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
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
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.
Nick Dobbin, Jamie Highton, Samantha L. Moss and Craig Twist
with youth players. Prone Yo-Yo IR1 distance was most likely higher for senior players compared with youth and academy players, with distance possibly higher for academy compared with youth. Normative data for each playing position at youth, academy, and senior standard are presented in Table 2 , with
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.
Ricardo Rebelo-Gonçalves, Manuel João Coelho-e-Silva, Vítor Severino, Antonio Tessitore and António José Barata Figueiredo
Studies focused on position-related characteristics of young soccer players often ignore the goalkeepers. The aim of this study was to examine the effect of playing position on anthropometry, physiological attributes, soccer skills, and goal orientation across adolescence. One hundred forty-five soccer players age 11–19 y were assessed in training experience, body size, maturation, physiological parameters, soccer skills, and goal orientation. Factorial ANOVA was used to test the effect of age group, playing position, and respective interaction terms, while analysis of variance was used to compare goalkeepers vs outfielders in middle (under 13 [U-13] and U-15) and late (U-17 and U-19) adolescence. Discriminant analysis was used to identify the variables that contributed to explaining playing positions. Age group was a consistent source of variation for all variables except task and ego orientations. Fat mass, agility, endurance, dribbling speed, shooting accuracy, and passing were affected by the gradient derived from the classification between goalkeepers and outfielders. It was possible to correctly classify the playing position based on fat-free mass and 3 manipulative skills in younger players and on 4 skills in U-17 and U-19 soccer players. Future research should include longitudinal information to improve our understanding of the factors that contribute to distinguish goalkeepers from outfielders.
Jared A. Bailey, Paul B. Gastin, Luke Mackey and Dan B. Dwyer
Most previous investigations of player load in netball have used subjective methodologies, with few using objective methodologies. While all studies report differences in player activities or total load between playing positions, it is unclear how the differences in player activity explain differences in positional load.
To objectively quantify the load associated with typical activities for all positions in elite netball.
The player load of all playing positions in an elite netball team was measured during matches using wearable accelerometers. Video recordings of the matches were also analyzed to record the start time and duration of 13 commonly reported netball activities. The load associated with each activity was determined by time-aligning both data sets (load and activity).
Off-ball guarding produced the highest player load per instance, while jogging produced the greatest player load per match. Nonlocomotor activities contributed least to total match load for attacking positions (goal shooter [GS], goal attack [GA], and wing attack [WA]) and most for defending positions (goalkeeper [GK], goal defense [GD], and wing defense [WD]). Specifically, centers (Cs) produced the greatest jogging load, WA and WD accumulated the greatest running load, and GS and WA accumulated the greatest shuffling load. WD and Cs accumulated the greatest guarding load, while WD and GK accumulated the greatest off-ball guarding load.
All positions exhibited different contributions from locomotor and nonlocomotor activities toward total match load. In addition, the same activity can have different contributions toward total match load, depending on the position. This has implications for future design and implementation of position-specific training programs.
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