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The aim of this study was to quantify and compare the match load demands of U18, U23, and 1ST team players during the official season. A total of 65 matches and 495 (U18 = 146, U23 = 146, and 1ST team = 203) individual player game observations were included in this analysis. A 10-Hz global navigation satellite systems (GNSS) and 100-Hz triaxial acc...
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... researchers reported that the match represents the most important physical stimulus of the week and plays a key role in achieving long-term physical development ( Anderson et al., 2016;Morgans et al., 2018;Gualtieri et al., 2020). This study reported normative match data of age groups of professional players (Table 1) and the differences that exist between these groups ( Table 2), which can be very important for practitioners and sports science departments to have a better overview of physical demands from academy to 1ST team. Our analysis showed that U18 players generally perform less physical activity than U23 players and 1ST team players in some but not all the metrics analyzed ( Table 2). ...Context 3
... study reported normative match data of age groups of professional players (Table 1) and the differences that exist between these groups ( Table 2), which can be very important for practitioners and sports science departments to have a better overview of physical demands from academy to 1ST team. Our analysis showed that U18 players generally perform less physical activity than U23 players and 1ST team players in some but not all the metrics analyzed ( Table 2). HSR during matches was reported to be lower (small, p = 0.096) for U18 players than U23 players. ...Citations
... 15 This limitation may be attributed to the high cost associated with GPS technology, which could potentially hinder its availability for certain clubs aiming to monitor running demands in academy soccer matches. 16 Consequently, little is known about differences in match-related physical demands between elite senior and youth female soccer players from the same club. Utilizing teams from the same professional club offers an advantageous approach by mitigating the potential bias of comparing teams belonging to different contexts, cultures, habits, training methodology and playing styles. ...
... 12 This is particularly important because youth players (U15 and U18) need to be physically fit to progress through different age categories and competitive levels. 16 For example, Ramos et al. 11 demonstrated a progressive increase in high-intensity activities (i.e. HSR and sprints) and total number of ACCs (>1 m s −2 ) and decelerations (DCCs, <−1 m s −2 ) in female soccer players representing the national Brazilian teams (senior > U20 > U17). ...
... The lack of significant difference in TD among age categories implies that match-running volume may not be sensitive to discriminate physical load in female soccer players as running intensity. 16 Indeed, in most intra-playing position comparisons, senior players exceeded younger players in HSR and sprinting distances, but not in TD. Given that the long-term athletic development of youth female soccer players should be a priority for soccer coaches, it is important to develop well-designed speed training programmes to enhance their performance. ...
The objective of the study was to examine the match-running load of female soccer players competing at distinct age groups (U15, U18 and senior cohorts) belonging to the same professional club, over a competitive season. The external load variables of the official matches were monitored with Global Positioning System (GPS) technology: total distance (TD), at >18 km·h ⁻¹ (running), at >21 km·h ⁻¹ (high-speed running, HSR) and at >24 km·h ⁻¹ (sprint, SPR) distances, efforts at >85% of the maximal sprint speed (>85% MSS), acceleration load (aLoaD), accelerations (ACC2 and ACC3, >2 and >3 m·s ⁻² ) and decelerations (DEC2 and DEC3 <−2 and <−3 m·s ⁻² ). Overall, distances covered at running, HSR and sprinting were greater for senior players than their younger peers (U15 and U18; p < 0.05). Regarding HSR and sprints, no difference was found for sprints accumulated by central defender (CD) players in comparison to U18 and U15 ( p > 0.05). In addition, U18 and senior players engaged more often in ACC and DEC, >2 and >3 m·s ⁻² , respectively, than U15 players ( p < 0.05). In conclusion, older female soccer players are exposed to higher match load than their younger peers. These findings could be useful for soccer coaches to design specific speed development programmes across the long-term athletic development pathway.
... These garment-based wearables allow the electronics to be placed on the upper back between the scapulae, where they are safe and relatively unobtrusive. The STATSports Apex, for example, has been compared favourably with radar-based tracking technologies [129] and has been used to gain insight into the performance of football players in different age groups, the results of which could inform training programs [130]. The Nadi X, developed by startup company Wearable X [131], include accelerometers and haptic feedback in the form of vibrations that are designed to assist with obtaining and maintaining yoga positions. ...
E-textiles have emerged as a fast-growing area in wearable technology for sports and fitness due to the soft and comfortable nature of textile materials and the capability for smart functionality to be integrated into familiar sports clothing. This review paper presents the roles of wearable technologies in sport and fitness in monitoring movement and biosignals used to assess performance, reduce injury risk, and motivate training/exercise. The drivers of research in e-textiles are discussed after reviewing existing non-textile and textile-based commercial wearable products. Different sensing components/materials (e.g., inertial measurement units, electrodes for biosignals, piezoresistive sensors), manufacturing processes, and their applications in sports and fitness published in the literature were reviewed and discussed. Finally, the paper presents the current challenges of e-textiles to achieve practical applications at scale and future perspectives in e-textiles research and development.
... In contrast, the ability to accelerate at lower speeds (A0) and the slope of the A-S profile remains stable throughout the development of a young soccer player. However, since there could still be differences between age groups in game demands (Reynolds et al., 2021) and other performance metrics, this highlights the importance of monitoring the A-S profile, in order to individualise the training regime of a young soccer player, to prepare for the physical demands of the professional context. ...
... -1 ± 1.83 (Smalley et al., 2022), TD ~ 125.0m.min -1, HSR ~8.67m.min -1 (Hattersley et al., 2018) and by Reynolds et al. (2021) (academy category not stated) TD ~107.98m.min -1 , HSR ~ 6.59 m.min -1 . ...
... -1 ± 0.81 (Smalley et al., 2022) and ~1.15m.min -1 (Reynolds et al., 2021). Differences were also apparent with overseas U18's: Qatar TD 99.00m.min ...
... In recent years, numerous studies have employed tracking system microtechnologies, such as global positioning systems (GPS), to describe the physical demands of elite football players during matches [1], offering insights for training design [2]. Given the stochastic nature of football, physical demands on players continuously fluctuate in magnitude, effort, and time due to changing game dynamics [3,4], leading to differential intensity patterns and the most demanding passages (MDP) of physical activity [5][6][7][8]. ...
... The analysis of HMLD reported that AM (23.7 m·min 21 ) covered greater (p , 0.001, very large) distance than CB (15.9 m·min 21 ), although other positions have similar demands (CM, ST, and WB; Figure 6). The HMLD values reported in this study are similar to previous research data that showed English League 1 players to cover an average of 20.7 m·min 21 (37). However, the current study makes a step forward compared with Reynolds et al. (37) because it shows as practitioners need to consider the different players' positions match demands when they design their training drills to correctly train their players. ...
... The HMLD values reported in this study are similar to previous research data that showed English League 1 players to cover an average of 20.7 m·min 21 (37). However, the current study makes a step forward compared with Reynolds et al. (37) because it shows as practitioners need to consider the different players' positions match demands when they design their training drills to correctly train their players. Overall, some of the variation found in this study among the physical demands analysis could be because of the formation used by the club, which was a fluid 3-5-2 (13,24). ...
... Regarding HMLD, which is a parameter that takes into account both acceleration and deceleration activities, we found that location does not play a role in its variation (p 5 0.604, Figure 12), whereas we found a significant variation in results (p 5 0.010); specifically (after a contrast analysis), we found nonsignificant differences between drew versus lost (p 5 0.851) and lost versus won (p 5 0.188), but we found differences between drew versus won (p 5 0.012, very large). However, these HMLD values in practical terms are 21.4 m·min 21 (1,926 m per 90-minute match), 21.2 m·min 21 (1,908 m per 90-minute match), and 22.7 m·min 21 (2,043 m per 90-minute match), for drew, lost and won, respectively-these results are in line with previous research on this topic that found that English League 1 players cover an HMLD of 1,990 m per match (37). Considering what is said above, it is important for practitioners to understand if these variations among match results in terms of HMLD is actually meaningful and, therefore, deserves to be considered for tailoring the training strategies ahead of a match or after it. ...
Beato, M, Youngs, A, and Costin, AJ. The analysis of physical performance during official competitions in professional English football: Do positions, game locations, and results influence players’ game demands? J Strength Cond Res XX(X): 000–000, 2023—This study aimed, first, to verify if physical parameters were different between players' positions during official matches in English professional football, and second, if the game location (H and A) or results (W, L, D) affected players' physical performance. Twenty-five male professional football players of the same team were included in this data analysis (age = 27 ± 9 years) during the 2022–23 season. Players were divided into positions: center backs, wide backs, center midfielders, attacking midfielders, and strikers. The external load parameters were distance covered, high-speed running (HSR), sprinting distance, accelerations, decelerations, and high metabolic load distance (HMLD, meters > 25.5 w·kg ⁻¹ ) that were monitored using global navigation satellite systems Apex (STATSports). Linear mixed models' analysis for positions reported a significant difference in total distance ( p = 0.011), HSR ( p < 0.001), sprinting distance ( p < 0.001), accelerations ( p = 0.003), decelerations ( p = 0.002), and HMLD ( p < 0.001). Centre backs showed the lowest physical performance in the metrics analyzed, whereas players in the other positions frequently displayed a similar physical performance. Regarding locations and results, differences were only found between locations for decelerations ( p = 0.041) and between results for HMLD ( p = 0.010). In conclusion, physical performance was influenced by players' positions, whereas game location or results seem to not affect physical performance during official competitions. Consequently, practitioners can physically prepare their players independently from the location of the match or of the possible game results, whereas specific positional training is requested to optimally prepare their players.
... An increase in match physical and technical performance parameters has been reported in professional football over the last decade (Bush et al., 2015;Bradley et al., 2016;Reynolds et al., 2021). In another study in the literature, it was shown that there are different physical requirements between teams depending on various factors (Rampinini et al., 2007). ...
The aim of the study is to compare the performance of the teams in the Bundesliga in the 2022/23 season according to the league ranking and to examine the relationship between these parameters and the points collected by the teams at the end of the season. The sample of the study consists of 612 matches played in the Bundesliga in the 2022/23 season. The data of the matches were collected from the Bundesliga official website; 8 technical, tactical, and 4 physical performance, 12 parameters in total were evaluated. Teams were group as top, middle and bottom according to their end-of-season rankings. MANOVA test was performed to reveal the difference between the teams and effect sizes were reported as partial eta squared (ηp 2). Pearson Correlation Test was applied to determine the relationships between the performance parameters of the teams and the points they collected. As a result of the analyses, it was determined that the top ranked teams had a statistically significant difference in the number of goals scored and conceded, number of shots and total points compared to the middle and bottom ranked teams. Significant positive relationships were found between total points and possession of the ball, accurate passing, goals scored, shots scored at very high and excellent level, and significant negative relationships were found with goals conceded and number of air balls won at high level. As a result, it can be said that the teams should passes the ball more, use the ball positively, utilise the opportunities positively, increase the number of goals and shots scored and decrease the number of goals conceded in order to take their place in the top ranks.
... In the last decade, it has been reported that there has been an increase in match physical and technical performance parameters in professional soccer (Bush, Barnes, Archer, Hogg & Bradley, 2015;Bradley et al., 2016;Reynolds, Connor, Jamil & Beato, 2021), soccer players covered 8-13 km during the match (Reilly, 2003) and this distance is covered with an intermittent exercise regime (Di Salvo, Gregson, Atkinson, Tordoff & Drust, 2009). In another study in the literature, it was shown that there are different physical requirements between teams depending on various factors (Rampinini, Coutts, Castagna, Sassi & Impellizzeri, 2007). ...
The aim of this study is to compare the performance of the matches played in the Bundesliga and Bundesliga 2 in the 2022-2023 season and to reveal the factors affecting the league ranking. Data were collected from the Bundesliga official website; 5 technical-tactical and 4 physical performance, 9 parameters in total were evaluated. Independent Samples T-Test was used to determine the differences between the groups, Pearson Correlation Test was used to determine the relationships between the parameters. As a result of the analyses, it was determined that the number of high intensity runs and sprints in the matches was significantly higher in BL. In addition, there were no significant relationships between the physical performance parameters in Bundesliga (BL) and the points collected by the teams at the end of the league and the league ranking; these relationships were determined to be with different levels of technical parameters. In Bundesliga 2 (BL2), along with technical parameters, significant relationships were found at different levels between running distance per match and league ranking and number of goals scored. As a result, it can be said that the teams in the top leagues play faster football than the teams in the lower leagues. In addition, since the teams in the higher leagues perform almost equally in terms of tactical and physical performance, it can be said that the teams in the lower leagues should utilise their opportunities positively in order to be successful, while the teams in the lower leagues should also have a higher running distance per match.
... In the current study, respondents were also undecided over whether academies prepare players physically for the FT. This is noteworthy because an increase in physical demands has been cited by both coaches and transitioning players (Morris et al. 2016;Swainston et al. 2020), and there is evidence of differences between the youth and senior levels when comparing training and match loads (Houtmeyers et al. 2021;Reynolds et al. 2021). In competitive matches, under-18 academy players generally record less high-speed running distance (>19.8 km.h -1 ) than under-23 players, and less sprinting distance (>25 km.h -1 ) than FT players (Reynolds et al. 2021). ...
... This is noteworthy because an increase in physical demands has been cited by both coaches and transitioning players (Morris et al. 2016;Swainston et al. 2020), and there is evidence of differences between the youth and senior levels when comparing training and match loads (Houtmeyers et al. 2021;Reynolds et al. 2021). In competitive matches, under-18 academy players generally record less high-speed running distance (>19.8 km.h -1 ) than under-23 players, and less sprinting distance (>25 km.h -1 ) than FT players (Reynolds et al. 2021). When examining differences in weekly training loads, under-19 academy players recorded greater low-velocity distances, due in part to longer session durations as well as a higher number of weekly sessions, but for sprint velocities (>25 km.h -1 ), the academy players recorded significantly less total distance than the FT (Houtmeyers et al. 2021). ...
... Apex 10 Hz is a multi GNSS augmented unit, capable of acquiring and tracking multiple satellite systems (e.g., GPS, GLONASS, Galileo, BeiDou) concurrently to provide the best possible position information. The Apex GNSS model reports information about the number of satellites connected (M = 14.9, SD = 1.5, range 11 to 21), which was slightly lower than reported in previous literature [27,28,30]. The Apex units present the following characteristics: 30 mm (wide) × 80 mm (high) dimensions, 48 g weight, 100 Hz gyroscope, 100 Hz tri-axial accelerometer, and 10 Hz magnetometer. ...
Despite load monitoring being considered an integral part of targeted performance management, including injury and illness prevention, there is currently no consensus of an effective monitoring system in professional soccer. Thus, the aims were to apply an integrative load monitoring approach, previously established in rink-hockey, in professional soccer; extend this approach with further data (Short Recovery and Stress Scale); assess this (extended) approach, thereby further evaluating the relationship between the used external load (EL) measures (total distance, distance above 55% and 70% of individual maximal speed, number of accelerations and decelerations > 4 m/s2, total loading) and the internal load (IL) measure session rate of perceived exertion training load (sRPE-TL) as well as between the used EL measures and sRPE. This retrospective observational cohort study analyzed data from a Swiss team collected over a 14 week-period during the 2021/22 season. Based on our findings, the integrative approach tested proved to be an applicable load monitoring tool in professional soccer, placing players on a fitness-fatigue continuum throughout the different microcycle sessions without using tests, thus providing relevant information to individually tailor training programs. sRPE-TL (ρ [95% CI] = .55 [.51 to .59] to .87 [.85 to .88]; all p < .001) better reflected the EL experienced by players than sRPE (ρ [95% CI] = .45 [.40 to .50] to .71 [.69 to .75]; all p < .001) supporting the definition of sRPE-TL as a measure of IL. However, for even stronger relevance of the tested tool, further research is warranted, especially to ascertain its sensitivity and determine an optimal selection of EL and IL measures. In sum, the present data clearly demonstrate the importance of load management taking place at an individual level, even within team structures, thereby analyzing a set of both EL and IL measures.
