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I bought a power meter. I understand that you should do an FTP test to work out your threshold. But until I have time to do this, could I take a reasonable guess from a recent 35 mile road race?

These are the graphs from Strava, for the estimated distribution, it says average 230W. Is this a good starting point? Or should I go higher or lower, or should I ignore the graphs because Strave is just trying to guess it from speed/hr.

Estimated power Curve

Estimated power distribution


Edit - same course but ridden with power meter:

I raced the same course again, here are the same graphs from strava. It was a much windier day, and my finish time was just under 3 minutes slower than the last race.

Power curve with power meter

25w distribution using power meter

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You own a power meter - just fit it and go for a hard ride.


For others who don't own a power meter (and lets face it, they're not cheap)

Its a poor data point, but a chap at work has a power meter and he can compare this number with strava's estimated power. We've compared ~three races and strava's number was high or low by up to 30%

So your 230W could be as low as 160W or as high as 300W. Repeated tests will help narrow the range.

Another analogue solution is to ride hard for ~20 minutes to the point you can say words but not a whole sentence. Then use Strava's estimator on that segment. Repeat.

If you have a Heart Rate Monitor, try and hold your heart rate at around ~90-95% of your rated maximum, which is about 220-(your age in years)

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    Note that 90-95% of (220-age) for 20 minutes isn't something you should jump into if you're not used to it. Just a little caveat as I would assume that anyone thinking about this already trains pretty hard. – Chris H Jun 3 '17 at 9:14
  • Will strava even provide a power breakdown (like is shown) if you don't use a power meter? I don't want to pay their pro fee to find out. It says "Estimated" but I wonder if that is simply because the smoothed the data from a ride not designed to generate such curves. Hence it is an "estimate" because explicit tests such as CP5, CP20, CP60 (critical power at differing durations) were not used generate the power curve. – Rider_X Jun 6 '17 at 19:10
  • For example you could have a power meter and do a LSD ride (long slow day) and then look at the power curve. It would be a poor estimate on the shorter time scale. Using "Estimate" effectively covers your @$$. – Rider_X Jun 6 '17 at 19:12
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    Plenty of detailed answers, but "go ride" is basically what it comes down to. I've since done the same course again with the power meter so I'll update my question with the results. – ilikeprogramming Jun 15 '17 at 11:13
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From training peaks

Perhaps an even more precise way of determining your FTP, yet one which still doesn’t require any formal testing, is to examine your normalized power during hard ~1 hour mass start races.

Assume you used your power meter at the race, you should look at your estimated power curve (first figure). This shows how much power you can put out on average over differing durations. If you look at the 1 hr mark, your FTP is around 250 watts. This may be an underestimate depending on how hard of a continuous effort your were putting in. Your overall average wattage for the ride (230 watts) is not what you want as the activity was longer than an hour. FTP is the maximal work you can do in an hour.

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About the best you can do is to set a some limits to an FTP estimate.

If the Strava data was not the actual power meter data, then as Criggie says the short answer is no, you can't rely on that at all.

As an aside I thought that files uploaded to Strava that had power data defaulted to showing the real power meter data rather than an estimate.

If it is the actual power meter data, then you can probably at least narrow down a lower limit for FTP (provided of course the power meter is of a reasonable standard and you have used installed and used it correctly, e.g. ensuring a torque zero was performed before the race).

As Rider_X mentioned above - the first lower limit will be the average power for the whole race (~1.5 hours), so your FTP will be higher than 230W (assuming the data is from the power meter and not a Strava estimate).

The next lower limit will be your average power for about an hour, which in this case is ~250W.

If you have some analytics software such as WKO4 or Golden Cheetah, then it can work out for you what the peak 1-hour Normalized Power was. That will be closer to FTP than average power. Peak 1-hour NP may still be lower or higher than FTP depending on how hard the race was but it will not typically be higher by any more than 5%.

So if the race wasn't that hard, then peak 1-hour NP is not going to help you much except to bump up the lower limit of your estimate from the 250W average power value.

However, if the race was hard then your FTP will likely be somewhere between 95%-100% of your 1-hour maximal Normalized Power.

That then will at least give you an estimate to use until you have better data to improve your FTP estimate.

In the meantime just collect your data and learn to use the meter correctly - it can be helpful later on the be able to assess the nature of the training you currently do as you begin to learn what changes to make to your routine.

Here's an old but still popular post of mine about ways to estimate your FTP. Number 5 on the list is using the Critical Power model, which can be augmented nowadays by use intelligent of the newer power-duration models (of which CP is an example):

http://alex-cycle.blogspot.com.au/2008/05/the-seven-deadly-sins.html

  • Strava reports "weighted average power" which appears to be Skiba's xPower. For a file from a 35 mile race, unless the race was on unusual terrain, both xP and NP will tend to be closer to FTP than MMP for an hour. – R. Chung Jun 3 '17 at 22:19
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    Thanks Robert. I'm not a Strava user. I have an account but my cyclocomputers are not GPS enabled (older SRM Powercontrols). If Strava reports xP then that's close enough to NP such that desktop software may not be required for the purpose of the OP's question (although it'd probably help in other ways). – alexsimmons Jun 4 '17 at 23:52
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    Here is a link showing that Strava weighted power appears to use the xPower algorithm. xPower should be a more stable estimate than normalized power. @R.Chung - I am curious why exponential decay statistical models are not used, rather than this deterministic formula. This could allow for athlete specific rates of decay (e.g., a pro should have a lower rate of decay - power vs duration - than a sportif rider). Perhaps its time for me to head to the primary literature... – Rider_X Jun 5 '17 at 18:45
  • Principle of parsimony i'd suggest. Or put another way - what practical purpose(s) would individual tailoring of an NP-like formula have? I'd start by listing what NP is used for now and ask if it matters for the purpose: e.g.: - Generating an Intensity rating for a ride - not really given it's a general indicator. - Input into TSS - again not really as "improving" strain measurement really isn't the issue and is not a new idea. - estimating FTP, not really - Pacing models, perhaps, but it's touch and go I'd say on whether it'd make all that much difference. – alexsimmons Jun 6 '17 at 21:09
  • As for a pro having a lower rate of decay, I'm not so sure. Riders with different proportional mixes of muscle fibre types are more likely to demonstrate differences in NP relative to their aerobic capacity as expressed by FTP (or other similar indicators) rather than the absolute level the rider is at. But even then, not by a lot. – alexsimmons Jun 6 '17 at 21:14

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