While some parameters are fully recovered (e.g. hormonal and technical), our systematic review shows that a period of 72 h post-match play is not long enough to completely restore homeostatic balance (e.g. muscle damage, physical and well-being status). The extent of the recovery period post-soccer game cannot consist of a 'one size fits all approach'. Additionally, the 'real match' (11 vs. 11 format) likely induces greater magnitudes of perceptual (DOMS) and biochemical alterations (e.g. muscle damage), while neuromuscular alterations were essentially similar. Overall, coaches must adjust the structure and content of the training sessions during the 72-h post-match intervention to effectively manage the training load within this time-frame.

BackgroundMonitoring athletes’ external load during a soccer match may be useful to predict post-match acute and residual fatigue. This estimation would allow individual adjustments to training programs to minimize injury risk, improve well-being, and restore players’ physical performance and inform the recovery process.MethodsUsing a systematic review and meta-analysis of the literature, the aim is to determine which monitoring variables would be the strongest predictors of acute (immediately) and residual (up to 72 h) fatigue states in soccer. PubMed, SPORTDiscus, and Web of Science databases were searched (until September 2018). Studies concurrently examining soccer match-related external load metrics and subjective and/or objective measures were selected to determine pooled correlations () with confidence intervals (CI). The quality and strength of the findings of each study were evaluated to identify overall levels of evidence.ResultsEleven studies were included (n = 165 athletes). Acute ( = 0.67; 95% CI = [0.40, 0.94]) and residual (24 h post-match, = 0.54; 95% CI = [0.35, 0.65]) changes in muscle damage markers and countermovement jump peak power output (CMJPPO) were, with moderate to strong evidence, largely correlated with running distance above 5.5 m s−1. No other external load metric was largely correlated with both biochemical and neuromuscular markers. For every 100-m run above 5.5 m·s−1, CK activity measured 24 h post-match increased by 30% and CMJPPO decreased by 0.5%. Conversely, the total distance covered did not present any evidence of a clear relationship with any fatigue-related marker at any time-point.ConclusionsRunning distance above 5.5 m·s−1 represents the most sensitive monitoring variable characterizing biochemical and neuromuscular responses, at least when assessed during the initial 24 h (not at 48 h/72 h) post-match recovery period. In addition, total distance covered is not sensitive enough to inform decision-making during the fatigue monitoring process.

This study analyzed training loads of youth soccer players and examined the influence of match-related contextual variables in internal training load and fatigue. A secondary aim was to investigate the variability of these parameters throughout the season. Thirteen highly trained under-19 players (18.6 ± 0.5 years) were followed during one season. Training load (daily) and fatigue scores (weekly) were assessed using rate of perceived exertion and a short questionnaire, respectively. Higher weekly training loads were reported after a defeat or draw compared to a win (2,342 ± 987 and 2,395 ± 613 vs. 1,877 ± 392 AU; p ≤ 0.05; d = 0.30-0.45). Weekly training loads were higher after playing an away match than after a home match (2,493 ± 821 vs. 2,153 ± 577 AU; p ≤ 0.05; d = 0.23). Within training sessions, the coefficients of variation for internal training load ranged from 5 to 72%. Throughout the season, the coefficients of variation for weekly training loads and fatigue scores ranged from 29 to 49% and 18 to 44%, respectively. Weekly training load decreased as the season progressed (p < 0.001); no changes were detected for the fatigue score. In conclusion, the large variation in internal training load within a session and its sensitivity to initial and subsequent match conditions underline the need for a more individualized approach. These findings and the stability of the fatigue scores throughout the season may indicate that highly trained players modulate their pace during training.

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According to the spring mass model, leg stiffness (characterized by the measure of kleg) behavior is theoretically dependent on lower limb joint and trunk stiffness. Yet, the influence of the trunk as a possible regulator of kleg is unknown. This study investigated the influence of abdominal training on kleg during hopping tasks. Fourteen young male (age 18.5 ± 0.5 years, height 176.4 ± 4.3 cm, weight 69.9 ± 5.5 kg) soccer players (national level) participated in the study. Two groups (bracing B group, n = 7 vs. hollowing transversus abdominis [TrA] H group, n = 7) with identical training load followed an 8-week training program for abdominal strengthening. Contact time, flight time, jump height, and kleg were measured with an OptoJump system during a standardized hopping task (2.2 Hz) before and after the training program. Results for each group showed that only the H group increased kleg after the intervention (+15.7%) compared with the B group (+5.9%). This difference was explained by a 6.5% decrease in contact time in H group (-2.4% in B) with increased flight time (+8.8% in H vs. +2% in B). A large increase was found for jump height in H (+16.9%) compared with B group (+4.4%). This study showed that TrA strengthening improves leg stiffness in hopping tasks. Our findings suggest the potential role of abdominal muscles in controlling "lumbopelvic" stiffness as a part of the spring according to the spring mass model, and thus influencing kleg by reduced ground contact phase.