Effects of Chronological Age, Relative Age, and Maturation Status on Accumulated Training Load and Perceived Exertion in Young Sub-Elite Football Players

Two periodization strategies in professional football and their influence on accumulated training load and its distribution: Differences between starters and non-starters

This study compared weekly training-load (TL), training-monotony (TM), and training-strain (TS) in 80 professional football players (28.1 ± 3.2 yrs, 78.0 ± 5.9 kg, and 182.0 ± 4.8 cm), considering two lengths (6 and 7 days between matches), two types of periodization strategies (placing the compensatory session in MD+1 [P1] or MD+2 [P2] post-match-day) and two players' status, starters, and non-starters. Using Global Positioning Technology, the monitored variables were: Player Load (PL), Total Distance (TD), distances at various speeds (>21 [HSR], >24 [VHSR], and > 27 [SPR] km·h-1), number of accelerations (>2 m·s-2, ACC), and decelerations (<-2 m·s-2, DEC). Kruskal-Wallis and Mann-Whitney non-parametric statistical tests were used for loading strategy differences. In both lengths and periodization strategies of the micro-cycles, non-starters trained more than starters. There were differences in the quantity (TL) and distribution (TM and TS) demand considering the micro-cycle's length and periodization strategy. In MD+1 (P1), non-starters accumulated higher TL, showing moderate to large Cohen's d magnitudes in HSR, VHSR, SPR, PL, and TD. For starters, training in MD+2 (P2) resulted in higher values (p < 0.05) of TL, TM and TS. The coaching staff needs to anticipate TL, TM, and TS by considering players' status, periodization strategy, and the number of training sessions between matches.

The Influence of Somatic Maturity on Anthropometrics and Body Composition in Youth Soccer Players

The primary aim of this investigation was to compare players' anthropometric (AP) and body composition (BC) characteristics between distinct maturity bands (pre-PHV, circa-PHV, post-PHV) in youth elite soccer. This study considered 320 male soccer players (mean age 13.8 y). Participants were from U14 (n = 157) and U15 (n = 163) age categories. The Khamis-Roche method was applied to calculate the percentage of predicted adult height (PAH) at the time of assessment based on which the players were further divided into maturity bands (pre-PHV ≤ 87%, circa-PHV = 88-95%, post-PHV > 95%). The findings indicated that most of the players were in the circa-PHV stage at the time of investigation. Measurements included height and weight. The estimates of BC parameters were derived using bioelectrical impedance (BIA) analysis. These various AP and BC attributes displayed significant differences among the maturity bands (F = 139.344-7.925; p < 0.001; large effect sizes) except in body fat mass (BFM) (F = 2.998; p = 0.051; small effect size). The current somatic maturity stage of the athletes should be considered when evaluating BC results, otherwise there is a risk of misinterpretation.

Resultant equations for training load monitoring during a standard microcycle in sub-elite youth football: a principal components approach

Applying data-reduction techniques to extract meaningful information from electronic performance and tracking systems (EPTS) has become a hot topic in football training load (TL) monitoring. The aim of this study was to reduce the dimensionality of the internal and external load measures, by a principal component approach, to describe and explain the resultant equations for TL monitoring during a standard in-season microcycle in sub-elite youth football. Additionally, it is intended to identify the most representative measure for each principal component. A principal component analysis (PCA) was conducted with a Monte Carlo parallel analysis and VariMax rotation to extract baseline characteristics, external TL, heart rate (HR)-based measures and perceived exertion. Training data were collected from sixty sub-elite young football players during a 6-week training period using 18 Hz global positioning system (GPS) with inertial sensors, 1 Hz short-range telemetry system, total quality recovery (TQR) and rating of perceived exertion (RPE). Five principal components accounted for 68.7% of the total variance explained in the training data. Resultant equations from PCA was subdivided into: (1) explosiveness, accelerations and impacts (27.4%); (2) high-speed running (16.2%); (3) HR-based measures (10.0%); (4) baseline characteristics (8.3%); and (5) average running velocity (6.7%). Considering the highest factor in each principal component, decelerations (PCA 1), sprint distance (PCA 2), average HR (PCA 3), chronological age (PCA 4) and maximal speed (PCA 5) are the conditional dimension to be considered in TL monitoring during a standard microcycle in sub-elite youth football players. Current research provides the first composite equations to extract the most representative components during a standard in-season microcycle in sub-elite youth football players. Futures research should expand the resultant equations within training days, by considering other well-being measures, technical-tactical skills and match-related contextual factors.

Clustering U-14 Portuguese regional team football players by lower limb strength, power, dynamic balance, speed and change of direction: understanding the field position factor

Objectives

The aim of this study was to cluster U-14 Portuguese regional team football players based on variables related to lower limb strength and power, dynamic balance, linear sprint, and change of direction.

Method

The sample consisted of 22 young male soccer players (13.83 ± 0.44 years). A set of variables related to lower limb strength and power, dynamic balance, linear sprint, and change of direction was measured.

Results

Overall, a non-significant field position was observed. The countermovement jump (p < 0.001, η² = 0.73), squat jump (p < 0.001), and 30 m linear sprint (p = 0.001) were the main variables responsible for establishing the clusters. Cluster 1 was characterized by a high slalom, i.e., it took longer to complete the test (speed and change of direction) and a low composite score in the dynamic balance. Cluster 2 was characterized by high squat jump, countermovement jump, and reactive strength ratio (lower limb strength and power). Cluster 3 was characterized by low squat jump and countermovement jump (lower limb strength and power), and a high 30 m sprint, i.e., it took longer to complete the test (speed and change of direction). Based on the results of the territorial map, the clusters consisted of: (i) cluster 1: two forwards, one midfielder, and five defenders; (ii) cluster 2: three forwards, two midfielders, and two defenders, and; (iii) cluster 3: four midfielders and three defenders.

Conclusions

Players from different field positions composed the three clusters. There was no cluster composed exclusively of players of the same field position. The development of individualized and specific enrichment training programs should consider a cluster analysis, as the positional effect can be overlooked.

Tactical Knowledge by Decision Making and Motor Efficiency of Young Football Players in Different Playing Positions during a Three-a-Side Small-Sided Game

The aim of this study was to compare the tactical knowledge of young football players in different playing positions during a three-a-side small-sided game (SSG). Observational data was collected from 71 players (M = 12.16; SD = 1.55 years): 11 goalkeepers, 22 defenders, 15 midfielders, and 23 forwards. In total, 4 min of three-a-side SSGs (GR + 3 vs. 3 + GR) were recorded to assess tactical performance using a digital camera (GoPro Hero 6^® version 02.01). The SSGs were performed on a field with a constant area (36 × 27 m). Video analyses were performed using LongoMatch^® version 1.5.9 to record football performance; we then assessed tactical performance by using the Football Tactical Assessment System (Fut-Sat). This instrument evaluates the average of well-defined action indexes for each game in decision making principle and motor skills, specifically: (i) Decision Making Index (DMI); (ii) Motor Effectiveness Index (MEI); (iii) Effectiveness Index (I). The indexes were calculated by the ratio between the correct actions and the total. The Kruskal-Wallis test was used to evaluate differences between playing positions. The results showed that tactical performance by principles seems to be significantly different according to playing position. Differences were found between defenders and forwards (H = -11.92; p = 0.03) and defenders and midfielders (H = -16.13; p = 0.01) in contention principle. In conclusion, tactical knowledge of training based on the principles of the game can help coaches and players better understand and predict each player's actions during the game.

Exercise Biomechanics for Health: Evaluating Lifelong Activities for Well-Being

Biomechanics is a multidisciplinary study of the mechanical laws and principles that govern human movement and the functioning of biological systems [...].

Integrating physical and tactical factors in football using positional data: a systematic review

Background

Positional data have been used to capture physical and tactical factors in football, however current research is now looking to apply spatiotemporal parameters from an integrative perspective. Thus, the aim of this article was to systematically review the published articles that integrate physical and tactical variables in football using positional data.

Methods and Materials

Following the Preferred Reporting Item for Systematic Reviews and Meta-analyses (PRISMA), a systematic search of relevant English-language articles was performed from earliest record to August 2021. The methodological quality of the studies was evaluated using the modified Downs and Black Quality Index (observational and cross-sectional studies) and the Physiotherapy Evidence Database (PEDro) scale (intervention studies).

Results

The literature search returned 982 articles (WoS = 495; PubMed = 232 and SportDiscus = 255). After screening, 26 full-text articles met the inclusion criteria and data extraction was conducted. All studies considered the integration of physical and tactical variables in football using positional data (n = 26). Other dimensions were also reported, such as psychophysiological and technical factors, however the results of these approaches were not the focus of the analysis (n = 5). Quasi-experimental approaches considered training sets (n = 20) and match contexts (n = 6). One study analysed both training and play insights. Small sided-games (SSG) were the most common training task formats in the reviewed studies, with only three articles addressing medium-sided (MSG) (n = 1) and large-sided games (LSG) (n = 2), respectively.

Conclusions

Among the current systematic review, the physical data can be integrated by player's movement speed. Positional datasets can be computed by spatial movement, complex indexes, playing areas, intra-team and inter-team dyads. Futures researches should consider applying positional data in women's football environments and explore the representativeness of the MSG and LSG.

Maturation Selection Biases and Relative Age Effect in Italian Soccer Players of Different Levels

Simple Summary

Soccer academies and societies research young players who are supposed to possess great motor skills. In association with these, adolescents who appear to be talented exhibit more developed anthropometric and body composition features than untalented players. Although many selected soccer players appear to present an earlier maturation than their contemporaries, it is not clear whether soccer teams of different competition levels are aware of this aspect and considered these discrepancies in the scouting selection process. In addition, it remains unclear if the biological maturity and relative effect are two interchangeable methods of evaluation and if one of them deserves to be preferred by the soccer scouters. This research aims to investigate the effect of the team level, maturity status and relative-age effect, and their interactions, on body characteristics, cellularity, and physical performance in adolescent soccer players. Despite the relative age effect remaining the easier analysis to consider, the evaluation of maturity status seems to be the most reliable method to detect better capabilities due to early growth.

Abstract

Soccer is a sport practiced all over the world, in which players are expected to show specific physical and technical skills. Soccer academies look for young talented individuals to develop promising players. Although several parameters could affect the players’ performance, the relative age effect (RAE) and the maturity status appeared debated. Therefore, this study compared the differences in RAE and biological maturity among the players of two Italian soccer teams of different levels and to understand their interaction effects with the competition level on youth players’ physical characteristics and abilities. One hundred and sixty-two young soccer players from the U12 to U15 age categories of the elite (n = 98) and non-elite (n = 64) teams were recruited. The prevalence of maturity status and RAE was observed. Many anthropometric parameters, BIA vectors, and motor tests (CMJ, Sprint, RSA) were carried out. The maturity status had a greater effect on several anthropometric characteristics and on 15 m sprint, while it affected the CMJ only in U12 (F = 6.187, p ≤ 0.01). Differently, the RAE seemed to priorly affect the U13 and U15 categories in body composition, whereas its effect appeared on the 15-m sprint (F_{(3, 45)} = 4.147, p ≤ 0.01) and the RSA (F_{(3, 45)} = 3.179, p ≤ 0.05) in the U14 category. In addition, early matured players or those who were born in the first six months presented cellular characteristics similar to adult elite players. Soccer professionals should be encouraged to monitor the maturity status to better interpret changes in the physical performance of young soccer players to guide adequate training plans.

Weekly Training Load across a Standard Microcycle in a Sub-Elite Youth Football Academy: A Comparison between Starters and Non-Starters

Compensatory training sessions have been highlighted as useful strategies to solve the differential weekly training load between the players' starting status. However, the influence of the players' starting status is still understudied in sub-elite youth football. Thus, the aim of this study was to compare the weekly training load on a standard microcycle in starters and non-starters of a sub-elite youth football academy. The weekly training load of 60 young sub-elite football players was monitored during a 6-week period using an 18 Hz global positioning system (GPS), 1 Hz telemetry heart rate, rating of perceived exertion (RPE), and total quality recovery (TQR). The total distance (TD) covered presented a significant difference between starters and non-starters with a moderate effect (t = -2.38, Δ = -428.03 m, p = 0.018, d = 0.26). Training volume was higher in non-starters than in starter players (TD_Starters = 5105.53 ± 1684.22 vs. TD_Non-starters = 5533.56 ± 1549.26 m). Significant interactive effects were found between a player's starting status, playing time, and session duration in overall training load variables for within (F = 140.46; η² = 0.85; p < 0.001) and between-subjects (F = 11.63 to 160.70; η² = 0.05 to 0.76; p < 0.001). The player's starting status seems to only influence the training volume in sub-elite youth football, unless one considers the covariance of the playing time and session duration. Consequently, coaches should prioritize complementary training to equalize training volume and emphasize similar practice opportunities for non-starters. Future studies should evaluate the gap between training and match load, measuring the impact of recovery and compensatory sessions.

Training and match demands differ between the regular season and finals in semi-professional basketball

Basketball competitions often include a scheduled regular season followed by knock-out finals. Understanding training and match demands through the season can help optimize performance and reduce injury risk. This study investigated whether training and/or match demands differed between the regular season and finals, and whether these differences were dependent on player role. Average session intensity and volume and durations of relative exercise intensities (inactive, light, moderate-vigorous, maximal, supramaximal) were quantified during training sessions and matches using accelerometry in two semi-professional basketball teams (n = 23; 10 women, 13 men). Training and match demands were compared between the regular season (training: 445 observations; matches: 387 observations) and finals (training: 113 observations, matches: 75 observations) with consideration of player role (starters, in-rotation bench, out-rotation bench). During finals matches, starters received 4.4 min more playing time (p = 0.03), performed 14% more absolute maximal activity (p < 0.01) and had 8% less relative inactive time (p = 0.02) when compared to the regular season. Out-rotation bench players received 2.1 min less playing time (p < 0.01), performed 33% less absolute maximal activity (p = 0.01) and 57% less absolute supramaximal activity (p < 0.01) in finals when compared to the regular season. During finals training sessions, average training intensity was 5% higher (p = 0.02), absolute moderate-vigorous activity was 3% higher (p = 0.04), relative maximal activity was 12% higher (p < 0.01), and relative inactive time was 5% lower (p = 0.03) when compared to the regular season. These findings suggest starters need to be physically prepared for greater match demands during finals, while out-rotation bench players should supplement their training during finals with extra supramaximal activity to maintain their conditioning levels for matches.

Modeling the Major Influencing Factor on Match Running Performance during the In-Season Phase in a Portuguese Professional Football Team

The aim of this study was two-fold: (1) to analyze the influence of season phase (i.e., the start of the in-season and mid-in-season) on match running performance in a Portuguese professional football team; (2) to determine and model the main factor influencing match running performance during the in-season in this specific football team. Eighteen matches were collected by an 18 Hz global positioning system (GPS) from a professional Portuguese football team during the start of the in-season and mid-in-season. The match running performance was analyzed according to season phases, presenting significant differences in total distance (TD) (tlowerbound = 4.71, p < 0.001; tupperbound = −2.22, p = 0.002), average speed (AvS) (tlowerbound = 359.45, p < 0.001; tupperbound = −359.87, p < 0.001), and relative high speed running (rHSR) (tlowerbound = 13.10, p < 0.001; tupperbound = −10.21, p < 0.001). The logistic regression showed TD (β = −1.59, z = −2.84, p = 0.005) and AvS (β = 2.68, z = −2.84, p = 0.007) as the major factors influencing match running performance during seasonal variation. Sprints and accelerations showed no significance for predicting match running performance during the season phases (β = −0.05 to 1.07, z = −0.95 to 1.07, p = 0.29 to 0.72). Current research confirms that lower and upper bounds should be used to quantify seasonal differences on match running performance. TD and AvS were described as the main factors influencing match running performance during the in-season phase. Thus, it is important to highlight the pace and volume of the game to maximize match running performance.

The Role of Existential Concerns in the Individual's Decisions regarding COVID-19 Vaccine Uptake: A Survey among Non-Vaccinated Italian Adults during the Third Wave of the Pandemic

Recent studies have suggested that health constructs embraced by the Terror Management Theory (TMT) and the Basic Psychological Needs Theory (BPNT) may drive individuals' COVID-19 health-related decisions. This study examines the relationships between existential concerns (ECs; within the TMT), basic psychological needs (BPNs; within the BPNT) and COVID-19 vaccine hesitancy (VH), as well as the mediating role of negative attitudes toward COVID-19 vaccines. A cross-sectional survey was carried out from April to May 2021 on a sample of two hundred and eighty-seven adults (Mage = 36.04 ± 12.07; 59.9% females). Participants provided information regarding existential concerns, basic psychological needs, attitudes toward COVID-19 vaccines and vaccine hesitancy for Pfizer-BioNTech and AstraZeneca vaccines separately. Higher vaccine hesitancy (32.1%) and vaccine resistance (32.8%) rates were found for AstraZeneca than for Pfizer-BioNTech COVID-19 vaccine (22.3% and 10.1%, respectively). Structural equation modeling showed that existential concerns were related to Pfizer-BioNTech and AstraZeneca vaccine hesitancy both directly and indirectly through negative attitudes toward potential side effects of COVID-19 vaccines. The findings of the study confirm that the TMT is efficient in explaining COVID-19 vaccine hesitancy. Targeted efforts are needed to increase the acceptance of COVID-19 vaccines.