Inspired by a question in the Too fast for D Grade at age 74 thread I thought I’d plot the w/kg distribution for Zwifters.
First, the power data. Ideally you’d trawl ZwiftPower and extract the FTP for every single rider but as that’s not practical I did the next best thing, looked up the results for the L’Etape Du Tour Stage 3 from Jul 2020 ZwiftPower - Login
As you can see, that stage was up Ven Top so it ensured that most people would be doing a steady effort of between 1 and 3 hours depending on ability with very little freewheeling or drafting. Also, 1,616 finishers meant a useful set of data. As this was also a popular Zwift event it would probably generate a more representative distribution of the Zwift population rather than just those who race.
As the time taken for the event would be so different for everyone I settled on comparing the 20 minute best power for everyone rather than the average power for the whole ride. Some people might have been racing, some might have taken it easy knowing they had 3 hours ahead of them.
There are limits to the kinds of conclusions you can draw from this data set so do not treat these figures as absolute facts. Full access to Zwiftpower would be needed if you wanted more accurate data.
With those disclaimers out of the way onto the distribution plot. 20 minute w/kg along the X axis, numbers on the Y axis.
Notice how 2.6 and 3.3 w/kg spike over the lower values and the dip at 4.2w/kg. Interesting coincidence how those values just happen to be near the C, B and A cat limits. Hmmm.
If we adjust the w/kg by mulitplying by 0.95% to get a ZwiftPower style FTP and then calculate the numbers that would fall within A, B ,C and D cats we get this:
A cat: 225
B cat: 688
C cat: 463
D cat: 214
Again, some interesting distributions. It shows that being the top of C cat would mean you are only in the top 58% of all Zwifters.
Here is the raw data if you’d like to do your own analysis: