Cycling Analytics now supports the new torque effectiveness and pedal smoothness metrics. What these metrics measure is a bit complex, so we’ll first look at what they mean.
This chart shows the power being applied to a pedal by a leg in a typical rotation of the cranks. It starts off positively on the downward movement, but there is a negative component in the second half of the rotation if the pedal isn’t completely unloaded or lifted up.
P+ is the power pushing the pedal forward, while P− is the power pushing the pedal in the opposite direction. Pmax is the maximum power applied to the pedal during the stroke, while Pavg is the average power applied to the pedal in the stroke.
Torque effectiveness measures how much of the power delivered to the pedal is pushing it forward. It is calculated as (P+ + P−) / P+ and is normally displayed as a percentage (P− will be a negative value or zero). A value of 100% means that all of the power was pushing the pedal in a positive direction (therefore, P− was zero). Values of 60–100% are common.
Pedal smoothness measures how smoothly power is delivered to the pedal throughout the revolution. It is calculated as Pavg / Pmax and is normally displayed as a percentage. A value of 100% means that the power is delivered constantly throughout the revolution. Values of 10–40% are common.
Torque effectiveness and pedal smoothness are measured independently for each leg, and this data is all calculated by the power meter, so Cycling Analytics gets four new streams of data from ride files that contain this. At the moment, the Garmin Vector with a Garmin Edge 510 or 810 (with the latest firmware updates for the power meter and computer) produce this data.
Now, onto what Cycling Analytics does with this data.
The Power vs. L/R balance analysis chart has been replaced by the Power vs. L/R … chart, which shows how power balance, torque effectiveness and pedal smoothness vary with power output. The chart above shows the torque effectiveness of the left leg in red and right leg in blue for one particular ride. It is noteworthy that the torque effectiveness becomes higher as the power output increases, there is a lot more variation at lower power outputs, and, for this ride, the right leg has consistently higher values than the left.
Because torque effectiveness and pedal smoothness are measured independently for each leg, this chart can show the data for each leg separately, or all the data together (which is the default behaviour).
Here we have pedal smoothness, which also increases with power output, with the right leg having consistently higher values than the left.
This chart also shows the left/right power balance, which shows the proportion of power coming from each pedal. The value is the proportion of power coming from the left pedal, so this ride is slightly biased towards the left leg. The left/right/both leg setting has no affect here.
It’s also possible to change the opacity of the points drawn in this chart. On longer rides, because there are more points, there can be a big blob of solid colour, so reducing the opacity makes it possible to see variations in the point density again.
In the ride summary the average of each of these values is displayed. The charts (as pictured above) give a better indication of what this data looks like. For example, overall, the average of 65% for the right leg doesn’t sound very high, but the chart above shows that this value is much higher at higher power outputs. This also means that different rides could have different values based on their composition. However, the difference between the two values here represents a meaningful difference that is shown on the charts.
The main ride chart shows the average values for this data when selections are made. It doesn’t yet show the actual values for each second.
That’s all for now. Based on the recent survey, it looks like segments (which won’t work in the same way as Strava’s) and an improved power curve chart are coming soon.
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