To apply a new method to identify, classify, and follow up young swimmers based on their performance and its determinant factors over a season and analyze the swimmers' stability over a competitive season with that method. Fifteen boys and 18 girls (11.8±0.7 y) part of a national talent-identification scheme were evaluated at 3 different moments of a competitive season. Performance (ie, official 100-m freestyle race time), arm span, chest perimeter, stroke length, swimming velocity, speed fluctuation, coefficient of active drag, propelling efficiency, and stroke index were selected as variables. Hierarchical and k-means cluster analysis were computed. Data suggested a 3-cluster solution, splitting the swimmers according to their performance in all 3 moments. Cluster 1 was related to better performances (talented swimmers), cluster 2 to poor performances (nonproficient swimmers), and cluster 3 to average performance (proficient swimmers) in all moments. Stepwise discriminant analysis revealed that 100%, 94%, and 85% of original groups were correctly classified for the 1st, 2nd, and 3rd evaluation moments, respectively (0.11≤Λ≤0.80; 5.64≤χ2≤63.40; 0.001<P≤.68). Membership of clusters was moderately stable over the season (stability range 46.1-75% for the 2 clusters with most subjects). Cluster stability is a feasible, comprehensive, and informative method to gain insight into changes in performance and its determinant factors in young swimmers. Talented swimmers were characterized by anthropometrics and kinematic features.

The benefits of warm-up in sports performance has received a special interest in the current literature. However, there is a large gap of knowledge about the tasks to be performed, specifically in the real competitive environment. The purpose of the study was to verify the acute effects of a warm-up including ballistic exercises in 100 m running performance. In addition, a second 100 m trial was assessed to better understand the warm-up effects in training and competition. Eleven men (25.4 ± 6.2 years of age, 1.76 ± 0.08 m of height, 78.2 ± 8.6 kg of body mass) were submitted to three different protocols, in a randomized order: no warm-up (NWU), typical warm-up (WU) and WU complemented with ballistic exercises (PAP). Biomechanical, physiological and psychophysiological variables were assessed. Differences were found between the three conditions assessed in the first 100 m sprint with 7.4% and 7.6% faster performances after the WU and PAP, compared to NWU. Stride length was higher in the second part of the 100 m after PAP compared with WU. These results highlight the positive effects of warm-up for sprinting performance. The inclusion of ballistic exercises, besides being used to improve sprint performance, can increase stride length in the final of the 100 m race.

The purpose of this study was to analyze the effect of gender and energetics on biomechanics and performance of masters swimmers over 1 season. Twenty-five masters swimmers (14 male and 11 female) were assessed 3 times (TP1, TP2, and TP3) during a season (male personal record in 200-m freestyle event: 173.00 ± 31.41 seconds: female personal record in 200-m freestyle event: 200.73 ± 25.02 seconds). An incremental 5 × 200-m step test was selected to evaluate velocity at 4 mmol·l⁻¹ of blood lactate concentration (v4), maximal blood lactate concentration after exercise (La(peak)), maximal oxygen uptake (V̇O2max), stroke frequency, stroke length (SL), stroke index (SI), and propelling efficiency of the arm stroke (η(p)). The 200-m freestyle performance and average swimming velocity (v200) were also monitored. Significant differences were observed between males and females for the 200-m freestyle performance, SL, SI, and La(peak). Performance (205.18 ± 24.47 seconds; 197.45 ± 20.97 seconds; 193.45 ± 18.12 seconds), SL (1.69 ± 0.17 m; 1.79 ± 0.13 m; 1.78 ± 0.15 m), SI (1.68 ± 0.31 m²·c⁻¹·s⁻¹; 1.83 ± 0.27 m²·c⁻¹·s⁻¹; 1.85 ± 0.27 m²·c⁻¹·s⁻¹), η(p) (0.32 ± 0.04; 0.33 ± 0.03; 0.33 ± 0.04), and V̇O2max (38.71 ± 3.44 ml·kg⁻¹·min⁻¹; 43.43 ± 3.71 ml·kg⁻¹·min⁻¹; 43.95 ± 7.02 ml·kg⁻¹·min⁻¹) have changed significantly throughout the season (TP1, TP2, and TP3, respectively) in female swimmers. In male, significant changes were found in η(p) (0.33 ± 0.07; 0.36 ± 0.05; 0.36 ± 0.06) and V̇O2max (41.65 ± 7.30 ml·kg⁻¹·min⁻¹; 45.19 ± 6.55 ml·kg⁻¹·min⁻¹; 50.19 ± 9.65 ml·kg⁻¹·min⁻¹) over the season (TP1, TP2, and TP3, respectively). Gender presented a significant effect on SL (TP2: η(p)² = 0.29; TP3: η(p)² = 0.37), SI (TP2: η(p)² = 0.25), and La(peak) (TP3: η(p)² = 0.42). v4 (TP1: η(p)² = 0.23), SL (TP1: η(p)² = 0.46), SI (TP1: η(p)² = 0.78; TP2: η(p)² = 0.37; TP3: η(p)² = 0.32), and η(p) (TP1: η(p)² = 0.28) had a significant effect on performance. Male masters swimmers have better performance, SL, SI, and La(peak) than female counterparts. Female masters swimmers enhanced significantly the 200-m freestyle performance over the season due to the improvement in swimming technique (SL, SI, and η(p)) and energetic factors (v4 and V̇O2max). Nonsignificant improvements were observed for the males' performance. Gender has a significant effect on SL, SI, and La(peak). Therefore, performance is more dependent on technical factors than energetics.

This study aimed to identify the effects of different pitch configurations on youth players positional and physical performances. Forty players participated in a Gk + 5vs5 + Gk small-sided game under four conditions: regular condition (regular), pitch with the direction of competitive matches; sided condition (sided), goals were changed to width; different pitch orientation (≠orientation), performed in side-to-side line compared to competitive matches; dynamic pitch (dynamic), boundaries were randomly changed every minute by: regular pitch; decrease 6 m width; diamond shape. The following variables were considered: players' effective playing space, distance between teammates' dyads time spent synchronized, average speed and a ratio between the distance covered at different intensities and distance covered while recovering. Overall, players exhibited better performances in pitches that are more representative of the environmental information seen during competitive matches (regular and ≠orientation). However, coaches may also use different boundary conditions to promote the players' ability to adapt to different context information.

The purpose of this study was to analyse the effect of players' dismissals on the outcome of attacks in elite futsal matches, and to establish the performance profile of the attacks made in numerical superiority by elite futsal teams. One hundred and twenty five attacking game situations in numerical superiority (dismissal of opponents from defensive team) were analysed from the regular season of the Spanish professional Futsal League. The effect of contextual-related variables (quality of opposition, match-location, match-periods, opponent team's fouls, match-status, attack-duration and match-type) on goal effectiveness was analysed using binomial logistic regression and two-step cluster analysis. Results from the binary logistic regression showed that the highest attack effectiveness was achieved when the teams play at home, perform the attack during minutes 33-36 and the opposing team has 3 fouls. Secondly, the two-step cluster analysis technique allowed identifying four types of attacks when the teams were playing with numerical superiority. The results showed the great importance (in order) of match-type, match-status, attacking team's fouls, match-period, quality of opposition, opposing team's fouls, match-location, goal situation, and attack duration. The identified trends may help coaches to design the superiority/inferiority scenarios more specifically during training and to monitor them during competition.

The aim was to develop a path-flow analysis model for young swimmers' performance based on biomechanical and energetic parameters, using structural equation modeling. Thirty-eight male young swimmers served as subjects. Performance was assessed by the 200-m freestyle event. For biomechanical assessment the stroke length, the stroke frequency and the swimming velocity were analyzed. Energetics assessment included the critical velocity, the stroke index and the propulsive efficiency. The confirmatory model explained 79% of swimming performance after deleting the stroke index-performance path, which was nonsignificant (SRMR = 0.06). As a conclusion, the model is appropriate to explain performance in young swimmers.

The aim of this study was to compare the effects of 2 different warm-up intensities on 100-m swimming performance in a randomized controlled trial. Thirteen competitive swimmers performed two 100-m freestyle time-trials on separate days after either control or experimental warm-up in a randomized design. The control warm-up included a typical race-pace set (4 × 25 m), whereas the experimental warm-up included an aerobic set (8 × 50 m at 98-102% of critical velocity). Cortisol, testosterone, blood lactate ([La]), oxygen uptake (V[Combining Dot Above]O2), heart rate, core (Tcore and Tcorenet) and tympanic temperatures, and rating of perceived exertion (RPE) were monitored. Stroke length (SL), stroke frequency (SF), stroke index (SI), and propelling efficiency (ηp) were assessed for each 50-m lap. We found that V[Combining Dot Above]O2, heart rate, and Tcorenet were higher after experimental warm-up (d > 0.73), but only the positive effect for Tcorenet was maintained until the trial. Performance was not different between conditions (d = 0.07). Experimental warm-up was found to slow SF (mean change ±90% CL = 2.06 ± 1.48%) and increase SL (1.65 ± 1.40%) and ηp (1.87 ± 1.33%) in the first lap. After the time-trials, this warm-up had a positive effect on Tcorenet (d = 0.69) and a negative effect on [La] (d = 0.56). Although the warm-ups had similar outcomes in the 100-m freestyle, performance was achieved through different biomechanical strategies. Stroke length and efficiency were higher in the first lap after the experimental warm-up, whereas SF was higher after control warm-up. Physiological adaptations were observed mainly through an increased Tcore after experimental warm-up. In this condition, the lower [La] after the trial suggests lower dependency on anaerobic metabolism.

Countermovement jump (CMJ) has been extensively used in training; yet, limited and contradictory kinematic data are available for trained subjects. To our best knowledge, no other studies have evaluated the associations between force-time curve characteristics and CMJ in a large sample of trained athletes using a linear transducer. Thus, the aim of this study was to determine the association between force-time measures and CMJ performance collected with a linear transducer. Thirty-five trained athletes were asked to perform 3 maximal weighted CMJ using a linear transducer attached to a barbell (17 kg). The data indicated that the maximal rate of force development (RFD(max)) was strongly related to CMJ displacement (r = 0.809/0.807, p < 0.001) and also to the percentage of peak force (r = -0.823/-0.809, p < 0.001) at RFD(max). Velocity and displacement at RFD(max) were not correlated to CMJ height. It was therefore concluded that the percentage of PF applied at RFD(max) and RFD(max) were the best predictive variables for CMJ performance in this study.

To investigate the effect of warm-up on 100-m swimming performance. Twenty competitive swimmers (with a training frequency of 8.0 ± 1.0 sessions/wk) performed 2 maximal 100-m freestyle trials on separate days, with and without prior warm-up, in a counterbalanced and randomized design. The warm-up distance totaled 1000 m and replicated the swimmers' usual precompetition warm-up strategy. Performance (time), physiological (capillary blood lactate concentrations), psychophysiological (perceived exertion), and biomechanical variables (distance per stroke, stroke frequency, and stroke index) were assessed on both trials. Performance in the 100-m was fastest in the warm-up condition (67.15 ± 5.60 vs 68.10 ± 5.14 s; P = .01), although 3 swimmers swam faster without warm-up. Critical to this was the 1st 50-m lap (32.10 ± 2.59 vs 32.78 ± 2.33 s; P < .01), where the swimmers presented higher distance per stroke (2.06 ± 0.19 vs. 1.98 ± 0.16 m; P = .04) and swimming efficiency compared with the no-warm-up condition (stroke index 3.46 ± 0.53 vs 3.14 ± 0.44 m2 · c1 · s1; P < .01). Notwithstanding this better stroke-kinematic pattern, blood lactate concentrations and perceived exertion were similar between trials. These results suggest that swimmers' usual warm-up routines lead to faster 100-m freestyle swimming performance, a factor that appears to be related to better swimming efficiency in the 1st lap of the race. This study highlights the importance of performing swimming drills (for higher distance per stroke) before a maximal 100-m freestyle effort in similar groups of swimmers.

The aim of this study was to analyse the relative age effect (RAE) in competitive swimming. The best 50 Portuguese swimmers (12- to 18-year-olds) for the main individual swimming pool events of both genders were considered. Analysis was conducted on 7813 swimming event participants, taking account of respective swimmer birth dates and the Fédération Internationale de Natation points gained. Differences in the distribution of birth dates by quarter year were determined using the Chi-square. A one-way analysis of variance ANOVA was used to test for differences measured in points between individuals by quarterly birth year intervals. A two-way analysis of variance ANOVA was also conducted to test the interaction between gender and seasonal birth date with regard to performance. The results show an inequitable distribution (p<0.01) of birth dates by quarter for almost all age groups and both genders. However, the distribution of birth dates by quarter for each considered swim event shows that RAE seems to exist only for 12-year-old females and 12- to 15-year-old males. Analysing mean swimming performance, post-hoc results (p<0.01) show no consistency in RAE. Higher performance occurs among older swimmers only in 100 m butterfly (female 1998, 1st≠2nd quarter, p=0.003). The results also show no interaction between gender and seasonal birth date (p<0.01). Findings of this study show that a higher number of swimmers, particular males, are born in the first two quarters of the year, although there is mostly no effect of seasonal birth date on performance differences within the top 50 swimmers.