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Purpose: To prescribe training loads to improve performance, one must know how an athlete is responding to loading. The maximal rate of heart-rate increase (rHRI) during the transition from rest to exercise is linearly related to changes in endurance exercise performance and can be used to infer how athletes are responding to changes in training load. Relationships between rHRI and anaerobic exercise performance have not been evaluated. The objective of this study was to evaluate relationships between rHRI and anaerobic exercise performance. Methods: Eighteen recreational strength and power athletes (13 male and 5 female) were tested on a cycle ergometer for rHRI, 6-second peak power output, anaerobic capacity (30-s average power), and blood lactate concentration prior to (PRE), and 1 (POST1) and 3 (POST3) hours after fatiguing high-intensity interval cycling. Results: Compared with PRE, rHRI was slower at POST1 (effect size [ES] = −0.38, P = .045) but not POST3 (ES = −0.36, P = .11). PPO was not changed at POST1 (ES = −0.12, P = .19) but reduced at POST3 (ES = −0.52, P = .01). Anaerobic capacity was reduced at POST1 (ES = −1.24, P P P P = .11). rHRI was positively related to PPO (B = 0.19, P = .03) and anaerobic capacity (B = 0.14, P = .005) and inversely related to blood lactate concentration (B = −0.22, P = .04). Conclusions: rHRI is linearly related to acute changes in anaerobic exercise performance and may indicate how athletes are responding to training to guide the application of training loads.

Objectives: To identify and summarise the contextual factors associated with running demands in elite male Australian football (AF) gameplay that have been reported in the literature. Design: Scoping review Methods: A contextual factor in sporting gameplay is a variable associated with the interpretation of results, yet is not the primary objective of gameplay. Systematic literature searches were performed in four databases to identify what contextual factors associated with running demands in elite male AF have been reported: Scopus, SPORTDiscus, Ovid Medline and CINAHL, for terms constructed around Australian football AND running demands AND contextual factors. The present scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and narrative synthesis was conducted. Results and Conclusion: A total of 36 unique articles were identified by the systematic literature search, which included 20 unique contextual factors. The most studied contextual factors were position (n = 13), time in game (n = 9), phases of play (n = 8), rotations (n = 7) and player rank (n = 6). Multiple contextual factors, such as playing position, aerobic fitness, rotations, time within a game, stoppages, and season phase appear to correlate with running demands in elite male AF. Many identified contextual factors have very limited published evidence and thus additional studies would help draw stronger conclusions Refereed/Peer-reviewed

Refereed/Peer-reviewed Objectives: Maximal aerobic speed (MAS) may be predicted from 2.0 km time trial (TT) running speed in male Australian Rules football (AF) players. Given the between-sex differences in physiological variables precursory to endurance performance, and the impact of this on MAS distance limit, this study determined running speed across various TT distances best approximating MAS in female AF players. Method: 33 female AF players completed assessments of MAS and TT performance separated by at least 48 h. In a randomised order, half of the athletes completed TT distances of 1.2, 1.6 and 2.0 km, and the other half completed distances of 1.4, 1.8 and 2.2 km. Bias, limits of agreement (LOA) and linear mixed modelling determined agreement between TT-derived running speed and MAS. Results: Average speed for all TT distances were different to MAS (bias≥0.59 ± 0.45 km·h−1; p ≤ 0.015) with the exception of the 1.4 km TT (bias = −0.12 ± 0.26 km·h−1; p = 0.34). LOA was narrowest for the 1.4 km TT(±0.76 km·h−1; ±6.1%) compared to other TT distances (±0.82–1.67 km·h−1; ±6.7–12.9%). A significant linear association between bias and TT distance (r = −0.73; p < 0.001) indicated TT speed would be equal to MAS when a 1.4–1.5 km TT was completed, and that MAS may be predicted from any distance between 1.2 and 2.2 km. Conclusions: MAS was best approximated by a 1.4–1.5 km TT in female AF players, but may be predicted from TT speed for any distance between 1.2 and 2.2 km. TT-derived MAS provides a time and resource efficient method for the quantification of aerobic fitness and prescription of future training intensities.

Salagaras, BS, Mackenzie-Shalders, KL, Nelson, MJ, Fraysse, F, Wycherley, TP, Slater, GJ, McLellan, C, Kumar, K, and Coffey, VG. Comparisons of daily energy intake vs. expenditure using the GeneActiv accelerometer in elite Australian Football athletes. J Strength Cond Res 35(5): 1273–1278, 2021—To assess validity of the GeneActiv accelerometer for use within an athlete population and compare energy expenditure (EE) with energy and macronutrient intake of elite Australian Football athletes during a competition week. The GeneActiv was first assessed for utility during high-intensity exercise with indirect calorimetry. Thereafter, 14 professional Australian Football athletes (age, 24 ± 4 [SD] y; height, 1.87 ± 0.08 m; body mass, 86 ± 10 kg) wore the accelerometer and had dietary intake assessed via dietitian-led 24-hour recalls throughout a continuous 7 days of competition period (including match day). There was a significant relationship between metabolic equivalents and GeneActiv g·min−1 (SEE 1.77 METs; r2 = 0.64; p < 0.0001). Across the in-season week a significant difference only occurred on days 3 and 4 (day 3: energy intake [EI] EI 137 ± 31 kJ·kg−1·d−1; 11,763 ± 2,646 kJ·d−1 and EE: 186 ± 14 kJ·kg−1·d−1; 16,018 ± 1973 kJ·d−1; p < 0.05; d = −1.4; day 4: EI: 179 ± 44 kJ·kg−1·d−1, 15,413 ± 3,960 kJ·d−1 and EE: 225 ± 42 kJ·kg−1·d−1; 19,313 ± 3,072 kJ·d−1; d = −0.7). Carbohydrate intake (CI) was substantially below current sports nutrition recommendations on 6 of 7 days with deficits ranging from −1 to −7.2 g·kg−1·d−1 (p < 0.05), whereas daily protein and fat intake was adequate. In conclusion, the GeneActiv provides effective estimation of EE during weekly preparation for a professional team sport competition. Australian Footballers attempt to periodize dietary EI to varying daily training loads but fail to match expenditure on higher-training load days. Specific dietary strategies to increase CI may be beneficial to achieve appropriate energy balance and macronutrient distribution, particularly on days where athletes undertake multiple training sessions. Refereed/Peer-reviewed

© 2018 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (February 2018) in accordance with the publisher’s archiving policy, Objective To determine the change in walking gait biomechanics after total hip arthroplasty (THA) for osteoarthritis (OA) compared to the pre-operative gait status, and to compare the recovery of gait following THA with healthy individuals. Methods Systematic review with meta-analysis of studies investigating changes in gait biomechanics after THA compared to (1) preoperative levels and (2) healthy individuals. Data were pooled at commonly reported time points and standardised mean differences (SMDs) were calculated in meta-analyses for spatiotemporal, kinematic and kinetic parameters. Results Seventy-four studies with a total of 2,477 patients were included. At 6 weeks postoperative, increases were evident for walking speed (SMD: 0.32, 95% confidence intervals (CI) 0.14, 0.50), stride length (SMD: 0.40, 95% CI 0.19, 0.61), step length (SMD: 0.41, 95% CI 0.23, 0.59), and transverse plane hip range of motion (ROM) (SMD: 0.36, 95% CI 0.05, 0.67) compared to pre-operative gait. Sagittal, coronal and transverse hip ROM was significantly increased at 3 months (SMDs: 0.50 to 1.07). At 12 months postoperative, patients demonstrated deficits compared with healthy individuals for walking speed (SMD: −0.59, 95% CI −1.08 to −0.11), stride length (SMD: −1.27, 95% CI -1.63, −0.91), single limb support time (SMD: −0.82, 95% CI −1.23, −0.41) and sagittal plane hip ROM (SMD: −1.16, 95% CI −1.83, −0.49). Risk of bias scores ranged from seven to 24 out of 26. Conclusions Following THA for OA, early improvements were demonstrated for spatiotemporal and kinematic gait patterns compared to the pre-operative levels. Deficits were still observed in THA patients compared to healthy individuals at 12 months.

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Purpose: Correlations between fatigue-induced changes in exercise performance and maximal rate of heart rate (HR) increase (rHRI) may be affected by exercise intensity during assessment. This study evaluated the sensitivity of rHRI for tracking performance when assessed at varying exercise intensities. Method: Performance (time to complete a 5-km treadmill time-trial [5TTT]) and rHRI were assessed in 15 male runners following 1 week of light training, 2 weeks of heavy training (HT), and a 10-day taper (T). Maximal rate of HR increase (measured in bpm·s−¹) was the first derivative maximum of a sigmoidal curve fit to HR data recorded during 5 min of running at 8 km·h⁻¹ (rHRI⁸–¹³ᵏᵐ·ʰ−¹), and during subsequent transition to 13 km·h−¹ (rHRI⁸–¹³ᵏᵐ·ʰ−¹) for a further 5 min. Results: Time to complete a 5-km treadmill time-trial was likely slower following HT (effect size ± 90% confidence interval = 0.16 ± 0.06), and almost certainly faster following T (–0.34 ± 0.08). Maximal rate of HR increase during 5 min of running at 8 km·h−¹ and rHRI⁸–¹³ᵏᵐ·ʰ−¹ were unchanged following HT and likely increased following T (0.77 ± 0.45 and 0.66 ± 0.62, respectively). A moderate within-individual correlation was found between 5TTT and rHRI⁸–¹³ᵏᵐ·ʰ−¹ (r value ± 90% confidence interval = –.35 ± .32). However, in a subgroup of athletes (n = 7) who were almost certainly slower to complete the 5TTT (4.22 ± 0.88), larger correlations were found between the 5TTT and rHRI⁸–¹³ᵏᵐ·ʰ−¹ (r = –.84 ± .22) and rHRI⁸–¹³ᵏᵐ·ʰ−¹ (r = –.52 ± .41). Steady-state HR during rHRI assessment in this group was very likely greater than in the faster subgroup (≥ 1.34 ± 0.86). Conclusions: The 5TTT performance was tracked by both rHRI⁸–¹³ᵏᵐ·ʰ−¹ and rHRI⁸–¹³ᵏᵐ·ʰ−¹. Correlations between rHRI and performance were stronger in a subgroup of athletes who exhibited a slower 5TTT. Individualized workloads during rHRI assessment may be required to account for varying levels of physical conditioning. Refereed/Peer-reviewed

Purpose: Being able to identify how an athlete is responding to training would be useful to optimise adaptation and performance. The maximal rate of heart rate increase (rHRI), a marker of heart rate acceleration has been shown to correlate with performance changes in response to changes in training load in male athletes; however, it has not been established if it also correlates with performance changes in female athletes. Methods: rHRI and cycling performance were assessed in six female cyclists following 7 days of light training (LT), 14 days of heavy training (HT) and a 10 day taper period. rHRI was the first derivative maximum of a sigmoidal curve fit to R-R data recorded during 5 min of cycling at 100 W. Cycling performance was assessed as work done (kJ) during time-trials of 5 (5TT) and 60 (60TT) min duration. Results: 5TT was possibly decreased at HT (ES ± 90% confidence interval = − 0.16 ± 0.25; p = 0.60), while, 5TT and 60TT very likely to almost certainly increased from HT to taper (ES = 0.71 ± 0.24; p = 0.007 and ES = 0.42 ± 0.19; p = 0.02, respectively). Large within-subject correlations were found between rHRI, and 5TT (r = 0.65 ± 0.37; p = 0.02) and 60TT (r = 0.70 ± 0.31; p = 0.008). Conclusions: rHRI during the transition from rest to light exercise correlates with training induced-changes in exercise performance in females, suggesting that rHRI may be a useful monitoring tool for female athletes. Refereed/Peer-reviewed

BackgroundFoods rich in nutrients, such as nitrate, nitrite, L-arginine and polyphenols, can promote the synthesis of nitric oxide (NO), which may induce ergogenic effects on endurance exercise performance. Thus, consuming foods rich in these components, such as almonds, dried grapes and dried cranberries (AGC), may improve athletic performance. Additionally, the antioxidant properties of these foods may reduce oxidative damage induced by intense exercise, thus improving recovery and reducing fatigue from strenuous physical training. Improvements in NO synthesis may also promote cerebral blood flow, which may improve cognitive function.Methods and analysisNinety-six trained male cyclists or triathletes will be randomised to consume ~2550 kJ of either a mixture of AGC or a comparator snack food (oat bar) for 4 weeks during an overreaching endurance training protocol comprised of a 2-week heavy training phase, followed by a 2-week taper. The primary outcome is endurance exercise performance (5 min time-trial performance) and secondary outcomes include markers of NO synthesis (plasma and urinary nitrites and nitrates), muscle damage (serum creatine kinase and lactate dehydrogenase), oxidative stress (F2-isoprostanes), endurance exercise function (exercise efficiency, submaximal oxygen consumption and substrate utilisation), markers of internal training load (subjective well-being, rating of perceived exertion, maximal rate of heart rate increase and peak heart rate) and psychomotor speed (choice reaction time).ConclusionThis study will evaluate whether consuming AGC improves endurance exercise performance, recovery and psychomotor speed across an endurance training programme, and evaluate the mechanisms responsible for any improvement.Trial registration numberACTRN12618000360213.

Purpose: Knowledge of aerobic performance capacity allows for the optimisation of training programs in aerobically dominant sports. Maximal aerobic speed (MAS) is a measure of aerobic performance; however, the time and personnel demands of establishing MAS are considerable. This study aimed to determine whether time-trials (TT), which are shorter and less onerous than traditional MAS protocols, may be used to predict MAS. Methods: 28 Australian Rules football players completed a test of MAS, followed by TTs of six different distances in random order, each separated by at least 48 h. Half of the participants completed TT distances of 1200, 1600 and 2000 m, and the others completed distances of 1400, 1800 and 2200 m. Results: Average speed for the 1200 and 1400 m TTs were greater than MAS (P < 0.01). Average speed for 1600, 1800, 2000 and 2200 m TTs were not different from MAS (P > 0.08). Average speed for all TT distances correlated with MAS (r = 0.69–0.84; P < 0.02), but there was a negative association between the difference in average TT speed and MAS with increasing TT distance (r = −0.79; P < 0.01). Average TT speed over the 2000 m distance exhibited the best agreement with MAS. Conclusions: MAS may be predicted from the average speed during a TT for any distance between 1200 and 2200 m, with 2000 m being optimal. Performance of a TT may provide a simple alternative to traditional MAS testing. Refereed/Peer-reviewed

Objectives: Heart rate kinetics are faster in well-trained athletes at exercise onset, indicating sensitivity to training status, but whether they track performance changes due to changes in training load is unknown. Design: Randomised, counterbalanced, cross-over. Methods: 17 cyclists completed two weeks of light and two weeks of heavy training. The day after each training period heart rate was recorded during 5. min cycling at 100. W to determine the maximal rate of heart rate increase. Participants then performed a 5. min cycle time-trial after which heart rate recovery was determined. Results: Work during 5. min cycle time-trial decreased 3.5% (P