While the training-load models were significantly correlated during each training mode, weaker relationships were observed during specific conditioning. Comparisons suggest that the HR-based models were less effective in detecting periodized increases in training load, particularly during court-based, intermittent, multidirectional drills. The practical benefits and sensitivity of the sRPE model support its use across different basketball training modes.
Borges, NR and Driller, MW. Wearable lactate threshold predicting device is valid and reliable in runners. J Strength Cond Res 30(8): 2212-2218, 2016-A commercially available device claiming to be the world's first wearable lactate threshold predicting device (WLT), using near-infrared LED technology, has entered the market. The aim of this study was to determine the levels of agreement between the WLT-derived lactate threshold workload and traditional methods of lactate threshold (LT) calculation and the interdevice and intradevice reliability of the WLT. Fourteen (7 male, 7 female; mean ± SD; age: 18-45 years, height: 169 ± 9 cm, mass: 67 ± 13 kg, V[Combining Dot Above]O2max: 53 ± 9 ml·kg·min) subjects ranging from recreationally active to highly trained athletes completed an incremental exercise test to exhaustion on a treadmill. Blood lactate samples were taken at the end of each 3-minute stage during the test to determine lactate threshold using 5 traditional methods from blood lactate analysis which were then compared against the WLT predicted value. In a subset of the population (n = 12), repeat trials were performed to determine both inter-reliability and intrareliability of the WLT device. Intraclass correlation coefficient (ICC) found high to very high agreement between the WLT and traditional methods (ICC > 0.80), with TEMs and mean differences ranging between 3.9-10.2% and 1.3-9.4%. Both interdevice and intradevice reliability resulted in highly reproducible and comparable results (CV < 1.2%, TEM <0.2 km·h, ICC > 0.97). This study suggests that the WLT is a practical, reliable, and noninvasive tool for use in predicting LT in runners.
Despite increasing participation rates in masters sport and extensive research examining age-related changes in performance, little is known about the effect of age on recovery kinetics in masters athletes. This narrative review focuses on the relationship between aging and sport participation, and the effect on both performance and recovery following an exercise bout. Current research suggests the effect of age on performance and recovery may be smaller than originally suggested and that increasing sedentary lifestyles appear to play a larger role in any observed decrements in performance and recovery in masters athletes. Currently, it appears that performance decrements are inevitable with age. However, performance capacities can be maintained through systematic physical training. Moreover, the limited current research suggests there may be an age effect on recovery kinetics following an exercise bout, although further research is required to understand the acute and chronic recovery processes in the masters athlete.
PurposeThe aims of this study were to: (1) provide a comprehensive physiological profile of simulated basketball activity and (2) identify temporal changes in player responses in controlled settings.MethodsState-level male basketball players (n = 10) completed 4 × 10 min simulated quarters of basketball activity using a reliable and valid court-based test. A range of physiological (ratings of perceived exertion, blood lactate concentration ([BLa−]), blood glucose concentration ([BGlu]), heart rate (HR), and hydration) and physical (performance and fatigue indicators for sprint, circuit, and jump activity) measures were collected across testing.ResultsSignificantly reduced [BLa−] (6.19 ± 2.30 vs. 4.57 ± 2.33 mmol/L; p = 0.016) and [BGlu] (6.91 ± 1.57 vs. 5.25 ± 0.81 mmol/L; p = 0.009) were evident in the second half. A mean HR of 180.1 ± 5.7 beats/min (90.8% ± 4.0% HRmax) was observed, with a significant increase in vigorous activity (77%–95% HRmax) (11.31 ± 6.91 vs. 13.50 ± 6.75 min; p = 0.024) and moderate decrease in near-maximal activity (>95% HRmax) (7.24 ± 7.45 vs. 5.01 ± 7.20 min) in the second half. Small increases in performance times accompanied by a significantly lower circuit decrement (11.67% ± 5.55% vs. 7.30% ± 2.16%; p = 0.032) were apparent in the second half.ConclusionThese data indicate basketball activity imposes higher physiological demands than previously thought and temporal changes in responses might be due to adapted pacing strategies as well as fatigue-mediated mechanisms.
The present data show lower MPS rates in well-trained masters triathletes over 3 d of training, and this likely contributes to poorer muscle protein repair and remodeling. Furthermore, acute recovery of cycle TT performance tended to be poorer in the masters triathletes.
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