Training and Match Demands of Elite Rugby Union.

ABSTRACT: Cousins, BEW, Morris, JG, Sunderland, C, Bennett, AM, Shahtahmassebi, G, and Cooper, SB. Training and match demands of elite rugby union. J Strength Cond Res 37(1): 141-148, 2023-This study aimed to examine training and match demands associated with elite Rugby Union. Eighty-nine elite players were monitored using subjective (session ratings of perceived exertion) and objective (global positioning systems: distance and high-speed running [defined as >70% of individual maximum speed] distance) methods, alongside key performance indicator variables in matches (e.g., number of tackles made). These were compared between positions (forwards vs. backs) and league of competition (Premiership vs. Championship). Statistical significance was accepted as p < 0.05. Analysis revealed that backs covered greater distance (by 704 m, p < 0.001) in training and 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 with forwards. In matches, the forwards experience greater key performance indicator demand (tackles: 78%; tackle assists: 207%; breakdown entries: 324%; contact events: 117%; all p < 0.001) compared with backs. 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 with the Championship. Overall, these findings confirm that the running demands of Rugby Union are higher in backs, whereas contact actions are higher in forwards, with further differences between the Premiership and Championship. This comprehensive examination of the demands of elite Rugby Union could be used to ensure the specificity of training protocols for elite Rugby Union clubs, specific to both playing position (forward or back) and level of competition (Premiership or Championship).

CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models.

SUMMARY: In constraint-based metabolic modelling, physical and biochemical constraints define a polyhedral convex set of feasible flux vectors. Uniform sampling of this set provides an unbiased characterization of the metabolic capabilities of a biochemical network. However, reliable uniform sampling of genome-scale biochemical networks is challenging due to their high dimensionality and inherent anisotropy. Here, we present an implementation of a new sampling algorithm, coordinate hit-and-run with rounding (CHRR). This algorithm is based on the provably efficient hit-and-run random walk and crucially uses a preprocessing step to round the anisotropic flux set. CHRR provably converges to a uniform stationary sampling distribution. We apply it to metabolic networks of increasing dimensionality. We show that it converges several times faster than a popular artificial centering hit-and-run algorithm, enabling reliable and tractable sampling of genome-scale biochemical networks. AVAILABILITY AND IMPLEMENTATION: https://github.com/opencobra/cobratoolbox . CONTACT: ronan.mt.fleming@gmail.com or vempala@cc.gatech.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sex differences in adolescents' glycaemic and insulinaemic responses to high and low glycaemic index breakfasts: a randomised control trial.

During puberty young people undergo significant hormonal changes which affect metabolism and, subsequently, health. Evidence suggests there is a period of transient pubertal insulin resistance, with this effect greater in girls than boys. However, the response to everyday high and low glycaemic index (GI) meals remains unknown. Following ethical approval, forty adolescents consumed a high GI or low GI breakfast, in a randomised cross-over design. Capillary blood samples were taken during a 2-h postprandial period, examining the glycaemic and insulinaemic responses. Maturity offset and homoeostatic model assessment (HOMA) were also calculated. The glycaemic response to the breakfasts was similar between boys and girls, as shown by similar peak blood glucose concentrations and incremental AUC (IAUC) following both high and low GI breakfasts (all P>0·05). Girls exhibited a higher peak plasma insulin concentration 30 min post-breakfast following both high GI (P=0·043, g=0·69) and low GI (P=0·010, g=0·84) breakfasts, as well as a greater IAUC following high GI (P=0·041, g=0·66) and low GI (P=0·041, g=0·66) breakfasts. HOMA was positively correlated with the insulinaemic responses (all P<0·0005) and maturity offset (P=0·037). The findings of the present study suggest that pubertal insulin resistance affects the postprandial insulinaemic responses to both high and low GI meals. Specifically, girls exhibit a greater insulinaemic response than boys to both meals, despite similar glycaemic responses. This study is the first to report the glycaemic and insulinaemic responses to everyday meals in boys and girls, supporting the recommendation for young people to base their diet on low GI carbohydrates.

Synthetic playing surfaces increase the incidence of match injuries in an elite Rugby Union team.

OBJECTIVES: To examine differences in match injury incidence between three playing surfaces in elite Rugby Union. DESIGN: Prospective cohort. METHODS: Match injury incidence was assessed in 89 elite Rugby Union players over two-seasons of professional competition (44 matches, 1014 h player exposure). Match injury incidence was assessed on three different playing surfaces; natural grass, hybrid (natural grass combined with approximately 3% synthetic fibres) and fully synthetic (sand and rubber infill). Overall injury incidence, contact and non-contact injury incidence, and the incidence of minor (≤7 d lost) and major (≥8 d lost) injuries were considered using mixed effect models. RESULTS: Overall match injury incidence doubled on hybrid and synthetic surfaces compared to natural grass (hybrid: OR = 2.58 [95% CI 1.65-4.03], p < 0.001; synthetic: OR = 2.16 [95% CI 1.07-4.37], p = 0.033). Furthermore, the odds of sustaining a contact injury on a pitch containing any synthetic content also increased compared to natural grass (hybrid: OR = 2.31 [95% CI 1.41-3.78], p = 0.001; synthetic: OR = 2.19 [95% CI 1.00-4.77], p = 0.049). The hybrid surface elicited a four times greater likelihood of non-contact injury incidence compared to natural grass (OR = 4.18 [95% CI 1.16-15.04], p = 0.028). However, the playing surface did not affect the severity of match injuries (all p > 0.05). CONCLUSIONS: The present study suggests that even a small percentage (3%) of synthetic content in the playing surface significantly increases match injury incidence, with an effect seen on both contact and non-contact injury incidence. These findings are important to enable practitioners to be aware of the injury implications of playing matches on hybrid and synthetic pitches.

Match and Training Load Exposure and Time-Loss Incidence in Elite Rugby Union Players.

OBJECTIVE: To investigate the impact of match and training load on time-loss incidence in elite, professional Rugby Union players. MATERIALS AND METHODS: Eighty-nine Rugby Union players were monitored over two seasons of training and competition. Load was measured for all training sessions and matches using subjective [session ratings of perceived exertion (sRPE) load; RPE × session duration] and objective [global positioning systems (GPS); distance and high-speed running distance] methods and quantified using multiple approaches; absolute match and training load, acute:chronic workload ratio (ACWR), exponentially weighted moving average (EWMA) and cumulative 7, 14, 21, and 28 d sums. Mixed effect models were used to assess the effect of each variable on time-loss incidence. RESULTS: Of the 474 time-loss incidences that occurred across the two seasons, 50.0% were contact injuries (86.5% occurred during matches and 13.5% during training), 34.8% were non-contact injuries (31.5% occurred during matches and 68.5% during training) and 15.2% were cases of illness. 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 EWMA 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 the ACWR 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). CONCLUSION: Overall, the absolute sRPE load variable best explained the variance in time-loss incidence, followed by absolute distance and absolute high-speed running distance. Whilst the model fit using the EWMA approach was not as good as the absolute load variables, it was better than when the same variables were calculated using the ACWR method. Overall, these findings suggest that the absolute match and training load variables provide the best predictors of time-loss incidence rates, with sRPE load likely to be the optimal variant of those examined here.