What's Cool In Road Cycling

Finding Form: Power-Based Performance Model

I hope everyone is enjoying the Tour de France and PEZ’s unique coverage as much as I am. With the Alps and Pyrenees behind us, it is quite evident which riders had form, lost their form, or found their form. Let’s take a closer look at what the commonly used cycling term “form” exactly is.

Daniel Coyle describes “form” in Lance Armstrong’s War as “one of the more mysterious elements of bike racing, possessing an otherness that is revealed in its preposition… referring to the elusive moment when all systems are working at optimum efficiency”.

The etymology of “form” goes back to eighteenth century horse racing where sheets would be passed out to the betters detailing the past performances of each horse. Doesn’t that sound familiar to the media speculation from the race results of the Dauphine and Tour de Suisse? I think so.

For the athletes, coaches and directeur sportifs “in the know” Tour de France form is a known quantity and not mysterious at all. In fact, it is a closely guarded secret from the competition and consequently the media. Form is the result of a strategically selected race schedule, and a carefully managed training plan leading into the Tour*.

What is “Form”?
In cycling the word form describes a combination of physiological & psychological qualities that enable peak athletic performance(s). Form is power output. Form is “going good” when you want to go good. Form is having a ton of matches to burn in a race. Form is feeling like you can rip the cranks off the bike. For those athletes racing** with their powermeter, form may be measured with an all time high peak power output. Or simply, it may be setting a PR up your favorite climb.

It is important to recognize that cyclists will not always be on form or may even ever have it. Athletes must first “go big” with their training before they have the chance to decrease their volume and elicit form. Scientifically, form is just the right balance between exercise induced physiological adaptations and the time required to optimize those changes. An even geekier definition is a positive impulse-response relationship: a value calculated by the amount of training you’ve done and the recovery you’ve taken.

A Predictive Performance Model
You may be familiar with the heart-rate based (TRIMPS) model developed by Dr. Eric Bannister in the mid 1970’s and popularized by triathletes in the nineties. Bannister’s model uses raw heart rate data to understand how training affects athletic performance. In essence, how much to train and when to rest in order to achieve the ultimate form.

In the 1990’s French physiologists, Thierry Busso and his colleagues took Bannister’s TRIMPS model a step further. They developed an impulse-response algorithm to show the relationship between the positive gains from training adaptations and the negative gains from fatigue. Busso’s lab crudely calculated the training impulse by multiplying the number of intervals performed by their intensity. These training units were entered into the algorithm to calculate the response. To validate the model, laboratory based performance tests were shown to match the response predicted by the model.

Since Busso’s work, the raw data accumulated from downloading daily powermeter files has become the ultimate measure of an athlete’s daily training impulse. Dr. Andy Coggan’s metric, training stress score (TSS), enables us capitalize on Bannister’s and Busso’s original work with a power-based performance model. When it comes to training with power, this separates the men from the boys. As Lance likes to describe his F-One equipment, this is the “Shit That Will Kill Them”***.

Lance, bro, when you are done with number seven, send me your files leading up to the Tour and we’ll model out your performance. Have your people contact my people.

Proof of Concept
In the meantime, here is how my training looks in the model. Over the past 8 months I successfully used the model to predict and plan my peak performances for my top goal events in June. Suffice it to say I was on form and this model helped me prepare, plan, and taper into my events. During this time I got the results I wanted and generated all time high peak power outputs during my events. And, it felt like I could rip the cranks off the bike.

In the figure above, the positive gain from training is defined as Chronic Training Load or CTL. Acute Training Load or ATL reflects short term fatigue. Form, a.k.a. Training Stress Balance a.k.a. the response is calculated in the algorithm from CTL & ATL.

The number one take home point from the graphic above is that the yellow trace (TSB) was at its highest for my goal events. I used the model to manage my training for the greatest TSB and consequently my best race results in the month of June.

As the saying goes, a picture is worth a thousands words and I couldn’t agree more and then some. In my next Toolbox I’ll elaborate on this model further and discuss the principles of training behind it.

Until then, good luck with your form and enjoy the rest of the Tour de France!

Banister, E.W.; Calvert, T.W.; Savage, M.V.; and Bach, T.M. “A systems model of training for athletic performance.” Aust. J. Sports Med 7:57-61, 1975

Busso, T.; Benoit, H.; Bonnefoy, R.; Feasson, L.; and Lacour, J.R. “Effects of training frequency on the dynamics of performance response to a single training bout.” J Appl Physiol 92: 572-580, 2002

Busso, T.; Denis D.; Bonnefoy, R.; Geyssant, A.; and Lacour, J.R. “Modeling of adaptations to physical training by using a recursive least squares algorithm.” J Appl Physiol 82: 1685-1693, 1997

* Sprinters will adjust their form to be optimal for the first part of the Tour while the GC contenders will use the initial flat stages to taper down into their peak form for the upcoming mountains

** I distinguish between racing and training because nine times out of ten, athletes see their personal best peak power outputs in races compared to their training. The extra adrenaline and motivation associated with competition bring outs the best data. That’s not to say you won’t generate great evidence of form in your training, you will if you or your coach is tracking your training data.

***from Daniel Coyle’s ”Lance Armstrong’s War”, HarperCollins, 2005

Frank Overton
Frank is a full time professional USA cycling certified coach, and category 1 road racer. He earns a living eliciting form from his athletes around their most important races. Check out FasCat Coaching @

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