# Efficiency

We use TrainingPeaks and the data provided form our athletes to derive valuable insight from each workout.

Most people would look at this and think: How many ways can you look at watts? Heart rate, is it high or low? Well, it goes much deeper than that. To show an example of what we look at, I wanted to show 2 riders, riding together, on cool Saturday morning for 100k.

To start off, I wanted to say that some people are just gifted bio-mechanically, for certain movements. Their weight, proprioception ability, proportions, heart and lung capacity, and a host of other traits are inherited. These traits can be trained and enhanced so that anyone theoretically could compete at a high level. In the end however, some movements and specific activities (sports) may favor one person over the other.

Let's look at the two riders A and B:

Rider A: 3yrs cycling, 6ft, 180lbs. 300w FTP, 188HRmax. 34yrs Male. 3.7w/Kg

Rider B: 4yrs cycling, 5'7", 120lbs, 195w FTP, 210HRmax, 28yrs Male 3.57w/Kg

When you look at them Rider A has a higher w/Kg and therefore is going to be faster. That is IF he rides at the same %intensity factor as Rider B. Rider A will cover a greater distance in the same amount of time. Of course, this is not considering environmental factors, hills, etc.

We have a real world example (so there are other factors such as wind, weather, bike, drafting, fatigue......) With that said, both riders rode 100k on the same course together. Rider A did complete the course faster, but let's look a little deeper on how the ride went and what we learned.

• Rider A is much more efficient on the bike. The measure of efficiency is called aerobic decoupling (link to more info at the bottom of the post). For every watt that he puts on the pedals, he is about 25% more efficient in his energy expenditure. (See EF of 1.62) Therefore, he can put down 25% more power for longer even though he only has an 4% higher power output when normalized for weight. To try and use an analogy- Rider A has a better "MPG" rating.

Above: RIDER A

• Rider B rode a higher w/Kg of 2.92 vs. 2.53 for Rider A. Since this figure is normalized for weight, you would think that Rider B would have rode faster. This is not the case. Although there are other factors to consider in the physics of cycling (downhill momentum being one), how he rode during the ride is a key factor. Rider A pulled away in the last 15 minutes.  you can see that there is large decoupling in HR compared to wattage towards the end of the ride. You can see the pink/purple line start a trend downward as HR stayed the same or increased. The fatigue was mounting and the EF score(1.23) helps us find this quickly.

Above: RIDER B

To wrap up this small dive, I took a snapshot of that last 33mins for each rider to show how strong each was during that time.

Rider A shows an EF of 1.52

Rider B shows an EF of only .94

The last thing to keep in mind is that this measure is specific to a sport. We can baseline and then look at improvement relative to the individual. Knowing both of these riders, Rider A is a much stronger cyclist, but Rider B is a much stronger runner. In fact, when looking at run files you could flip the efficiency scenario.

This shows that to optimally coach someone, you need to build a deep understanding of their strengths and weaknesses and bring out the best parts of their physiology. In triathlon training work vs reward is key to train efficiently. Applying effort/hours of training in the right areas is key.