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Purpose: Mental fatigue is emerging as an important consideration for elite sporting performance, yet it is rarely monitored. The present study assessed changes in mental fatigue in professional team-sport athletes across 2 seasons and examined the relationship between mental fatigue and other athlete self-report measures of well-being. Methods: Elite netballers contracted to all teams competing in Australia's premier professional netball competition during the 2018 and 2019 seasons (N = 154) participated. Using 5-point Likert scales, mental fatigue, fatigue (physical), tiredness, sleep quality, stress, mood, and motivation were assessed daily across 2 seasons composed of 14 round and finals series. Results: The ratings of mental fatigue significantly changed during both seasons. In 2018, lower ratings of mental fatigue were reported in round 1 versus 3, 4, 6, 8, and 14; round 7 versus 6; and round 6 versus 10 (P <.05). In 2019, lower ratings of mental fatigue were identified for round 1 versus 3, 9, 10 to 14, and semifinal; round 2 versus 10 to 13; and 5 versus 10 to 12 (P <.05). Ordinal regression revealed significant differences between mental fatigue and physical fatigue (P <.001), tiredness (P <.001), stress (P <.001), mood (P <.001), and motivation (P <.05). Conclusions: The present study found mental fatigue to significantly fluctuate across a season in elite netballers. Moreover, perceived mental fatigue differed from physical fatigue, tiredness, stress, mood, and motivation. The data impress the need for mental fatigue to be included as an independent measure of athlete well-being. Monitoring of mental fatigue can allow practitioners to implement strategies to manage its influence on performance. [ABSTRACT FROM AUTHOR]

Purpose: This study investigated the satisfaction of elite female cyclists with their body weight (BW) in the context of race performance, the magnitude of BW manipulation, and the association of these variables with menstrual function. Methods: Female competitors in the Australian National Road Cycling Championships (n = 32) and the Oceania Championships (n = 5) completed a questionnaire to identify current BW, BW fluctuations, perceived ideal BW for performance, frequency of weight consciousness, weight-loss techniques used, and menstrual regularity. Results: All but 1 cyclist reported that female cyclists are “a weight-conscious population,” and 54% reported having a desire to change BW at least once weekly; 62% reported that their current BW was not ideal for performance. Their perceived ideal BW was (mean ± SD) 1.6 ± 1.6 kg (2.5% ± 2.5%) less than their current weight (P < .01), and 73% reported that their career-lowest BW was either “beneficial” or “extremely beneficial” for performance. 65% reported successfully reducing BW in the previous 12 months with a mean loss of 2.4 ± 1.0 kg (4.1% ± 1.9%). The most common weight-loss technique was reduced energy intake (76%). Five cyclists (14%) had been previously diagnosed as having an eating disorder by a physician. Of the 18 athletes not using a hormonal contraceptive, 11 reported menstrual dysfunction (oligomenorrhea or amenorrhea). Conclusion: Elite Australian female cyclists are a weight-conscious population who may not be satisfied with their BW leading into a major competition and in some cases are frequently weight conscious. [ABSTRACT FROM AUTHOR]

Some athletes avoid dairy in the meal consumed before exercise due to fears about gastrointestinal discomfort. Regular exclusion of dairy foods may unnecessarily reduce intake of high quality proteins and calcium with possible implications for body composition and bone health. This study compared the effects of meals that included (Dairy) or excluded (Control) dairy foods on gastric comfort and subsequent cycling performance. Well-trained female cyclists (n = 32; mean ± SD; 24.3 ± 4.1 y; VO2peak 57.1 ± 4.9 ml/kg/min) completed two trials (randomized cross-over design) in which they consumed a meal (2 g/kg carbohydrate and 54 kJ/kg) 2 hr before a 90-min cycle session (80 min at 60% maximal aerobic power followed by a 10-min time trial; TT). The dairy meal contained 3 servings of dairy foods providing ~1350 mg calcium. Gut comfort and palatability were measured using questionnaires. Performance was measured as maximum mean power during the TT (MMP10min). There was no statistical or clinical evidence of an effect of meal type on MMP10min with a mean difference (Dairy – Control) of 4 W (95% CI [–2, 9]). There was no evidence of an association between pretrial gut comfort and meal type (p = .15) or between gut comfort delta scores and meal type postmeal (p = .31), preexercise (p = .17) or postexercise (p = .80). There was no statistical or clinical evidence of a difference in palatability between meal types. In summary, substantial amounts of dairy foods can be included in meals consumed before strenuous cycling without impairing either gut comfort or performance. [ABSTRACT FROM AUTHOR]

Physical profile data from elite, sub-elite, regional, under 21s (U21), under 19s (U19) and under 17s (U17) (n = 845) players from a state netball association in Australia were analysed. Within season changes were examined for the elite and sub-elite players. Longitudinal changes were examined for the elite across four consecutive netball seasons. Elite were significantly older (24.3 ± 3.4years), taller (182.4 ± 7.2cm) and heavier (73.42 ± 6.95kg) than other playing levels (p < 0.001, ES 0.49–3.26) and had higher vertical jump (VJ) data compared to all groups (p < 0.001, ES 0.47–0.93). U17's were significantly faster than elite, sub-elite and U19 players over 5m (p < 0.05, ES 0.36–0.58) while elite were faster over 20m compared to all groups (p < 0.01, ES 0.45–0.72). Elite achieved a greater distance (1350.8m; p < 0.05, ES 0.32–0.50) in the Yo-YoIRT1 compared to the sub-elite, regional, U19 and U17. VJ height significantly increased from the 2014 (51.6 ± 4.8cm) to the 2017 season (59.6 ± 6.3cm) for the elite players (p < 0.01, ES 1.18). Yo-YoIRT1 test scores increased significantly between the pre-season and in-season phases (p < 0.05, ES 0.17). [ABSTRACT FROM AUTHOR]

Purpose: Stroke rate (SR) has not been considered in previous research examining the relative roles of the limbs in front-crawl performance. This study compared velocity, aerobic power ([Formula: see text]) and metabolic cost (C) between whole body (WB) and arms only (AO) front-crawl swimming across various intensities while controlling SR.Methods: Twenty Australian national swimmers performed six 200 m front-crawl efforts under two conditions: (1) WB swimming and, (2) AO swimming. Participants completed the 200 m trials under three SR conditions: "low" (22-26 stroke-cycles min(-1)), "moderate" (30-34 stroke-cycles min(-1) and "high" (38-42 stroke-cycles min(-1)). [Formula: see text] was continuously measured, with C, velocity, SR, and kick rate calculated for each effort.Results: Regardless of the SR condition and sex, AO velocity was consistently lower than WB velocity by ~11.0 % (p < 0.01). AO [Formula: see text] was lower than WB [Formula: see text] at all SR conditions for females (p < 0.01) and at the "high" SR for males (p < 0.01). C did not differ between WB and AO at any SR for both sexes (p > 0.01). When C was expressed as a function of velocity, WB and AO regression equations differed for males (p = 0.01) but not for females (p = 0.087). Kick rate increased as SR increased (p < 0.01), though the kick-to-stroke rate ratio remained constant.Conclusion: Elite swimmers gain ~11 % in velocity from their kick and, when used in conjunction with the arm stroke at the swimmers' preferred frequency, the metabolic cost of WB and AO swimming is the same. Coaches should consider these results when prescribing AO sets if their intention is to reduce the metabolic load. [ABSTRACT FROM AUTHOR]

The article evaluates repeated high-intensity exercise performance testing for training professional rugby league and rugby union players in Queensland, Australia. The reliability and sensitivity of the test was assessed with the correlation of test performance with sprint speed and intermittent running recovery measurements. Data was analyzed using statistical methods such as analysis of variance, repeated measures statistics, and descriptive statistics.

Australian Football, the most popular football code in Australia, is a contact sport played by two teams of 18 players who contest play over four 20-minute quarters; the object of the game is to score the most points through goal kicking. Sixteen professional senior sides compete against each other in the Australian Football League (AFL) and, similar to other football codes, game demands at the elite level in the AFL have changed considerably in recent years. Early time-motion analysis studies highlighted the long periods of time players spent in low intensity activities (standing and walking). While recent studies utilizing global positioning systems (GPS) technology are somewhat in agreement with earlier findings, available evidence suggests that the game is getting faster. For example, 'playing on' after a mark (a feature of the game where players who catch the ball on the full from a kick longer than 15m are awarded a free kick) is now much quicker. Indeed, rule changes in recent years have increased the flow and speed of the game; there has been a reduction in the time taken for umpires to restart play, and for players to kick-in (after the opposition kicks a behind) or take a set shot at goal. Nomadic players (a broad term for midfielders and ruckmen because they follow play over the entire playing field) cover slightly greater distances (12 310m) than both forwards (11 920m) and backs (11 880m) in a game. Compared with players in other positions, midfielders are consistently found to spend the most time at higher intensities (running and sprint efforts with movement velocities >4.44 m/sec), complete more high intensity efforts (∼98 per game), sustain them for longer and have shorter recovery periods between high intensity exercise bouts (∼90 seconds on average). 'Ruckmen' have similar but less intense running profiles, while forwards and backs generally have less game involvement but have a more intermittent running profile (longer recovery periods with shorter duration high intensity exercise bouts and less time spent in constant pace running). Endurance fitness remains very important for players at the elite level of competition, as does upper and lower body strength and power. In addition, given the increasing speed at which Australian Football is now played, repeated sprint ability of players is arguably more important now than it was in previous years. There are no significant differences in these measures between playing position. Similarly, speed over 10-40m does not appear to differ between playing position. Establishing the reliability of distance and velocity-derived GPS data in highly specific game-related activities is needed; once achieved, GPS data have the potential to accurately inform coaches of the position-specific demands on their players and to drive the development of training practices that reflect the changing demands of the game. [ABSTRACT FROM AUTHOR]

The objective of this study is to compare the effects of constant- and variable-intensity cycling on gross efficiency (GE) and to compare estimates of energy expenditure (EE) made using indirect calorimetry (CAL) with estimates derived from commercially available power meters. Methods: Nine national team female road cyclists completed a GE test (GEtest = 4 min at approximately 45%, approximately 55%, approximately 65%, and approximately 75% maximal aerobic power (MAP)) before and after 10.5 min of either constant- (CON)- or variable- (VAR)- intensity cycling averaging approximately 55% MAP. GE measured before, after, and during CON and VAR cycling was compared. Total EE (Id) for 10.5 min of VAR cycling was estimated using indirect CAL and compared with estimates on the basis of mechanical power [Schoberer Rad Messtechnik (SRM)] using the group mean GE, each athlete's mean GE, and each athlete's power to GE regression. Results: There was no effect of VAR on GEtests (P = 0.74). GE reduced from 19.1% ± 0.4% (mean ± SE) during the pretrial GEtests to 18.7% ± 0.4% during the posttrial GEtests (P < 0.05) in both conditions. Differences in GE (mean + SD) measured during CON (18.4% ± 1.6%) and VAR cycling (18.6% ± 1.1%) were trivial (P = 0.28). SRM-based estimates of EE were most accurate when using individual athlete's power GE regression using Pre- and Post-VAR GEtest, data combined (Δ ̄X (%) ± 90% CI, 0.3 ± 0.8; R2 0.98, P <0.001). Group mean estimates were within approximately 1% of CAL, although individual errors were approximately 11%. Conclusion: Findings support the use of calibrated power meters for estimating cycling EE. For trained female road cyclists, total mechanical work (kj) multiplied by 5.3 (GE = 19%) provides a valid estimation of total EE during variable-intensity cycling <75% MAP, although determining each athlete's GE improves accuracy greatly. [ABSTRACT FROM AUTHOR]