A contemporary multi-modal mechanical approach to training monitoring in elite professional soccer

Owen, Adam; Djaoui, Léo; Newton, Matthew; Malone, Shane; Mendes, Bruno

doi:10.1080/24733938.2017.1334958

Cited by 57 publications

(120 citation statements)

References 25 publications

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“…To optimize adaptation across the various phases of the season, staff constantly altered the structure and composition of the microcycle, so that the individual and collective performances were not impacted. Because of variations in the number of days between matches (40,43), this study only analyzed training weeks where players had 6 days between successive matches, and the training week composed of 5 training sessions that had a clear focus on an upcoming match (35). Based on the recommendations of Akenhead et al (3), training load data were analyzed with respect to the number of days before or after a match (MD minus or plus).…”

Section: Methodsmentioning

confidence: 99%

“…25.2 km$h 21 ) were quantified. The speed thresholds used have been established based on previous studies (40,42,44). The following variables were also quantified: the number of intense accelerations/decelerations (ACC/DEC; .3m $s 22 ), average metabolic power (AMP; W$kg 21 ), and high metabolic load distance (HMLD; m .…”

Section: Methodsmentioning

confidence: 99%

“…Using such technology within training and competition enables coaches to not only understand the distinct game requirements of various playing positions but to also recognize the conditioning needs for the individual roles within the team (15,17,34). As midfielders (MFs) cover twice the high-intensity game distance compared with central defenders (CDs) (11), it is not surprising that research has focused on position-specific training (40). Although, limited data exist on training loads relative to match play across position, and such information could aid practitioners considering a position-specific approach (10).…”

Section: Introductionmentioning

confidence: 99%

“…Although general and position-specific preparations are key, applied staff still have to strike a fine balance between loading the players enough for positive adaptation without elevating the risk of injury (22,25,26). The general consensus is that load metrics are lower in the session before competition, confirming the concept of tapering (19,23,40). However, limited data exist on the loading patterns after competition for players with game time vs. partial or no game time.…”

Section: Introductionmentioning

confidence: 99%

“…However, limited data exist on the loading patterns after competition for players with game time vs. partial or no game time. This is particularly important because players with reduced game time will require a training session that replicates competition loads, whereas those players completing the game will require a recovery session instead (40,43). Therefore, more research on loading strategies the day after a game would be advantageous for coaches, as it would provide them with a practical framework.…”

Section: Introductionmentioning

confidence: 99%

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Quantification of a Professional Football Team's External Load Using a Microcycle Structure

Martín-García

Díaz

Bradley

et al. 2018

Journal of Strength and Conditioning Research

150

229

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Martín-García, A, Gómez Díaz, A, Bradley, PS, Morera, F, and Casamichana, D. Quantification of a professional football team's external load using a microcycle structure. J Strength Cond Res 32(12): 3520-3527, 2018-The aims of this study were to (a) determine the external load of a football team across playing position and relative to competition for a structured microcycle and (b) examine the loading and variation the day after competition for players with or without game time. Training and match data were obtained from 24 professional football players who belonging to the reserve squad of a Spanish La Liga club during the 2015/16 season using global positioning technology (n = 37 matches and n = 42 training weeks). Training load data were analyzed with respect to the number of days before or after a match (match day [MD] minus or plus). Training load metrics declined as competition approached (MD-4 > MD-3 > MD-2 > MD-1; p < 0.05; effect sizes [ES]: 0.4-3.1). On the day after competition, players without game time demonstrated greater load in a compensatory session (MD + 1C) that replicated competition compared with a recovery session (MD + 1R) completed by players with game time (MD + 1C > MD + 1R; p < 0.05; ES: 1.4-1.6). Acceleration and deceleration metrics during training exceeded 50% of that performed in competition for MD + 1C (80-86%), MD-4 (71-72%), MD-3 (62-69%), and MD-2 (56-61%). Full backs performed more high-speed running and sprint distance than other positions at MD-3 and MD-4 (p < 0.05; ES: 0.8-1.7). The coefficient of variation for weekly training sessions ranged from ∼40% for MD-3 and MD-4 to ∼80% for MD + 1R. The data demonstrate that the external load of a structured microcycle varied substantially based on the players training day and position. This information could be useful for applied sports scientists when trying to systematically manage load, particularly compensatory conditioning for players without game time.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%