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PURPOSE: As the start of the 10th Rugby Union World Cup approaches, performance staff will be working on the final elements of their teams' preparation. Much of this planning and preparation will be underpinned by the latest performance science research. In this invited commentary, we discuss contemporary performance science research in rugby union centered around 4 key performance domains. First, we outline a systematic approach to developing an overall understanding of the game demands and how performance staff can enhance the players' preparedness for competition. We then move on to outline our understanding of the training science domain, followed by a brief overview of effective recovery strategies at major tournaments. Finally, we outline research in the area of competition-day strategies and how they can positively impact players' readiness to compete. CONCLUSIONS: Evaluating a team's preparation for the Rugby Union World Cup can be achieved by mapping their performance plan based on the 4 domains outlined above.

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This study aimed to describe the worst-case scenarios (WCS) of professional soccer players by playing position in different durations and analyse WCS considering different contextual variables (match half, match location and match outcome). A longitudinal study was conducted in a professional soccer team. Data were collected from different WCS durations in the total distance (TD), high-speed running distance (HSRD), and sprinting distance (SPD). A mixed analysis of variance was performed to compare different WCS durations between playing positions and contextual variables, making pairwise comparisons by Bonferroni post hoc test. Positional differences were found for TD (p < 0.01, ω p 2 = 0.02), HSRD (p < 0.01, ω p 2 = 0.01) and SPD (p < 0.01, ω p 2 = 0.02). There was a significant interaction when comparing WCS by match half in TD (F = 6.1, p < 0.01, ω p 2 = 0.07) but no significant differences in HSRD (p = 0.403, ω p 2 = 0) or SPD (p = 0.376, ω p 2 = 0). A significant interaction was identified when comparing WCS by match location in TD (F = 51.5, p < 0.01, ω p 2 = 0.14), HSRD (F = 19.15, p < 0.01, ω p 2 = 0.05) and SPD (F = 8.95, p < 0.01, ω p 2 = 0.01) as well as WCS by match outcome in TD (F = 36.4, p < 0.01, ω p 2 = 0.08), HSRD (F = 13.6, p < 0.01, ω p 2 = 0.04) and SPD (F = 7.4, p < 0.01, ω p 2 = 0.02). Positional differences exist in TD, HSRD, and SPD in match-play WCS, and contextual variables such as match half, match location and match outcome have a significant impact on the WCS of professional soccer players.

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Quantifying game and training demands in basketball allows to determine player's readiness and optimizes preparation to perform and reduce injury risks. Available research is using tracking technology to perform general descriptions of the game activities at professional levels, but somehow, is not exploring the possibilities of gathering data from new variables that can contribute with complementary information for the coaching staffs. The aim of this study was to identify changes in locomotor ratio, at higher and lower speeds, during the game quarters from elite under-18 basketball teams. Ninety-four male players participated in the study (age: 17.4 ± 0.74 years; height: 199.0 ± 0.1 cm; body mass: 87.1 ± 13.1 kg) from different playing positions, Guards (n = 35), Forwards (n = 42), and Centers (n = 17). Data were gathered from an international tournament and players' movements were measured using a portable ultra-wide band position-tracking system (WIMU PRO®, Realtrack Systems, Almeria, Spain). The following variables were measured: (1) relative distance in different speed zones: walking (<6.0 km·h-1), jogging (6.0-12.0 km·h-1), running (12.1-18.0 km·h-1), high-intensity running (18.1-24.0 km·h-1), and sprinting (>24.1 km·h-1); and (2) player load, vector magnitude expressed as the square root of the sum of the squared instantaneous rates of change in acceleration in each of the three planes divided by 100. Afterward, these variables were used to calculate players' locomotor ratio (player load per meter covered) at higher (running, high-intensity running, and sprinting) and lower speeds (walking and jogging). Results from the locomotor ratio at both lower and higher speeds presented a significant effect for the quarter (F = 7.3, p < 0.001 and F = 7.1, p < 0.001, respectively) and player position (F = 3.1, p = 0.04, F = 9.2, p < 0.001, respectively). There was an increase in the locomotor ratio from game quarter (Q) Q1 to Q4 at lower speeds, but contrary trends at higher speeds, i.e., the values have decreased from Q1 to Q4. Also, forwards and centers of the best teams presented lower values at higher speeds. Altogether, the findings may be used by coaching staffs as a first baseline to elaborate normative behavior models from the players' performance and also to induce variability and adaptation in specific practice planning.

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This is a descriptive, cross-sectional study describing the physiological responses during competitive matches and profile of elite exponents of an emerging martial art sport, pencak silat. Thirty exponents (21 males and 9 females) were involved in the study. Match responses (i.e. heart rate (HR) throughout match and capillary blood lactate concentration, [La], at pre-match and at the end of every round) were obtained during actual competitive duels. Elite silat exponents' physiological attributes were assessed via anthropometry, vertical jump, isometric grip strength, maximal oxygen uptake, and the Wingate 30 s anaerobic test of the upper and lower body, in the laboratory. The match response data showed that silat competitors' mean HR was > 84% of estimated HR maximum and levels of [La] ranged from 6.7 - 18.7 mMol(-1) during matches. This suggests that competitive silat matches are characterised by high aerobic and anaerobic responses. In comparison to elite taekwondo and judo athletes' physiological characteristics, elite silat exponents have lower aerobic fitness and grip strength, but greater explosive leg power (vertical jump). Generally, they also possessed a similar anaerobic capability in the lower but markedly inferior anaerobic capability in the upper body.