feature (not arbitrary estimated). The one and four weeks, used for the acute and chronic load, are approximation of these time decays, that correspond to the time needed to dissipate the training effects. In other words, the time decays have nothing to do with the time windows for the calculation of an average. The parameters of the model are calculated for each individual and do not use the same values for all of the athletes. Finally, it is an additive model and not a ratio like the ACWR. Therefore, in no way can it provide a framework or a relevant reference model. In addition, the use of the ratio between acute and chronic is another problem well-known by statisticians for a long time5. Ratios add unnecessary noise and the ACWR in particular does not properly normalise the acute by the chronic neither mathematically nor conceptually.15 However, the domino effect is that other researchers have tried (and are still trying) to develop new metrics without any conceptual framework and rationale underpinning them17 they are just numbers without any practical meaning. Embracing these metrics just generates additional confusion.
a team or organisation. Not only searching for literature but evaluating its strength and quality. This means that other than specific knowledge in the sport area, good knowledge on research methods and statistics is paramount. The first critical aspect we warn practitioners is related to the nature and goal of the studies. Even if the studies would be methodologically sound (but they are not), they are all descriptive in nature with just a few ‘failed’ attempts to create predictive models. Indeed, no studies have tried to establish a cause-effect relation between training load and injuries in team sports. Predictive models, even if appropriately developed and their predictive validity demonstrated, can be useful but are not deemed to provide causal associations. This means that manipulating the features included in the model cannot change the likelihood of a future event (unless there is cause-effect relation that should be purposely examined). To check this is the case, just read the aims section of any paper to see whether the researchers have tried to establish a causal relation and how. Although experimental studies are the gold standard for cause-effect, there are methods developed to use observational data for causal inferences and these should be explicitly reported in the papers.18 Whilst these methods do not guarantee a cause-effect, they do provide higher level of evidence than studies just running correlational/regression analysis until they do not find something. Just for this fundamental reason, no recommendations on how to manipulate the training load to change injury occurrence can be provided.
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There are other methodological problems suggesting some of the observed associations can be just artefacts and spurious, questioning their relevance even from a pure descriptive perspective for creating theories or principles. The first problem is conceptual. Associations that have been reported in the literature with new metrics that lack any biological, physiological or mechanical explanation connecting them with injury mechanisms. Injury occurs because the stress and strain experienced by a tissue structure exceeded the tissue structure strength. Training load metrics and indicators (in relation to injuries) should reflect these two components: tissues structure strength or structure stress and strain. A conceptual framework on the mechanical causes of injuries has been recently presented14 (https://osf.io/ preprints/sportrxiv/vzxga/). No studies in football have presented plausible reference for conceptual frameworks associating the training load measures to these mechanical causes of injuries. Most studies just used what provided by companies and devices. The only attempt to reconcile metrics such as acute (last week), chronic load (last 4 weeks) and their ratio (acute:chronic workload ratio, ACWR)7, 8 is the Banister model. Liberally adapting this famous model ‘acute load’ was used as indicator of fatigue and ‘chronic load’ of fitness. However, this model was created for performance (mainly endurance sports) and not injuries. Additionally, the model has no physiological explanation (it is a mathematical model). This model is additive and combines two equations that use training load adjusted using time decays calculated from the data
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Without delving too deep into technical details (these will be addressed soon in purposely prepared scientific publications), among the methodological problems of the literature there are suboptimal statistical analyses (e.g. not accounting for the recurrence of injuries), low sample size, overfitting, selective reporting, p-harking, poor handling of missing data, etc. In addition, there are the poor practices favoured by the lack of a reference conceptual framework, which gives the researchers too many degrees of freedom, i.e. they can choose and select whatever they want increasing the risk of false discoveries. Just by manipulating one feature such as the selection of the number and the reference categories typical in some statistical analysis, it has been shown that it can generate at least 42% of false discoveries.4 Indeed, it is typical to classify metrics such as ACWR in categories. In soccer, some studies have used 3,13 others 416 and others 63 categories. The very high false discoveries were obtained just varying one feature of the analysis! Well, there are unfortunately, several other features that have been modified without any justification: data trimming methods, selection of metrics, training load measures, time windows for calculating the averages (from one day to weeks), time lag between training load calculation and injury occurrence, missing data handling, etc. Last but not least, even injury definitions are not consistent among studies: contact, combination of contact and non-contact, match-loss, both training and match-loss injuries, complaints requiring medical attention, complaints or injuries requiring a training session modification, combination of upper and lower body injuries and often unspecified severities/days lost. With these premises it is clear that the area is very prone