Examining the demands and load of elite Rugby Union: influence on time-loss incidence occurrence and severity

Cousins, B.E.W., 2020. Examining the demands and load of elite Rugby Union: influence on time-loss incidence occurrence and severity. PhD, Nottingham Trent University.

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The studies described in this thesis were undertaken to examine the physical demands of elite Rugby Union and the subsequent impact on time-loss (injury and illness) incidence. Specifically, this thesis examined the demands of Rugby Union training and match play across two leagues of competition (Premiership and Championship) and between forwards and backs (the two main positional groups in Rugby Union). In addition, the thesis examined the effect of key performance indicators (such as tackles, contact carries and breakdown entries) and playing surface on time-loss incidence in matches; alongside the effect of training and match load on all time-loss incidences. Finally, the thesis also considered the severity (i.e. number of days lost) of time-loss incidences; specifically examining how training and match load affect the severity of time-loss incidences when they occur.

The first experimental chapter (Chapter IV) examined match and training demands associated with elite Rugby Union. Training and match load were assessed in eighty-nine players using both subjective (sRPE load) and objective (GPS) methods, alongside a host of key performance indicators in matches (tackles, tackle assists, tackles missed, contact carries, breakdown entries and contact events). These were compared between positions (forwards vs. backs) and league of competition (Premiership vs. Championship), using mixed effect models. Analysis revealed that backs covered a greater distance in training (by 704 m, p<0.001) and a greater distance (by 7.6 m.min-1, p<0.001) and high-speed running distance (by 1.22 m.min-1, p<0.001) in matches, compared to forwards. In matches, the forwards experienced greater contact demands (tackles: 78%; tackle assists: 207%; breakdown entries: 324%; contact events: 117%; all p<0.001) compared to backs. When comparing the Premiership and Championship, the number of tackles (53%, p<0.001) and tackles missed (35%, p=0.001) were greater, whereas contact carries (12%, p=0.010) and breakdown entries (10%, p=0.024) were lower, in the Premiership compared to the Championship. Overall, these findings suggest that the running demands of Rugby Union are higher in backs, whilst contact actions are higher in forwards; with further differences between the Premiership, where the defensive, tackle-centred demand was higher, compared to the Championship where the attacking, ball carrying, demand was increased.

The second experimental chapter (Chapter V) examined whether the key performance indicator variables examined in chapter IV had an impact on match injury incidence. The effect of each key performance indicator (tackles, tackle assists, tackles missed, contact carries, breakdown entries and contact events) on match injury incidence was assessed using mixed effect models. Overall match injury rate was 137.2 per 1000 h match exposure, with the most common site of injury being the head / face (21.7 per 1000 h) and knee (also 21.7 per 1000 h). The incidence of contact injuries was higher than non-contact injury incidence (119.4 per 1000 h vs. 17.8 per 1000 h, respectively). There was no effect of any of the key performance indicators on match injury incidence, when quantified in absolute terms or relative to match duration of each individual player (all p>0.05). Therefore, in conclusion, monitoring such variables is not recommended for assessing injury risk. This may be due to every aspect of Rugby Union, from training to match play, requiring a high level of physical exertion and contact.

The third experimental chapter (Chapter VI) examined whether playing surface had an impact on match injury incidence. Three playing surfaces (grass, hybrid (some synthetic content) and fully synthetic) were modelled against match injury incidence. Injury incidence was more than twice as great on the hybrid playing surface (Odds ratio (OR) = 2.58, p<0.001) and synthetic playing surface (OR = 2.16, p = 0.033), compared to grass. When considering the modality of the injury (i.e. contact or non-contact), the odds of sustaining a contact injury on the hybrid surface (OR = 2.31, p = 0.001) and synthetic surface (OR = 2.19, p = 0.049) was over two times greater compared to grass. The odds of sustaining a non-contact injury was over four times greater on the hybrid surface compared to grass (OR = 4.18, p = 0.028). Despite the influence of playing surface on injury incidence, there were no differences in the severity of injury (minor severity: ≤7 d vs. major severity: ≥8 d) between time-loss incidences that occurred on each surface (all p>0.05). Therefore, these findings suggest that artificial surfaces increase the incidence of injury (both contact and non-contact injuries); yet there is no difference in the severity of the injuries that occur during matches on each surface.

The fourth experimental chapter (Chapter VII) examined the impact of match and training load on time-loss incidence occurrence, in both matches and training. sRPE load, distance and high-speed running distance were quantified using absolute values, the acute:chronic workload ratio (ACWR) and the exponentially weighted moving average (EWMA). The absolute match and training load variables provided the best explanation of the variance in time-loss incidence occurrence (sRPE load: p<0.001, Akaike information criterion (AIC) = 2936; distance: p<0.001, AIC = 3004; high-speed running distance: p<0.001, AIC = 3025). The exponentially weighted moving average approach (EWMA sRPE load: p<0.001, AIC = 2980; EWMA distance: p<0.001, AIC = 2980; EWMA high-speed running distance: p=0.002, AIC = 2987) also explained more of the variance in time-loss incidence occurrence than when the same variables were quantified using the acute:chronic workload ratio approach (ACWR sRPE load: p = 0.091, AIC = 2993; ACWR distance: p = 0.008, AIC = 2990; ACWR high-speed running distance: p=0.153, AIC = 2994). Overall, the absolute sRPE load variable best explained the variance in time-loss incidence occurrence, followed by absolute distance and absolute highspeed running distance. Furthermore, the EWMA approach was better at explaining the variance in time-loss incidence than when the same variables were calculated using the ACWR.

The fifth, and final, experimental chapter (Chapter VIII) examined the effect of each load variable on the severity (minor: ≤7 d lost; major: ≥8 d lost) of time-loss incidence. Overall, 57.0% (270) of all time-loss incidence had minor severity, with injuries split 49.5% (199) minor to 50.5% (203) major and illness 98.6% (71) minor and only 1.4% (1) major. The EWMA sRPE load variable best explained the likelihood of sustaining a major severity over a minor severity time-loss incidence (p<0.001, AIC = 436), followed by EWMA distance (p = 0.001, AIC = 437), absolute distance (p = 0.004, AIC = 440), absolute sRPE load (p = 0.011, AIC = 442) and ACWR sRPE load (p = 0.024, AIC = 443). Overall, these findings suggest that as match and training load increases, there is a concomitant increase in the likelihood of a major (compared to minor) time-loss incidence occurring. Furthermore, more of the variance in the severity of time-loss incidence is explained by the EWMA and absolute load quantified variables above the ACWR quantified variables.

Overall the results from this thesis provide novel evidence regarding the match and training demands of elite Rugby Union and how these demands relate to time-loss incidence risk. The key findings are that: (i) key performance indicators (such as the number of tackles made) did not affect injury incidence in matches; (ii) a synthetic playing surface increases injury incidence occurrence in matches; (iii) higher levels of match and training load increase time loss incidence and the severity of the time-loss incidences; (iv) sRPE load appears to explain more of the variance in time-loss incidence and severity than GPS derived variables (distance and high-speed running distance); and, (v) the exponentially weighted moving average and absolute approaches to load quantification are better indicators of the change in time-loss incidence risk and severity than the acute:chronic workload ratio approach..

Item Type: Thesis
Creators: Cousins, B.E.W.
Date: June 2020
Divisions: Schools > School of Science and Technology
Record created by: Linda Sullivan
Date Added: 22 Feb 2021 11:52
Last Modified: 31 May 2021 15:06
URI: https://irep.ntu.ac.uk/id/eprint/42346

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