Differences in gender and performance in off-road triathlon

The aims of this study were: (1) to examine performance trends and compare elite male and female athletes at the off-road triathlon (1.5-km swim, 30-km mountain biking, and 11-km trail running) world championships since its inception in 1996, and (2) to compare gender-related differences between off-road triathlon and conventional road-based triathlon. Linear regression analyses and ANOVA were used to examine performance trends and differences between the sexes. Elite male performance times stabilized over the 2005-2009 period, whereas elite female performance times continued to improve, especially for the run leg. Differences in performance times between the sexes were less marked in swimming than in mountain biking and running, whereas differences in power output were more marked for mountain biking than for swimming and running. In addition, differences in cycling between the sexes were greater for off-road than conventional on-road triathlon. The specific aspects of mountain biking (e.g. level and terrain) may partly explain the significant differences between the sexes recorded in cycling for off-road triathlon. Future studies will need to focus on the physiological bases of off-road triathlon and how they differ from conventional triathlon.     

Optimizing recovery to support multi-evening cycling competition performance

Road criterium and track bicycle racing occur at high speeds, demand repeated high power outputs, last 10–90?min, and offer little chance for recovery after the event. Consecutive evenings of criterium and track racing are respectively known as speed-week or six-day events and take place in evening hours over the course of a week. Given the schedule and timing of these competitions, return to homeostasis can be compromised. No recommendations exist on how to optimize recovery for cyclists participating in these types of repeated evening competitions. Criterium and track cyclists spend considerable time, near and above the individual lactate threshold and therefore mostly utilize carbohydrate as their chief energy substrate. Henceforth, pre – and post-race nutrition and hydration is examined and recommendations are brought forward for carbohydrate, protein, and fluid intake. As evening high-intensity exercise perturbs sleep, strategies to optimize sleep are discussed and recommendations for an optimal sleep environment are given. Active recovery is examined, and the benefits of a short duration low intensity exercise reviewed. Passive recovery methods such as compression garments and cold water immersion are recommended, while evidence for massage, pneumatic compression devices, and neuromuscular electrical stimulation is still lacking. Optimizing recovery strategies will facilitate a return to the resting state following strenuous night competition.     

Caffeine withdrawal and high-intensity endurance cycling performance

In this study, we investigated the impact of a controlled 4-day caffeine withdrawal period on the effect of an acute caffeine dose on endurance exercise performance. Twelve well-trained and familiarized male cyclists, who were caffeine consumers (from coffee and a range of other sources), were recruited for the study. A double-blind placebo-controlled cross-over design was employed, involving four experimental trials. Participants abstained from dietary caffeine sources for 4 days before the trials and ingested capsules (one in the morning and one in the afternoon) containing either placebo or caffeine (1.5 mg · kg(-1) body weight · day(-1)). On day 5, capsules containing placebo or caffeine (3 mg · kg(-1) body weight) were ingested 90 min before completing a time trial, equivalent to one hour of cycling at 75% peak sustainable power output. Hence the study was designed to incorporate placebo-placebo, placebo-caffeine, caffeine-placebo, and caffeine-caffeine conditions. Performance time was significantly improved after acute caffeine ingestion by 1:49 ± 1:41 min (3.0%, P = 0.021) following a withdrawal period (placebo-placebo vs. placebo-caffeine), and by 2:07 ± 1:28 min (3.6%, P = 0.002) following the non-withdrawal period (caffeine-placebo vs. caffeine-caffeine). No significant difference was detected between the two acute caffeine trials (placebo-caffeine vs. caffeine-caffeine). Average heart rate throughout exercise was significantly higher following acute caffeine administration compared with placebo. No differences were observed in ratings of perceived exertion between trials. A 3 mg · kg(-1) dose of caffeine significantly improves exercise performance irrespective of whether a 4-day withdrawal period is imposed on habitual caffeine users.     

Correlates of simulated hill climb cycling performance

The aim of this study was to assess the relationship between several commonly used aerobic and anaerobic cycle ergometer tests and performance during a treadmill cycling hill climb. Eight competitive cyclists (age 27+/-7 years; body mass 73.2+/-5.2 kg; height 177+/-6 cm; mean +/- s) completed six tests in random order: a lactate minimum test; a Wingate anaerobic power test; and two 6-km climbs at 6% and two 1-km climbs at 12% gradient performed on a motorized treadmill. The mean times and power outputs for the 6-km and 1-km climbs were 16:30+/-1:08 min: s and 330+/-17.8 W, and 4:19+/-0:27 min: s and 411+/-24.4 W, respectively. The best individual predictor of 6-km and 1-km performance times was the time for the corresponding climb at the other distance (r = 0.97). The next strongest predictor of both hill climb performances was the average power produced during the Wingate test divided by body mass. Stepwise regression analysis showed that the two variables contributing most to the prediction equation for both climbs were the Wingate average power per unit of body mass and maximal aerobic power divided by total mass (rider + bike), which together accounted for 92 and 96% of the variability in the 6-km and 1-km climbs. In conclusion, among competitive cyclists, the Wingate average power per unit of body mass was the best single predictor of simulated cycling hill climb performance at the distance and gradient used.     

Non-circular chainring improves aerobic cycling performance in non-cyclists

Non-circular chainrings alter the crank velocity profile over a pedalling cycle. The aim of this study was to investigate the effect of this altered crank velocity profile on the aerobic performance compared to a circular chainring (CC). Ten male non-cyclists performed two incremental maximal tests at 80?rpm on a cycle ergometer: one with a circular (Shimano) and the other with a non-circular chainring Osymetric^® (Somovedi), at least 50?h apart. Each test started with a workload of 100?W lasting 3?min. During the first 12?min, the workload was increased by 30?W every 3?min. Thereafter, the workload was increased by 30?W every 2?min until exhaustion. The power output, the intra-cycle crank angular velocity and the physiological parameters were monitored continuously, averaged over the last 30?s of each increment and at exhaustion, and compared for the two chainrings. Results showed a higher maximal aerobic power attained with the non-circular chainring (362.6?±?37.9 vs. 338.8?±?32.6?W, p?相似文献   

Physiological responses to 1000-m ergometer time-trial performance in outrigger canoeing

Abstract

Graded exercise tests are commonly used to assess peak physiological capacities of athletes. However, unlike time trials, these tests do not provide performance information. The aim of this study was to examine the peak physiological responses of female outrigger canoeists to a 1000-m ergometer time trial and compare the time-trial performance to two graded exercise tests performed at increments of 7.5 W each minute and 15 W each two minutes respectively. 17 trained female outrigger canoeists completed the time trial on an outrigger canoe ergometer with heart rate (HR), stroke rate, power output, and oxygen consumption ([Vdot]O₂) determined every 15 s. The mean (± s) time-trial time was 359 ± 33 s, with a mean power output of 65 ± 16 W and mean stroke rate of 56 ± 4 strokes · min^?1. Mean values for peak [Vdot]O₂, peak heart rate, and mean heart rate were 3.17 ± 0.67 litres · min^?1, 177 ± 11 beats · min^?1, and 164 ± 12 beats · min^?1 respectively. Compared with the graded exercise tests, the time-trial elicited similar values for peak heart rate, peak power output, peak blood lactate concentration, and peak [Vdot]O₂. As a time trial is sport-specific and can simultaneously quantify sprint performance and peak physiological responses in outrigger canoeing, it is suggested that a time trial be used by coaches for crew selection as it doubles as a reliable performance measure and a protocol for monitoring peak aerobic capacity of female outrigger canoeists.     

Physiological responses to 1000-m ergometer time-trial performance in outrigger canoeing

Graded exercise tests are commonly used to assess peak physiological capacities of athletes. However, unlike time trials, these tests do not provide performance information. The aim of this study was to examine the peak physiological responses of female outrigger canoeists to a 1000-m ergometer time trial and compare the time-trial performance to two graded exercise tests performed at increments of 7.5 W each minute and 15 W each two minutes respectively. 17 trained female outrigger canoeists completed the time trial on an outrigger canoe ergometer with heart rate (HR), stroke rate, power output, and oxygen consumption (VO2) determined every 15 s. The mean (+/- s) time-trial time was 359 +/- 33 s, with a mean power output of 65 +/- 16 W and mean stroke rate of 56 +/- 4 strokes min(-1). Mean values for peak VO2, peak heart rate, and mean heart rate were 3.17 +/- 0.67 litres min(-1), 177 +/- 11 beats min(-1), and 164 +/- 12 beats min(-1) respectively. Compared with the graded exercise tests, the time-trial elicited similar values for peak heart rate, peak power output, peak blood lactate concentration, and peak VO2. As a time trial is sport-specific and can simultaneously quantify sprint performance and peak physiological responses in outrigger canoeing, it is suggested that a time trial be used by coaches for crew selection as it doubles as a reliable performance measure and a protocol for monitoring peak aerobic capacity of female outrigger canoeists.     

Diurnal variation in cycling performance: influence of warm-up

We examined the effects of time of day on a cycling time trial with and without a prolonged warm-up, among cyclists who tended towards being high in "morningness". Eight male cyclists (mean +/- s: age = 24.9 +/- 3.5 years, peak power output = 319 +/- 34 W, chronotype = 39 +/- 6 units) completed a 16.1-km time trial without a substantial warm-up at both 07:30 and 17:30 h. The time trial was also completed at both times of day after a 25-min warm-up at 60% of peak power. Power output, heart rate, intra-aural temperature and category ratings of perceived exertion (CR-10) were measured throughout the time trial. Post-test blood lactate concentration was also recorded. Warm-up generally improved time trial performance at both times of day (95% CI for improvement = 0 to 30 s), but mean cycling time was still significantly slower at 07:30 h than at 17:30 h after the warm-up (95% CI for difference = 33 to 66 s). Intra-aural temperature increased as the time trial progressed (P < 0.0005) and was significantly higher throughout the time trials at 17:30 h (P = 0.001), irrespective of whether the cyclists performed a warm-up or not. Blood lactate concentration after the time trial was lowest at 07:30 h without a warm-up (P = 0.02). No effects of time of day or warm-up were found for CR-10 or heart rate responses during the time trial. These results suggest that 16.1-km cycling performance is worse in the morning than in the afternoon, even with athletes who tend towards 'morningness', and who perform a vigorous 25-min warm-up. Diurnal variation in cycling performance is, therefore, relatively robust to some external and behavioural factors.     

Laboratory predictors of uphill cycling performance in trained cyclists

ABSTRACT

This study aimed to assess the relationship between an uphill time-trial (TT) performance and both aerobic and anaerobic parameters obtained from laboratory tests. Fifteen cyclists performed a Wingate anaerobic test, a graded exercise test (GXT) and a field-based 20-min TT with 2.7% mean gradient. After a 5-week non-supervised training period, 10 of them performed a second TT for analysis of pacing reproducibility. Stepwise multiple regressions demonstrated that 91% of TT mean power output variation (W kg^?1) could be explained by peak oxygen uptake (ml kg^?1.min^?1) and the respiratory compensation point (W kg^?1), with standardised beta coefficients of 0.64 and 0.39, respectively. The agreement between mean power output and power at respiratory compensation point showed a bias ± random error of 16.2 ± 51.8 W or 5.7 ± 19.7%. One-way repeated-measures analysis of variance revealed a significant effect of the time interval (123.1 ± 8.7; 97.8 ± 1.2 and 94.0 ± 7.2% of mean power output, for epochs 0–2, 2–18 and 18–20 min, respectively; P < 0.001), characterising a positive pacing profile. This study indicates that an uphill, 20-min TT-type performance is correlated to aerobic physiological GXT variables and that cyclists adopt reproducible pacing strategies when they are tested 5 weeks apart (coefficients of variation of 6.3; 1 and 4%, for 0–2, 2–18 and 18–20 min, respectively).     

Diurnal variation in cycling performance: Influence of warm-up

We examined the effects of time of day on a cycling time trial with and without a prolonged warm-up, among cyclists who tended towards being high in “morningness”. Eight male cyclists (mean?±?s: age = 24.9?±?3.5 years, peak power output = 319?±?34?W, chronotype = 39?±?6 units) completed a 16.1-km time trial without a substantial warm-up at both 07:30 and 17:30?h. The time trial was also completed at both times of day after a 25-min warm-up at 60% of peak power. Power output, heart rate, intra-aural temperature and category ratings of perceived exertion (CR-10) were measured throughout the time trial. Post-test blood lactate concentration was also recorded. Warm-up generally improved time trial performance at both times of day (95% CI for improvement = 0 to 30?s), but mean cycling time was still significantly slower at 07:30?h than at 17:30?h after the warm-up (95% CI for difference = 33 to 66?s). Intra-aural temperature increased as the time trial progressed (P <?0.0005) and was significantly higher throughout the time trials at 17:30?h (P = 0.001), irrespective of whether the cyclists performed a warm-up or not. Blood lactate concentration after the time trial was lowest at 07:30?h without a warm-up (P = 0.02). No effects of time of day or warm-up were found for CR-10 or heart rate responses during the time trial. These results suggest that 16.1-km cycling performance is worse in the morning than in the afternoon, even with athletes who tend towards ‘morningness’, and who perform a vigorous 25-min warm-up. Diurnal variation in cycling performance is, therefore, relatively robust to some external and behavioural factors.     

Carbohydrate and carbohydrate + protein for cycling time-trial performance

Carbohydrate intake during endurance exercise delays the onset of fatigue and improves performance. Two recent cycling studies have reported increased time to exhaustion when protein is ingested together with carbohydrate. The purpose of the present study was to test the hypothesis that ingestion of a carbohydrate + protein beverage will lead to significant improvements in cycling time-trial performance relative to placebo and carbohydrate alone. Thirteen cyclists completed 120 min of constant-load ergometer cycling. Thereafter, participants performed a time-trial in which they completed a set amount of work (7 kJ kg(-1)) as quickly as possible. Participants completed four experimental trials, the first for familiarization and then three randomized, double-blind treatments consisting of a placebo, carbohydrate, and carbohydrate + protein. Participants received 250 ml of beverage every 15 min during the constant-load ride. Time-trial performance for carbohydrate (37.1 min, s = 3.8) was significantly (P < 0.05) faster than placebo (39.7 min, s = 4.6). Time-trial performance for carbohydrate + protein (38.8 min, s = 5.5) was not significantly different from either placebo or carbohydrate. Ingestion of a carbohydrate beverage during two hours of constant-load cycling significantly enhanced subsequent time-trial performance compared with placebo. The carbohydrate + protein beverage provided no additional performance benefit.     

Effects of high-intensity intermittent priming on physiology and cycling performance

The pre-event warm-up or “priming” routine for optimising cycling performance is not well-defined or uniform to a specific event. We aimed to determine the effects of varying the intensity of priming on 3 km cycling performance. Ten endurance-trained male cyclists completed four 3 km time-trials (TT) on four separate occasions, each preceded by a different priming strategy including “self-selected” priming and three intermittent priming strategies incorporating 10 min of constant-load cycling followed by 5 × 10 s bouts of varying relative intensity (100% and 150% of peak aerobic power, W_peak, and all-out priming). The self-selected priming trial (379 ± 44 W) resulted in similar mean power during the 3 km TT to intermittent priming at 100% (376 ± 45 W; ?0.7%; unclear) and 150% (374 ± 48 W; ?1.5%, unclear) of W_peak, but significantly greater than all-out priming (357 ± 45 W; ?5.8%, almost certainly harmful). Differences between intermittent and self-selected priming existed with regards to heart rate (6.2% to 11.5%), blood lactate (?22.9% to 125%) and VO₂ kinetics (?22.9% to 8.2%), but these were not related to performance outcomes. In conclusion, prescribed intermittent priming strategies varying in intensity did not substantially improve 3 km TT performance compared to self-selected priming.     

A comparison of the cycling performance of cyclists and triathletes

The aim of this study was to compare the cycling performance of cyclists and triathletes. Each week for 3 weeks, and on different days, 25 highly trained male cyclists and 18 highly trained male triathletes performed: (1) an incremental exercise test on a cycle ergometer for the determination of peak oxygen consumption (VO2peak), peak power output and the first and second ventilatory thresholds, followed 15 min later by a sprint to volitional fatigue at 150% of peak power output; (2) a cycle to exhaustion test at the VO2peak power output; and (3) a 40-km cycle time-trial. There were no differences in VO2peak, peak power output, time to volitional fatigue at 150% of peak power output or time to exhaustion at VO2peak power output between the two groups. However, the cyclists had a significantly faster time to complete the 40-km time-trial (56:18 +/- 2:31 min:s; mean +/- s) than the triathletes (58:57 +/- 3:06 min:s; P < 0.01), which could be partially explained (r = 0.34-0.51; P < 0.05) by a significantly higher first (3.32 +/- 0.36 vs 3.08 +/- 0.36 l x min(-1)) and second ventilatory threshold (4.05 +/- 0.36 vs 3.81 +/- 0.29 l x min(-1); both P < 0.05) in the cyclists compared with the triathletes. In conclusion, cyclists may be able to perform better than triathletes in cycling time-trial events because they have higher first and second ventilatory thresholds.     

A mathematical model for simulating cycling: applied to track cycling

A review of existing mathematical models for velodrome cycling suggests that cyclists and cycling coaches could benefit from an improved simulation tool. A continuous mathematical model for cycling has been developed that includes calculated slip and steering angles and, therefore, allows for resulting variation in rolling resistance. The model focuses on aspects that are particular, but not unique, to velodrome cycling but could be used for any cycling event. Validation of the model is provided by power meter, wheel speed and timing data obtained from two different studies and eight different athletes. The model is shown to predict the lap by lap performance of six elite female athletes to an average accuracy of 0.36% and the finishing times of two elite athletes competing in a 3-km individual pursuit track cycling event to an average accuracy of 0.20%. Possible reasons for these errors are presented. The impact of speed on steering input is discussed as an example application of the model.     

Physiological determinants of elite mountain bike cross-country Olympic performance

Detailed physiological phenotyping was hypothesized to have predictive value for Olympic distance cross-country mountain bike (XCO-MTB) performance. Additionally, mean (MPO) and peak power output (PPO) in 4 × 30 s all-out sprinting separated by 1 min was hypothesized as a simple measure with predictive value for XCO-MTB performance. Parameters indicative of body composition, cardiovascular function, power and strength were determined and related to XCO-MTB national championship performance (n = 11). Multiple linear regression demonstrated 98% of the variance (P < 0.001) in XCO-MTB performance (t_XCO-MTB; [min]) is explained by maximal oxygen uptake relative to body mass (VO_2peak,rel; [ml/kg/min]), 30 s all-out fatigue resistance (FI; [%]) and with a minor contribution from quadriceps femoris maximal torque (T_max; [Nm]): t_XCO-MTB = ?0.217× VO_2peak,rel.–0.201× FI+ 0.012× T_max+ 85.4. Parameters with no additional predictive value included hemoglobin mass, leg peak blood flow, femoral artery diameter, knee-extensor peak workload, jump height, quadriceps femoris maximal voluntary contraction force and rate of force development. Additionally, multiple linear regression demonstrated parameters obtained from 4x30s repeated sprinting explained 88% of XCO-MTB variance (P < 0.001) with t_XCO-MTB = ?5.7× MPO+ 5.0× PPO+ 55.9. In conclusion, XCO-MTB performance is predictable from VO_2peak,rel and 30 s all-out fatigue resistance. Additionally, power variables from a repeated sprint test provides a cost-effective way of monitoring athletes XCO-MTB performance.     

Practical precooling: effect on cycling time trial performance in warm conditions

The purpose of this study was to compare the effects of two practical precooling techniques (skin cooling vs. skin + core cooling) on cycling time trial performance in warm conditions. Six trained cyclists completed one maximal graded exercise test (VO2(peak) 71.4 +/- 3.2 ml x kg(-1) x min(-1)) and four approximately 40 min laboratory cycling time trials in a heat chamber (34.3 degrees C +/- 1.1 degrees C; 41.2% +/- 3.0% rh) using a fixed-power/variable-power format. Cyclists prepared for the time trial using three techniques administered in a randomised order prior to the warm-up: (1) no cooling (control), (2) cooling jacket for 40 min (jacket) or (3) 30-min water immersion followed by a cooling jacket application for 40 min (combined). Rectal temperature prior to the time trial was 37.8 degrees C +/- 0.1 degrees C in control, similar in jacket (37.8 degrees C +/- 0.3 degrees C) and lower in combined (37.1 degrees C +/- 0.2 degrees C, P < 0.01). Compared with the control trial, time trial performance was not different for jacket precooling (-16 +/- 36 s, -0.7%; P = 0.35) but was faster for combined precooling (-42 +/- 25 s, - .8%; P = 0.009). In conclusion, a practical combined precooling strategy that involves immersion in cool water followed by the use of a cooling jacket can produce decrease in rectal temperature that persist throughout a warm-up and improve laboratory cycling time trial performance in warm conditions.     

Practical precooling: Effect on cycling time trial performance in warm conditions

Abstract

The purpose of this study was to compare the effects of two practical precooling techniques (skin cooling vs. skin + core cooling) on cycling time trial performance in warm conditions. Six trained cyclists completed one maximal graded exercise test ([Vdot]O_2peak 71.4 ± 3.2 ml · kg^?1 · min^?1) and four ～40 min laboratory cycling time trials in a heat chamber (34.3°C ± 1.1°C; 41.2% ± 3.0% rh) using a fixed-power/variable-power format. Cyclists prepared for the time trial using three techniques administered in a randomised order prior to the warm-up: (1) no cooling (control), (2) cooling jacket for 40 min (jacket) or (3) 30-min water immersion followed by a cooling jacket application for 40 min (combined). Rectal temperature prior to the time trial was 37.8°C ± 0.1°C in control, similar in jacket (37.8°C ± 0.3°C) and lower in combined (37.1°C ± 0.2°C, P < 0.01). Compared with the control trial, time trial performance was not different for jacket precooling (?16 ± 36 s, ?0.7%; P = 0.35) but was faster for combined precooling (?42 ± 25 s, ?1.8%; P = 0.009). In conclusion, a practical combined precooling strategy that involves immersion in cool water followed by the use of a cooling jacket can produce decrease in rectal temperature that persist throughout a warm-up and improve laboratory cycling time trial performance in warm conditions.     

Knowledge is power: Issues of measuring training and performance in cycling

ABSTRACT

Mobile power meters provide a valid means of measuring cyclists’ power output in the field. These field measurements can be performed with very good accuracy and reliability making the power meter a useful tool for monitoring and evaluating training and race demands. This review presents power meter data from a Grand Tour cyclist’s training and racing and explores the inherent complications created by its stochastic nature. Simple summary methods cannot reflect a session’s variable distribution of power output or indicate its likely metabolic stress. Binning power output data, into training zones for example, provides information on the detail but not the length of efforts within a session. An alternative approach is to track changes in cyclists’ modelled training and racing performances. Both critical power and record power profiles have been used for monitoring training-induced changes in this manner. Due to the inadequacy of current methods, the review highlights the need for new methods to be established which quantify the effects of training loads and models their implications for performance.