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Eduardo A. Abade, Bruno V. Gonçalves, Nuno M. Leite and Jaime E. Sampaio

Purpose:

To provide the time–motion and physiological profile of regular training sessions (TS) performed during the competitive season by under-15 (U15), under-17 (U17), and under-19 (U19) elite-level Portuguese soccer players.

Methods:

One hundred fifty-one elite players of U15 (age 14.0 ± 0.2 y, n = 56), U17 (age 15.8 ± 0.4 y, n = 66), and U19 (age 17.8 ± 0.6 y, n = 29) participated in the study during a 9-wk period. Time–motion and body-impact data were collected using GPS technology (15 Hz) across 38 randomly selected TS that resulted in a total of 612 samples. In addition, heart rate (HR) was continuously monitored (1 Hz) in the selected TS.

Results:

The total distances covered (m) were higher in U17 (4648.3 ± 831.9), followed by U19 (4212.5 ± 935.4) and U15 (3964.5 ± 725.4) players (F = 45.84, P < .001). Total body impacts and relative impacts were lower in U15 (total: 490.8 ± 309.5, F = 7.3, P < .01), but no differences were identified between U17 (total: 584.0 ± 363.5) and U19 (total: 613.1 ± 329.4). U19 players had less high- and very-high-intensity activity (above 16 km/h; F = 11.8, P < .001) and moderate-intensity activity (10.0–15.9 km/h; F = 15.07, P < .001). HR values showed significant effects of zone (F = 575.7, P < .001) and interaction with age group (F = 9.7, P < .001), with pairwise differences between all zones (zone 1, <75%; zone 2, 75–84.9%; zone 3, 85–89.9%; zone 4, ≥90%). All players spent most of their time below 75% HRmax (U15, ~50%; U17, ~42%; U19, ~50%).

Conclusion:

Results showed high variability between TS, refraining from identifying meaningful trends when measuring performance, although different demands were identified according to age group. The U15 TS were less physiologically demanding, probably because of increased focus on small-sided games to develop basic tactical principles and technical skills. The focus on game-like situations imposed higher external and internal workloads on U17 and U19 players.

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Antonio García de Alcaraz, David Valadés and José M. Palao

Purpose:

To assess the evolution of the volleyball’s game demands throughout players’ development in men’s volleyball.

Methods:

A total of 150 sets and 6.671 rallies were analyzed. The sample was composed of 30 sets each by under-14, under-16, under-19, national senior, and international senior teams (1.291, 1.318, 1.310, 1.372, and 1.380 rallies for each category, respectively). Sets included in the sample were stratified and then randomly selected. The variables studied included play time, rest time, rallies played, jumps, hits, types of ball contact, types of game interruptions, performance of the game phases, and performance of the actions. Student t and Mann Whitney U tests were used to analyze specific differences between categories.

Results:

The results showed significant reductions in the play times of the rally (from 8.91 to 6.79 s) and the set (6 min 23 s to 4 min 30 s), significant increases in the rest times of the rally (19.64 to 26.53 s) and the set (13 min 44 s to 20 min 27 s), and a significant increase in the number of jumps per set (113.5 to 181.3). Significant improvements in the reception performance (1.57 to 2.45 out of 3), attack performance (2.13 to 2.67 out of 4), and side-out-phase success (48.4% to 69.6%) were found. Throughout the players’ development, data show an increase in the speed, intensity, and efficacy of the side-out phase.

Conclusions:

The findings provide reference values to guide athletes’ development and to monitor training and matches both physically and technically tactically.

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Stein G.P. Menting, Marco J. Konings, Marije T. Elferink-Gemser and Florentina J. Hettinga

participants were categorized in age groups based on the skater’s year of birth and the year in which the analyzed race was performed. Participants younger than 17 years were placed in the group under 17 (U17), participants who were 17 and 18 years old were placed in group under 19 (U19), participants who were

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Romuald Lepers, Paul J. Stapley and Thomas Cattagni

similar durations: 50-m swimming, 200-m track cycling, and 100-m sprint running. Methods To investigate the age-related decline in swimming (1500 and 50 m), cycling (1 h and 200 m), and running (10 and 100 m), we compared the actual world-best performances achieved in the following age groups: 18 to 39

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Ken Pitetti, Ruth Ann Miller and E. Michael Loovis

adolescents with developmental disabilities. Data Analysis Data were collected over a 6-year period. Some participants were evaluated 2–6 times as they advanced in age group (Table  3 ). Previous work has established that BOT test scores assessed on a yearly basis are not influenced by a practice effect in

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Thomas Cattagni, Vincent Gremeaux and Romuald Lepers

. She was a French white, retired beautician, and was living in Burgundy, France. Her anthropometric characteristics are displayed in Table  1 . DL had broken 3 world records (3000-, 5000-, and 10,000-m running) in the 80-to-84-year-old age-group category, by the age of 80. For example, her record in 10

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Roberto Baldassarre, Marco Bonifazi, Paola Zamparo and Maria Francesca Piacentini

-water competitions. Nonconventional Races The world of OWS includes races longer than 25 km, such as the Marathon-Swim Lake Zurich, Manhattan Island Swim, and Maratona del Golfo Capri-Napoli, performed by elite and age-group athletes. In the Marathon-Swim Lake Zurich (26 km), participation has increased over the

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Angela Heidenfelder, Thomas Rosemann, Christoph A. Rüst and Beat Knechtle

Purpose:

To examine pacing strategies of ultracyclists competing in the Race Across AMerica (RAAM), the world’s longest ultracycling race, covering ~4860 km from the West to the East coast of America.

Methods:

Age, cycling speed at and across time stations, race distance, relative difference in altitude between time stations, wind velocity, wind gradient, and temperature at each time station were recorded for women and men competing from 2010 to 2014. Changes in cycling speed and power output of elite and age-group finishers were analyzed using mixed-effects regression analyses.

Results:

Cycling speed decreased across time stations for women and men where men were faster than women. Power output decreased across time stations in women and men and was lower for women for all finishers, the annual 3 fastest, and age group 60–69 y but not for age groups 18–49 and 50–59 y. The change in temperature and altitude had an influence on cycling speed and power output in all finishers, the annual top 3, nonfinishers, and in all different age groups for both women and men but in the age group 50–59 y altitude had no influence on cycling speed.

Conclusions:

Positive pacing (ie, decrease in speed throughout the race) seemed to be the adequate strategy in the RAAM. The top 3 finishers started faster and had a higher power output at the start than less successful competitors, achieved the highest peak cycling speeds and power output, and maintained peak cycling speed and power output longer before slowing down.

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Jason D. Vescovi

The aim of this study was to examine the impact of maximum sprint speed on peak and mean sprint speed during youth female field hockey matches. Two high-level female field hockey teams (U-17, n = 24, and U-21, n = 20) were monitored during a 4-game international test series using global position system technology and tested for maximum sprint speed. Dependent variables were compared using a 3-factor ANOVA (age group, position, and speed classification); effect sizes (Cohen d) and confidence limits were also calculated. Maximum sprint speed was similar between age groups and positions, with faster players having greater speed than slower players (29.3 ± 0.4 vs 27.2 ± 1.1 km/h). Overall, peak match speed in youth female field hockey players reaches approximately 90% of maximum sprint speed. Absolute peak match speed and mean sprint speed during matches were similar among the age groups (except match 1) and positions (except match 2); however, peak match speed was greater for faster players in matches 3 and 4. No differences were observed in the relative proportion for mean sprint speeds for age groups or positions, but slower players consistently displayed similar relative mean sprint speeds by using a greater proportion of their maximum sprint speed.