Power Data Analysis: Solo Break vs. Sitting In

Posted by Verve on April 13, 2015 in
InfoCrank data analysis

Thinking of going off the front solo in your next race or group ride? Here’s the difference between sitting in the pack or going solo in Stage 3 of the Pro Women’s race at the 2015 Redlands Bicycle Classic. These stats might make you think twice about attacking from the gun or maybe make you realise just how much you can save by sitting in and being patient. Alizee Brien (Can) and Patricia Schwager (Swi) of Team TIBCO-SVB have shared their race data for this interesting and informative comparison.

How it went down

Alizee was in the break which went very early and built a max lead of two minutes on the field. She was caught about 7km from the finish, and her efforts earned her the sprint jersey.

Patricia was our field general and was in the bunch all day directing traffic. When the field blew up on the final climb, Paddy rode a moderate tempo so as to conserve energy for the next two days.

The take-away

This is great comparison as both riders have the same FTP, an impressive 4.3 w/kg. As far as the effort on race day, they couldn’t have been more different although both averaged about the same speed, 19.1 mph (30.7km/h).

Our solo breakaway ride, Alizee spent the majority of the race in Zone 3 (tempo) and Zone 4 (threshold) with still very significant efforts in Zone 5 (VO2) and Zone 6 (anaerobic).  However, our road captain directing the team in the field spent most of the day in Zone 1 (recovery), Zone 2 (endurance) and Zone 3 (tempo). It is important to note she was being attentive, covering moves and finding and directing teammates, as you can see by the amount of time spent in Zone 6 (anaerobic) using short bursts of power to move about the pack.

You can see the total physiological toll of the stage expressed in the metrics training load and intensity.

Alizee recorded a load of 206 while Patricia came in at 152, showing that Alizee had a much harder day despite them both riding the same course. The Intensity percentage also shows the same result, Alizee had a much more intense effort while Patricia conserved energy for the last two stages.

The Stats

Alizee Brien Patricia Schwager
Weight 68 55
FTP 290 235
FTP W/kg 4.3 4.3
Average Watts 249 160
Average W/kg 3.7 2.9
Effective Power 264 186
Effective W/kg 3.9 3.4
Training Load 206 152
Intensity 91% 78%

Stage3Summary_1Stage3Summary_2

Glossary

FTP (Functional Threshold Power): The maximum average power in watts that a rider can sustain for approximately 60 minutes.

Watts/kg (Watts per kilogram): Converts watts to a metric that compares power output between cyclists of different weights. Also known as power-to-weight ratio. Compares apples to apples (watts per kilogram) instead of apples to oranges (watts).

Effective Power: This uses the same power data that is used for calculating average power and it means something similar but it takes into account the way higher powers are disproportionally harder. The idea is that the ride would be just as hard if this was the average power for the entire ride. This number is calculated using a method developed by Andrew Coggan, which involves calculating the fourth root of the average of the fourth powers of the 30s rolling average of the power data.

Training Load: This is calculated as intensity2 × duration. This indicates how taxing on the body the ride was. A one hour time trial will by definition have a training load of 100. Andrew Coggan also came up with this.

Intensity: This is calculated as effective power / FTP (FTP, or functional threshold power, which is the maximum power output that can be sustained for one hour, must first be set). This indicates how hard the ride was. Shorter rides can have higher intensities. A one hour time trial will have by definition an intensity of 100%. Andrew Coggan came up with this.

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Team TIBCO-SVB bikes have been equipped with InfoCrank for 2015.

For the 2015 season Verve Cycling has sponsored the TIBCO-SVB Professional Women’s Pro Cycling team with InfoCrank, the new gold standard in power meters.

UPDATE: We received some questions around left-right balance and have posted both Alizee and Patricia’s 20-minute peak power files. You can take a look at these below.

Alizee, the solo rider shows a much more evenly balanced, higher power output.

Alizee Brien (Can)

The rider sitting in the field, Patricia, shows much more uneven, lower power output.

Patricia Schwager (Swi)

Read more in the comments sections below.

What does it take to support a team leader aiming for the general classification? We take a look at the life of a domestique and the physical demands involved in supporting a rider during a week-long tour.

Read: A week in the life of a domestique

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  • do you have anything showing the… Left/Right balance throughout the ride? This is more out of curiosity than anything as I don’t know enough to understand if it is at all relevant.

    I recently finished a short race and seemed to end up with 53% on my right leg – per the Garmin Connect estimates (using a spider based power meter). Interesting to watch the balance shift over my ride and at different intensities. Do well trained athletes have similar variations?

    • Hi Jon. The base data will have L/R balance, but Training Peaks does not show it clearly in it’s current form. For that reason, Verve usually recommends Cycling Analytics, but of course, Training Peaks still has many users, including this rider.
      Can I just caution you in taking any particular action other than monitoring your pedalling action when using a spider based or less than accurate power device. The spider based uses an algorithm than is more wrong than right. The others have potentially wrong numbers to start with.

      If you want some information on these issues, you could read http://www.biobike.us/torque-analysis.html which shows how torque analysis works (Verve designed and manufactured the BioBike iCrank) and how spider based analysis gets it wrong. Suffice to say, that a wrong interpretation on balance and individual crank torque numbers could lead to a wrong diagnosis.

    • Hi Jon,
      Great Question. I will post two snapshots of each rider’s 20 min peak power. Alizee, the solo rider shows a much more evenly balanced, higher power output. The rider sitting in the field, Patricia, shows much more uneven, lower power output. This is very typical. When riders are just cruising along, drafting, etc. they tend to let the dominant leg take over because they are not focused on putting out power. When a rider gets on the gas, the power distribution frequently evens out as the rider concentrates on being smooth, efficient, and powerful. Make sense? Let me know if you have any other questions.

    • Hi again Jon,

      We have posted a snapshot of Alizee and Patricia’s 20-minute peak power data in the article above. Enjoy!