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

Abstract

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.

Within- and between-mesocycle variations of well-being measures in top elite male soccer players: a longitudinal study

“…Starters exhibited significantly greater values for ACWR of DOMS than non-starters in M2, M7, M9, and also ACWR of fatigue values were found to be significantly greater in starters than non-starters in M7. On one hand, each mesocycle showed 2 injuries for starters, but on the other hand, higher values of injuries were reported in M1, M3, M4, M6, M7 and M9 (range of 4-6 injuries) which once again does not confirm that ACWR has higher sensibility to detect injuries [45][46][47][48][49][50][51].…”

Contributors to negative biopsychosocial health or performance outcomes in rugby players (CoNBO): a systematic review and Delphi study protocol

“…13 For example, injury is a clear negative player outcome, with a significant body of research calling for wider stakeholder engagement when developing prevention strategies. [14][15][16] Furthermore, involving those directly influenced by the outcomes of specific innovation strategies (ie, persons required to authorise behaviour change) is a key component of the research process. 17 The rugby codes (rugby union, rugby league and rugby sevens, hereafter referred to as 'rugby') are played worldwide by men and women, from youth to senior ages, and amateur to international.…”

“…For example, research suggests that athletes exposed to both minimal and maximal training and match play demands are more susceptible to such outcomes (ie, physical and mental fatigue, injury)12 while a U-shaped relationship has been found between 4-week cumulative load and subsequent injury risk among professional male rugby union players 13. For example, injury is a clear negative player outcome, with a significant body of research calling for wider stakeholder engagement when developing prevention strategies 14–16. Furthermore, involving those directly influenced by the outcomes of specific innovation strategies (ie, persons required to authorise behaviour change) is a key component of the research process 17…”

A Narrative Review for a Machine Learning Application in Sports: An Example Based on Injury Forecasting in Soccer

“…As a matter of fact, injury-related absenteeism from training and matches for top-league players results in a total cost (in terms of player’s recovery, rehabilitation, and players’ salary) of EUR 188 million per season [ 1 ]. In addition to soccer, players of other team sports (e.g., rugby, Australian football, and American football) are subjected to a high number of injuries (81 and 6 injuries per 1000 matches and training hours, respectively) [ 2 , 3 , 4 ]. In contrast, a low number of injuries was detected in kayakers.…”