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Federico Pizzuto, Matteo Bonato, Gialunca Vernillo, Antonio La Torre and Maria Francesca Piacentini

Purpose:

To analyze how many finalists of the International Association of Athletics Federations (IAAF) World Junior Championships (WJCs) in the middle- and long-distance track events had dropped out from high-level competitions.

Methods:

Starting from 2002, the 8 male and the 8 female finalists in the middle- and long-distance events of 6 editions of the WJC were followed until 2015 to evaluate how many missed the IAAF rankings for 2 consecutive years starting from the year after WJC participation. For those still competing at elite level, their careers were monitored.

Results:

In 2015, 61% of the 2002, 54.8% of the 2004, 48.3% of the 2006, 37.5% of the 2008, 26.2% of the 2010, and 29% of the 2012 WJC finalists were not present in the IAAF rankings. Of the 368 athletes considered, 75 (20.4%) were able to achieve the IAAF top 10 in 2.4 ± 2.2 y. There is evidence of relationships between dropout and gender (P = .040), WJC edition (P = .000), and nationality (P = .010) and between the possibility to achieve the IAAF top 10 and dropout (P = .000), continent (P = .001), relative age effect (P = .000), and quartile of birth (P = .050).

Conclusions:

Even if 23 of the finalists won a medal at the Olympic Games or at the World Championships, it is still not clear if participation at the WJC is a prerequisite to success at a senior level.

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Luca Filipas, Emiliano Nerli Ballati, Matteo Bonato, Antonio La Torre and Maria Francesca Piacentini

Purpose: To analyze the pacing profiles of the world’s top 800-m annual performances between 2010 and 2016, comparing men’s and women’s strategies. Methods: A total of 142 performances were characterized for overall race times and 0-to-200-m, 200-to-400-m, 400-to-600-m, and 600-to-800-m split times using available footage from YouTube. Only the best annual performance for each athlete was considered. Overall race and split speed were calculated so that each lap speed could be expressed as a percentage of the mean race speed. Results: The mean speed of the men’s 800-m was 7.73 (0.06) m·s−1, with the 0-to-200-m split faster than the others. After the first split, the speed decreased significantly during the 3 subsequent splits (P < .001). The mean speed of the women’s 800-m was 6.77 (0.05) m·s−1, with a significative variation in speed during the race (P < .001). The first split was faster than the others (P < .001). During the rest of the race, speed was almost constant, and no difference was observed between the other splits. Comparison between men and women revealed that there was an interaction between split and gender (P < .001), showing a different pacing behavior in 800-m competitions. Conclusions: The world’s best 800-m performances revealed an important difference in the pacing profile between men and women. Tactics could play a greater role in this difference, but physiological and behavioral characteristics are likely also important.

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Lorenzo Pugliese, Simone Porcelli, Matteo Bonato, Gaspare Pavei, Antonio La Torre, Martina A. Maggioni, Giuseppe Bellistri and Mauro Marzorati

Purpose:

Recently, some studies have suggested that overall training intensity may be more important than training volume for improving swimming performance. However, those studies focused on very young subjects, and/or the difference between high-volume and high-intensity training was blurred. The aim of this study was to investigate in masters swimmers the effects of manipulation of training volume and intensity on performance and physiological variables.

Methods:

A group of 10 male masters swimmers (age 32.3 ± 5.1 y) performed 2 different 6-wk training periods followed by 1 wk of tapering. The first period was characterized by high training volume performed at low intensity (HvLi), whereas the second period was characterized by low training volume performed at high intensity (LvHi). Peak oxygen consumption (V̇O2peak) during incremental arm exercise, individual anaerobic threshold (IAT), and 100-m, 400-m, and 2000-m-freestyle time were evaluated before and at the end of both training periods.

Results:

HvLi training significant increased V̇O2peak (11.9% ± 4.9% [mean change ± 90%CL], P = .002) and performance in the 400-m (–2.8% ± 1.8%, P = .002) and 2000-m (–3.4% ± 2.9%, P = .025), with a likely change in IAT (4.9% ± 4.7%, P > .05). After LvHi training, speed at IAT (12.4% ± 5.3%, P = .004) and 100-m performance (–1.2% ± 0.8%, P = .001) also improved, without any significant changes in V̇O2peak, 2000-m, and 400-m.

Conclusions:

These findings indicate that in masters swimmers an increase of training volume may lead to an improvement of V̇O2peak and middle- to long-distance performance. However, a subsequent period of LvHi training maintains previous adjustments and positively affects anaerobic threshold and short-distance performance.

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Martina A. Maggioni, Matteo Bonato, Alexander Stahn, Antonio La Torre, Luca Agnello, Gianluca Vernillo, Carlo Castagna and Giampiero Merati

Purpose: To investigate the effects of ball drills and repeated-sprint-ability training during the regular season in basketball players. Methods: A total of 30 players were randomized into 3 groups: ball-drills training (BDT, n = 12, 4 × 4 min, 3 vs 3 with 3-min passive recovery), repeated-sprint-ability training (RSAT, n = 9, 3 × 6 × 20-m shuttle running with 20-s and 4-min recovery), and general basketball training (n = 9, basketball technical/tactical exercises), as control group. Players were tested before and after 8 wk of training using the following tests: V˙O2max, squat jump, countermovement jump, Yo-Yo Intermittent Recovery Test Level 1 (YIRT1), agility T test, line-drill test, 5-/10-/20-m sprints, and blood lactate concentration. A custom-developed survey was used to analyze players’ technical skills. Results: After training, significant improvements were seen in YIRT1 (BDT P = .014, effect size [ES] ± 90% CI = 0.8 ± 0.3; RSAT P = .022, ES ± 90% CI = 0.7 ± 0.3), the agility T test (BDT P = .018, ES ± 90% CI = 0.7 ± 0.5; RSAT P = .037, ES ± 90% CI = 0.7 ± 0.5), and the line-drill test (BDT P = .010, ES ± 90% CI = 0.3 ± 0.1; RSAT P < .0001, ES ± 90% CI = 0.4 ± 0.1). In the RSAT group, only 10-m sprint speeds (P = .039, ES ± 90% CI = 0.3 ± 0.2) and blood lactate concentration (P = .004, ES ± 90% CI = 0.8 ± 1.1) were improved. Finally, technical skills were increased in BDT regarding dribbling (P = .038, ES ± 90% CI = 0.8 ± 0.6), shooting (P = .036, ES ± 90% CI = 0.8 ± 0.8), passing (P = .034, ES ± 90% CI = 0.9 ± 0.3), rebounding (P = .023, ES ± 90% CI = 1.1 ± 0.3), defense (P = .042, ES ± 90% CI = 0.5 ± 0.5), and offense (P = .044, ES ± 90% CI = 0.4 ± 0.4) skills. Conclusions: BDT and RSAT are both effective in improving the physical performance of basketball players. BDT had also a positive impact on technical skills. Basketball strength and conditioning professionals should include BDT as a routine tool to improve technical skills and physical performance simultaneously throughout the regular training season.