMP of 3 duration have no significant differences (chow test, p > 0.05). 3. The difference in actual training duration between samples was the main reason for the difference in the application effect of sRPE, because the actual training duration ratio of LIT was 89.7 ± 16.4%; MIT, 98.5 ± 6.2%; and HIT, 94.4 ± 13.5%.
UNASSIGNED: 1. The linear relationship between sRPE and TRIMP (LRsRPE-TRIMP) is more significant in LIT compared to that in MIT and HIT. 2. Variations in the duration of LIT sessions do not affect the consistency of the relationship between sRPE and TRIMP. 3. Discrepancies between actual and planned training durations directly impact the significance of the LRsRPE-TRIMP.

This study aimed to achieve two objectives: firstly, to analyze the relationships between aerobic fitness, as represented by the VIFT, and the heart rate and locomotor responses of youth male soccer players across various teams; and secondly, to compare players with lower and higher VIFT in terms of performance outcomes extracted during small-sided games (SSGs). A total of twenty-six youth male soccer players, aged 16.5 ± 0.32 years, with 3.4 ± 1.1 years of experience, voluntarily participated in the study. These players belonged to two regional-level tier 2 teams (trained/developmental). In the initial week of observation, the 30-15 Intermittent Fitness Test was implemented to measure the final velocity (VIFT) achieved by the players. Subsequently, the 5v5 format of play was conducted twice a week over two consecutive weeks, during which heart rate responses and locomotor demands were measured. The Pearson product-moment correlation test revealed a significant correlation between VIFT and the total distance covered during the 5v5 format (r = 0.471 [95% CI: 0.093; 0.721], p = 0.015). Conversely, small and non-significant correlations were identified between VIFT and mean heart rate (r = 0.280 [95% CI: - 0.126; 0.598]; p = 0.166), VIFT and peak heart rate (r = 0.237 [95% CI: - 0.170; 0.569]; p = 0.243), as well as VIFT and high-speed running (r = 0.254 [95% CI: - 0.153; 0.580]; p = 0.211). Players with higher VIFT demonstrated a significantly greater total distance, with a large effect size (+ 6.64%; p = 0.015; d = 1.033), compared to those with lower VIFT. Our findings suggest that improved performance in VIFT may lead to covering more distance in 5v5 matches. However, the lack of significant associations between VIFT and heart rate levels during SSGs suggests that they are not strongly correlated, possibly because VIFT is more closely linked to locomotor profile. As a practical implication, coaches may consider organizing players during SSGs based on their VIFT if the goal is to standardize locomotor demands.