Far too often athletes get caught staring at data points that will just leave them down a slippery slope. While at times the data points they like to reference or have a little bit of understanding of can’t help them and are of value but often times they can lead you down the wrong path. all of this is said with bated breath because it is definitely a double-edged sword when it comes to data and which parts matter when.
I am going to present to you a very simple way that I look at an athlete’s progress based on where he is an athlete and data points that to me, are black and white that are a good example of fitness and/or gains.
For this particular example I used to data points to compare races over time. I utilized normalized power and aerobic decoupling during the race.
In the three races that I sampled, two of them where what most would consider hilly and one of them was what most would consider flat. Ironman Chattanooga features more longer sustain climbs with a little bit of rollers, Ironman Wisconsin has some sustained climbs but is more rollers and Ironman Texas has a few small inclines but is majority flat.
Course Difficulty Rating –
2017 IMChoo –
Swim – River
Bike – 1.5
Run – 3.1
2018 IMTX –
Swim – Lake
Bike – 1.2
Run – 0.4
2019 IMWI –
Swim – Lake
Bike – 2.2
Run – 1.6
Total Bike Elevation (as recorded on his Garmin) –
2017 IMChoo – 4,808 ft gain
2018 IMTX – 1,224
2019 IMWI – 4,120
Bike Split Times – (from athlete’s device)
2017 IMChoo – 5:38 (115 miles)
2018 IMTX – 4:58 (110 miles)
2019 IMWI – 5:39 (112 miles)
The common recurring theme with most athletes is they will look at their bike split time and immediately judge their overall performance for that portion of the race. Often times, they struggle to be able to make fair comparisons of course difficulty, weather conditions (wind, water temps, humidity, air temp) and immediately assume slower is just in fact that, slower.
In all actuality slower is slower, until it is not. Confused yet?
What if an athlete was more aerobically efficient but slower finish time? What if an athlete rode an all time NP PR for a race of that distance and was slower? Are they then still slower? It all depends on your definition of growth and/or success.
Aerobic fitness can be seen in a few different ways but for this race I chose the aerobic decoupling (or Pw:Hr)
(you can learn more about that here: https://www.trainingpeaks.com/blog/how-to-use-aerobic-decoupling/)
Aerobic decoupling will give you a great snapshot of the athlete’s aerobic fitness as it pertains to long course racing. 0% being even and a delta of 10% or more as a flag of overexertion or lack of aerobic fitness (this can also be indicative of dehydration/nutritional issues, impending sickness and a few other factors)
The other data point I am using for this is Normalized Power (NP). NP is defined as Essentially, normalized power, is a weighted average of the pedaling you have done during a particular ride. This metric gives extra emphasis to high-output efforts and accounts for surges or spikes in power. In other words, a great metric to see the true work being done.
In the next blog post I will show you what I discovered and why it matters more than a finishing time.