I am looking to analyze my 2019 LT100MTB race file along the following lines:
Time that I was stopped (i.e. power = 0, and speed = 0)
Time that I was walking my bike (i.e. power = 0, and speed 0 < 3mph
Time that I was coasting (i.e. power = 0, and speed > 3mph
Time that I was under power
For #4, I would also like to know what average power, NP, and average HR were. It would also be very cool if I could bucket this by HR ranges.
I’m racing this year again, and I know that my FTP is probably 20-25W lower, and my weight is probably 6 lbs heavier. However, I know that my pwr/HR at 131-139 BPM is probably 12-16% better, and on a W/kg basis that would be ~9-13% better. Given this is where my HR was for most of the race “under power”, I’m looking to make some crude estimates for my estimated finish time this year… Coasting, walking, and stopped bits should all be about the same this year, I figure.
use this site to make your fit file into csv. Then just do what you want to do with the raw data using IF statements in excel. Should be straight forward.
That was a great idea! Unfortunately. the file size limit is 2mb, and my file is 2.002mb. If only I was 1% faster in 2019, the file might have been small enought…ugh.
Its been awhile, I believe Golden Cheetah and intervals.icu do not have any form of scripting. There is some user graphing in intervals, but AFAIK nothing to support that time/metrics by speed analysis.
The latest versions of Golden Cheetah use R for data analysis. Very powerful, but takes some effort to learn to use. If you go the Golden Cheetah route, there is a Google Group for it if you need help.
@wbendus, this sounds like something that I might be able to help you with by writing up a quick Python script. If you can DM me a .tcx file from your race activity, I can parse it for you and return the raw data as a .csv for you to analyze in Excel. If you’re not particularly comfortable with Excel or you want some more detailed output, I wouldn’t mind helping you out with some of the analysis as well (i.e., analyzing the amount of time you spent in each of the four zones you outlined, as well as bucketing that data by heart rate ranges).
Let me know if this is something you’d like some help with!
(To export the activity as a .tcx file from Garmin, you can click the ‘Settings’ cog icon on your activity, and then select Export to TCX. To export the activity as a .tcx file from Strava, you can click on the three dots (…) on your activity and then select Export Original.)
Thanks for the offer, @RobertBahensky . I actually just scrolled through my file and manually calculated intervals where I was ‘under [loaded] power’, which worked out to be ~8:45 of my 11:18 elapsed time, meaning I was coasting/walking/stopped for about 2:33 of the time.
My time weighted average power was ~155W and time weighted average HR was ~138BPM for that 8:45 powered time. Based on my pwr/hr graph from 2019, that 155W would have been ~89.1% of the 174W I would have typically gotten in 2019 at 138BPM at sea level. I estimate that my total “system weight” in 2019 was ~97.9kg (rider/bike/fuel/hydration/tools), implying avg w/kg of 1.58.
This year, I expect that I will weigh ~2.5kg more, and that my total system weight will be ~100.5kg. If I get 89.1% of my 2021 pwr/hr this year for a comparable 138BPM HR average, my average power might be 175W, implying my w/kg would be ~1.74, or ~10.3% better. If I am 10.3% faster in my powered sections, my powered time would be estimated at ~7:55, or 50 minutes faster! My coasting/stopped/walking time is probably similar.
I’m glad you were able to figure this out, @wbendus! Please keep us posted on how your crude estimates line up with your actual race results after this year’s LT100MTB!
I don’t have any experience with MTB riding, so I’m not sure how the numbers would play themselves out on a race like LT100MTB where: 1) there is a lot of descending/ascending, and 2) average speeds are generally lower than those in other disciplines like road racing or time trial racing.
That said, be mindful of the fact that power does not translate linearly to speed… which is to say that a ~10.3% increase in your W/kg will not translate to a ~10.3% increase in average speed. Rather, the increase in speed will be lower than the increase in power which you’ve estimated (so, in this case, anywhere in the ballpark of ~3-8% faster?..). This effect becomes more pronounced the faster a rider you are (i.e., marginal gains start to kick in).
In my opinion, any estimate would be fairly useless without being run through a more advanced system like BestBikeSplit (or whatever the equivalent happens to be for MTB riding dynamics).
I only bring this up so that you are careful about setting performance expectations on the basis of your estimates… with your estimates being as crude as they are, your result on race day could end up being better than you’ve estimated, or—if other factors come into play—you might even perform worse than in 2019 (fingers crossed that this doesn’t happen!). The challenging part of this whole equation to consider is that you’ve improved your cardiovascular efficiency (i.e., heart rate at a given power), but simultaneously shifted your power curve downwards and gained a non-trivial amount of weight… the interplay between these variables is just too complicated to assess the accuracy of your estimate.
Enjoy yourself on race day, and don’t worry too much about the numbers! Good luck!
Holy smokes that’s a lot of over analyzing. Just ride your bike as hard as you can for the given time. If it’s 10 degrees hotter or you only sleep 4hrs the night before or your body reacts to the fueling differently or there’s a wind out of the north on the return trip…all those numbers go out the window.
If you’re walking that much you should put on a smaller chainring or bigger cassette.
