A commentary on soccer match-play simulations for applied research and practice. Issue 2 (3rd April 2023) - Field, Adam C.; Harper, Liam D.; W. F. Aldous, Jeffrey; Page, Richard M.
ABSTRACT: Soccer is a fast-growing area of research, demonstrated by a 10-fold increase in the number of PubMed articles derived from the search term 'soccer' between 2001 and 2021. The scope of contemporary soccer-related articles ranges from match-play observations to laboratory evaluations of performance. The activity profile of soccer match-play is variable and techniques to collect data within matches are limited. Soccer-specific simulations have been developed to simulate the evolving demands of match-play. The evolutionary designs of novel simulations provide a reproducible exercise stimulus for varying researcher and practitioner objectives. The applied researcher can utilise simulations to investigate the efficacy of nutritional interventions and environmental stress on performance, while assessing the physiological and biomechanical responses to representations of match-play. Practitioners can adopt simulations for rehabilitation to progressively facilitate return-to-play processes, while implementing extra top-up conditioning sessions for unused and partial-match players. However, there are complexities involved with the selection of varying simulations which are dependent on the research question or practical application. There also remains a paucity of published information to support researchers and practitioners in selecting from differing simulation models. To assist with researcher and practitioner interpretations, we present a commentary of the current simulations to inform decision-making processes for research and training purposes and enhance the application of future research. An objective scoring system was adopted for rating the research and practical applications of each simulation design. Overall scores of 22, 16 and 18 out of 36 were revealed for free-running ( n = 7), non-motorised- ( n = 4) and motorised-treadmill-based simulations ( n = 4), respectively.