Positioning and displacement patterns of young players during 5v5, 7v7, 9v9, and 11v11 soccer matches

Abstract

This study aimed to analyse the effect of game format and age-group on positioning and displacement of soccer players (age ranging from 6.94 ± 0.7 to 13.46 ± 0.5 years; height ranging from 125.36 ± 6.04 to 159.16 ± 7.78 cm; weight ranging from 27.16 ± 5.75 to 49.89 ± 8.89 kg). Linear and non-linear analyses were used to capture the spatial distribution variability and relative positioning of the players during soccer matches. Variables were assessed using global positioning system technology. Results suggest significant effect of the game formats in spatial distribution variability (η 2 = 0.142, p < 0.001) and relative positioning (η 2 = 0.926; p < 0.001) of the players. The variability decreased and mean covered area increased as game format increased. There also was a significant effect of the age-group in spatial distribution variability (η 2 = 0.120, p < 0.001) and relative positioning (η 2 = 0.405; p < 0.001). The U10 age-group presented significantly higher values than other age-groups (p < 0.001). These findings can provide an opportunity for coaches and governmental bodies to maximise the efficiency of the soccer matches conditions.

A directional ellipse to describe directional behavior and player activity area in soccer

“…The MR ellipse area determined by Yue et al 11 has been recently used (i) to compare players of different skill level in different numerical relations, finding that national level players have rounder and less overlapped ellipses than regional level players 23 ; (ii) to compare U-14 players’ positions on different field surfaces, finding that central midfielders cover higher areas, especially on dirt field surface 12 ; (iii) and to assess the effect of age-groups and pitch dimensions during soccer matches, finding that ellipse areas increase as pitch dimensions increase. 24 Even if this last study maintained the length/width ratio by increasing the field dimensions proportionally, the results from the present study are in accordance with this last study since the present study showed that increasing the pitch length—and consequently the area per player—elicited larger individual playing areas in all ellipse models. Nevertheless, it is still unclear whether the division of labor induced by reduced pitch length modifies common ellipse spaces accordingly.…”

Effects of numerical unbalance constraints on workload and tactical individual actions during ball possession small-sided soccer games across different age groups

“…However, when the individual or age-related speed thresholds are used, younger players tend to sprint more and run the same total distance as their older counterparts (Mendez-Villanueva et al, 2011). Consequently, younger players may find it difficult to explore the space to keep a balanced unit and tend to pursue the ball across the playing area (Brito et al, 2019). This results in the need to keep running at higher intensities.…”

Sport Performance Analysis with a Focus on Racket Sports: A Review

“…Performance analysis objectives can be captured in a variety of ways and for a variety of sports. For example, we can mention the following: identification of potential by: Arede et al [2], Woods et al [3], Waldron and Worsfold [4], Woods et al [5,6], Lago-Fuentes et al [7], specific performance of a young player by Saphie et al [8], Brito et al [9,10], Karakulak [11], Gimenez-Egido et al [12], Analysis of technical skills (movement patterns, for example) by: Santos et al [13], Nassis [14], Mangan et al [15], Saavedra et al [16], Challis et al [17], Hökelmann and Richter [18]. Player's performance analysis during the game (match analysis that includes stroke position, ball movement, match sequence, and player's substitutions) is covered in detail in: Pereira et al [19], Michael et al [20], Caballero et al [21], Slawson et al [22], Belli et al [23], Gal et al [24].…”

“…Tennis publications provide the most keywords (114), followed by badminton (62), padel tennis (49), table tennis (29), and squash (21). (9). As more technology for in-game analysis becomes available, the keywords used in tennis publications become more specific.…”