will serve to improve physical programming within LTPD pathways. Methods Experimental Approach to the Problem A mixed, between-within-groups, repeated-measures design was used to assess the magnitude of change over time by playing position. Variables of interest were anthropometric measures (height and
Niall Casserly, Ross Neville, Massimiliano Ditroilo and Adam Grainger
Anne Delextrat and Semah Kraiem
The physiological load experienced during basketball drills is crucial to understand players’ adaptation to team-sport training and plan physical-conditioning programs.
To compare mean heart-rate (HRmean) responses by playing position during 2-a-side (2v2) and 3-a-side (3v3) ball drills in male junior basketball players and explore the relationship between HRmean and repeated-sprint ability (RSA).
Thirtyone players volunteered to participate in this study. On separate occasions, they performed 2v2 and 3v3 ball drills and 6 repetitions of shuttle-run sprints of 20 m (10+10 m), departing every 20 s (RSA). Ball drills took place on the full length but only half the width of the court and were three 4-min bouts separated by 1-min rest periods. An analysis of variance (ANOVA) assessed the effect of the number of players on court (2v2 vs 3v3) and playing position (guards vs forwards vs centers) on HRmean, and a Pearson correlation coefficient evaluated the relation between HRmean and RSA.
The main results showed greater HRmean in 2v2 than in 3v3 ball drills (P < .001) in all playing positions (90.7% ± 1.3% vs 87.6% ± 3% of HRpeak in guards, 91.3% ± 2.1% vs 87.5% ± 3.7% of HRpeak for forwards, and 88.2% ± 3.5% vs 82.2% ± 5.6% of HRpeak in centers, respectively, for 2v2 and 3v3). In addition, centers were characterized by lower HRmean than guards and forwards in 3v3 only (P = .018).
These results suggest that 2v2 drills should be preferred to 3v3 drills for aerobic conditioning, in particular for centers. Finally, RSA does not seem to influence players’ acute responses to ball drills.
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.
Fabio Giuliano Caetano, Murilo José de Oliveira, Ana Lorena Marche, Fábio Yuzo Nakamura, Sergio Augusto Cunha and Felipe Arruda Moura
The purposes of this study were to investigate sprints and to characterize repeated-sprint sequences (RS) performed by athletes during professional futsal matches. We analyzed 97 players during 5 official matches using the DVideo automatic tracking system. The sprints were analyzed during the first and second halves according to playing position, and RS were categorized according to the number of sprints and the time between them. The results showed an increase (F[1, 2520] = 3.96; P = .046) in the sprint duration from the first (mean = 3.1 ± 1.3) to the second half (mean = 3.2 ± 1.2). However, no differences were found for other variables (distance covered, peak velocity, initial velocity, recovery time between sprints, and sprints performed per minute) or among playing positions. In addition, when considering RS, the results showed that RS comprising two sprints interspersed with a maximum of 15 seconds of recovery were significantly more frequent than other RS. The findings of this study characterizing the sprinting features of futsal players can help coaches to plan physical training and assessments according to the requirements of the sport.
Sally A.M. Fenton, Joan L. Duda and Timothy Barrett
The aims of this study were (1) to determine minutes of moderate-to-vigorous physical activity (PA) and vigorous PA accrued in youth sport football (also internationally referred to as soccer), and the contribution toward daily weekend moderate-to-vigorous PA and vigorous PA for males aged 9-16 years, and (2) to investigate variability in these outcomes related to age and playing position. One hundred and nine male grassroots footballers (Mean age = 11.98 ± 1.75 years) wore a GT3x accelerometer for 7 days. Weekend youth sport football participation and playing position were recorded. Youth sport football moderate-to-vigorous PA (M = 51.51 ± 17.99) and vigorous PA (M = 27.78 ± 14.55) contributed 60.27% and 70.68% toward daily weekend moderate-to-vigorous PA and vigorous PA, respectively. Overall, 36.70% of participants accumulated ≥60 min moderate-to-vigorous PA and 69.70% accrued < 20 min of vigorous PA during youth sport. For participants aged 13 to16 years, youth sport football moderate-to-vigorous PA and vigorous PA were significantly higher, and contributed a greater amount toward daily weekend moderate-to-vigorous PA and vigorous PA than for participants aged 9-12 years (p = >.01). Youth sport football is an important source of moderate-to-vigorous PA and vigorous PA at the weekend for male youth, and particularly for adolescents. Participation may offer opportunity for weekend engagement in vigorous PA toward health enhancing levels.
Marco Cardinale, Rodney Whiteley, Ahmed Abdelrahman Hosny and Nebojsa Popovic
Handball is an Olympic sport played indoors by 6 court players and 1 goalkeeper with rolling substitutions. Limited data exist on elite players competing in a world championship, and virtually no information exists on the evolution of time–motion performance over the course of a long tournament.
To analyze time–motion characteristics of elite male handball players of the last world championships, played in Qatar in 2015.
384 handball players from 24 national teams.
The athletes were analyzed during 88 matches using a tracking camera system and bespoke software (Prozone Handball v. 1.2, Prozone, Leeds, UK).
The average time on court (N = 2505) during the world championships for all players was 36:48 ± 20:27 min. Goalkeepers and left and right wings were on court most of the playing time (GK 43.00 ± 25:59 min; LW 42:02 ± 21:07 min; RW 43:44 ± 21:37 min). The total distance covered during each game (2607.5 ± 1438.4 m) consisted mostly of walking and jogging. The cumulative distance covered during the tournament was 16,313 ± 9423.3 m. Players performed 857.2 ± 445.7 activity changes with a recovery time of 124.3 ± 143 s. The average running pace was 78.2 ± 10.8 m/min. There was no significant difference between high-ranked and lower-ranked teams in terms of distance covered in different locomotion categories.
Specific physical conditioning is necessary to maximize performance of handball players and minimize the occurrence of fatigue when performing in long tournaments.
Luka Svilar, Julen Castellano, Igor Jukic and David Casamichana
), which has been previously proposed 10 to measure training modes, could be a useful option to remove the redundancy in variables used to monitor load or to know if players are stimulated similarly, according to their playing position. The previous research 11 , 12 of elite-level players has confirmed
253 Division I (professional-style teams with athletic scholarships) and 232 Division III (non-scholarship, largely avocational) programs. Most team webpages were organized in a similar format, listing the name, hometown, high school, height, weight and playing position of each player, as well as a
Hugh H.K. Fullagar, Robert McCunn and Andrew Murray
on the physical needs of each playing position. For instance, an OL’s primary role is defending the line of scrimmage to either protect the QB trying to complete a throw or aid a RB as they run the ball, which involves contesting DLs who weigh up to 150 kg. 43 Thus, a focus for this position may
Robert McCunn, Hugh H.K. Fullagar, Sean Williams, Travis J. Halseth, John A. Sampson and Andrew Murray
professional playing experience, highlighting the potential influence of this factor on injury risk. In addition to this challenge, American football is characterized by disparate playing positions and athlete somatotypes, 8 further complicating the issue of training program design. 9 Unsurprisingly, playing