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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.
RESUMEN
The main objective of this study was to describe the repetition of external load high-demanding scenarios and very high-demanding scenarios of match play for velocity, distance, and neuromuscular locomotor variables of an elite futsal team. Additionally, we also checked how these high- and very high-demanding scenarios were distributed throughout the microcycle. The most demanding scenario (measured using a rolling average method with a 1-min time window) of match play was measured out of thirteen elite futsal players using a local positioning system in the course of thirteen official matches and six in-season microcycles. A mean of the top three match play observations for each variable and each player were used to determine the most demanding scenario (100%) reference value. Data were reanalyzed to count the number of high-demanding scenarios (80-90% of the individual most demanding scenario) and very high-demanding scenarios (>90% of the individual most demanding scenario). The number of scenarios was analyzed with respect to the number of days prior to the match [match day (MD) minus X] and a bootstrap confidence interval approach was used to assess differences between MD. During a single match, players have to cope with repeated high- and very high-demanding scenarios. Moreover, the training session 2 days prior to the match was the one most similar to the match, surpassing it only in scenarios of locomotor velocity variables, albeit with significantly fewer scenarios of neuromuscular variables. The number of high- and very high-demanding scenarios in the training session prior to the match dropped significantly in comparison with the rest of the microcycle and the match. This new monitoring method may help practitioners to establish an accurate assessment of external load demands in competition and training.
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The aim of this study was to analyse the variance of training load between male and female football and futsal players. The statistical analysis tested the variance between gender and type of sport during training sessions. Fifty-nine male and female amateur football and futsal amateur players were monitored during 48 training sessions. The heart rate (HR) responses and the percentage of time spent in zones of intensity were analysed during training sessions. Differences were found in football between the gender and the dependent variables of %HRmax (p value = 0.001; η (2) = 0.042; minimum effect), %time in Z2 (p value = 0.001; η (2) = 0.054; minimum effect), %time in Z4 (p value = 0.001; η (2) = 0.031; minimum effect) and %time in Z5 (p value = 0.001; η (2) = 0.053; minimum effect). The analysis in male players revealed differences between football and futsal in %HRmax (p value = 0.001; η (2) = 0.172; minimum effect). Similar results were found in female category (p value = 0.001; η (2) = 0.040; minimum effect). In this study it was possible to verify that female players spent more time in high intensity zones and that futsal training sessions are more intense than football sessions. Based on such results, coaches and fitness trainers may identify the physiological characteristics of training load imposed to different sports and genders and optimize the training plan for specific categories.
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This study aims to describe the time-motion and physiological performance profiles of footballers whose ages are under 15 (U15), under 17 (U17), and under 19 (U19) during a typical week of a competitive season. A total of 151 elite Portuguese players U15 (age 14.0 ± 0.2; n = 56), U17 (age 15.8 ± 0.4; n = 66), and U19 (age 17.8 ± 0.6; n = 19) were monitored during 33 training sessions (TSs) (U15 n = 12; U17 n = 11; and U19 n = 10 TSs). The TS data were captured at 15 Hz by global positioning systems devices and divided into post-match (session after the match), prematch (session before the match), and middle week (average of remaining sessions). The U15 middle week showed a higher number of sprints, distance covered in intermediate speed zones, and time spent above 90% HRmax, while the prematch presented a higher distance covered above 18 km · h(-1) and time spent below 75% HRmax. In U17, both prematch and post-match data presented lower values than middle-week data in most of the variables. The post-match data in U19 presented higher values of distance covered above 13 km · h(-1), body impacts above 10 G, and time spent above 85% HRmax, while middle week showed higher values in body impacts in most of the zones. In addition, the prematch data presented 35% to 100% less values than the middle-week data. Understanding the weekly workload variations according to the competition and the developmental ages of the players can contribute to optimising short- and mid-term planning.