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Paul S. Bradley and Jack D. Ade

Time–motion analysis is a valuable data-collection technique used to quantify the physical match performance of elite soccer players. For over 40 years, researchers have adopted a “traditional” approach when evaluating match demands by simply reporting the distance covered or time spent along a motion continuum of walking through to sprinting. This methodology quantifies physical metrics in isolation without integrating other factors, and this ultimately leads to a 1-dimensional insight into match performance. Thus, this commentary proposes a novel “integrated” approach that focuses on a sensitive physical metric such as high-intensity running but contextualizes this in relation to key tactical activities for each position and collectively for the team. In the example presented, the integrated model clearly unveils the unique high-intensity profile that exists due to distinct tactical roles, rather than 1-dimensional “blind” distances produced by traditional models. Intuitively, this innovative concept may aid coaches’ understanding of the physical performance in relation to the tactical roles and instructions given to the players. In addition, it will enable practitioners to effectively translate match metrics into training and testing protocols. This innovative model may well aid advances in other team sports that incorporate similar intermittent movements with tactical purpose. Evidence of the merits and application of this new concept is needed before the scientific community accepts this model as it may well add complexity to an area that conceivably needs simplicity.

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Jack D. Ade, Jamie A. Harley and Paul S. Bradley

Purpose:

To quantify the physiological responses, time–motion characteristics, and reproducibility of various speed-endurance-production (SEP) and speed-endurance-maintenance (SEM) drills.

Methods:

Sixteen elite male youth soccer players completed 4 drills: SEP 1 v 1 small-sided game (SSG), SEP running drill, SEM 2 v 2 SSG, and SEM running drill. Heart-rate response, blood lactate concentration, subjective rating of perceived exertion (RPE), and time–motion characteristics were recorded for each drill.

Results:

The SEP and SEM running drills elicited greater (P < .05) heart-rate responses, blood lactate concentrations, and RPE than the respective SSGs (ES 1.1–1.4 and 1.0–3.2). Players covered less (P < .01) total distance and high-intensity distance in the SEP and SEM SSGs than in the respective running drills (ES 6.0–22.1 and 3.0–18.4). Greater distances (P < .01) were covered in high to maximum acceleration/deceleration bands during the SEP and SEM SSGs than the respective running drills (ES 2.6–4.6 and 2.3–4.8). The SEP SSG and generic running protocols produced greater (P < .05) blood lactate concentrations than the respective SEM protocols (ES 1.2–1.7). Small to moderate test–retest variability was observed for heart-rate response (CV 0.9–1.9%), RPE (CV 2.9–5.7%), and blood lactate concentration (CV 9.9–14.4%); moderate to large test–retest variability was observed for high-intensity-running parameters (CV > 11.3%) and the majority of accelerations/deceleration distances (CV > 9.8%) for each drill.

Conclusions:

The data demonstrate the potential to tax the anaerobic energy system to different extents using speed-endurance SSGs and that SSGs elicit greater acceleration/deceleration load than generic running drills.