https://nova.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:40488 Wed 13 Jul 2022 14:41:37 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:32691 Wed 11 Jul 2018 15:26:24 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:32056 2 max and a 3 km time trial) on a nonmotorized treadmill in the heat (33° C). Trials consisted of precooling by combined cold-water immersion and ice slurry ingestion (PRE), midcooling by combined facial water spray and menthol mouth rinse (MID), a combination of all methods (ALL), and control (CON). Performance time was significantly faster in MID (13.7 ± 1.2 minutes; p < 0.01) and ALL (13.7 ± 1.4 minutes; p = 0.04) but not PRE (13.9 ± 1.4 minutes; p = 0.24) when compared with CON (14.2 ± 1.2 minutes). Precooling significantly reduced rectal temperature (initially by 0.5 ± 0.2° C), mean skin temperature, heart rate and sweat rate, and increased iEMG activity, whereas midcooling significantly increased expired air volume and respiratory exchange ratio compared with control. Significant decreases in forehead temperature, thermal sensation, and postexercise blood prolactin concentration were obser ved in all conditions compared with control. Performance was improved with midcooling, whereas precooling had little or no influence. Midcooling may have improved performance through an attenuated inhibitory psychophysiological and endocrine response to the heat.]]> Thu 26 Apr 2018 12:18:57 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:37102 Thu 20 Aug 2020 12:10:20 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:28051 Sat 24 Mar 2018 07:41:02 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:30145 p < 0.01; r(s) = 0.71, p < 0.01, respectively). No significant correlations were evident for defensive skill involvements during SSG and match-play. Overall, it appears that the selected SSG provided players with ample opportunity to practice match-specific skills. In addition, the transfer of these opportunities seems confined to offensive rather then defensive skills.]]> Sat 24 Mar 2018 07:34:34 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:29670 -1) of offensive, defensive and overall involvements was coded for each group using a notation system and a practical coach skill analysis tool. Multivariate analysis of variance (MANOVA) revealed a significant effect of playing position on skill involvements (F = 9.06; P < 0.001; ES = 0.41). Hit-up forwards performed a significantly greater frequency of offensive (0.31 ± 0.10), defensive (0.42 ± 0.15) and overall involvements (0.74 ± 0.19) when compared to adjustables (0.20 ± 0.08, 0.28 ± 0.08 and 0.52 ± 0.15, respectively) and outside backs (0.20 ± 0.12, 0.11 ± 0.07 and ± 0.31 ± 0.17, respectively). Further, adjustables performed a significantly greater number of defensive (0.28 ± 0.08) and overall involvements (0.52 ± 0.15) when compared to outside backs (0.11 ± 0.07 and 0.31 ± 0.17, respectively). The findings of this study suggest that it is important to consider a junior player's positional group when analysing their skill involvements. Information gained from this study could assist in the design of specific training methodologies for junior rugby league players in high-level talent development programmes.]]> Sat 24 Mar 2018 07:32:21 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:34259 Mon 25 Feb 2019 11:39:34 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:47574 Mon 23 Jan 2023 14:00:44 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:36024 max to total cycling mass (body mass including competition clothing and bicycle mass), maximum power output sustained over 60 s relative to total cycling mass, peak left hand grip strength and two-line decision-making score. Previous models for Olympic distance MTB performance demonstrated merit (R² = 0.93; P > 0.05) although subtle changes improved the fit, significance and normal distribution of residuals within the model (R² = 0.99; P < 0.01), highlighting differences between the disciplines. The high level of predictive accuracy of the new XC4H model further supports the use of a multidimensional approach in predicting MTB performance. The difference between the new, XC4H and previous Olympic MTB predictive models demonstrates subtle differences in physiological requirements and performance predictors between the two MTB disciplines.]]> Fri 24 Jan 2020 16:36:12 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:36015 −1 · min⁻¹) completed an incremental cycling test, maximal hand grip strength test, cycling power profile (maximal efforts lasting 6–600 s), decision-making test and an individual XCO-MTB time-trial (34.25 km). A hierarchical approach using multiple linear regression analyses was used to develop predictive models of performance across 10 circuit subsections and the total time-trial. The strongest model to predict overall time-trial performance achieved prediction accuracy of 127.1 s across 6246.8 ± 452.0 s (adjusted R² = 0.92; P < 0.01). This model included VO2max relative to total cycling mass, maximal mean power across 5 and 30 s, peak left hand grip strength, and response time for correct decisions in the decision-making task. A range of factors contributed to the models for each individual subsection of the circuit with varying predictive strength (adjusted R2: 0.62–0.97; P < 0.05). The high prediction accuracy for the total time-trial supports that a multidimensional approach should be taken to develop XCO-MTB performance. Additionally, individual models for circuit subsections may help guide training practices relative to the specific trail characteristics of various XCO-MTB circuits.]]> Fri 24 Jan 2020 16:29:09 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:38022 −1 (5-second effort) and 4.1 ± 0.6 W·kg⁻¹ (600-second effort). No differences in absolute peak power or cadence were identified between groups across any effort length (p > 0.05). However, the XCO-MTB cyclists produced greater mean power outputs relative to body mass than the NC-MTB during the 60-second (6.9 ± 0.8 vs 6.4 ± 0.6 W·kg−1; p = 0.002), 240-second (4.7 ± 0.7 vs. 3.8 ± 0.4 W·kg−1; p < 0.001), and 600-second (4.1 ± 0.6 vs. 3.4 ± 0.3 W·kg⁻¹; p < 0.001) efforts. The PPA is a useful discriminative assessment tool for XCO-MTB and highlights the importance of aerobic power for XCO-MTB performance.]]> Fri 23 Jul 2021 16:22:56 AEST ]]>