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Martin Buchheit, Alberto Mendez-Villanueva, Marc Quod, Thomas Quesnel and Said Ahmaidi

Purpose:

The aim of the current study was to compare the effects of speed/agility (S/A) training with sprint interval training (SIT) on acceleration and repeated sprint ability (RSA) in well-trained male handball players.

Methods:

In addition to their normal training program, players performed either S/A (n = 7) or SIT (n = 7) training for 4 wk. Speed/agility sessions consisted of 3 to 4 series of 4 to 6 exercises (eg, agility drills, standing start and very short sprints, all of <5 s duration); each repetition and series was interspersed with 30 s and 3 min of passive recovery, respectively. Sprint interval training consisted of 3 to 5 repetitions of 30-s all-out shuttle sprints over 40 m, interspersed with 2 min of passive recovery. Pre- and posttests included a countermovement jump (CMJ), 10-m sprint (10m), RSA test and a graded intermittent aerobic test (30-15 Intermittent Fitness Test, VIFT).

Results:

S/A training produced a very likely greater improvement in 10-m sprint (+4.6%, 90% CL 1.2 to 7.8), best (+2.7%, 90% CL 0.1 to 5.2) and mean (+2.2%, 90% CL –0.2 to 4.5) RSA times than SIT (all effect sizes [ES] greater than 0.79). In contrast, SIT resulted in an almost certain greater improvement in VIFT compared with S/A (+5.2%, 90% CL 3.5 to 6.9, with ES = –0.83).

Conclusion:

In well-trained handball players, 4 wk of SIT is likely to have a moderate impact on intermittent endurance capacity only, whereas S/A training is likely to improve acceleration and repeated sprint performance.

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Hani Al Haddad, Ben M. Simpson and Martin Buchheit

This study compares different approaches to monitor changes in jump and sprint performance while using either the best or the average performance of repeated trials. One hundred two highly trained young footballers (U13 to U17) performed, in 2 different testing sessions separated by 4 mo, 3 countermovement jumps (n = 87) and 2 sprints (n = 98) over 40 m with 10-m splits to assess acceleration (first 10 m) and maximal sprinting speed (best split, MSS). Standardized group-average changes between the 2 testing periods and the typical error (TE) were calculated and compared for each method. The likelihood of substantial changes in performance for each individual player was also calculated. There was a small increase in jump performance (+6.1% for best and +7% for average performance). While 10-m time was likely unchanged (+~1.2% for both best and average performance), MSS showed likely small improvements (+~2.0% for both best and average performance). The TEs for jumping performance were 4.8% (90% confidence limits 4.3;5.6) and 4.3% (3.8;5.0) for best and average values, respectively; 1.8% (1.6;2.1) and 1.7% (1.5;1.9) for 10-m time and 2.0% (1.8;2.3) and 2.0% (1.8;2.3) for MSS. The standardized differences between TE were likely unclear or trivial for all comparisons (eg, 10-m, 0.01 [–0.09;0.10]). The numbers of players showing a likely increase or decrease in performance were 30/0 and 29/0 for best and average jump performances, 9/4 and 12/2 for 10-m times, and 33/4 and 33/4 for MSS. In conclusion, the 2 monitoring approaches are likely to provide similar outcomes.

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Mark Russell, Aden King, Richard. M. Bracken, Christian. J. Cook, Thibault Giroud and Liam. P. Kilduff

Purpose:

To assess the effects of different modes of morning (AM) exercise on afternoon (PM) performance and salivary hormone responses in professional rugby union players.

Methods:

On 4 occasions (randomized, crossover design), 15 professional rugby players provided AM (~8 AM) and PM (~2 PM) saliva samples before PM assessments of countermovement-jump height, reaction time, and repeated-sprint ability. Control (passive rest), weights (bench press: 5 × 10 repetitions, 75% 1-repetition maximum, 90-s intraset recovery), cycling (6 × 6-s maximal sprint cycling, 7.5% body mass load, 54-s intraset recovery), and running (6 × 40-m maximal sprints, 20-s intraset recovery) interventions preceded (~5 h) PM testing.

Results:

PM sprint performance improved (P < .05) after weights (>0.15 ± 0.19 s, >2.04% ± 2.46%) and running (>0.15 ± 0.17 s, >2.12% ± 2.22%) but not cycling (P > .05). PM jump height increased after cycling (0.012 ± 0.009 m, 2.31% ± 1.76%, P < .001) and running (0.020 ± 0.009 m, 3.90% ± 1.79%, P < .001) but not weights (P = .936). Reaction time remained unchanged between trials (P = .379). Relative to control (131 ± 21 pg/mL), PM testosterone was greater in weights (21 ± 23 pg/mL, 17% ± 18%, P = .002) and running (28 ± 26 pg/mL, 22% ± 20%, P = .001) but not cycling (P = .072). Salivary cortisol was unaffected by AM exercise (P = .540).

Conclusions:

All modes of AM exercise improved at least 1 marker of PM performance, but running appeared the most beneficial to professional rugby union players. A rationale therefore exists for preceding PM competition with AM exercise.

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Hani Al Haddad, Ben M. Simpson, Martin Buchheit, Valter Di Salvo and Alberto Mendez-Villanueva

This study assessed the relationship between peak match speed (PMS) and maximal sprinting speed (MSS) in regard to age and playing positions. MSS and absolute PMS (PMSAbs) were collected from 180 male youth soccer players (U13–U17, 15.0 ± 1.2 y, 161.5 ± 9.2 cm, and 48.3 ± 8.7 kg). The fastest 10-m split over a 40-m sprint was used to determine MSS. PMSAbs was recorded using a global positioning system and was also expressed as a percentage of MSS (PMSRel). Sprint data were compared between age groups and between playing positions. Results showed that regardless of age and playing positions, faster players were likely to reach higher PMSAbs and possibly lower PMSRel. Despite a lower PMSAbs than in older groups (eg, 23.4 ± 1.8 vs 26.8 ± 1.9 km/h for U13 and U17, respectively, ES = 1.9 90%, confidence limits [1.6;2.1]), younger players reached a greater PMSRel (92.0% ± 6.3% vs. 87.2% ± 5.7% for U13 and U17, respectively, ES = –0.8 90% CL [–1.0;–0.5]). Playing position also affected PMSAbs and PMSRel, as strikers were likely to reach higher PMSAbs (eg, 27.0 ± 2.7 vs 23.6 ± 2.2 km/h for strikers and central midfielders, respectively, ES = 2.0 [1.7;2.2]) and PMSRel (eg, 93.6% ± 5.2% vs 85.3% ± 6.5% for strikers and central midfielders, respectively, ES = 1.0 [0.7;1.3]) than all other positions. The findings confirm that age and playing position affect the absolute and relative intensity of speed-related actions during matches.

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Ina Garthe, Truls Raastad, Per Egil Refsnes, Anu Koivisto and Jorunn Sundgot-Borgen

When weight loss (WL) is necessary, athletes are advised to accomplish it gradually, at a rate of 0.5–1 kg/wk. However, it is possible that losing 0.5 kg/wk is better than 1 kg/wk in terms of preserving lean body mass (LBM) and performance. The aim of this study was to compare changes in body composition, strength, and power during a weekly body-weight (BW) loss of 0.7% slow reduction (SR) vs. 1.4% fast reduction (FR). We hypothesized that the faster WL regimen would result in more detrimental effects on both LBM and strength-related performance. Twenty-four athletes were randomized to SR (n = 13, 24 ± 3 yr, 71.9 ± 12.7 kg) or FR (n = 11, 22 ± 5 yr, 74.8 ± 11.7 kg). They followed energy-restricted diets promoting the predetermined weekly WL. All athletes included 4 resistance-training sessions/wk in their usual training regimen. The mean times spent in intervention for SR and FR were 8.5 ± 2.2 and 5.3 ± 0.9 wk, respectively (p < .001). BW, body composition (DEXA), 1-repetition-maximum (1RM) tests, 40-m sprint, and countermovement jump were measured before and after intervention. Energy intake was reduced by 19% ± 2% and 30% ± 4% in SR and FR, respectively (p = .003). BW and fat mass decreased in both SR and FR by 5.6% ± 0.8% and 5.5% ± 0.7% (0.7% ± 0.8% vs. 1.0% ± 0.4%/wk) and 31% ± 3% and 21 ± 4%, respectively. LBM increased in SR by 2.1% ± 0.4% (p < .001), whereas it was unchanged in FR (–0.2% ± 0.7%), with significant differences between groups (p < .01). In conclusion, data from this study suggest that athletes who want to gain LBM and increase 1RM strength during a WL period combined with strength training should aim for a weekly BW loss of 0.7%.

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Denise Jennings, Stuart Cormack, Aaron J. Coutts, Luke J. Boyd and Robert J. Aughey

Purpose:

To examine the difference in distance measured by two global positioning system (GPS) units of the same model worn by the same player while performing movements common to team sports.

Methods:

Twenty elite Australian football players completed two trials of the straight line movement (10, 20, 40 m) at four speeds (walk, jog, stride, sprint), two trials of the changes of direction (COD) courses of two different frequencies (gradual and tight), and five trials of a team sport running simulation circuit. To assess inter-unit variability for total and high intensity running (HIR) distance measured in matches, data from eight field players were collected in three Australian Hockey League (AHL) matches during the 2009 season. Each subject wore two GPS devices (MinimaxX v2.5, Catapult, Australia) that collected position data at 5 Hz for each movement and match trial. The percentage difference ±90% confidence interval (CI) was used to determine differences between units.

Results:

Differences (±90% CI) between the units ranged from 9.9 ± 4.7% to 11.9 ± 19.5% for straight line running movements and from 9.5 ± 7.2% to 10.7 ± 7.9% in the COD courses. Similar results were exhibited in the team sport circuit (11.1 ± 4.2%). Total distance (10.3 ± 6.2%) and HIR distance (10.3 ± 15.6) measured during the match play displayed similar variability.

Conclusion:

It is recommended that players wear the same GPS unit for each exercise session to reduce measurement error. The level of between-unit measurement error should be considered when comparing results from players wearing different GPS units.

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Ryu Nagahara, Mirai Mizutani, Akifumi Matsuo, Hiroaki Kanehisa and Tetsuo Fukunaga

preceding acceleration. In contrast, Morin et al 6 and Rabita et al 8 found no significant relationship between averaged vertical force or impulse over a 40-m distance and either maximal speed or mean running speed over 40 m. They demonstrated that a larger propulsive force or impulse during the

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Bruno Marrier, Alexandre Durguerian, Julien Robineau, Mounir Chennaoui, Fabien Sauvet, Aurélie Servonnet, Julien Piscione, Bertrand Mathieu, Alexis Peeters, Mathieu Lacome, Jean-Benoit Morin and Yann Le Meur

countermovement jump (CMJ) and repeated-sprint performance in professional rugby union players. Similarly, afternoon performance was improved in rugby union players who had performed morning physical assessments (eg, CMJ, 40-m sprints, bench press, and back squat), sprints (5 × 40 m), and whole-body resistance

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Marilia Silva Paulo, Javaid Nauman, Abdishakur Abdulle, Abdulla Aljunaibi, Mouza Alzaabi, Caroline Barakat-Haddad, Mohamud Sheek-Hussein, Syed Mahboob Shah, Susan Yousufzai and Tom Loney

- In 2016, 40% (M 49%; F 32%) of UAE adolescents aged 13–17 years met the screen time recommendations 7 (≤2 h/d) and this declined from ages 13–15 years (total 45%; M 52%; F 37%) to ages 16–17 years (total 34%; M 43%; F 25%). 3 A greater proportion of Emirati children met the screen time

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Carlos Marta, Ana R. Alves, Pedro T. Esteves, Natalina Casanova, Daniel Marinho, Henrique P. Neiva, Roberto Aguado-Jimenez, Alicia M. Alonso-Martínez, Mikel Izquierdo and Mário C. Marques

.5-m-tall), plyometric jumps above 0.3 to 0.5 m tall hurdles, and sets of 30-to-40-m-speed runs. The ST group was subjected to a ST program using a webbing system (TRX ® Pro Pack; Fitness Anywhere Inc, San Francisco, CA) that included chest press, push-up, triceps press, triceps extension, squat