Faster and Slower Posttraining Recovery in Futsal: Multifactorial Classification of Recovery Profiles

Differences between 48 and 72-hour intervals on match load and subsequent recovery: a report from the Brazilian under-20 national football team

Purpose

To compare the external and internal load and subsequent recovery of football players after international tournament matches separated by 48 h vs. 72 h.

Methods

A total of 14 male football players from the Brazilian National Team, competing in the 2019 South American Under-20 Championship, participated in the study. Match load was quantified using GPS variables and perceived exertion ratings (1). Additionally, before and 13-15 h after each match, players answered questions about the number of hours and quality of sleep, recovery status, and muscle soreness (0-10) and provided a blood sample for creatine kinase and reactive C-protein analysis. Values of all variables were compared between matches played with 48-h intervals (matches 1-4) and 72-h intervals (matches 5-8).

Results

No significant differences in performance or perceptual parameters were observed between matches (p = 0.136-0.953). However, CK was higher in matches 1-4 compared to matches 5 and 6; and ΔPCR was higher in matches 2 and 3 compared to matches 5 and 6, and in match 4 compared to matches 5 and 8.

Conclusions

After matches with a 48-h rest interval, players showed increased markers of inflammation and muscle damage compared to matches with a 72-h rest interval.

Preseason Training Improves Perception of Fatigue and Recovery From a Futsal Training Session

PURPOSE

To compare the posttraining recovery timeline of elite Brazilian futsal athletes before (Pre-PS) and after 10 weeks of the preseason (Post-PS) period of high-intensity technical-tactical training.

METHODS

At the start (n = 13) and at the end of the preseason (n = 7), under-20 male futsal players undertook fitness testing for maximal aerobic power, the countermovement jump (CMJ), and the 10-m sprint with change of direction. Furthermore, at both Pre-PS and Post-PS, the players participated in a training session where performance and psychophysiological measures were recorded before, immediately, 3, 24, and 48 hours postsession. The measures included CMJ, 10-m sprint, creatine kinase, Total Quality Recovery Scale, and Brunel Mood Scale. Effect size (ES) analyses compared fitness and posttraining recovery values for each parameter at Pre-PS versus Post-PS.

RESULTS

Only trivial ES (-0.02 to 0.11) was evident in maximal aerobic power, CMJ, and 10-m sprint at Post-PS compared with Pre-PS. For the timeline of recovery, only trivial and small ESs were evident for the 10-m sprint (-0.12 to 0.49), though CMJ recovery was improved at 3 hours (0.87) and 48 hours (1.27) at Post-PS and creatine kinase was lower at 48 hours (-1.33) at Post-PS. Perception of recovery was improved in Post-PS at 3 hours (1.50) and 24 hours postsession (0.92). Furthermore, perception of effort was lower immediately after the session (-0.29), fatigue was lower at 3 hours (-0.63), and vigor responses were improved in all postseason assessments (0.59 to 1.13).

CONCLUSION

Despite minimal changes in fitness, preseason training attenuated players' perception of effort and fatigue and improved their recovery profile following a high-intensity technical-tactical training session.

Activity Profile and Physical Performance of Match Play in Elite Futsal Players

Understanding the physical demands of futsal requires a precise quantification of the players’ activities during match play. This study aimed to (1) describe external load, identifying the differences between the first and second halves in official futsal matches; (2) identify the most important external workload metrics to profile the players; and (3) identify the collinearity between variables in the analysis of physical performance of futsal players. Match external load data were collected from male players (n = 28) in six games of the Final Eight of the Portuguese Futsal Cup 2018. The players increased the distance covered per minute at 12–18 km/h in the second half (p < 0.01). Dynamic stress load also increased in the second half (p = 0.01). The variables that best predicted the physical profile of each player were decelerations (predictor importance, PI = 1), walking (PI = 1), sprinting (PI = 1), jogging (PI = 0.997), total distance covered per minute (PI = 0.992), and metabolic power (PI = 0.989). Decelerations showed the highest association with the clusters levels (p < 0.001; PI = 1); this suggests decelerations as a potential candidate for best analyzing the physical load of futsal players. Overall, the data from this exploratory study suggest that distance covered per minute (m/min), number of sprints (>18 km/h), decelerations (greater than-2 m/s), and metabolic power (W/kg) are the variables that most discriminate the load intensity of elite futsal players.

External Responsiveness of the SuperOpTM Device to Assess Recovery After Exercise: A Pilot Study

Post-exercise recovery is a complex process involving a return of performance and a physiological or perceptual feeling close to pre-exercise status. The hypothesis of this study is that the device investigated here is effective in evaluating the recovery state of professional cyclists in order to plan effective training. Ten professional male cyclists belonging to the same team were enrolled in this study. Participants performed a 7-day exercise program [D1, D4, and D7: low-intensity training; D2 and D5: passive recovery; D3: maximum oxygen consumption (VO2Max) test (for maximum mechanical power assessment only); and D6: constant load test]. During the week of monitoring, each morning before getting up, the device assessed each participant's so-called Organic Readiness {OR [arbitrary unit (a.u.)]}, based on blood pressure (BP), heart rate (HR), features of past exercise session, and following self-perceived condition. Based on its readings and algorithm, the device graphically displayed four different colors/values, indicating general exercise recommendations: green/3 = "you can train hard," yellow/2 = "you can train averagely," orange/1 = "you can train lightly," or red/0 = "you should recover passively." During the week of research, morning OR values and Bonferroni post-hoc comparisons showed significant differences between days and, namely, values (1) D2 (after low intensity training) was higher than D4 (after VO2Max test; P = 0.033 and d = 1.296) and (2) D3 and D6 (after passive recovery) were higher than D4 (after VO2Max test; P = 0.006 and d = 2.519) and D5 (after low intensity training; P = 0.033 and d = 1.341). The receiver operating characteristic analysis area under curve (AUC) recorded a result of 0.727 and could differentiate between D3 and D4 with a sensitivity and a specificity of 80%. Preliminarily, the device investigated is a sufficiently effective and sensitive/specific device to assess the recovery state of athletes in order to plan effective training.

Influence of Faster and Slower Recovery-Profile Classifications, Self-Reported Sleep, Acute Training Load, and Phase of the Microcycle on Perceived Recovery in Futsal Players

PURPOSE

To determine whether daily perceived recovery is explained from a multifactorial single-session classification of recovery (ie, faster vs slower) or other circumstantial factors (ie, previous training load, self-reported sleep, or phase of the microcycle).

METHODS

Nineteen elite male futsal players were initially allocated to a recovery-classification group (faster recovery, slower physiological, or slower perceptual) based on previous research using a multifactorial cluster-analysis technique. During 4 ensuing weeks of preseason, training loads were monitored via player load, training impulse, and session rating of perceived exertion. Before each day's training, players reported their perception of recovery (Total Quality of Recovery scale [TQR]) and the number of hours and perceived quality of sleep the night prior. A hierarchical linear mixed model was used to analyze the effect of the different recovery profiles, training load, sleep, and phase of the microcycle (ie, start, middle, end) on daily TQR.

RESULTS

The recovery classification of players (P = .20), training load (training impulse, P = .32; player load, P = .23; session rating of perceived exertion, P = .46), and self-reported hours slept the night before (P = .45) did not significantly influence TQR. However, perceived sleep quality (P < .01) and phase of the microcycle (P < .01) were significantly associated with TQR (r2 = .41).

CONCLUSIONS

Neither recovery classification nor prior training load influenced perceived recovery during the preseason. However, higher TQR was evident with better self-reported sleep quality, whereas lower values were associated with phases of the training week.