WKO+ 3.0: Comparing Files with Multi-File/Range Analysis Tells a More Complete Story
10 February 2010
By Dirk Friel
Most cyclists like to test themselves up climbs and see how they compare to others. This is usually done through comparing finishing times and boasting about who has the highest average power, lowest heart rate, etc. But just imagine the unlimited possibilities if you could layer multiple power and heart rate files on top of each other to compare data between different individuals? A more complete picture would emerge about the true relative stress of each rider and might actually show who had the easier, or most impressive ride.
Well, there’s no need to wait any longer. WKO+ 3.0 is here with a new Multi-File/Range Analysis (MFRA) feature designed to help each rider get faster by comparing their own data over time, as well as the ability to compare themselves with others.
Multi-File Analysis in Action
Here is a great case study which shows some true benefits of comparing two athlete files within the new WKO+ 3.0 MFRA feature. In this example, two riders rode up the same climb, which took 17 minutes to complete. Most people would think if they both started together, and ended together, there isn’t much else to discuss. However, by overlaying the two files and comparing the two data sets you can quickly see how the two riders had vastly different experiences.
Heart Rate
Rider A: Average- 163, Max 170
Rider B: Average- 163, Max 173
Let’s start by comparing heart rate. The two riders had the same average heart rate. Interesting, again that must mean they rode at nearly the same intensity levels. Hardly, take a deeper look at how the two heart rate graphs compare. Even though they both averaged the same heart rate over the length of the file, Rider B’s pulse was quickly rising near the end which indicates he was rapidly nearing exhaustion.
So, if Rider B’s heart rate was quickly rising and nearing exhaustion, how did the two riders average the same value at the end? Well take a look at the beginning of the heart rate graph. Rider A actually started this hill interval earlier and caught up to Rider B. You can see how Rider A started with a higher heart rate — 156 — versus Rider’s B’s starting pulse of 144.
In addition, take a look at how within just the first four minutes Rider B’s heart rate rose to above Riders A’s. This indicates a quick rise in lactate levels and the onset of fatigue. Rider B meanwhile maintained a steady and consistent pulse throughout the file and could have probably maintained this pace for 60 or more minutes. Clearly that is not the case for Rider B.
Wattage
Rider A: Average-302w , 303np, Max 483w
Rider B: Average- 335w, 336np, Max 628
Overall the average watts were higher for Rider B even though they were climbing at the same pace. This is due to the fact that Ride B weighs 20+lbs more than Rider A.
Comparing absolute watts between each rider has little value when you consider the difference in body weight. The more relevant metric would be the power to weight ratio for each rider. Rider A averaged 4.5 watts per kilogram of body weight while Rider B averaged 4.4 watts per kilogram. Now, when you layer in the knowledge of Rider B’s heart rate quickly rising and exhaustion nearing it isn’t hard to conclude that Rider B was in the upper training zones burning matches quickly. Rider A was much more under control and able to maintain the pace for a much longer amount of time.
Cadence
Rider A- 79rpm
Rider B- 88rpm
Rider A pushed a bigger gear as compared to Rider B which can easily be seen across the length of the file. Some riders tend to ride more efficiently at higher cadence levels as compared to others. Lighter riders also tend to climb out of the saddle more which can sometimes lower cadence averages.
One last metric which clearly shows how these two riders were not riding at equal intensity levels is the power-to-heart rate-ratio percentage of change, also known as “Decoupling. ” This metric can be an indicator of the aerobic efficiency, or fatigue levels, of a rider which is clearly not the same between these two riders.
The PW:HR values of these two riders were:
Rider A- 5.8%
Rider B- 9.5%
Being able to compare and cross reference multiple metrics between two files, or ride segments, paints a more complete picture, which can’t be extrapolated from purely looking at average values or finish times.
Take a few minutes to download WKO+ 3.0 and give the Multi-File/Ride Analysis feature a try. You can also learn more about MFRA here and read more about Decoupling here.
Have fun and enjoy.
2 Responses to “WKO+ 3.0: Comparing Files with Multi-File/Range Analysis Tells a More Complete Story”
February 18th, 2010 at 2:05 pm
Interesting how the endurance training of Rider A compares with the sprint training of Rider B.
February 24th, 2010 at 10:52 am
Please make it possible to toggle the X axis between time and distance. I’m finding that half of the MFRA I set up need to be viewed by distance and not time.