Do you Play or Do you Train? Insights From Individual Sports for Training Load and Injury Risk Management in Team Sports Based on Individualization

Boullosa, Daniel; Casado, Arturo; Claudino, João Gustavo; Jiménez-Reyes, Pedro; Ravé, Guillaume; Castaño-Zambudio, Adrián; Lima-Alves, Adriano; Oliveira, S. A.; Dupont, Grégory; Granacher, Urs

doi:10.3389/fphys.2020.00995

Cited by 21 publications

(21 citation statements)

References 68 publications

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“…It therefore must be acknowledged that other measures of load (either internal or external) may display more consistent patterns; however, in the context of the league-wide data capture in this study, sRPE was the most practical load measurement to be included. Similarly, although this study assessed and accounted for several contextual factors, when making decisions on injury risk in athletes, a broad range of factors must be considered as opposed to looking at any one training load metric [49,50]. A second limitation is the lack of a lag-period in the analysis, which has previously been reported as important, as spikes in load can increase risk in injury for up to four weeks [15,51,52].…”

Section: Limitationsmentioning

confidence: 99%

Training Load and Injury Risk in Elite Rugby Union: The Largest Investigation to Date

et al. 2020

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Training load monitoring has grown in recent years with the acute:chronic workload ratio (ACWR) widely used to aggregate data to inform decision-making on injury risk. Several methods have been described to calculate the ACWR and numerous methodological issues have been raised. Therefore, this study examined the relationship between the ACWR and injury in a sample of 696 players from 13 professional rugby clubs over two seasons for 1718 injuries of all types and a further analysis of 383 soft tissue injuries specifically. Of the 192 comparisons undertaken for both injury groups, 40% (all injury) and 31% (soft tissue injury) were significant. Furthermore, there appeared to be no calculation method that consistently demonstrated a relationship with injury. Some calculation methods supported previous work for a “sweet spot” in injury risk, while a substantial number of methods displayed no such relationship. This study is the largest to date to have investigated the relationship between the ACWR and injury risk and demonstrates that there appears to be no consistent association between the two. This suggests that alternative methods of training load aggregation may provide more useful information, but these should be considered in the wider context of other established risk factors.

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Section: Limitationsmentioning

confidence: 99%

Training Load and Injury Risk in Elite Rugby Union: The Largest Investigation to Date

et al. 2020

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“…Monitoring loads allows one to identify the consequence of training plans on the players and to individualize the analysis [ 5 ]. Although it is useful to look for accurate measures representing the impact in a training session [ 6 ], interpretation of the load variations across a period of time also seems to be important [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

In-Season Internal and External Workload Variations between Starters and Non-Starters—A Case Study of a Top Elite European Soccer Team

et al. 2021

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Background and Objectives: Interpretation of the load variations across a period seems important to control the weekly progression or variation of the load, or to identify in-micro- and mesocycle variations. Thus, the aims of this study were twofold: (a) to describe the in-season variations of training monotony, training strain and acute:chronic workload ratio (ACWR) through session ratings of perceived exertion (s-RPE), total distance and high-speed running (HSR); and (b) to compare those variations between starters and non-starters. Materials and Methods: Seventeen professional players from a European First League team participated in this study. They were divided in two groups: starters (n = 9) and non-starters (n = 8). The players were monitored daily over a 41-week period of competition where 52 matches occurred during the 2015–2016 in-season. Through the collection of s-RPE, total distance and HSR, training monotony, training strain and ACWR were calculated for each measure, respectively. Data were analyzed across ten mesocycles (M: 1 to 10). Repeated measures ANOVA was used with the Bonferroni post hoc test to compare M and player status. Results: The results revealed no differences between starters vs. non-starters (p > 0.05). M6 had a greater number of matches and displayed higher values for monotony (s-RPE, total distance and HSR), strain (only for total distance) and ACWR (s-RPE, TD and HSR). However, the variation patterns for all indexes displayed some differences. Conclusions: The values of both starters and non-starters showed small differences, thus suggesting that the adjustments of training workloads that had been applied over the season helped to reduce differences according to the player status. Even so, there were some variations over the season (microcycles and mesocycles) for the whole team. This study could be used as a reference for future coaches, staff and scientists.

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“…But, paradoxically, studies with these populations are scarce. Most PAPE studies have been conducted with recreationally active subjects and team sports athletes [14,15], whose sport performances are not solely dependent on muscle power [46]. This may be problematic for the applicability of most published approaches, reinforcing the suggestion of better characterizing the population of athletes.…”

Section: Warm-upmentioning

confidence: 99%

“…The implementation of these strategies should be performed with caution, given the complex nature of the competitive demands [46] and the need for different recovery strategies [59]. To the best of our knowledge, there is no evidence exploring the potential summative effect of both priming and re-warm-up strategies based on PAPE.…”

Section: Testing and Monitoringmentioning

confidence: 99%

Post-activation performance enhancement strategies in sport: a brief review for practitioners

Boullosa¹

2021

Hum Mov.

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In this review, we will present and critically discuss how different conditioning exercises can be implemented in training, testing, and competition for the enhancement of performances in different sports, via post-activation performance enhancement and other delayed potentiation responses. The potentiation approaches described here include warming up, testing and monitoring, re-warm-up and priming strategies, and complex training. The post-activation performance enhancement responses can be best described following the new taxonomy, which allows the identification of the best strategies in every specific sport setting. This requires identifying the post-activation performance enhancement factors, which are the condi tioning activity, the verification test, the population of athletes; and potential moderators (i.e. exercise type and loading, timing; recovery interval, target exercise, performance parameter; training background, age, and sex). The inherent limitations to these approaches, including the gaps in literature requiring further studies, may be overcome in practice by using individualized approaches.

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Do you Play or Do you Train? Insights From Individual Sports for Training Load and Injury Risk Management in Team Sports Based on Individualization

Cited by 21 publications

References 68 publications

Training Load and Injury Risk in Elite Rugby Union: The Largest Investigation to Date

Training Load and Injury Risk in Elite Rugby Union: The Largest Investigation to Date

In-Season Internal and External Workload Variations between Starters and Non-Starters—A Case Study of a Top Elite European Soccer Team

Post-activation performance enhancement strategies in sport: a brief review for practitioners

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