Quantifying Fatigue in the Rugby Codes: The Interplay Between Collision Characteristics and Neuromuscular Performance, Biochemical Measures, and Self-Reported Assessments of Fatigue

Changes in Physical Fitness, Muscle Damage and Cognitive Function in Elite Rugby Players over a Season

This study proposes to monitor the physical, immune and cognitive responses and adaptations of elite rugby players throughout the season based on the loads performed. Anthropometric measurements, physical fitness tests (e.g., muscle strength and power, linear and change-of-direction speed, cardiorespiratory fitness) and analyses of serum concentrations of markers of muscle damage (creatine kinase [CK] and lactate dehydrogenase [LDH]) and brain-derived neurotrophic factor (BDNF) were carried out over a sporting season (24 weeks) for 17 elite rugby players (10 forwards and 7 backs) aged 18.91 ± 0.76 years. The physical fitness test results show improvements in the performance of both forwards and backs over the season (p < 0.05), with an advantage for backs compared with forwards in most tests (p < 0.05). Muscle damage markers decreased at the end of the season compared with the baseline levels for forwards (p < 0.05). CK levels were unchanged for the backs, but there were increased LDH concentrations at the end of the season compared with baseline (p < 0.05). Serum BDNF levels decreased for the total group between the second and third sampling (p < 0.05). The muscular and physical capacities of rugby players differ according to their playing position. Immune responses and adaptations, as well as BDNF levels, vary throughout the season and depend on the physical load performed.

The influence of external loads on post-match neuromuscular fatigue in international rugby union: A partial least squares correlational analysis

The aims were to determine the relationship(s) between match-play external load and post-match neuromuscular fatigue as latent constructs, the contribution of the specific measured variables to these latent constructs, and how these differ between forwards and backs in elite rugby union. Forty-one elite male rugby union players (22 forwards and 19 backs) from the same international rugby union team were tested, with data included from the 2020 and 2021 international seasons (11 matches; 146 player appearances). Player's match-play external loads were quantified using microtechnology (for locomotor activities) and video analysis (for collision actions). Neuromuscular fatigue was quantified using countermovement jump tests on force plates which were conducted ~ 24 to 48 hours pre- and post-match. Partial least squares correlation (PLSC) leave one variable out (LOVO) procedure established the relative variable contribution to both external load (X matrix) and neuromuscular fatigue (Y matrix) constructs. Linear mixed-effects models were then constructed to determine the variance explained by the latent scores applied to the variables representing these constructs. For external load, both locomotor and collision variables were identified for the forwards and the backs, although the identified variables differed between groups. For neuromuscular fatigue, jump height was identified as a high contributor for the forwards and the backs, with concentric impulse and reactive strength index high contributors only for the backs. The explained variance between the external load and neuromuscular fatigue latent constructs at the individual player level was 4.4% and 32.2% in the forwards and the backs models, respectively. This discrepancy may be explained by differences in match-play external loads and/or the specificity of the tests to measure indicators of fatigue. These may differ due to, for example, the activities undertaken in the different positional groups.

Challenges and opportunities of artificial intelligence implementation within sports science and sports medicine teams

The rapid progress in the development of automation and artificial intelligence (AI) technologies, such as ChatGPT, represents a step-wise change in human's interactions with technology as part of a broader complex, sociotechnical system. Based on historical parallels to the present moment, such changes are likely to bring forth structural shifts to the nature of work, where near and future technologies will occupy key roles as workers or assistants in sports science and sports medicine multidisciplinary teams (MDTs). This envisioned future may bring enormous benefits, as well as a raft of potential challenges. These challenges include the potential to remove many human roles and allocate them to semi- or fully-autonomous AI. Removing such roles and tasks from humans will make many current jobs and careers untenable, leaving a set of difficult and unrewarding tasks for the humans that remain. Paradoxically, replacing humans with technology increases system complexity and makes them more prone to failure. The automation and AI boom also brings substantial opportunities. Among them are automated sentiment analysis and Digital Twin technologies which may reveal novel insights into athlete health and wellbeing and team tactical patterns, respectively. However, without due consideration of the interactions between humans and technology in the broader system of sport, adverse impacts are likely to be felt. Human and AI teamwork may require new ways of thinking.

Real-World Fatigue Testing in Professional Rugby Union: A Systematic Review and Meta-analysis

BACKGROUND

Professional rugby union is a high-intensity contact sport with position-specific high training and match volumes across a season that may lead to periods of fatigue if above a typically experienced threshold. This study assesses the influence of match play and/or training on fatigue levels in rugby union players.

OBJECTIVE

We aimed to perform a systematic review and meta-analysis of measures used to assess fatigue status in male professional rugby union players.

METHODS

Using electronic databases (PubMed, SPORTDiscus, Web of Science, Cochrane Library, EMBASE, and MEDLINE), a systematic review of fatigue testing in rugby union was conducted on (1) neuromuscular, (2) subjective self-report, (3) biochemical, and (4) heart rate-derived measures.

RESULTS

Thirty-seven articles were included in this systematic review, of which 14 were further included in a meta-analysis. The results of the meta-analysis revealed small, yet not significant, decreases in countermovement jump height immediately after (effect size [ES] =  - 0.29; 95% confidence interval [CI] - 0.64 to 0.06), 24 h (ES =  - 0.43; 95% CI - 3.99 to 3.21), and 48 h (ES =  - 0.22; 95% CI - 0.47 to 0.02) after exposure to rugby union match play or training. Reported wellness (ES =  - 0.33; 95% CI - 1.70 to 1.04) and tiredness (ES =  - 0.14; 95% CI - 1.30 to 1.03) declined over a period of a few weeks (however, the results were not-statistically significant), meanwhile muscle soreness increased (ES = 0.91; 95% CI 0.06 to 1.75) within the 96 h after the exposure to rugby union match play or training. Finally, while cortisol levels (ES = 1.87; 95% CI - 1.54 to 5.29) increased, testosterone declined (ES =  - 1.54; 95% CI - 7.16 to 4.08) within the 24 h after the exposure. However, these results were not statistically significant.

CONCLUSIONS

Subjective measures of muscle soreness can be used to assess fatigue after match play and training in rugby union players. Within-study and between-study variability for countermovement jump height, biochemical markers, and heart rate-derived measures means the utility (practical application) of these measures to assess fatigue in professional rugby union players after matches and training is unclear.

CLINICAL TRIAL REGISTRATION

PROSPERO ID: CRD42020216706.