Author reply to Weaving et al.: comment on: ‘A contemporary multi-modal mechanical approach to training monitoring in elite professional soccer: a mathematical problem?’

Abstract

Dear Editor, We thank the authors of this particular paper for their constructive comments on our manuscript first published within Science and Medicine in football in 2017 (Owen et al. 2017) and welcome the opportunity to address some of the points raised. Overall, we agree with the points made and we welcome further debate within this research area. Furthermore, we take great satisfaction from the discussion the manuscript has caused within the practical and academic communities across professional team sport codes. We also hope these debates will allow for the opportunity for future research within other team sport codes across this multi-modal approach to monitoring. The main concerns raised by Weaving et al. (2020) relate to the collinearity of specific external loading measures that are provided from GPS micro sensor technology within the practical setting daily. We do not disagree with the comments on this fact; indeed, extensive reviews and additional manuscripts across the training load literature have reported on this issue across the preceding three-year period post the initial publication of the manuscript into multi-modal models in 2017. Additionally, while practically through mediums like social media and podcasts, there may have been an increase in interest within the topic area; academically, one additional research manuscript has been published in this area (Owen et al. 2019), highlighting the need for increased debate and refinement of the multi-modal approach originally published in 2017. This research, we hope, will incorporate the specific statistical requirements that may reduce the highlighted collinearity within the original model proposed by Owen and colleagues in 2017. It should be noted by academics that previous literature has reported on the disconnect between practitioners and academics with respect to embedded sports science research (Malone et al. 2019). The research reported that while research collaborations were mainly formed to improve team performance, academics ranked journal articles with increased importance, while practitioners rated one-to-one communication as more preferential. Furthermore, potential barriers were found in terms of staff buy-in, with practitioners reporting a preference for ‘fast’ type research. Overall, practitioners preferred ‘fast’ informal research dissemination compared to the ‘slow’ quality control approach of academics. The above highlights how research over time can improve any methodological issues associated with specific measures, but also how practitioners are concerned with the here and now, and getting staff buy-in through open communication channels with backroom teams and management within a high-performance setting. From its inception, the multi-modal approach was created to condense down specific external loading reports for applied practitioners into two key variables of volume and intensity represented by specific percentage values, in order to allow for a more simplistic process of external load dissemination between performance staff and technical staff within soccer. We acknowledge, however, that not all models are without limitations, based on additional research within the area of ratios, that these data within the multi-model model may mathematically scale across specific players depending on their performance within the training and match-play (Lolli et al. 2018). However, the main purpose of the creation of the external training load measures within the model was to provide an approach to practitioners that would engage technical staff of elite sporting organisations who anecdotally have limited interest in engaging with sport science professionals due to the ever-increasing data within the applied field. We feel that since the model’s inception it has allowed for increased communication between staff members within high-performance teams across multiple sporting codes based. However, we acknowledge that specific improvements are required to the model, based on the constructive feedback from Weaving et al. (2020). The original model (Owen et al. 2017) did not include a PCA but it should be noted that the original paper was developed to show-case a concept for practitioners with respect to external training load analysis. It was expected that this model would be modified by readers to fit their contextual environments. For example, through ‘fast’ informal research dissemination, the authors of the original manuscript have observed practitioners within team sport settings applying average match-running performance within the model, replacing the average maximal performance measures within the original model in addition to completing PCA on measures and selecting the most appropriate measures to include within their specific context. However, to date, these different multi-model iterations have not been published within peer-reviewed journals. As such, we hope that through these two communications (Weaving et al. 2020; Owen et al. 2017), there is an increase in analysis of the multi-modal concept within team sports. Like all new concepts within sport science and science, these are subject to peer review analysis resulting in limitations being discussed and debated over-time; these discussions then result in new research that ultimately progresses the topic area. The original model was aimed at practitioners who were concerned about reducing the gap of understanding between training and game external loading reports for technical staff through a data reductionist approach that resulted in the creation of two targeted training measures namely: percentage volume SCIENCE AND MEDICINE IN FOOTBALL 2022, VOL. 6, NO. 2, 270–271 https://doi.org/10.1080/24733938.2021.1942539