CP - Mean Max NP Curve

AshesGlory

I have an old workout which if I understand the term correctly is a "NP buster". It has made my Mean Max NP Curve for the season pretty useless. Is there any way I can exclude just this single workout from my season mean max np curve?

Spunout

re-asign it to a new athlete, such as yourself #2.

So your default athlete (yourself #1) does not contain this workout.

daveryanwyoming

Alternatively you could redefine the workout as Cross Training, or Other and then filter your Mean Maximal Graph to exclude that type of workout.

-Dave

frenchyge

How about assigning it to the 'NP Buster' workout category?

daveryanwyoming

That's sort of what I was thinking with "other" I mean it might screw up an NP based MMC, but it's still valid TSS for the Performance Manager. It seems ashame to assign it to a fictitous athlete and not get credit for the work done

AshesGlory

Excellent. That worked like a charm. I reassigned the sport category of the offending workout to an unused category, and then in the options for the MMNP curve selected only the "Bike" sport under "sports to include". All other charts are unaffected. Thanks.

frenchyge

I'm curious how the NP from that one workout makes all the other NPs in the MMC (NP) worthless? Is there some reason to believe that you couldn't generate that same NP again under similar conditions, so that it needs to be thrown out as a false reading?

The MMC represents history of what you have done, and assuming the data aren't really old it's relevant to what you can do. Why do you think that one workout is not representative of what you can do?

AshesGlory

The normalized powers from the workout exceeded my capabilities for a large range of durations so masked my real capabilities. For example the MMNP(60) was more than 10% higher than my FTP, and corresponded to my MMP(10). The VI for the w/o was 2.58 and comprised L6 intervals.

djconnel

First, I'll assume here NP is for pacing and for predicting FTP. I separate it from an NP used for determining TSS. TSS can be calculated with a separate formula, if necessary.

NP is calculated from smoothed power w/ a 30 second smooth. I'll call smoothed power "P*". Basically integrate P*^4 over time (I'll call this meta-work -- work is the integral of power over time).

If, at constant power, I can generate more meta-work in a short interval than I can in a longer one, at an appropriately reduced constant power, I can get an NP buster.

Another possible NP problem is, if optimizing pacing based on a fixed NP for a given duration, I will tend to over-predict how much harder I can go for a shorter interval, for example to go extra hard on a climb and less hard on the descent. This is sort of the opposite problem. NP should be tuned to avoid NP busters, and to avoid over-predicting what I can do at shorter efforts.

There are two components to the NP formula: the smoothing time and the exponent. Defaults are 30 seconds and 4.

Now, NP uses a rolling average: the first thing I change in my calculations is to use an exponential average, as is used in ATL and CTL, as this is more physiologically representative (for example, representative of blood lactate levels, or ATP levels, following time-variable power). With exponential smoothing, a 15 second time constant (the CTL time constant is default 42 days, for example) is about the same as a 30-second running average (the conventional NP). This time constant marks the transition from "short-duration" efforts, which are primarily anaerobic, and "long-duration efforts", which are more dominated by aerobic capacity, and are valid predictors of FTP. If I set the smoothing time to 0, and have a massive jump, I can do a bunch of jumps then forecast a high 1-hour power. This may well be an invalid prediction: an "NP buster".

The second thing to be tuned is the exponent. The exponent of 4 says: if I halve the duration, I can supply 2^(1/4) - 1 = 19% more power. I know I can't supply 19% more power at 10 minutes than at 20 minutes, for example. So for me, an exponent of 4 is obviously too low. Maybe I can supply 6% more power. 2^(1/12) =~ 1.06, so for me, an exponent of 12 makes more sense.

I've looked at several NP busters folks have sent me, and using an exponent of 12, a time constant of 60 seconds seems to work fairly well. I got two files of one guy with really high anaerobic capacity but low aerobic capacity, and for him, I used 90 seconds, and nailed his FTP on both files, but with 60 seconds, I overpredicted FTP. So to me this suggests at least a 90 second time constant for him. But for others, the same 90 second time constant predicted well under FTP in what were reportedly brutally hard 1-hour race files. 60 seconds worked better at getting close to FTP. So I think the time constant needs to be tuned a bit based on an individuals ratio of aerobic to anaerobic capacities.

The test of an NP formula isn't just if it over-predicts FTP, but whether it over-predicts critical power at any duration. So if I plot NP^n * t, where NP is the near-optimal maximal NP at duration t, n is the NP exponent, versus duration t, for t of at least a few smoothing constants, I shouldn't see any long-term rises or drops. If I see a significant drop, I'll get an "NP buster" for some duration. If I see a sharp rise, I'll produce unobtainable optimization strategies. (my maximal power curve currently has a sharp dip at 20 minutes.... this is because this is close to my slower times up Old La Honda Road, not because of physiology, so it's for these criteria, the curve needs to be relatively optimal: ie there need to be maximal efforts over a range of durations spanning the curve).

So in summary, this is what I use for myself: a 60 second (optionally up to 90 for some riders) exponential smoothing along with an exponent of 12. I haven't done enough testing on this yet, and would be curious to see if others find it generates less of an "NP buster" problem.

Dan

zaskar

Anyway to change the NP to avg power?

djconnel

Using average power instead of NP would certainly solve the NP buster problem, but would result in a huge over-prediction of available power at shorter durations. For example, if I can average FTP for 1 hour, it would suggest averaging 2 FTP for half an hour up a hill, then coasting downhill for half an hour at zero power, is also possible (obviously I'd coast further than I climbed, but let's not sweat the small details ). Of course, doubling power going from 1 hour to 30 minutes isn't possible.

acoggan

1. Exponential smoothing is more physiologically plausible, but in practice I haven't found it to really make any difference.

2. If you're going to use exponential smoothing, the appropriate time constant from a physiological perspective is something in the 25-30 s range - 60-90 s is clearly far too long.

3. An exponent of 12 is simply implausible from a physiological (metabolic) perspective).

Bottom line: I think that your search for an improved algorithm has led you to oversmooth the data, then overweight it to compensate.

acoggan

Man, that ol' normalized power algorithm really sucks, eh?

Would you mind sending your file (along with a brief description of how you arrived at your functional threshold power) to me at acoggan at earthlink dot net? I'd like to add it to my collection of NP busters.

djconnel

What is the shortest trial which has been demonstrated to predict FTP?

For example, I don't have my Allen and Coggan handy, But a quick web search turned up:
http://www.springerlink.com/content/76tuhlu02a80j9mx/

From Fig B, an example, for one subject:
power = 15371 J / t + 205.4 W.

From which I get a characteristic time for anaerobic power:

tau = 15371 J / 205.4 W = 74.83 seconds

In other words, it takes an effort of at least 75 seconds before most of the power is guaranteed to come from the aerobic component. This is basically the average of the range I proposed. The shortest duration in this particular trial was approximately 130 seconds. For much shorter durations than "tau", the critical power model suggests total work is conserved, consistent with being in the "smoothing regime".

It would be interesting to see how closely various smoothing constants come to reproducing the published critical power data, taking "meta-work" as a constraint (ie integral P*^n dt).

Again, the lower bound on the exponent was based on pacing strategies for durations well above the smoothing time constant. Using 4 gives me extremely optimistic results for shortening the duration of the effort.

Dan