When to Pull the Trigger: Conceptual Considerations for Approximating Head Acceleration Events Using Instrumented Mouthguards.

Head acceleration events (HAEs) are acceleration responses of the head following external short-duration collisions. The potential risk of brain injury from a single high-magnitude HAE or repeated occurrences makes them a significant concern in sport. Instrumented mouthguards (iMGs) can approximate HAEs. The distinction between sensor acceleration events, the iMG datum for approximating HAEs and HAEs themselves, which have been defined as the in vivo event, is made to highlight limitations of approximating HAEs using iMGs. This article explores the technical limitations of iMGs that constrain the approximation of HAEs and discusses important conceptual considerations for stakeholders interpreting iMG data. The approximation of HAEs by sensor acceleration events is constrained by false positives and false negatives. False positives occur when a sensor acceleration event is recorded despite no (in vivo) HAE occurring, while false negatives occur when a sensor acceleration event is not recorded after an (in vivo) HAE has occurred. Various mechanisms contribute to false positives and false negatives. Video verification and post-processing algorithms offer effective means for eradicating most false positives, but mitigation for false negatives is less comprehensive. Consequently, current iMG research is likely to underestimate HAE exposures, especially at lower magnitudes. Future research should aim to mitigate false negatives, while current iMG datasets should be interpreted with consideration for false negatives when inferring athlete HAE exposure.

Quantifying head acceleration exposure via instrumented mouthguards (iMG): a validity and feasibility study protocol to inform iMG suitability for the TaCKLE project.

Instrumented mouthguards (iMGs) have the potential to quantify head acceleration exposures in sport. The Rugby Football League is looking to deploy iMGs to quantify head acceleration exposures as part of the Tackle and Contact Kinematics, Loads and Exposure (TaCKLE) project. iMGs and associated software platforms are novel, thus limited validation studies exist. The aim of this paper is to describe the methods that will determine the validity (ie, laboratory validation of kinematic measures and on-field validity) and feasibility (ie, player comfort and wearability and practitioner considerations) of available iMGs for quantifying head acceleration events in rugby league. Phase 1 will determine the reliability and validity of iMG kinematic measures (peak linear acceleration, peak rotational velocity, peak rotational acceleration), based on laboratory criterion standards. Players will have three-dimensional dental scans and be provided with available iMGs for phase 2 and phase 3. Phase 2 will determine the on-field validity of iMGs (ie, identifying true positive head acceleration events during a match). Phase 3 will evaluate player perceptions of fit (too loose, too tight, bulky, small/thin, held mouth open, held teeth apart, pain in jaw muscles, uneven bite), comfort (on lips, gum, tongue, teeth) and function (speech, swallowing, dry mouth). Phase 4 will evaluate the practical feasibility of iMGs, as determined by practitioners using the system usability scale (preparing iMG system and managing iMG data). The outcome will provide a systematic and robust assessment of a range of iMGs, which will help inform the suitability of each iMG system for the TaCKLE project.

Collision activity during training increases total energy expenditure measured via doubly labelled water.

PURPOSE: Collision sports are characterised by frequent high-intensity collisions that induce substantial muscle damage, potentially increasing the energetic cost of recovery. Therefore, this study investigated the energetic cost of collision-based activity for the first time across any sport. METHODS: Using a randomised crossover design, six professional young male rugby league players completed two different 5-day pre-season training microcycles. Players completed either a collision (COLL; 20 competitive one-on-one collisions) or non-collision (nCOLL; matched for kinematic demands, excluding collisions) training session on the first day of each microcycle, exactly 7 days apart. All remaining training sessions were matched and did not involve any collision-based activity. Total energy expenditure was measured using doubly labelled water, the literature gold standard. RESULTS: Collisions resulted in a very likely higher (4.96 ± 0.97 MJ; ES = 0.30 ± 0.07; p = 0.0021) total energy expenditure across the 5-day COLL training microcycle (95.07 ± 16.66 MJ) compared with the nCOLL training microcycle (90.34 ± 16.97 MJ). The COLL training session also resulted in a very likely higher (200 ± 102 AU; ES = 1.43 ± 0.74; p = 0.007) session rating of perceived exertion and a very likely greater (- 14.6 ± 3.3%; ES = - 1.60 ± 0.51; p = 0.002) decrease in wellbeing 24 h later. CONCLUSIONS: A single collision training session considerably increased total energy expenditure. This may explain the large energy expenditures of collision-sport athletes, which appear to exceed kinematic training and match demands. These findings suggest fuelling professional collision-sport athletes appropriately for the "muscle damage caused" alongside the kinematic "work required".

Multiple Measures are Needed to Quantify Training Loads in Professional Rugby League.

This study aims to investigate the effect of training mode (conditioning and skills) on multivariate training load relationships in professional rugby league via principal component analysis. Four measures of training load (internal: heart rate exertion index, session rating of perceived exertion; external: PlayerLoad™, individualised high-speed distance) were collected from 23 professional male rugby league players over the course of one 12 wk preseason period. Training was categorised by mode (skills or conditioning) and then subjected to a principal component analysis. Extraction criteria were set at an eigenvalue of greater than 1. Modes that extracted more than 1 principal component were subject to a varimax rotation. Skills extracted 1 principal component, explaining 57% of the variance. Conditioning extracted 2 principal components (1st: internal; 2nd: external), explaining 85% of the variance. The presence of multiple training load dimensions (principal components) during conditioning training provides further evidence of the influence of training mode on the ability of individual measures of external or internal training load to capture training variance. Consequently, a combination of internal and external training-load measures is required during certain training modes.

Movement and physical demands of school and university rugby union match-play in England.

BACKGROUND: In England, rugby union is a popular sport and is widely played within schools. Despite the large participation numbers, the movement and physical demands of the sport and how they progress by age have not been explored. METHOD: Ninety-six male rugby union players wore microtechnology devices during six rugby union matches within the education pathway to investigate the movement and physical demands of match-play. To quantify the positional differences and progression by age, data were obtained for participants at the under 16 (U16) (n=31 participants), under 18 (U18) (n=34 participants) and university (n=31 participants) levels. Players were further divided in forwards and backs. Data were analysed using magnitude-based inferences. RESULTS: For the movement demands, U16 total distance and 'striding' was likely higher for forwards than backs, whereas at U18, unclear differences were observed and from university players the inverse was observed (very likely). In all age groups sprint distance was likely to very likely greater for backs than forwards. Forwards had greater physical demands than backs at all age groups. For consecutive age groups, U16 had a likely higher relative distance than U18, and U18 had a likely lower relative distance than university players. Physical demands were similar across age groups for forwards, and greater for backs at older age groups. CONCLUSION: The movement and physical demands of rugby union players participating in schools (U16 and U18), may not be as expected, however, the findings from university players show a similar pattern to the senior game.