The activity profiles of highly trained young soccer players were examined in relation to age, playing position and physical capacity. Time-motion analyses (global positioning system) were performed on 77 (U13-U18; fullbacks [FB], centre-backs [CB], midfielders [MD], wide midfielders [W], second strikers [2 (nd)S] and strikers [S]) during 42 international club games. Total distance covered (TD) and very high-intensity activities (VHIA; >16.1 km·h (-1)) were computed during 186 entire player-matches. Physical capacity was assessed via field test measures (e. g., peak running speed during an incremental field test, VVam-eval). Match running performance showed an increasing trend with age ( P<0.001, partial eta-squared (η (2)): 0.20-0.45). When adjusted for age and individual playing time, match running performance was position-dependent ( P<0.001, η (2): 0.13-0.40). MD covered the greater TD; CB the lowest ( P<0.05). Distance for VHIA was lower for CB compared with all other positions ( P<0.05); W and S displayed the highest VHIA ( P<0.05). Relationships between match running performance and physical capacities were position-dependent, with poor or non-significant correlations within FB, CB, MD and W (e. g., VHIA vs. VVam-eval: R=0.06 in FB) but large associations within 2 (nd)S and S positions (e. g., VHIA vs. VVam-eval: R=0.70 in 2 (nd)S). In highly trained young soccer players, the importance of fitness level as a determinant of match running performance should be regarded as a function of playing position.

Peak locomotor intensity can be modulated during SSGs of various formats and durations to either overload or underload match demands, with 4v4 placing the greatest and the least emphasis on MechW and HS, respectively. Additionally, in relation to match demands central defenders and central midfielders tend to be the most and least overloaded during SSGs, respectively.

The purpose of this study was to quantify match play intensity distribution in young soccer players in relation to age, playing position and physical fitness. Distance covered and heart rate were measured (global positioning system) on 103, highly-trained young players (Under13 to Under 18) during 42 international club games. Maximal sprinting speed (MSS), estimated maximal aerobic speed (MAS) and maximal heart rate (HRmax) were assessed via field test measures. Distance covered and heart rate (HR) were categorized into 5 intensity zones relative to MSS and MAS and HR(max), respectively. Intensity distribution was significantly influenced by both age and playing position with younger groups, wide-midfielders and strikers covering the greatest distance above the MAS. There was a significant, negative, large-to-very large correlation (r= -0.52-0.74) between MAS and the distance run at speeds above MAS for all positions except strikers. HR responses were not different across age groups and playing positions. Distance covered below MAS were lower in the second half for all positions (P<0.05; 0.08<η(2)<0.20), while distance covered at intensities above MAS were maintained (P>0.1; 0.00<η(2)<0.03). This reduction in distance covered below MAS was not related to a player's physical capacity. Except for strikers, a superior aerobic fitness level was unlikely to affect total distance covered but was associated with a reduced individual running demand during the game.

This study examined the occurrence and nature of repeated-sprint sequences (RSS) in highly-trained young soccer players, as a function of age, playing position and playing time. Time-motion analyses using a global positioning system (GPS) were performed on 99 highly-trained young soccer (U13, U14, U15, U16, U17 and U18) players during 42 international games. Sprint activities were defined as at least a 1-s run at intensities higher than 61% of the individual peak running velocity; RSS, as a minimum of 2 consecutive sprints interspersed with a maximum of 60  s. During the first half of games the younger teams had a greater number of RSS than the older teams (P<0.001): U13>U14>U16>U15>U18>U17. The younger players also performed more (e. g., U14 vs. U17: 2.8±0.3 vs. 2.6±0.3, P<0.05) and longer (e. g., U14 vs. U17: 2.8±0.5 vs. 2.6±0.5 s, P<0.05) sprints per sequence than the older players. RSS occurrence was also affected by playing position and decreased throughout the game in most age-groups (P<0.001). Both the occurrence and the nature of RSS are affected by age, position and playing time. Present results also question the importance of repeated-sprint ability as a crucial physical component of soccer performance in developing players.

The aims of the current study were to examine the magnitude of between-GPS-models differences in commonly reported running-based measures in football, examine between-units variability, and assess the effect of software updates on these measures. Fifty identical-brand GPS units (15 SPI-proX and 35 SPIproX2, 15 Hz, GPSports, Canberra, Australia) were attached to a custom-made plastic sled towed by a player performing simulated match running activities. GPS data collected during training sessions over 4 wk from 4 professional football players (N = 53 files) were also analyzed before and after 2 manufacturer-supplied software updates. There were substantial differences between the different models (eg, standardized difference for the number of acceleration >4 m/s2 = 2.1; 90% confidence limits [1.4, 2.7], with 100% chance of a true difference). Between-units variations ranged from 1% (maximal speed) to 56% (number of deceleration >4 m/s2). Some GPS units measured 2-6 times more acceleration/deceleration occurrences than others. Software updates did not substantially affect the distance covered at different speeds or peak speed reached, but 1 of the updates led to large and small decreases in the occurrence of accelerations (-1.24; -1.32, -1.15) and decelerations (-0.45; -0.48, -0.41), respectively. Practitioners are advised to apply care when comparing data collected with different models or units or when updating their software. The metrics of accelerations and decelerations show the most variability in GPS monitoring and must be interpreted cautiously.