Endurance Analytics

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Think power is complicating cycling? Think again.

People make a lot of excuses when they dont want to pay for something. It's a waste of money. I dont need it. What would I want with one of those? We've heard all of these procrastinations from cyclists and triathletes on the verge of buying a power meter. Another objection that we hear a lot is "it's too complicated". The purpose of this article is to highlight why power is in fact simplifying, not complicating, cycling.

"The amateur wants the gimmick but the expert sees the beauty in simplicity"

There are a lot of gimmicks in cycling. Go-faster wheels, frames, and components, for example. Some of them are worth your money, but some of them aren't. And sometimes you can only take that decision when you know what magnitude of improvements you are looking at. At CPL we use performance modelling to evaluate potential gimmicks in the simplest possible language. We use science to reduce cycling to a set of energy demands (climbing, aerodynamic resistance, etc), a set of scenarios relevant to you, and then the simplicity of the answer - speed effects and time savings.

Performance questions

At CPL our guiding principles and objectives correlate well with the idea of "performance questions", a term we first heard from the E.I.S.

  1. What data do we have or can we get?
  2. What questions do we have?
  3. What really matters? And the answer is almost always "speed!"

There is one phrase of which we all should be aware when discussing the merits of equipment, strategies, or riding scenarios and that phrase is "it depends". Too often "it depends" means "I dont know", even when it's coming from a supposed expert. One of the reasons we created CPL was a chronic tiredness with "it depends" and a need to properly answer performance questions.

Seek clarity, not fuzziness

A lot has been written about the finer aspects of the coaching process, in cycling, in triathlon, and wider. But for sports which are supposedly so advanced some really important parts of the process are still in the dark ages. Only power gives riders a concrete evaluation of current ability and concrete assessments of progress. But accurate goal setting requires power based predictive performance modelling of the type that we've developed. Fuzzy goals lead to fuzzy preparation and fuzzy performances. Fuzziness is hard to understand, whereas things that are clearly defined promote simplicity.

Mind your ifs and buts

On the quest to become, or train, a better bike rider there are a lot of if's and but's. "If we drop 5 kilos, what's the benefit?". "If we find 20 watts, what's the effect?" Too many if's and buts make life complicated. At CPL we prefer simple answers which is why we apply performance modelling for scenario analysis. We coin the term "Mass Delta" to provide a simple metric of how much faster a given rider will go, on a given course, with a reduction in weight. "Power Delta" is the equivalent, when the "if" is increased power. These sorts of capabilities, rooted in power, undoubtedly simplify cycling.

The new language of cycling

Power has not just changed the language of cycling, it has created it. Coaches and riders can now communicate with an accuracy and expressiveness that was never before possible. We now have names for training patterns, like "2x20" and "FTP", that convey the same details to us as "suspension" or "cantilever" might convey between engineers. Sensations of form or lack of form can be communicated in terms of ability to hold a certain power for a certain duration. And injuries can be described in terms of the power output or torque that causes the problem. Many of us have have come to take this language for granted, but how often do we stop to reflect on just how much power has in fact simplified our lives?

Put a number on it

The things that win races - times and speeds - are measured in numbers, as are finishing positions. If these criticial aspects of success can be defined with numbers then why not the things that make them possible? Form, fitness, weight, endurance, explosiveness, etc. Plan your race or your season, dont't speculate. Power and all of the numbers that follow are there to simplify life, not complicate it.

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.