Endurance Analytics

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Coach-rider communication and the need for power

Last year an article in the cycling press asked the question "are power meters killing the art of coaching?" It's conclusion, after some detectable anti-power sentiment, was that coach-rider communication is key and therefore the art of coaching must trump the use of power data, positioned we suppose as the scientific opposition.

Of course the infamous Dr Ferrari to this day includes the caption "coaching is art" on his website 53x12.com and he has a point. Science gives us models of the world, but the best users of those models know how to combine and interpret quite a few, having regard for their limitations and applicability to unique circumstances such as events and riders. This process, intuition, triangulation, call it what you will, is well described as an art form and fits with the role of a coach.

But to suggest that power meters or power data might be somehow diminishing, rather than enhancing or enabling this art, is frankly the wrong question. What makes a coach-rider relationship flourish, as the article points out, is communication. Communication requires language, and we believe that the most powerful language the sport now has is power itself.

Now why is power the key to coach-rider communication?


The language of power based training allows us to be succinct and expressive about the makeup of training sessions, with great accuracy. Imagine, for example, being an engineer before anybody had developed a vocabulary to describe different building designs. You'd be using dozens of words to describe concepts that now need one or two. Training sessions are the same - once a rider understands what is a "2x20 @ 105% FTP" communication is eased and enhanced.


A doctor would have a hard time evaluating a critically ill patient without access to a modern suite of diagnostic capabilities such as blood and ECG data. These tools reveal more about the patient's state than words will ever do and anyone who has ever laid in a hospital bed will recognise that at doctors rounds far more time is invested in checking these diagnostics than asking the patient how he is. In cycling the diagnostic capability of power - pre or post training and pre or post race - simply trumps a lot of verbal communication in it's richness and value. The really important communication then becomes the eventual diagnosis, prognosis or prescription facilitated by the data.

How hard & how fast

Your assessment of RPE is not my assessment, just as your heart rate is not my heart rate. Some people are simply terrible at evaluating how close they are/were to blowing, especially relatively new bike riders. Cycling was crying out for an objective measure of intensity before power came along but coaches and riders must communicate on three major topics: duration, intensity and frequency of training. Only power allows riders to be benchmarked on ability. Power = Speed, with just a few parameters in the middle. Rider benchmarking and goal setting, fundamental parts of the coaching process, are practically impossible without power data. You cannot communicate what you cannot define.

How sick or how injured

Sickness often manifests itself as the inability to achieve a certain intensity while injuries tend to be evident at certain power outputs, torques or cadences. Power data is therefore incredibly expressive when the unfortunate time comes to communicate either of these problems.

Form and history

A rider without a history of power data has no context in which a coach can place him. What is his baseline, untrained level of fitness? How far is he above that, and how much headroom does he have? What types of training has he best responded to? Some coaches would admit that coaching riders without power data feels almost dishonest. Dishonest because it imposes some very real limits to the amount of value a coach can add.

Distance learning

We live in an internet age where a significant number of riders have never met their coach, nor will they ever really need to. Cycling is not football or any other team sport characterised by group, face-to-face training sessions that may or may not end in the pub. Power data is not a web protocol but it might as well be. It opens all kinds of possibilities in terms of two way, coach-rider-coach communication, which nowadays increasingly has to be virtual.

Power is changing the game. Don't be one of the naysayers who claim it's damaging racing or coaching or it might just damage your job.

The Measure of a Cyclist

August is wedding season here in Europe and we were recently involved with having a suit fitted and tailored. The process, done properly, involves an awful lot of measurements that together could do a pretty good job of describing the form and physique of the customer. No one measurement defines the perfect suit and this got us thinking about how, in the modern world of power meters and sport science, no one metric is sufficient to define the ability of a bike rider.

So what is the measure of a cyclist? There are romantics and journalists who might turn to words such as "class", "panache", or "tenacity" but let's suspend the BS for a few minutes and look at the set of metrics that we have come to understand are required to comprehensively define the ability of a cyclist. Even for natural number fans there is much more to consider than one simple "watts per kilo" - equivalent to an off-the-peg but poorly defined "size 50 suit"...

Critical Power (Watts)

Critical Power (CP) is what’s left when we strip away the power a rider can produce on a short term basis, “in the red zone”. That means it’s equivalent to power that can be produced aerobically, through “aerobic energy pathways”, and for a relatively long time. The gold standard model for identifying a rider’s CP, from just 2 or 3 short field tests, is the Monod Critical Power Model. Of all rider metrics CP is the most important for the vast majority of cycling events.

Anaerobic Work Capacity (Joules)

Anaerobic Work Capacity (AWC) is the size of a rider’s “red zone”, or the amount of energy they can produce over and above CP, before they need to slow down and recharge. Because AWC is an amount of energy it’s measured in joules. Since a joule is “1 watt for 1 second” AWC can be spent very quickly, at a power output way above CP, or more slowly, for example riding just a bit above CP for several minutes. The Monod Critical Power Model is also the tool of choice to identify a rider’s AWC. Some sport scientists refer to AWC as W’ - “W prime”.

AWC Recharge Velocity (Tau)

When a rider’s power output dips below Critical Power he isn’t spending his anaerobic work capacity, so if it’s depleted then there is an opportunity for the body to recharge it. Consistently riding above and then below CP isn’t particularly efficient, but the demands of a race or considerations of a pacing strategy may win the argument. Speed of recharge is key, and recent research (primarily by Dr Phil Skiba) has provided a framework in which to model AWC recharge. The lower a rider’s power output, relative to critical power, the faster AWC will recharge. Another determinant of that speed is a mathematical function known as the “Tau function” which can either be based on a general population of cyclists, or calibrated to the individual using power based field tests.

Velocity of Oxygen Dynamics (Seconds)

Imagine a rider accelerates from a standing start and upto Critical Power - the level at which all power is still assumed to be coming from the aerobic pathway. He’s never exceeded CP, so did he use any AWC? The answer is yes, because it takes a bit of time for his aerobic system to fire up to full capacity, and in the meantime the energy that’s not being produced aerobically has to come from somewhere. The faster a rider’s aerobic system can accelerate the better, because AWC is preserved and the cost of recharging it is avoided. This can be important in events with highly variable power demands, or for events that involve hard efforts straight from the gun, such as the pursuit. Acceleration of the aerobic system is typically modelled as an exponential function where velocity is explained by it’s half life in seconds.

Neuromuscular Power (Watts)

Sprinting requires explosive efforts that rely on an energy system distinct from the aerobic and anaerobic pathways, as well as a rider’s ability to activate and deploy muscle. Aside from very specific track applications we’ve yet to be convinced of the need for a formal model of neuromuscular power. The metric here is simply “best average power over 5 seconds”. Perhaps more than others this metric is sensitive to the quality of a rider’s power meter (how frequently does it capture data, and how does it measure angular velocity of the crank?).

Fatigue Index (%/Tx2)

The Critical Power model suggests that if we strip the power a rider can produce from anaerobic sources then we arrive at one number – critical power – that he ought to be able to maintain aerobically, and indefinitely. Of course this isn’t realistic – ride beyond an hour or two and everyone will fatigue, even though their aerobic engine isn’t actually getting smaller. So what’s going on? Lots of complex processes and factors contribute to fatigue but rather than try to model all of these factors we like the concept of the “Fatigue Curve” – a model which simply fits a curve to the tendency for a rider’s power output to decay with time, though at an ever reducing rate. The underlying mathematical function gives us a very useful summary number – by what percentage does a riders power output reduce when ride time doubles – and we call this %/Tx2.

Body Mass (Kilos)

The more a rider weighs, the more power he needs to climb at a given speed, accelerate at a given speed, or even to move across a flat road at a given speed. That last bit may be surprising, but it’s a fact that the amount of power needed to roll across any road is a function of tyre rolling resistance and the amount of weight pressing down on those tyres. There is nothing complicated about measuring rider weight, but it is still an essential metric.

Aerodynamic Drag (CdA)

At race speeds some 80 – 90% of a rider’s power is being used to overcome aerodynamic drag, so some measure of how aero or not the rider is must be important. A rider’s “coefficient of drag” multiplied by “frontal area” (CdA) is the standard metric. The whole of a rider’s morphology – including height and weight – will have an impact, as well as flexibility and core strength. We can do a good job of estimating rider’s CdA from height and weight alone. With a suitable field test, involving power data, we can do an even better job. No description of a rider can be complete without some estimate of CdA.

So there you have it – 8 measurements that together describe the ability of a cyclist. Not all are easy to measure, and not all are important to every type of event, but the good news is that the metrics important to the most popular events are also the most measurable using nothing more complicated than a power meter. Now what can we do with these metrics? First, this kind of total description of a rider can be invaluable to coaches looking to deliver improvements having excellent specificity for target events. But by extension these metrics have great applicability in CPL performance modelling.

One way to define performance modelling is simulating the performance of a given rider, on a given course, under given conditions, and the better we can define the given rider then the further we can go. By defining a rider in terms of the above metrics performance modelling can deliver the best possible insights in terms of performance prediction, performance benchmarking, goal setting, optimal pacing, equipment evaluation, and more.

In conclusion we would encourage all riders and coaches to take a multi dimensional view of testing and defining ability, using at least the metrics relevant to current goals. And of course, with benefits like the above, to embrace the considerable potential of performance modelling.

Where are you on the Power Learning Curve?

We’re celebrating an anniversary this month – 10 years since our first SRM training system arrived from the factory. As if you didn’t know it already this particular sample of German engineering has given us years of gold standard accuracy and unwavering reliability, much like most SRMs we’re aware of. We've learned an awful lot about power since the turn of the century, and the purpose of this post is to share our thoughts on the learning curve that comes with integrating power into your cycling. The accompanying graphic is an extract from a presentation we give on the subject - drop us a line if you'd like to host one.

Basics - A better heart rate monitor

The first justification for training with power is often “a more real time measure of intensity”. Power output doesn’t lag heart rate response, so it’s far superior for the monitoring of effort (the basics of pacing) and the execution of intervals. It’s also a measure of output that is not subject to external factors, so training by reference to power zones is frequently more accurate. Given such an objective measure of output it becomes clear that power is a great tool for comparing rider’s abilities and “power profiling” is the term for that. Together these are the immediate benefits of using power.

Paradigms - Descriptive analytics

The richness of power data has facilitated a number of new analytical techniques or metrics which expand on the idea of profiling rider’s ability and help to diagnose where improvements can be made. The Critical Power curve is an essential tool for expressing and explaining how a rider’s ability to deliver power decays as duration of effort increases. Simply looking at where a rider pushed his limits on this curve is a useful way of diagnosing racing performances or failures.

Several tools were developed in quick succession by Dr Andrew Coggan of the Peaks Coaching Group. Quadrant Analysis represents a way to uncover the neuromuscular demands of different types of event, pairing power and cadence data, and to improve training specificity. Training Stress Score (TSS) is a power enabled metric of training load, adjusted for intensity. Training Stress Balance (TSB) compares short term and long term TSS as a method to predict a rider’s form assuming Form = Fitness + Freshness = Chronic Training Load (long term TSS) minus Acute Training Load (short term TSS).

Finally in the area of descriptive analytics power data, used carefully and appropriately, can allow us to estimate and iteratively improve a rider’s aerodynamic drag. These are all retrospective techniques relying on the study of past ride data.

Performance modelling – Predictive analytics

The greatest opportunities in the use of power data are now in the area of forward looking, predictive analytics. This is the area CPL has been working to develop and the principle here is - “How can we use holistic performance modelling, enabled by power data, to deliver intelligence that will make riders faster, or just more successful?”

The first benefit of Performance Modelling is the ability to set real goals. When you can convert power output into a projected time on course, or a target time on course into a required power output then, aside from the motivational benefits, there are real possibilities to intelligently choose, prepare for, and target events. A simple extension of this is scenario analysis – how much faster or slower are certain conditions or rider attributes and can these be targeted?

Performance modelling, with good data, enables Equipment Optimisation. Read “free speed” (at least in terms of effort). Another route to free speed is Optimal Pacing Strategy. The fastest way to the finish line is rarely a constant power output - but it takes some serious analytics and computing power to identify the optimal strategy for a given rider. We do that.

Some cutting edge applications of performance modelling are energy budgeting and management of Anaerobic Work Capacity – the latter inspired by Dr Phil Skiba at Physfarm Training Systems.

Wherever you are on the power learning curve, or wherever your clients are, there is always more to learn. Investing in a power meter is really only the beginning. Riding a bike – fast – is no longer just a physical challenge and the more you learn, the more achievable speed is out there.

"Air pressure is everything"

The hour record is a hot topic at the moment and we have seen great interest in predicting how far both Alex Dowsett could go and how far Bradley Wiggins will go this Sunday June 7th. Based on comments in the media it is clear that Wiggins was hoping for unusually low air pressure this first week in June but just how much of a difference can this make?

Accompanying this article is a chart from the UK National Physics Laboratory (NPL) in Teddington, just across London from the Olympic Velodrome, which shows a time series of local air pressure during the last year. You can see that 1013mb, the typically accepted average global air pressure at sea level, is around about the average observation while 990mb and 1030mb could be considered towards the low and high ends of normal. By applying these numbers in our popular Power Calculator we see that, with some sensible estimates and at hour record pace, the difference between 990 and 1030 is very significant – at least 600 metres – and for less gifted riders might represent the difference between smashing the record and a near miss.

We can’t overemphasise the importance of air pressure when the goal is riding as fast as possible. It’s the very reason riders go to altitude – either for the physiological effects or, in the case of record attempts, to gain what could almost be considered an unfair advantage over sea level times. Our Effects of Altitude model demonstrates the extent of speed &/or power savings that can be had with increasing altitude, versus typical physiological costs. And if Wiggins does as predicted, setting an almost unacheivable mark for the hour, then just maybe the only way to beat it will be some future plan at altitude.

Turning back to the air pressure in London we have long used historical data from the NPL to consider the relative benefits of riding a time trial event based on forecast weather. One of the inputs to our Time Trial Sector Model is air pressure and we can show you just where a forecast value stands in the normal distribution of UK pressures. We display “faster days in the year”, “slower days in the year”, and relative speed and power advantages of the range of pressure percentiles.

At the time of writing the forecast for Wiggins’ ride is not looking favorable. Heat and possibly humidity can be determined by climate control at the velodrome, set at the preference of Wiggins’ team, but air pressure is forecast at a very high 1033mb. Just to recap – if that forecast comes to pass then Wiggins has been unlucky and could go 600m slower than in an atmospheric pressure at the luckier end of the scale. One final thought – track and field records in athletics have long been rectified for wind assistance...is it time cycling did the same for air pressure?

The New Language of Cycling

This month like never before the cycling press is awash with power meter stories. We’ve seen price cuts from Quarq, Pioneer and Power2Max. New devices from Powertap, Rotor, and Garmin – plus several other projects somewhere between prototype and mainstream. It would be fair to say that the power meter market is progressing at a speed few can keep a track of. So where is all of this precision hardware heading? Well, we’ve been saying for years that power meters are destined for ubiquity, like heart rate monitors and cycling computers before them. In fact they are significantly more useful, so ought to achieve even greater uptake. Indeed the only thing standing between where we are now, and a power meter on every serious cyclist’s bike, is the realisation that power is absolutely key to cycling.

But why is power so important? Well it’s what we like to call “the unifying variable” of cycling performance. It’s the one thing that completely explains everything a rider has got (in terms of human output) at the same time as everything he needs (in physical or engineering terms) to achieve a given speed on the road. Speed of course is the essential element of racing, so power is becoming the language of racing. Now take a look at the diagram accompanying this post – we’ve been opening power seminars with this for the last couple of years.

Power Supply

Power supply is really the sum product of all physiological energy systems (aerobic, anaerobic, etc) factored by a rider’s state of motivation and fatigue. All of cycling physiology can be boiled down to “how much power can I/he/she produce” while how it’s produced almost doesn’t matter. Almost we say, because the details and complexities have a role in developing training strategies that improve output, and in the finer points of performance modelling.
Notice how we said power supply is more than just physiology. Yes, power is the product of the human body mixing fuel with oxygen, then converting that into mechanical work, but it’s more than that. There is no better metric of fatigue or psychological factors too. Power is, as sport scientists would say, an inderdisplinary factor and it’s corollaries Watts/Kilo and Watts/CdA are continually demonstrated as the greatest explanatory factors in cycling performance.

Power Demand

Think of power demand as the combination of 1) the demands of the event (that set of prerequisites so famously analysed by Team Sky) including course, weather, required speed; 2) the state of the rider, size, weight, etc; and 3) equipment choices. Change any one of these elements and power demands change. The key point is that, once again, they can all be explained in terms of power.
Consider these “performance questions”:

• What ability does rider X need to complete course Y in time Z?
• How will that change if he’s fitter, lighter, or more aero?
• Which equipment choices will maximise his speed given predicted conditions?
All of these question and many more can be answered with a little research, power data, and the appropriate modelling techniques.

It will take a while yet before the current wave of power meters breaks across the cycling world. But when it does we expect to see a great realisation - that power is much more than just a number reported by the most fashionable cycling accessory. To think of it like that is to be stuck in the dark ages of heart rate monitoring. No, power IS modern cycling – the language of ability, the metric of goals and objectives, and the benchmark of equipment. And as physiologist Allen Lim put it recently “power has changed the language of professional cycling”. Parlez vous power?

Introducing the CPL Blog

Welcome to our blog. Since CPL began we’ve been working hard to stay abreast of developments in the fields of cycling and triathlon science. But things move fast at the cutting edge - so we hope that the blogging format will help us keep you up-to-date.

In the coming months we’re planning a series of posts to help followers unleash the phenomenal power of Performance Modelling.  Using computer modelling to simulate rider performance on any course allows us to uncover countless truths. We’ll look at competitor benchmarking, goal setting, scenario analysis, equipment and pacing optimisation, among other applications. Check back to catch it all.

Right now we’re in the middle of July and the Tour de France is entering the mountains. The cycling world is on the verge of it’s annual crescendo. We have a bunch of reflections, numbers and more to share, benefitting always from the analytical tools we’re continuing to develop. Perhaps you have a suggestion for a post you’d like to see – just get in touch and let us know.

Until the next time.