Monitoring Elite Youth Football Players’ Physiological State Using a Small-Sided Game: Associations With a Submaximal Running Test

Abstract

Purpose: To examine the utility of a standardized small-sided game (SSG) for monitoring within-player changes in mean exercise heart rate (HRex) when compared with a submaximal interval shuttle-run test (ISRT). Methods: Thirty-six elite youth football players (17 [1] y) took part in 6 test sessions across an in-season period (every 4 wk). Sessions consisted of the ISRT (20-m shuttles, 30″:15″ work:rest ratio, 70% maximal ISRT) followed by an SSG (7v7, 80 × 56 m, 6 min). HRex was collected during both protocols, with SSG external load measured as high-speed running distance (>19.8 km·h–1) and acceleration distance (>2 m·s−2). Data were analyzed using linear mixed-effect models. Results: Controlling for SSG external load improved the model fit describing the SSG–ISRT HRex relationship (χ2 = 12.6, P = .002). When SSG high-speed running distance and SSG acceleration distance were held constant, a 1% point change in SSG HRex was associated with a 0.5% point change in ISRT HRex (90% CI: 0.4 to 0.6). Inversely, when SSG HRex was held constant, the effects of a 100-m change in SSG high-speed running distance and a 21-m change in SSG acceleration distance on ISRT HRex were −1.0% (−1.5 to −0.4) and −0.6% points (−1.1 to 0.0), respectively. Conclusions: An SSG can be used to track within-player changes in HRex for monitoring physiological state. Given the uncertainty in estimates, we advise to only give meaning to changes in SSG HRex >2% points. Additionally, we highlight the importance of considering external load when monitoring SSG HRex.

A Worldwide Survey on The Practices and Perceptions of Submaximal Fitness Tests in Team Sports

“…Few practitioners reported using intermittent-variable SMFT, each adopting game-based formats (i.e., sided games). Although considered more feasible 16 , the control over the numerous contextual factors (e.g., number of players, tactics, rules) across assessments influencing locomotor outputs is likely prohibitive 17,18 . Such challenges may explain why few studies have used this practice longitudinally 19 .…”

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“…However, the reported relationships were not excellent, and the researchers suggested this may be due to rarely occurring events during the sided-games (e.g., counterattacks) potentially lowering the standardisation of external load, subsequently influencing HRex. 8 Indeed, substantial within-athlete variability in HSR during sided-games was reported in a recent meta-analysis. 11 Although it is unrealistic to expect perfect associations between two materially different running assessments (i.e., continuous versus intermittent), monitoring HRex in passing or kicking drills (compared to sided-games) might allow for greater standardisation of external loads, possibly yielding closer associations with HRex during discrete SMFTs, and thereby providing improved insights into the physiological state.…”

“…Recently, researchers have attempted to infer an athlete's physiological state in-situ by monitoring internal responses during intermittent-variable SMFTs. 8,9 These assessments, administered in the form of technical-tactical drills (e.g., sided-games), could potentially eliminate the need for discrete testing. For example, Lacome et al 9 reported that after controlling for external intensities, within-athlete changes in internal responses during soccer sided-games largely associated with HRex during a continuous-fixed SMFT (CF-SMFT) paced at 12 km•h -1 .…”

“…However, scheduling of the sided-games within-session or within-micro-cycle was not controlled, which may confound internal-external relationships given the potential for a cardiac drift (within-session) and/or plasma volume changes (within-micro-cycle). 2,10 Houtmeyers et al 8 controlled for within-session and within-micro-cycle scheduling while examining associations in HRex during an individualised intermittent-incremental SMFT (70% Intermittent Shuttle-Run Test) and a 6-minute soccer sided-game (7v7, 80×56 m).…”

“…To note, prior studies have reported model results on full datasets alone, which may risk over-fitting. 8,9 This study aimed to address this limitation by assessing predictive performance on out-of-sample data, providing insights into the generalisability of the models. 14…”