Movement Patterns and Metabolic Responses During an International Rugby Sevens Tournament.

PURPOSE: To investigate the running demands and associated metabolic perturbations during an official rugby sevens tournament. METHODS: Twelve elite players participated in 7 matches wearing GPS units. Maximal sprinting speed (MSS) and maximal aerobic speed (MAS) were measured. High-intensity threshold was individualized relative to MAS (>100% of MAS), and very-high-intensity distance was reported relative to both MAS and MSS. Blood samples were taken at rest and after each match. RESULTS: Comparison of prematch and postmatch samples revealed significant (P < .01) changes in pH (7.41-7.25), bicarbonate concentration ([HCO3-]) (24.8-13.6 mmol/L), and lactate concentration ([La]) (2.4-11.9 mmol/L). Mean relative total distance covered was 91 ± 13 m/min with ~17 m/min at high-intensity. Player status (whole-match or interchanged players), match time, and total distance covered had no significant impact on metabolic indices. Relative distance covered at high intensity was negatively correlated with pH and [HCO3-] (r = .44 and r = .42, respectively; P < .01) and positively correlated with [La] (r = .36; P < .01). Total distance covered and distance covered at very high intensity during the 1-min peak activity in the last 3 min of play were correlated with [La] (r = .39 and r = .39, respectively; P < .01). CONCLUSIONS: Significant alterations in blood-metabolite indices from prematch to postmatch sampling suggest that players were required to tolerate a substantial level of acidosis related to metabolite accumulation. In addition, the ability to produce energy via the glycolytic energy pathway seems to be a major determinant in match-related running performance.

Relationship Between Blood Flow and Performance Recovery: A Randomized, Placebo-Controlled Study.

PURPOSE: To investigate the effect of different limb blood-flow levels on cycling-performance recovery, blood lactate concentration, and heart rate. METHODS: Thirty-three high-intensity intermittent-trained athletes completed two 30-s Wingate anaerobic test sessions, 3 × 30-s (WAnT 1-3) and 1 × 30-s (WAnT 4), on a cycling ergometer. WAnT 1-3 and WAnT 4 were separated by a randomly assigned 24-min recovery intervention selected from among blood-flow restriction, passive rest, placebo stimulation, or neuromuscular electrical-stimulation-induced blood flow. Calf arterial inflow was measured by venous occlusion plethysmography at regular intervals throughout the recovery period. Performance was measured in terms of peak and mean power output during WAnT 1 and WAnT 4. RESULTS: After the recovery interventions, a large (r = .68 [90% CL .42; .83]) and very large (r = .72 (90% CL .49; .86]) positive correlation were observed between the change in calf arterial inflow and the change in mean and peak power output, respectively. Calf arterial inflow was significantly higher during the neuromuscular-electrical-stimulation recovery intervention than with the blood-flow-restriction, passive-rest, and placebo-stimulation interventions (P < .001). This corresponds to the only intervention that allowed performance recovery (P > .05). No recovery effect was linked to heart rate or blood lactate concentration levels. CONCLUSIONS: For the first time, these data support the existence of a positive correlation between an increase in blood flow and performance recovery between bouts of high-intensity exercise. As a practical consideration, this effect can be obtained by using neuromuscular electrical stimulation-induced blood flow since this passive, simple strategy could be easily applied during short-term recovery.

Positive effect of specific low-frequency electrical stimulation during short-term recovery on subsequent high-intensity exercise.

The objective of this study was to test how low-frequency electrical stimulation (LFES; Veinoplus Sport (AdRem Technology, Paris, France)) of the calf muscles affects recovery indices compared with 2 other commonly used recovery methods (active, ACT; passive, PAS). The tests used assessed predominantly anaerobic performance after short-term (15 min) recovery, and the kinetics of blood markers. Fourteen highly trained female handball players completed 2 Yo-Yo Intermittent Recovery tests (level 2; YYIR2) separated by a 15-min recovery period. During recovery, 1 of 3 recovery methods (ACT, LFES or PAS) was randomly selected. Performance (i.e., distance run) was measured at the end of each YYIR2 test. Blood lactate, pH, bicarbonate concentrations, heart rate, respiratory gas exchange and tissue saturation index for the lateral gastrocnemius were recorded. LFES showed a very likely beneficial effect on performance during the second YYIR2 relative to PAS and a possible beneficial effect relative to ACT (distance Pre vs. Post; LFES: -1.8%; ACT: -7.6%; PAS: -15.9%). Compared with PAS recovery, LFES and ACT recovery clearly showed a faster return to baseline for blood lactate, pH and bicarbonate concentrations during the recovery period. LFES of the calf muscles and, to a lesser extent, ACT recovery appear to effectively improve short-term recovery between 2 bouts of exhausting exercises. These methods could be of benefit if applied during half-time, for sports involving successive rounds, or where only a limited recovery period is available.

Improvement of energy expenditure prediction from heart rate during running.

We aimed to develop new equations that predict exercise-induced energy expenditure (EE) more accurately than previous ones during running by including new parameters as fitness level, body composition and/or running intensity in addition to heart rate (HR). Original equations predicting EE were created from data obtained during three running intensities (25%, 50% and 70% of HR reserve) performed by 50 subjects. Five equations were conserved according to their accuracy assessed from error rates, interchangeability and correlations analyses: one containing only basic parameters, two containing VO2max or speed at VO2max and two including running speed with or without HR. Equations accuracy was further tested in an independent sample during a 40 min validation test at 50% of HR reserve. It appeared that: (1) the new basic equation was more accurate than pre-existing equations (R(2) 0.809 versus. 0,737 respectively); (2) the prediction of EE was more accurate with the addition of VO2max (R(2) = 0.879); and (3) the equations containing running speed were the most accurate and were considered to have good agreement with indirect calorimetry. In conclusion, EE estimation during running might be significantly improved by including running speed in the predictive models, a parameter readily available with treadmill or GPS.