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The aim of this study was to identify differences in time-motion, modified training impulse, body load and movement behaviour between defenders, midfielders and forwards, during an 11-a-side simulated football game. Twenty elite youth male footballers from the same squad participated in this study (age: 18.1 ± 0.7 years old, body mass: 70.5 ± 4.3 kg, height: 1.8 ± 0.3 m and playing experience: 9.4 ± 1.3 years). All data were collected using GPS units (SPI-Pro, GPSports, Canberra, Australia). The movement behaviour was measured with kinematic data, used to calculate position-specific centroids (defenders, midfielders and forwards), and processed with non-linear statistical procedures (approximate entropy normalised and relative phase). There were significant effects and interactions in all variables across the players' positions. The results showed that displacements of all players (defenders, midfielders and forwards) were nearer and more coordinated with their own position-specific centroids than with the other centroids. However, this coupling effect was stronger in midfield players and weaker in forwards. All players' dynamical positioning showed more irregularity when related to the forwards' centroid, as a consequence of their need to be less predictable when playing. The time-motion and physiological variables showed lower activity in forward players. Adding together, the results may contribute to a better understanding of players' specific performances and football complexity.

The present study explored how football players' dynamic positional data can be used to assess tactical behaviour by measuring movement patterns and inter-player coordination. A pre post-test design was used to assess the effects of a 13-week constructivist and cognitivist training program by measuring behaviour in a 5 × 5 football small-sided game, played on a 60 × 40 m outdoor natural turf pitch. Data was captured at 5 Hz by GPS devices (SPI Pro, GPSports, Canberra, Australia) and analysed with non-linear signal processing methods. Approximate entropy values were lower in post-test situations suggesting that these time series became more regular with increasing expertise in football. Relative phase post-test values showed frequent periods with a clear trend to moving in anti-phase, as measured by players' distance to the centre of the team. These advances may open new research topics under the tactical scope and allow narrowing the gap between sports sciences and sports coaching., (© Georg Thieme Verlag KG Stuttgart · New York.)

The purpose of this study was to compare sprint test performance performed by football players of different ages and levels of competition. One hundred and forty six Portuguese players from different teams completed the test (seven maximal sprints interspersed with 25 s active recovery). A 6 (level of competition: 1(st) national division, 2(nd) national division, 1(st) regional division, sub 16, sub 14, sub 12) 7 (sprint trial: sprint 1, sprint 2, sprint 3, sprint 4, sprint 5, sprint 6, sprint 7) repeated measures ANOVA was carried out on subjects sprint times. The main effect of level of competition was statistically significant, F(5, 140) = 106.28, p < 0.001. Subjects from 1(st) national division were significantly faster than subjects from 2(nd) national division; subjects from 1(st) regional division obtained similar performances when compared to sub 16 and sub 14 level; subjects from sub 12 level were the slowest. The main effect of sprint trial was also statistically significant, F (6, 840) = 7.37, p < 0.001. Mean sprint times from the first trial were significantly slower than mean sprint times from the second, third and fourth trial. Results from the fifth, sixth and seventh trials were slower, denoting a decrement in performance. The two main effects were qualified by a significant level of competition x sprint trial interaction, F (30, 840) = 9.47 p < 0.001, identifying markedly different performance profiles. Coaches should be aware that normative data regarding this test can play a very important role if used frequently and consistently during the whole season. Key PointsGroups of different ages (Sub 16, Sub 14 and Sub 12) and groups of different training quality (1(st) and 2(nd) national divisions and 1(st) regional division) were clearly discriminated by sprint test performances.Professional players exhibited higher performances in sprint test.Fatigue effects were the strongest between 5th to the 7th sprint.