Anthropometric variables, propulsive force and biological maturation: A mediation analysis in young swimmers

The mediation effect of liver and anthropometric indices on the relationship between incidence of diabetes and physical activity: results of 5-year follow up azar cohort study

BACKGROUND

It has been documented that regular physical activity is considered one of the most effective strategies for preventing diabetes; however, it is not the sole contributing factor. Therefore, we decided to evaluate the meditation effect of liver function and anthropometric indices on the relationship between incidence of diabetes and physical activity (PA) in the Azar cohort population.

MATERIALS AND METHODS

Subjects who were diabetic in the baseline phase from 15,006 participants in study of azar cohort population were excluded and to follow up, a total of 13,253 people was included in the analysis. Demographic characteristics, physical activity, 10 anthropometric indices (AI) and seven liver indices (LI) were measured. Evaluated and displayed using Pearson correlation heatmap and canonical correlation of liver and anthropometric indices. The Generalized Structural Equation Modeling (GSEM) with the Maximum Likelihood method employed to estimate the model.

RESULTS

During the follow-up years, a total of 685 participants developed diabetes. The measurements of the AI were significantly higher in subjects with diabetes (P < .001). Patients with diabetes were older, had a higher proportion of women, and had lower values of PA (P < .05). Body Roundness Index (BRI) and Waist height ratio (WHtR) exhibited the largest AUCs for predicting diabetes onset risk (both AUC = 0.6989) among these anthropometric measures. The increase in AI (RR [95%CI] = 1.25 [1.22,1.29], P < .001) and liver enzyme (LE) (RR [95%CI] = 1.14 [1.08.1.19], P < .001) increase the risk of diabetes by 25% and 14%, respectively. Despite the mediation effects of AI and Liver Enzymes for an increase of one MET of PA, the risk of developing diabetes decreases by 5% (RR [95% CI] = .95 [.92,.99], P = .013). Around VAF = 53% of the association between PA and diabetes onset (Total effect: RR [95% CI] = .90 [.87,.94], P < .001) was mediated by AI and LE.

CONCLUSIONS

A low level of PA was found to be significantly correlated with high levels of AI and LI, all of which are associated with an increased risk of developing diabetes. These analyses provide evidence that when the relationship between PA and diabetes is mediated by AI and LI this association becomes stronger, with AI playing a more significant role than LI.

Is Warm-Up Preservation Modulated by Biological Maturation and Sex? Effects on Lower Limbs Performance

Children and adults may react differently to warm-up preservation due to different physical characteristics. This study aimed to: (i) assess the impact of different rewarm-up routines in swimmers during a transition phase (20-25 min), including passive rest (SWU) or dynamic activities (RWU), on countermovement jump and swimming start performances, and (ii) explore potential RWU adaptations considering maturity offset (peak height velocity-PHV) and sex. Performance was analyzed using mixed effect ANCOVA, considering protocol, maturity offset (pre-PHV, mid-PHV, post-PHV, and adv. post-PHV), and sex. Results favored RWU over SWU with substantial magnitudes for jump height: pre-PHV (min-20, ES = 1.21; min-25, ES = 1.65), mid-PHV (min-20, ES = 1.23; min-25, ES = 1.14), post-PHV (min-20, ES = 1.37; min-25, ES = 0.73), and adv. post-PHV (min-20, ES = 1.03; min-25, ES = 0.65). Significant interactions at 25 min (p = 0.033, 0.047) showed that RWU outperformed SWU, especially in younger groups (pre-PHV, mid-PHV). RWU was superior to SWU for the reactive strength index at 20 min (p = 0.042) and 25 min (p = 0.047), with females having lower RSI than males at 20 min (p = 0.008, p = 0.015) and 25 min (p = 0.049) in later developmental stages. The flight distance (p = 0.009) and horizontal hip velocity (p = 0.014) revealed significant three-way interactions, with the male adv. post-PHV group responding better to RWU. Knee angular velocity was also higher after RWU, with male adv. post-PHV group showing more pronounced improvements (p = 0.016). These results suggest that though RWU had higher influence in male adults, it is a valuable approach for varying ages athletes.

Effects of anthropometrics, thrust, and drag on stroke kinematics and 100 m performance of young swimmers using path-analysis modeling

The aim of this study was to understand the interactions between anthropometric, kinetic, and kinematic variables and how they determine the 100 m freestyle performance in young swimmers. Twenty-five adolescent swimmers (15 male and 10 female, aged 15.75 ± 1.01 years) who regularly participated in regional and national competitions were recruited. The 100 m freestyle performance was chosen as the variable to be predicted. A series of anthropometric (hand surface area-HSA), kinetic (thrust and active drag coefficient (CDA )), and kinematic (stroke length (SL); stroke frequency (SF), and swimming speed) variables were measured. Structural equation modeling (via path analysis) was used to develop and test the model. The initial model predicted performance with 90.1% accuracy. All paths were significant (p < 0.05) except the thrust-SL. After deleting this non-significant path (thrust-SL) and recalculating, the model goodness-of-fit improved and all paths were significant (p < 0.05). The predicted performance was 90.2%. Anthropometrics had significant effects on kinetics, which had significant effects on kinematics, and consequently on the 100 m freestyle performance. The cascade of interactions based on this path-flow model allowed for a meaningful prediction of the 100 m freestyle performance. Based on these results, coaches and swimmers should be aware that the swimming predictors can first meaningfully interact with each other to ultimately predict the 100 m freestyle performance.

Load-Velocity Profile and Active Drag in Young Female Swimmers: An Age-Group Comparison

PURPOSE

The present study aimed to establish differences in load-velocity profiling, active drag (AD), and drag coefficient (Cd) between 3 age groups of female swimmers.

METHODS

Thirty-three swimmers (11, 13, or 16 y old) were recruited. The individual load-velocity profile was determined for the 4 competitive swimming strokes. The maximal velocity (V0), maximal load (L0), L0 normalized to the body mass, AD, and Cd were compared between the groups. A 2-way analysis of variance and correlation analysis were conducted.

RESULTS

Compared with their younger counterparts, 16-year-old swimmers generally had larger V0, L0, and AD, which was particularly evident when comparing them with 11-year-old swimmers (P ≤ .052). The exception was breaststroke, where no differences were observed in L0 and AD and Cd was smaller in the 16-year-old group than the 11-year-old group (P = .03). There was a negative correlation between Cd and V0 for all groups in backstroke (P ≤ .038) and for the 11-year-old group and 13-year-old group in breaststroke (P ≤ .022) and front crawl (P ≤ .010). For the 16-year-old group, large correlations with V0 were observed for L0, L0 normalized to the body mass, and AD (P ≤ .010) in breaststroke and for L0 and AD with V0 in front crawl (P ≤ .042). In butterfly, large negative correlations with V0 were observed in the 13-year-old group for all parameters (P ≤ .027).

CONCLUSIONS

Greater propulsive force is likely the factor that differentiates the oldest age group from the younger groups, except for breaststroke, where a lower Cd (implying a better technique) is evident in the oldest group.

Growing up and reaching for the top: A longitudinal study on swim performance and its underlying characteristics in talented swimmers

The present study strived to gain a more profound understanding of the distinctions in development between swimmers who are considered to be on track to the elite level at late junior age (males aged 16; females aged 15) compared to those who are not. In this effort, swimmers were followed during their pubertal years (males aged 13-15; females aged 12-14), which marks a period when performance development aligns with maturation. Longitudinal data of 90 talented sprint and middle-distance swimmers on season best times (SBT) and underlying performance characteristics (anthropometrics, maximal swimming velocity, stroke index [SI] and countermovement jump [CMJ]) were collected over three swimming seasons. Based on their SBT at late junior age (males aged 16; females aged 15), swimmers were classified as high-performing late juniors or lower-performing late juniors. Retrospectively studying these swimmers, we found that all but two high-performing late juniors were already on track to the elite level at early junior age (males aged 13; females aged 12), evidenced with faster SBT throughout puberty compared to their lower-performing peers (p < 0.05). Independent sample t-tests revealed that high-performing late juniors significantly outscored their lower-performing peers when they were early juniors on maximal swimming velocity (males aged 13-15 and females aged 12-14), SI (males aged 13 and 14; females aged 12), CMJ (females aged 14) and height (females aged 13 and 14, p < 0.05). Additionally, multilevel models showed faster rates of development for high-performing late juniors on maximal swimming velocity (males and females) and SI (males) compared to lower-performing peers throughout puberty (p < 0.05). Higher initial levels of SBT and underlying performance characteristics at early junior age as well as the faster rates of development on SBT, maximal swimming velocity and SI (males only) during the pubertal years, may be crucial factors in maintaining the trajectory towards the elite level after puberty.

A comparison of load cell and pressure sensors to measure in-water force in young competitive swimmers

The purpose of this study was to compare the in-water force of young competitive swimmers using tethered swimming and differential pressure sensors. Thirty-one swimmers (16 girls and 15 boys) were randomly assigned to perform two in-water tests. Swimmers completed two maximum bouts of 25 m front crawl with a differential pressure system and a 30 s maximum bout with an attached load cell (tethered-swimming). The peak force (FPEAK, in N) of dominant and non-dominant upper limbs was retrieved for further analysis. Comparison between methods revealed significant differences in all force variables (p ≤ 0.05) and the biases (mean differences) were large in girls (FPEAK dominant, 45.89 N; FPEAK non-dominant, 43.79 N) and boys (FPEAK dominant, 67.26 N; FPEAK non-dominant, 61.78 N). Despite that, simple linear regression models between the two methods showed significant relationships with a moderate effect in all variables for girls, whereas in boys a high and moderate effect was verified for FPEAK of dominant and non-dominant limbs (respectively). It seems that using pressure sensors and tethered swimming leads to different FPEAK values in young competitive, where correction factors are needed to compare data between both methods.

Analysis of upper limb propulsion in young swimmers in front-crawl through Statistical Parametric Mapping

This study aimed to: (i) verify the within-subject effect of the dominant and non-dominant upper limb propulsion during consecutive arm-pulls through discrete (average) and continuous analysis (SPM), and; (ii) compare young swimmers' propulsion between both upper limbs through discrete (average) and continuous analysis (Statistical Parametric Mapping - SPM). The sample consisted of 17 young male swimmers (age = 16.02 ± 0.61-years) who regularly participate in national and international level competitions. A set of kinematic and propulsion variables were measured during a 25-m maximal trial in front-crawl. Statistical analysis of propulsion was performed using discrete variables and through SPM. Swimming velocity showed a significant decrease over time. A significant interaction between the "time" (consecutive arm-pulls) and "side" (dominant vs. non-dominant) effects was observed in both statistical analyzes. Only the dominant upper limb demonstrated a significant "time" effect with a significant difference (p < 0.05) between the first and third arm-pulls. SPM indicated that the "time" effect was observed between the ∼ 34% and ∼ 42% of the arm-pull. The differences between the first and third arm-pull were verified between the ∼ 32% and ∼ 43% of the arm-pull. A non-significant "side" effect was verified in both analyzes. Therefore, SPM analysis provided more sensitive and accurate outputs than discrete analysis. This will allow coaches to design specific training drills focused on specific moments of the arm-pull.

Interaction of Kinematic, Kinetic, and Energetic Predictors of Young Swimmers' Speed

PURPOSE

The aim of this study was to assess the interaction of kinematic, kinetic, and energetic variables as speed predictors in adolescent swimmers in the front-crawl stroke.

DESIGN

Ten boys (mean age [SD] = 16.4 [0.7] y) and 13 girls (mean age [SD] = 14.9 [0.9] y) were assessed.

METHODS

The swimming performance indicator was a 25-m sprint. A set of kinematic, kinetic (hydrodynamic and propulsion), and energetic variables was established as a key predictor of swimming performance. Multilevel software was used to model the maximum swimming speed.

RESULTS

The final model identified time (estimate = -0.008, P = .044), stroke frequency (estimate = 0.718, P < .001), active drag coefficient (estimate = -0.330, P = .004), lactate concentration (estimate = 0.019, P < .001), and critical speed (estimate = -0.150, P = .035) as significant predictors. Therefore, the interaction of kinematic, hydrodynamic, and energetic variables seems to be the main predictor of speed in adolescent swimmers.

CONCLUSIONS

Coaches and practitioners should be aware that improvements in isolated variables may not translate into faster swimming speed. A multilevel evaluation may be required for a more effective assessment of the prediction of swimming speed based on several key variables rather than a single analysis.

Identifying Differences in Swimming Speed Fluctuation in Age-Group Swimmers by Statistical Parametric Mapping: A Biomechanical Assessment for Performance Development

The aim of this study was to compare the assessment of swimming speed processed as a discrete variable and as a continuous variable in young swimmers. One-hundred and twenty young swimmers (60 boys: age = 12.91 ± 0.86 years; 60 girls: age = 12.46 ± 0.94 years) were analysed. The dataset for each sex was divided into three tiers: (i) tier #1 - best-performing swimmers; (ii) tier #2: intermediate-performing swimmers, and; (iii) tier #3 - poorest-performing swimmers. As a discrete variable, swimming speed showed significant sex and tier effects, and a significant sex*tier interaction (p < 0.001). Speed fluctuation showed a non-significant sex effect (p > 0.05), a significant tier effect (p < 0.001), and a non-significant sex*tier interaction (p > 0.05). As a continuous variable, the swimming speed time-curve presented significant sex and tier effects (p < 0.001) throughout the stroke cycle, and a significant sex*tier interaction (p < 0.05) in some moments of the stroke cycle. Swimming speed fluctuation analysed as a discrete variable and as a continuous variable can be used in a complementary way. Nonetheless, SPM can provide deeper insight into differences within the stroke cycle. Thus, coaches and practitioners should be aware that different knowledge about the swimmers' stroke cycle can be learned by assessing swimming speed using both methods.

Body composition and anthropometrics of young male swimmers in relation to the tethered swimming and kinematics of 100-m front crawl race

BACKGROUND

The aim was to analyze the relationship of body mass and predicted muscle mass of body segments on swimming kinematics and tethered swimming indices, and further assess the influence of those indices on 100-m front crawl performance of adolescent male swimmers.

METHODS

In 19 volunteer swimmers (age: 13.5±0.44 years, height: 168.6±7.77 cm, body mass: 56.9±10.57 kg), the predicted muscle mass of body segments was assessed with bioelectrical impedance analysis. The kinematic indices of swimming (stroke rate - SR, stroke length - SL, and stroke index - SI) were calculated from a video recording of a 100-m front crawl race. The strength indices (maximum and average value of force, average impulse per single cycle, force decline) were collected in a 30-second front crawl tethered swimming test.

RESULTS

The average tethered swimming force was positively correlated with surface swimming speed (0.505; P≤0.05). Indices of SL, SI were influenced by average impulse per single cycle (0.58, 0.55; P≤0.05), and further the SI was strongly correlated with most specified speed indices of the 100-m race (0.59; P≤0.05).

CONCLUSIONS

It can be stated that the ability of force development in a single stroke, owing to strong interrelation with SI, is a good predictor in talent identification among young swimmers.

Using Statistical Parametric Mapping to Compare the Propulsion of Age-Group Swimmers in Front Crawl Acquired with the Aquanex System

Understanding the difference in each upper limb between age groups can provide deeper insights into swimmers’ propulsion. This study aimed to: (1) compare swimming velocity and a set of kinematical variables between junior and juvenile swimmers and (2) compare the propulsion outputs through discrete and continuous analyses (Statistical Parametric Mapping—SPM) between junior and juvenile swimmers for each upper limb (i.e., dominant and non-dominant). The sample was composed of 22 male swimmers (12 juniors with 16.35 ± 0.74 years; 10 juveniles with 15.40 ± 0.32 years). A set of kinematic and propulsion variables was measured at maximum swimming velocity. Statistical Parametric Mapping was used as a continuous analysis approach to identify differences in the propulsion of both upper limbs between junior and juvenile swimmers. Junior swimmers were significantly faster than juveniles (p = 0.04, d = 0.86). Although juniors showed higher propulsion values, the SPM did not reveal significant differences (p < 0.05) for dominant and non-dominant upper limbs between the two age groups. This indicates that other factors (such as drag) may be responsible for the difference in swimming velocity. Coaches and swimmers should be aware that an increase in propulsion alone may not immediately lead to an increase in swimming velocity.

Maturation-based Corrective Adjustment Procedures (Mat-CAPs) in youth swimming: Evidence for restricted age-group application in females

Inter-individual differences in maturation-associated development can lead to variations in physical performance, resulting in performance (dis)advantages and maturation selection bias within youth sport systems. To address such bias and account for maturational differences, Maturation-based Corrective Adjustment Procedures (Mat-CAPs) could be beneficial. The present study aimed to: (1) determine maturity timing distributions in youth female swimming; (2) quantify the relationship between maturation status and 100-m front-crawl (FC) performance; (3) implement Mat-CAPs to remove maturational influences upon swimming performance. For Aim 1 and 2, participants were 663 female (10–15 years) swimmers who participated in 100-m FC events at Australian regional, state, and national-level competitions between 2016–2020 and underwent anthropometric assessment (mass, height and sitting height) to estimate maturity timing and offset. For Aim 3, participants aged 10–13 years were categorised into maturity timing categories. Maturity timing distributions for Raw (‘All’, ‘Top 50%’ and ‘Top 25%’) and Correctively Adjusted swim times were examined. Chi-square, Cramer’s V and Odds Ratios determined the presence of maturation biases, while Mat-CAPs identified whether such biases were removed in targeted age and selection-groups. Results identified that between 10–13 years, a significantly higher frequency of ‘early’ maturers was apparent, although tapered toward higher frequencies of ‘Late-normative’ maturers by 14–15 years. A curvilinear relationship between maturity-offset and swim performance was identified (R²= 0.51, p<0.001) and utilised for Mat-CAPs. Following Mat-CAPs application, maturity timing biases evident in affected age-groups (10–13 years), and which were magnified at higher selection levels (‘Top 50%’ & ‘25%’ of swim performances) were predominantly removed. Findings highlight how maturation advantages in females occurred until approximately 13 years old, warranting restricted Mat-CAPs application. Mat-CAPS has the potential to improve female swimmer participation experiences and evaluation.

Gender Differences and the Influence of Body Composition on Land and Pool-Based Assessments of Anaerobic Power and Capacity

Consistent differences between males and females have been shown in land-based measurements of anaerobic power and capacity. However, these differences have not been investigated for a tethered 30-s maximal swimming test (TST). The purpose of this study is to explore gender differences in land and pool-based assessments of anaerobic power (Fpeak) and capacity (Fmean), as well as the influence of body composition. Thirteen males and fifteen females completed land (Wingate (WAnT)) and pool-based (TST) measures of anaerobic power and capacity previously described in the literature. Additionally, the subjects completed assessments of body composition via air displacement plethysmography. The males produced higher force than the females for Fpeak (p < 0.001) and Fmean (p = 0.008) during the TST. However, linear regression analysis determined that lean mass significantly predicted Fpeak (p = 0.002) and Fmean (p < 0.001) during the TST, while gender was no longer significant (p = 0.694 and p = 0.136, respectively). In conclusion, increases in anaerobic power and capacity (Fpeak and Fmean) may be a function of increased lean mass in males and females, warranting future research on the impact of resistance training programs on force production and swimming performance.

Comparing cross-sectional and longitudinal tracking to establish percentile data and assess performance progression in swimmers

To provide percentile curves for short-course swimming events, including 5 swimming strokes, 6 race distances, and both sexes, as well as to compare differences in race times between cross-sectional analysis and longitudinal tracking, a total of 31,645,621 race times of male and female swimmers were analyzed. Two percentile datasets were established from individual swimmers’ annual best times and a two-way analysis of variance (ANOVA) was used to determine differences between cross-sectional analysis and longitudinal tracking. A software-based percentile calculator was provided to extract the exact percentile for a given race time. Longitudinal tracking reduced the number of annual best times that were included in the percentiles by 98.35% to 262,071 and showed faster mean race times (P < 0.05) compared to the cross-sectional analysis. This difference was found in the lower percentiles (1st to 20th) across all age categories (P < 0.05); however, in the upper percentiles (80th to 99th), longitudinal tracking showed faster race times during early and late junior age only (P < 0.05), after which race times approximated cross-sectional tracking. The percentile calculator provides quick and easy data access to facilitate practical application of percentiles in training or competition. Longitudinal tracking that accounts for drop-out may predict performance progression towards elite age, particularly for high-performance swimmers.

Understanding the Role of Propulsion in the Prediction of Front-Crawl Swimming Velocity and in the Relationship Between Stroke Frequency and Stroke Length

Introduction: This study aimed to: 1) determine swimming velocity based on a set of anthropometric, kinematic, and kinetic variables, and; 2) understand the stroke frequency (SF)–stroke length (SL) combinations associated with swimming velocity and propulsion in young sprint swimmers.

Methods: 38 swimmers (22 males: 15.92 ± 0.75 years; 16 females: 14.99 ± 1.06 years) participated and underwent anthropometric, kinematic, and kinetic variables assessment. Exploratory associations between SL and SF on swimming velocity were explored using two two-way ANOVA (independent for males and females). Swimming velocity was determined using multilevel modeling.

Results: The prediction of swimming velocity revealed a significant sex effect. Height, underwater stroke time, and mean propulsion of the dominant limb were predictors of swimming velocity. For both sexes, swimming velocity suggested that SL presented a significant variation (males: F = 8.20, p < 0.001, η² = 0.40; females: F = 18.23, p < 0.001, η² = 0.39), as well as SF (males: F = 38.20, p < 0.001, η² = 0.47; females: F = 83.04, p < 0.001, η² = 0.51). The interaction between SL and SF was significant for females (F = 8.00, p = 0.001, η² = 0.05), but not for males (F = 1.60, p = 0.172, η² = 0.04). The optimal SF–SL combination suggested a SF of 0.80 Hz and a SL of 2.20 m (swimming velocity: 1.75 m s⁻¹), and a SF of 0.80 Hz and a SL of 1.90 m (swimming velocity: 1.56 m s⁻¹) for males and females, respectively. The propulsion in both sexes showed the same trend in SL, but not in SF (i.e., non-significant variation). Also, a non-significant interaction between SL and SF was observed (males: F = 0.77, p = 0.601, η² = 0.05; females: F = 1.48, p = 0.242, η² = 0.05).

Conclusion: Swimming velocity was predicted by an interaction of anthropometrics, kinematics, and kinetics. Faster velocities in young sprinters of both sexes were achieved by an optimal combination of SF–SL. The same trend was shown by the propulsion data. The highest propulsion was not necessarily associated with higher velocity achievement.

Young Swimmers' Classification Based on Performance and Biomechanical Determinants: Determining Similarities Through Cluster Analysis

The aim of this study was to classify and identify young swimmers' performance, and biomechanical determinant factors, and understand if both sexes can be clustered together. Thirty-eight swimmers of national level (22 boys: 15.92 ± 0.75 years and 16 girls: 14.99 ± 1.06 years) were assessed. Performance (swim speed at front crawl stroke) and a set of kinematic, efficiency, kinetic, and hydrodynamic variables were measured. Variables related to kinetics and efficiency (p < .001) were the ones that better discriminated the clusters. All three clusters included girls. Based on the interaction of these determinant factors, there are girls who can train together with boys. These findings indicate that not understanding the importance of the interplay between such determinants may lead to performance suppression in girls.

How Anthropometrics of Young and Adolescent Swimmers Influence Stroking Parameters and Performance? A Systematic Review

The purpose of this systematic review was to investigate the relationship between anthropometric characteristics, biomechanical variables and performance in the conventional swimming techniques in young and adolescent swimmers. A database search from 1 January 2001 to 30 June 2021 was done according to the PRISMA statement, with 43 studies being selected for analysis. Those manuscripts were divided in butterfly, backstroke, breaststroke and front crawl techniques as main categories. The results showed the importance of the anthropometric variables for the performance of the young swimmer, although there was a lack of variables common to the studies that analysed the butterfly, backstroke and breaststroke techniques. For the front crawl technique there is a consensus among studies on the advantage of having higher height and arm span values, variables that concurrently with high body mass and lean body mass values, contribute positively to better stroke length and stoke index values.

Biological Age in Relation to Somatic, Physiological, and Swimming Kinematic Indices as Predictors of 100 m Front Crawl Performance in Young Female Swimmers

BACKGROUND

Some swimmers reach high performance level at a relatively young age. The purpose of this study is to determine the relationship between adolescent female swimmers' 100 m front crawl race (Vtotal100) and several anthropometry, body composition, and physiological and specific strength indices.

METHODS

Nineteen adolescent female swimmers were examined for biological age (BA) and body composition. Oxygen uptake was measured during water-flume stage-test front crawl swimming with ventilatory thresholds examination. Specific strength indices were assessed during 30 s of tethered swimming. Stroke rate (SR), stroke length (SL), and stroke index (SI) were also examined.

RESULTS

BA was strongly correlated with anthropometrics and tethered swimming strength indices, and showed moderate to strong correlation with ventilatory thresholds. Speed of swimming in the race was moderately to largely correlated with speed at V˙O2&nbsp;max-VV˙O2max (r = 0.47-0.55; p < 0.05)-ventilatory thresholds (VAT,&nbsp;VRCP) (r = 0.50-0.85; p < 0.05), SL (r = 0.58-0.62; p < 0.05), and SI (r = 0.79-0.81; p < 0.01).

CONCLUSION

Results confirmed a significant role of biological maturation mediation on body composition and body size, ventilatory indices, and specific strength indices. BA was not a significant mediation factor influencing the swimming kinematics (SL, SI) and speeds of VAT, VRCP or VV˙O2&nbsp;max, which were strong predictors of the 100 m race.

Testosterone and lean mass show a positive correlation with the technical performance of footballers

BACKGROUND

Monitoring technical performance during a soccer match has become an indispensable practice, since the players perform different functions within the tactical system adopted by the team, resulting in specific technical actions that are fully responsive to the individual technical level of each player. Thus, current study aimed to investigate the possible direct and mediating relationship between salivary testosterone and the technical performance of semi-professional footballers during a training game.

METHODS

To characterize the sample, the anthropometric profile, body composition, biological maturation, lower limb power, speed, estimation of maximum oxygen consumption, and physical performance were used. To determine testosterone concentrations, saliva was collected before and after the training game, for subsequent measurement using enzyme immunoassay (ELISA) and Salimetrics Kits. For quantification of technical performance and participation with the ball during the training game, scout software was used from the footage of the training game. The reliability of the technical performance analyses was determined through the repetition test of two attempts (Cohen's Kappa agreement index).

RESULTS

The direct relationship between post-game testosterone and total participation with the ball in the second half; the direct relationship between the percentage of lean mass with post-game testosterone and an apparent relationship between percentage of lean mass and total participation with the ball from the set of relations mediated by post-game testosterone concentrations.

CONCLUSIONS

The results suggest that testosterone concentrations combined with high levels of lean mass may have a important role in the technical performance and participation with the ball of semi-professional footballers.