This was a good thread but it's quickly descending into rubbish like another well known thread. If CN don't ban Frank Day then I can only suggest that no-one respond to him, it's absolutely pointless.
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Thanks!
You guys are crazy. Anyone with half a brain knows that a good study tries to eliminate all variables except for the one being tested. If what you want to test is the question: for any given training program design will it make a difference whether one uses a HRM as the effort feedback device or a power meter as the effort feedback device? If that is the question then there would not be any intervention other than two groups are given a similar program and one group uses one device and the other uses another and then they are compared. While no study is ever perfect, isn't that what these studies tried to do? And, didn't they find no difference?acoggan said:
Fergie, that is the point. Both groups were able to complete the same program and achieve the same results using two different effort feedback devices. No advantage was seen by the group using the more expensive and supposedly more accurate device.CoachFergie said:
Polyarmour said:
We can only point out his trolling of this thread and hope the moderators step in.
FrankDay said:
If you understood racing and training with a power meter you would know that training isn't about slavishly following any type of feedback device. Training is about doing the necessary preparation to perform in any given event. The power meter tells us how well and how specifically we are doing this.
You would have found the same outcome had you compared watching Family Guy to The Simpsons. Which is coincidentally why I do my interval sessions watching TV or at least with music because watching either a PM or HRM does my head in.
Fergie, if you understood science you would understand that all I am pointing out is some of what the science says about the device compared to other tools used in training and racing, which is what you asked for when you started this thread, remember? My comments do not constitute a personal attack towards you or anyone else.CoachFergie said:
That having been said, one of the arguments given for using a power meter is it is more accurate and doesn't "lag" like a HRM. Then, above you state: "If you understood racing and training with a power meter you would know that training isn't about slavishly following any type of feedback device" Where is the advantage of having a more accurate feedback device if it isn't necessary or even desirable to monitor what is going on with it during the workout? In another post you state you "I do my interval sessions watching TV or at least with music because watching either a PM or HRM does my head in." If that is the case exactly how are you judging the effort of your sessions? What good does the power meter do you if all you are doing is checking, after the session, what you actually did? It isn't like you can take a mulligan and do it over if the pm averaged higher or lower than you wanted. Perhaps we can now understand why the studies haven't found any difference between the pm and the hrm - nobody actually pays much attention to either one of them during the workout.
FrankDay said:
The Swart and Robinson papers (to call them science is drawing a very long bow) say nothing about the device only that if you do the same training you get the same results. We already knew that.
Perhaps you should read Racing and Training with a Power Meter to find out the multitude of other reasons to race and train with one.
Personally because I race Track where you are not allowed to see the Power Meter (most are behind the saddle or have the screen taped over) I use the power meter to calibrate my RPE. Today I did a 3min test and had the screen covered so I could only see the clock.
You use the data to plan the next step. If I produced more watts then steady as she goes, and if not, then if it becomes a trend I make changes.
Yes because I like a little more stimuli than just a PM (video on the trainer, headphones on the road) EVERYONE does the same
FrankDay said:
I know you are in Troll mode but if I want an assessment of my scientific ability I will get it from an actual scientist.
Sweet Zombie Jesus! Can't there be a thread about power without this Frank Day idjit spamming it with his idiocy? Someone needs to start a thread about clocks, cyclometers, or some other measuring device so we can all laugh as Day denies those can be used for measuring training results.
Should we start reporting every one of this posts until the mods do something? Hint mods: There is a good reason why this spamming snake oil salesman was banned from Slowtwitch. He thinks crap flooding any thread that is remotely connected to his product or could be used to disprove his fraudulent claims is good advertising. Plus, unlike companies with legitimate products that pay for advertising, he gets a free ride. He does the same thing on other forums until they finally get sick of him and kick him off.
Durianrider's self-promotion was confined to a single thread. Why not make a "Power Cranks Fraud" thread and restrict Day's broscience to it?
Should we start reporting every one of this posts until the mods do something? Hint mods: There is a good reason why this spamming snake oil salesman was banned from Slowtwitch. He thinks crap flooding any thread that is remotely connected to his product or could be used to disprove his fraudulent claims is good advertising. Plus, unlike companies with legitimate products that pay for advertising, he gets a free ride. He does the same thing on other forums until they finally get sick of him and kick him off.
Durianrider's self-promotion was confined to a single thread. Why not make a "Power Cranks Fraud" thread and restrict Day's broscience to it?
FrankDay said:
That's the whole point though - you do the workout as prescribed, then go back and see if you have improved or are fatigued and then adjust your upcoming training to suit. The only time you should be watching your PM like a hawk while ridingis on recovery rides and during TT's. The rest of the time it is just a guide.
Overall a PM is simply a measurement tool to track improvement and fatigue and to confirm or negate training structure. You still don't grasp the concept of using a PM to adapt your training to suit your physiology and form
Remember, the best tool is no better than a hammer if you don't know how to use it.
I'm starting to suspect that Frank has a grudge against pro cycling, if you know what I meanBroDeal said:
The debate style can be worryingly similar...
I am sorry, I do understand it can be used to track improvement and all of those other things. Cool. All I am saying is the the science seems to be saying that the improvement any athlete on a similar program will see appears to be exactly the same if it isn't used. If you think it makes a difference for you cool, keep using it. I am simply saying that there is no evidence that it is as helpful as everyone seems to think it is.42x16ss said:That's the whole point though - you do the workout as prescribed, then go back and see if you have improved or are fatigued and then adjust your upcoming training to suit. The only time you should be watching your PM like a hawk while ridingis on recovery rides and during TT's. The rest of the time it is just a guide.
Overall a PM is simply a measurement tool to track improvement and fatigue and to confirm or negate training structure. You still don't grasp the concept of using a PM to adapt your training to suit your physiology and form
Remember, the best tool is no better than a hammer if you don't know how to use it.
To those who don't like my throwing ice water into a power meter love fest all I say is present some scientific data to support what you believe.
And, I think you will find it is not me that doesn't grasp the concept but, rather, I suspect, that it is a large percentage of the people who own one and haven't grasped the concept. A power meter can be a useful training tool if used properly. And, I think most will agree that many don't use it properly. Further, there is simply no evidence that a power meter is necessary nor sufficient for an optimum training or racing outcome.
FrankDay said:
More trolling. A power meter is ZERO percent helpful! It will do NOTHING, NADA, ZIPPO to your performance.
It will however measure like it's intended use.
We have. And yes Virginia a power meter does indeed measure power.
More trolling.
But true many don't use it properly or know what to look for in a power meter before they even sit down with WKO+ to figure out watts what.
Hence this thread
Well, if you want to discuss proper use then I guess you need to define "proper use" for what purpose? Then I guess one can ask what scientific evidence there is to support that what is put forth as "proper use" really is the best "proper use" since this thread was started to discuss the scientific basis of this device.CoachFergie said:But true many don't use it properly or know what to look for in a power meter before they even sit down with WKO+ to figure out watts what.
Hence this thread
So, let me ask this question. When you think of proper use of the power meter what do you think should be the ultimate purpose of the use that would then determine proper use? Are you looking to use the device to help optimize training outcome or something much simpler, like documenting workout time, intensity and improvement? Or, something else?
Polyarmour said:
Agree. I was encouraged when Fergie started thread. It could be very useful for those of us that use power meters in our training. It is now deteriorating to the level of Frank.
Examining pacing profiles in elite female road cyclists using exposure variation analysis.
Abbiss CR, Straker L, Quod MJ, Martin DT, Laursen PB.
Abstract
OBJECTIVE:
In this study, the amplitude and time distribution of power output in a variety of competitive cycling events through the use of a new mathematical analysis was examined: exposure variation analysis (EVA).
DESIGN:
Descriptive field study.
SETTING:
Various professional road cycling events, including; a 5-day-eight-stage tour race, a 1-day World Cup event and the Australian National Individual Time Trial Championships.
PARTICIPANTS:
9 elite female cyclists (mean (SD), mass = 57.8 (3.4) kg, height = 167.3 (2.8) cm, Vo(2)peak = 63.2 (5.2) ml kg(-1) min(-1)).
INTERVENTIONS:
None.
MAIN OUTCOME MEASUREMENTS:
The variation in power output and the quantification of the total time and acute time spent at various exercise intensities during competitive professional cycling were examined. Predefined levels of exercise intensity that elicited first ventilation threshold, second ventilation threshold and maximal aerobic power were determined from a graded exercise test performed before the events and compared with power output during each event.
RESULTS:
EVA exposed that power output during the time trial was highly variable (EVA(SD) = 2.81 (0.33)) but more evenly distributed than the circuit/criterium (4.23 (0.31)) and road race events (4.81 (0.96)).
CONCLUSION:
EVA may be useful for illustrating variations in the amplitude and time distribution of power output during cycling events. The specific race format influenced not only the overall time spent in various power bands, but also the acute time spent at these exercise intensities.
Abbiss CR, Straker L, Quod MJ, Martin DT, Laursen PB.
Abstract
OBJECTIVE:
In this study, the amplitude and time distribution of power output in a variety of competitive cycling events through the use of a new mathematical analysis was examined: exposure variation analysis (EVA).
DESIGN:
Descriptive field study.
SETTING:
Various professional road cycling events, including; a 5-day-eight-stage tour race, a 1-day World Cup event and the Australian National Individual Time Trial Championships.
PARTICIPANTS:
9 elite female cyclists (mean (SD), mass = 57.8 (3.4) kg, height = 167.3 (2.8) cm, Vo(2)peak = 63.2 (5.2) ml kg(-1) min(-1)).
INTERVENTIONS:
None.
MAIN OUTCOME MEASUREMENTS:
The variation in power output and the quantification of the total time and acute time spent at various exercise intensities during competitive professional cycling were examined. Predefined levels of exercise intensity that elicited first ventilation threshold, second ventilation threshold and maximal aerobic power were determined from a graded exercise test performed before the events and compared with power output during each event.
RESULTS:
EVA exposed that power output during the time trial was highly variable (EVA(SD) = 2.81 (0.33)) but more evenly distributed than the circuit/criterium (4.23 (0.31)) and road race events (4.81 (0.96)).
CONCLUSION:
EVA may be useful for illustrating variations in the amplitude and time distribution of power output during cycling events. The specific race format influenced not only the overall time spent in various power bands, but also the acute time spent at these exercise intensities.
Comparison of Power Outputs During Time Trialing
and Power Outputs Eliciting Metabolic Variables
in Cycle Ergometry
David Michael Morris and Rebecca Susan Shafer
The authors sought to compare power output at blood lactate threshold, maximal lactate steady state, and pH
threshold with the average power output during a simulated 20-km time trial assessed during cycle ergometry.
Participants (N = 13) were trained male and female cyclists and triathletes, all permanent residents at
moderate altitude (1,525–2,225 m). Testing was performed at 1,525 or 1,860 m altitude. Power outputs were
determined during a simulated 20-km time trial (PTT), at blood pH threshold (PpHT), at maximal lactate
steady state (PMLSS), and at blood lactate threshold determined by 2 methods: the highest power output that
did not result in consecutive and continued increases in blood lactate concentrations from exercising baseline
(PLT) and the highest power output that did not result in consecutive and continued increases of ≥1 mmol/L
in blood lactate concentrations from exercising baseline (PLT1). PLT, PLT1, and PMLSS were all significantly
lower than PpHT (p < .05) and PTT (p < .05). No significant difference was observed between PpHT and PTT
(p > .05). Significant correlations were observed between each of the metabolic variables, PLT, PLT1, PMLSS,
and PpHT, compared with PTT (p < .05). The authors conclude that, of the 4 metabolic variables, only PpHT
offered an accurate reflection of PTT.
and Power Outputs Eliciting Metabolic Variables
in Cycle Ergometry
David Michael Morris and Rebecca Susan Shafer
The authors sought to compare power output at blood lactate threshold, maximal lactate steady state, and pH
threshold with the average power output during a simulated 20-km time trial assessed during cycle ergometry.
Participants (N = 13) were trained male and female cyclists and triathletes, all permanent residents at
moderate altitude (1,525–2,225 m). Testing was performed at 1,525 or 1,860 m altitude. Power outputs were
determined during a simulated 20-km time trial (PTT), at blood pH threshold (PpHT), at maximal lactate
steady state (PMLSS), and at blood lactate threshold determined by 2 methods: the highest power output that
did not result in consecutive and continued increases in blood lactate concentrations from exercising baseline
(PLT) and the highest power output that did not result in consecutive and continued increases of ≥1 mmol/L
in blood lactate concentrations from exercising baseline (PLT1). PLT, PLT1, and PMLSS were all significantly
lower than PpHT (p < .05) and PTT (p < .05). No significant difference was observed between PpHT and PTT
(p > .05). Significant correlations were observed between each of the metabolic variables, PLT, PLT1, PMLSS,
and PpHT, compared with PTT (p < .05). The authors conclude that, of the 4 metabolic variables, only PpHT
offered an accurate reflection of PTT.
The Power Profile Predicts Road Cycling MMP
M. J. Quod, D. T. Martin, J. C. Martin, P. B. Laursen
Abstract
Laboratory tests of fitness variables have previously been shown to be valid predictors of cycling time-trial performance. However, due to the influence of drafting, tactics and the variability of power output in mass-start road races, comparisons between laboratory tests and competition performance are limited. The purpose of this study was to compare the power produced in the laboratory Power Profile (PP) test and Maximum Mean Power (MMP) analysis of competition data. Ten male cyclists (mean±SD: 20.8±1.5 y, 67.3±5.5 kg, V˙O2max 72.7±5.1 mL·kg−1·min−1) completed a PP test within 14 days of competing in a series of road races. No differences were found between PP results and MMP analysis of competition data for durations of 60-600 s, total work or estimates of critical power and the fixed amount of work that can be completed above critical power (W'). Self-selected cadence was 15±7 rpm higher in the lab. These results indicate that the PP test is an ecologically valid assessment of power producing capacity over cycling specific durations. In combination with MMP analysis, this may be a useful tool for quantifying elements of cycling specific performance in competitive cyclists.
M. J. Quod, D. T. Martin, J. C. Martin, P. B. Laursen
Abstract
Laboratory tests of fitness variables have previously been shown to be valid predictors of cycling time-trial performance. However, due to the influence of drafting, tactics and the variability of power output in mass-start road races, comparisons between laboratory tests and competition performance are limited. The purpose of this study was to compare the power produced in the laboratory Power Profile (PP) test and Maximum Mean Power (MMP) analysis of competition data. Ten male cyclists (mean±SD: 20.8±1.5 y, 67.3±5.5 kg, V˙O2max 72.7±5.1 mL·kg−1·min−1) completed a PP test within 14 days of competing in a series of road races. No differences were found between PP results and MMP analysis of competition data for durations of 60-600 s, total work or estimates of critical power and the fixed amount of work that can be completed above critical power (W'). Self-selected cadence was 15±7 rpm higher in the lab. These results indicate that the PP test is an ecologically valid assessment of power producing capacity over cycling specific durations. In combination with MMP analysis, this may be a useful tool for quantifying elements of cycling specific performance in competitive cyclists.
Physiology, Power Output and Racing Strategy of a Race across America (RAAM)
Finisher
Yorck Olaf Schumacher, Christoph Ahlgrim, Stephan Prettin, Torben Pottgiesser
Abstract
The Race across America (RAAM), a 4800km non-stop cycle race, is one of the most
demanding endurance sports events. We display the racing strategy, power output, heart rate,
hormonal levels and inflammatory markers of an athlete before and during the race, which he
completed in 10 days, 23 hours.
The athlete showed physiological characteristics of a well trained (non-elite) cyclist
(VO2peak 63ml/min/kg, heart volume 11.3 ml/kg). The race was mainly performed at low
intensities (mean power output 141W (±76W SD), heart rate 117 bpm (±14bpm SD)). During
the race, testosterone levels dropped initially by 30-40% and returned to baseline towards the
end. Cortisol remained elevated throughout (+75-90% compared to baseline). Markers of
inflammation (CRP), dehydration and protein catabolism (Albumin) were not affected. The
athlete used a race strategy with regular sleeping breaks (total rest: 91h, 45h of sleep).
Contrasting conventional racing strategies for the RAAM, which aim at minimizing sleep and
maximising ride time, our case demonstrates that by emphasizing regular recovery and sleep,
such alternative strategy might lead an equally successful race result.
Finisher
Yorck Olaf Schumacher, Christoph Ahlgrim, Stephan Prettin, Torben Pottgiesser
Abstract
The Race across America (RAAM), a 4800km non-stop cycle race, is one of the most
demanding endurance sports events. We display the racing strategy, power output, heart rate,
hormonal levels and inflammatory markers of an athlete before and during the race, which he
completed in 10 days, 23 hours.
The athlete showed physiological characteristics of a well trained (non-elite) cyclist
(VO2peak 63ml/min/kg, heart volume 11.3 ml/kg). The race was mainly performed at low
intensities (mean power output 141W (±76W SD), heart rate 117 bpm (±14bpm SD)). During
the race, testosterone levels dropped initially by 30-40% and returned to baseline towards the
end. Cortisol remained elevated throughout (+75-90% compared to baseline). Markers of
inflammation (CRP), dehydration and protein catabolism (Albumin) were not affected. The
athlete used a race strategy with regular sleeping breaks (total rest: 91h, 45h of sleep).
Contrasting conventional racing strategies for the RAAM, which aim at minimizing sleep and
maximising ride time, our case demonstrates that by emphasizing regular recovery and sleep,
such alternative strategy might lead an equally successful race result.
http://www.jssm.org/vol6/n4/14/v6n4-14pdf.pdf
Age-associated changes in VO2 and power output - A cross-sectional study of endurance trained New Zealand cyclists
Brown, SJ ; Ryan, HJ ; Brown, JA
Abstract:
Age-associated changes in power and maximal oxygen consumption (VO2max) were studied in a cross section of endurance trained cyclists. Subjects (n = 56) performed incremental cycling exercise, during which capillary blood lactate [La-] was measured. Power output increased by 30 Watts during each 5 minutes stage, with initial power output based on individual ability. When [La-] was >4.5 mmol·L-1, subjects were given a 10 min recovery at a power output approximately 50% below estimated power at [La-]4mmol. Subjects then performed an incremental test (1 minute stages) to VO2max. Decline in VO2max was 0.65 ml·kg-1·min-1·year-1 (r = -0.72, p < 0.01) for males, and 0.39 ml·kg-1·min-1·year-1 (r = -0.54, p < 0.05) for females. Power at VO2max decreased by 0.048 W kg-1·year-1 (r = -0.72, p < 0.01) in males. Power at [La-]4mmol decreased by 0.044 W kg-1·year-1 (r = -0.76, p < 0.01) in males, and by 0.019 W kg-1·year-1 (r = -0.53, p < 0.05) in females. Heart rate at VO2max (HRmax) showed a weaker correlation with age in males (r = -0.36, p < 0.05). The age-associated changes in maximum aerobic power and sub-maximal power were gender- specific, thus suggesting different age-related effects on the systems which support exercise in males and females.
Age-associated changes in VO2 and power output - A cross-sectional study of endurance trained New Zealand cyclists
Brown, SJ ; Ryan, HJ ; Brown, JA
Abstract:
Age-associated changes in power and maximal oxygen consumption (VO2max) were studied in a cross section of endurance trained cyclists. Subjects (n = 56) performed incremental cycling exercise, during which capillary blood lactate [La-] was measured. Power output increased by 30 Watts during each 5 minutes stage, with initial power output based on individual ability. When [La-] was >4.5 mmol·L-1, subjects were given a 10 min recovery at a power output approximately 50% below estimated power at [La-]4mmol. Subjects then performed an incremental test (1 minute stages) to VO2max. Decline in VO2max was 0.65 ml·kg-1·min-1·year-1 (r = -0.72, p < 0.01) for males, and 0.39 ml·kg-1·min-1·year-1 (r = -0.54, p < 0.05) for females. Power at VO2max decreased by 0.048 W kg-1·year-1 (r = -0.72, p < 0.01) in males. Power at [La-]4mmol decreased by 0.044 W kg-1·year-1 (r = -0.76, p < 0.01) in males, and by 0.019 W kg-1·year-1 (r = -0.53, p < 0.05) in females. Heart rate at VO2max (HRmax) showed a weaker correlation with age in males (r = -0.36, p < 0.05). The age-associated changes in maximum aerobic power and sub-maximal power were gender- specific, thus suggesting different age-related effects on the systems which support exercise in males and females.
veganrob said:
Let him show his true colours with his trolling. People thinking of purchasing a product from him will know who they are getting into bed with.
If you think he is trolling then report his post.
The critical power and related whole-body bioenergetic models
Hugh Morton
Abstract This paper takes a performance-based approach
to review the broad expanse of literature relating
to whole-body models of human bioenergetics. It begins
with an examination of the critical power model and its
assumptions. Although remarkably robust, this model
has a number of shortcomings. Attention to these has
led to the development of more realistic and more detailed
derivatives of the critical power model. The
mathematical solutions to and associated behaviour of
these models when subjected to imposed ‘‘exercise’’ can
be applied as a means of gaining a deeper understanding
of the bioenergetics of human exercise performance.
Hugh Morton
Abstract This paper takes a performance-based approach
to review the broad expanse of literature relating
to whole-body models of human bioenergetics. It begins
with an examination of the critical power model and its
assumptions. Although remarkably robust, this model
has a number of shortcomings. Attention to these has
led to the development of more realistic and more detailed
derivatives of the critical power model. The
mathematical solutions to and associated behaviour of
these models when subjected to imposed ‘‘exercise’’ can
be applied as a means of gaining a deeper understanding
of the bioenergetics of human exercise performance.
Reliability of Power in Physical
Performance Tests
Will G. Hopkins, Elske J. Schabort and John A. Hawley
The reliability of power in tests of physical performance affects the precision of
assessment of athletes, patients, clients and study participants. In this meta-analytic
review we identify the most reliable measures of power and the factors affecting
reliability. Our measures of reliability were the typical (standard) error of meas-
urement expressed as a coefficient of variation (CV) and the percent change in
the mean between trials. We meta-analysed these measures for power or work
from 101 studies of healthy adults. Measures and tests with the smallest CV in
exercise of a given duration include field tests of sprint running (~0.9%), peak
power in an incremental test on a treadmill or cycle ergometer (~0.9%), equivalent
mean power in a constant-power test lasting 1 minute to 3 hours on a treadmill
or cycle ergometer (0.9 to 2.0%), lactate-threshold power (~1.5%), and jump
height or distance (~2.0%). The CV for mean power on isokinetic ergometers
was relatively large (>4%). CV were larger for non athletes versus athletes (1.3 ×),
female versus male non athletes (1.4 ×), shorter (~1-second) and longer (~1-hour)
versus 1-minute tests (≤1.6 ×), and respiratory- versus ergometer-based measures
of power (1.4 to 1.6 ×). There was no clear-cut effect of time between trials. The
importance of a practice trial was evident in studies with >2 trials: the CV between
the first 2 trials was 1.3 times the CV between subsequent trials; performance
also improved by 1.2% between the first 2 trials but by only 0.2% between subsequent
trials. These findings should help exercise practitioners and researchers
select or design good measures and protocols for tests of physical performance.
Performance Tests
Will G. Hopkins, Elske J. Schabort and John A. Hawley
The reliability of power in tests of physical performance affects the precision of
assessment of athletes, patients, clients and study participants. In this meta-analytic
review we identify the most reliable measures of power and the factors affecting
reliability. Our measures of reliability were the typical (standard) error of meas-
urement expressed as a coefficient of variation (CV) and the percent change in
the mean between trials. We meta-analysed these measures for power or work
from 101 studies of healthy adults. Measures and tests with the smallest CV in
exercise of a given duration include field tests of sprint running (~0.9%), peak
power in an incremental test on a treadmill or cycle ergometer (~0.9%), equivalent
mean power in a constant-power test lasting 1 minute to 3 hours on a treadmill
or cycle ergometer (0.9 to 2.0%), lactate-threshold power (~1.5%), and jump
height or distance (~2.0%). The CV for mean power on isokinetic ergometers
was relatively large (>4%). CV were larger for non athletes versus athletes (1.3 ×),
female versus male non athletes (1.4 ×), shorter (~1-second) and longer (~1-hour)
versus 1-minute tests (≤1.6 ×), and respiratory- versus ergometer-based measures
of power (1.4 to 1.6 ×). There was no clear-cut effect of time between trials. The
importance of a practice trial was evident in studies with >2 trials: the CV between
the first 2 trials was 1.3 times the CV between subsequent trials; performance
also improved by 1.2% between the first 2 trials but by only 0.2% between subsequent
trials. These findings should help exercise practitioners and researchers
select or design good measures and protocols for tests of physical performance.
Peak power output, the lactate threshold, and time trial performance in cyclists.
Bentley DJ, McNaughton LR, Thompson D, Vleck VE, Batterham AM.
Abstract
PURPOSE:
To determine the relationship between maximum workload (W(peak)), the workload at the onset of blood lactate accumulation (W(OBLA)), the lactate threshold (W(LTlog)) and the D(max) lactate threshold, and the average power output obtained during a 90-min (W(90-min)) and a 20-min (W(20-min)) time trial (TT) in a group of well-trained cyclists.
METHODS:
Nine male cyclists (.VO(2max) 62.7 +/- 0.8 mL.kg(-1).min(-1)) who were competing regularly in triathlon or cycle TT were recruited for the study. Each cyclist performed four tests on an SRM isokinetic cycle ergometer over a 2-wk period. The tests comprised 1) a continuous incremental ramp test for determination of maximal oxygen uptake (.VO(2max) (L.min(-1) and mL.kg(-1).min(-1)); 2) a continuous incremental lactate test to measure W(peak), W(OBLA), W(LTlog), and the D(max) lactate threshold; and 3) a 20-min TT and 4) a 90-min TT, both to determine the average power output (in watts).
RESULTS:
The average power output during the 90-min TT (W(90-min)) was significantly (P < 0.01) correlated with W(peak) (r = 0.91), W(LTlog) (r = 0.91), and the D(max) lactate threshold (r = 0.77, P < 0.05). In contrast, W(20-min) was significantly (P < 0.05) related to .VO(2max) (L.min(-1)) (r = 0.69) and W(LTlog) (r = 0.67). The D(max) lactate threshold was not significantly correlated to W(20-min) (r = 0.45). Furthermore, W(OBLA) was not correlated to W(90-min) (r = 0.54) or W(20-min) (r = 0.23). In addition, .VO(2max) (mL.kg(-1).min(-1)) was not significantly related to W(90-min) (r = 0.11) or W(20-min) (r = 0.47).
CONCLUSION:
The results of this study demonstrate that in subelite cyclists the relationship between maximum power output and the power output at the lactate threshold, obtained during an incremental exercise test, may change depending on the length of the TT that is completed.
Bentley DJ, McNaughton LR, Thompson D, Vleck VE, Batterham AM.
Abstract
PURPOSE:
To determine the relationship between maximum workload (W(peak)), the workload at the onset of blood lactate accumulation (W(OBLA)), the lactate threshold (W(LTlog)) and the D(max) lactate threshold, and the average power output obtained during a 90-min (W(90-min)) and a 20-min (W(20-min)) time trial (TT) in a group of well-trained cyclists.
METHODS:
Nine male cyclists (.VO(2max) 62.7 +/- 0.8 mL.kg(-1).min(-1)) who were competing regularly in triathlon or cycle TT were recruited for the study. Each cyclist performed four tests on an SRM isokinetic cycle ergometer over a 2-wk period. The tests comprised 1) a continuous incremental ramp test for determination of maximal oxygen uptake (.VO(2max) (L.min(-1) and mL.kg(-1).min(-1)); 2) a continuous incremental lactate test to measure W(peak), W(OBLA), W(LTlog), and the D(max) lactate threshold; and 3) a 20-min TT and 4) a 90-min TT, both to determine the average power output (in watts).
RESULTS:
The average power output during the 90-min TT (W(90-min)) was significantly (P < 0.01) correlated with W(peak) (r = 0.91), W(LTlog) (r = 0.91), and the D(max) lactate threshold (r = 0.77, P < 0.05). In contrast, W(20-min) was significantly (P < 0.05) related to .VO(2max) (L.min(-1)) (r = 0.69) and W(LTlog) (r = 0.67). The D(max) lactate threshold was not significantly correlated to W(20-min) (r = 0.45). Furthermore, W(OBLA) was not correlated to W(90-min) (r = 0.54) or W(20-min) (r = 0.23). In addition, .VO(2max) (mL.kg(-1).min(-1)) was not significantly related to W(90-min) (r = 0.11) or W(20-min) (r = 0.47).
CONCLUSION:
The results of this study demonstrate that in subelite cyclists the relationship between maximum power output and the power output at the lactate threshold, obtained during an incremental exercise test, may change depending on the length of the TT that is completed.
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