Session-to-session variations in external load measures during small-sided games in professional soccer players

Abstract

The aims of this study were 1) to analyse session-to-session variations in different external load measures and 2) to examine differences in within-session intervals across different small-sided game (SSG) formats in professional players. Twenty professional soccer players (mean ± SD; age 28.1 ± 4.6 years, height 176.7 ± 4.9 cm, body mass 72.0 ± 7.8 kg, and body fat 10.3 ± 3.8%) participated in 3v3, 4v4, and 6v6 SSGs under different conditions (i.e., touch limitations and presence of goalkeepers vs. free touch and ball possession drill) over three sessions. Selected external load measures—including total distance (TD), high-intensity running (HIR, distance covered > 14.4 km . h -1 ), high-speed running (HSR, distance covered > 19.8 km . h -1 ), and mechanical work (MW, accelerations and deceleration > 2.2 m . s 2 )—were recorded using GPS technology during all SSG sessions. Small to large standardized typical errors were observed in session-to-session variations of selected measures across SSGs. TD . min -1 showed less variability, having a coefficient of variation (CV) of 2.2 to 4.6%, while all other selected external load measures had CV values ranging from 7.2% to 29.4%. Trivial differences were observed between intervals in TD . min -1 and HIR . min -1 for all SSGs, as well as in HSR . min -1 and MW . min -1 for most SSG formats. No reductions or incremental trends in session-to-session variations were observed when employing touch limitations or adding goalkeepers. The increased noise observed in higher speed zones (e.g., high-speed running) suggests a need for more controlled, running-based conditional drills if the aim is greater consistency in these measures.

Relationships Between Aerobic Performance, Hemoglobin Levels, and Training Load During Small-Sided Games: A Study in Professional Soccer Players

“…Using different approaches, other study have analyzed between-sets variations of SSGs and reported trivial-to-small standardized differences from the first set to the second set for TD when considering SSGs shorter and longer regimens ( Clemente et al, 2019a ). Also, the same pattern was reported for TD, HIR, and MW measures when considering different SSG formats (3v3, 4v4, and 6v6) with and without goalkeepers and with and without touch limitations ( Younesi et al, 2021 ). Some explanations for the variations in external load demands are the variability of individual and collective dynamics related to tactical behavior ( Clemente et al, 2020 ).…”

“…However, in that study, those metrics showed low R-squared values (R 2 = 27 and 2% for accelerations and decelerations, respectively). This could mean that MW measures contain a higher factor of unexplainable variability – in fact, previous studies have reported a higher coefficient of variation for those metrics within SSGs ( Ade et al, 2014 ; Aquino et al, 2019 ; Younesi et al, 2021 ). However, these comparisons must be carefully analyzed because our study considered MW measure, which encompasses both accelerations and decelerations, while other reported studies analyzed those metrics separately.…”

“…The potential relationships between those variables can assist coaches and practitioners in using SSGs as a more ecological and time-efficient monitoring tool of player’s physiological profile and performance capacity and might also serve as a complement to traditional running-based assessments. Additionally, several studies have analyzed between-session variations in the external and internal load measures of SSGs and suggested the use of standardized differences and small worthwhile change (SWC) to analyze the degree of changes/differences in performance between athletes instead of using percentages of changes ( Buchheit and Rabbani, 2014 ; Clemente et al, 2019b ; Younesi et al, 2021 ). Thus, it is important to understand how the load during SSGs may vary from session to session.…”

Submaximal Fitness Tests in Team Sports: A Theoretical Framework for Evaluating Physiological State

“…Such kinematic parameters are routinely collected using global positioning systems (GPS) or other tracking technologies (i.e., semi-automated pixel tracking, local positioning systems). In the team-sports SMFT framework, the use of level 1-2 mechanical outcome measures can occur in two scenarios: 1) monitoring the speed achieved to a submaximal exercise that is standardised by internal intensity responses [49,153], and 2) monitoring the changes in these variables during intermittent-variable standardised drills [61][62][63]70,85,89,98,108,112,119,131,154], since they are standardised by a variety of other parameters such as duration, sets, recovery and unique constraints (e.g., number of players, rules modifications). Whilst the former is considered less practical in team-sports for many pragmatic reasons, the latter are implemented as a part of the training plan, encompassing sport specific actions and are perhaps the most feasible to apply repeatedly [7,130].…”

“…In fact, studies examining level 1-2 variables during drill (passing drills) and game (SSG) exercises have highlighted their pragmatic advantages to deliver information related to athlete's training status [62,63,89,119]. However, it should be noted that intermittent-variable SMFT are influenced by a variety of contextual factors such as technical level, motivation and tactics [7,63], and have a higher degree of variation (test-retest reliability) compared to other SMFT modalities [61,63,154,155], and therefore, should not necessarily be interpreted in the aforementioned simplistic manner [7].…”