Firstly I haven't ridden the 200km version of the Audux Alpine Challenge so I will be doing a comparsion with Fitz Epic which I have ridden the last 2 years.
Fitz Epic
The Fitz Epic is an Audux ride here in Canberra around the base of the Brindabella mountain range taking in a number of major climbs. These are Fitz's Hill, Apollo Rd, and Corrin Rd. These climbs range in length from a mere 4km for Fitz's Hill to 12km for Corrin Rd.
The rest of the course os characterised by open rolling roads with shorter steeper climbs in the region of 300-600m.
The temperature at the time of year that is run is normally in the mid to high 20's and this normally accompanied with wind later in the day.
The check points are not of the quality of the AAC, but this due the smaller nature of the event and also that they are situated in the middle of no-where with no buildings, electricity, running water.
ACC250
My report from the ride is located here so I won't reiterate too much of it.
The AAC250 is an Audux ride starting from Bright and traversing through the Victorian mountain range taking in a number of major climbs. These are Mt Hotham, Falls Creek, and Towanga Gap. These climbs range in length from a meer 7km for Towanga Gap to close to 30km for Mt Hotham.
The rest of the course os characterised by a mixture of open roads with some shorter climbs in the region of 1-2km.
There are also three significant descents the First from Omeo, the second from Falls Creek and the final descent from Towanga Gap to the finish.
The temperature was in the high 20's little to no wind to speak of
The check points were some of the best I have seen with good facilities and plenty of food and water.
Multi-File Analysis
When version 3.0 of WKo was released I briefly mentioned the multi-file analysis feature of the software. What this allows is a comparsion between multiple rides on the same or similar courses (Yes, JD this would be perfect for your 100's of testing laps around Majura!).
The results once the files are combined is firstly a graphical plot with key metrics listed underneath for easy reference. The second result is a combined quadrant analysis plot of the files.
Graphical Plot of Fitz's v AAC250
Quadrant Analysis of Fitz's v AAC250
Conclusions
First up are the basic numbers,
AAC250
time: 8:42hr
work; 6048kJ
TSS 560
IF 0.81
VI 1.29
Normalised Power: 249w
Average Power: 193w
Average Speed: 27.9kph
Fitz Epic
time: 7:34hr
work; 5624kJ
TSS 543
IF 0.851
VI 1.29
Normalised Power: 267w
Average Power: 206w
Average Speed: 27.6kph
So we can see straight away that I had both a higher average and normalised power for Fitz than the AAC250. The VI of 1.29 indicates that there was a reasonable amount of coasting for both rides despite Fitz's having significantly less downhill.
On examination of quadrant analysis the % time spent in the 4 quadrants is roughly the same (within 3-5%). What is interesting is when the outliers are examined, the majority for quadrant II (high force/ low cadence) are from the Fitz's ride, and the for quadrant I (high force/ high cadence) from the AAC250 ride.
This shows that the climbing for Fitz's entailed a higher amount of low cadence/ high force climbing than the AAC250.
I would suggest that this is a result of the number of rolling hills and Fitz's Hill it's self.
In summary from this data I would conclude that Fitz's Epic is a "harder" ride to complete physically than the AAC250
That sort of fits with how I "felt" about the two rides. One note, Fitz's Epic is not an Audax ride, it's run by Pedal Power in the A.C.T..
ReplyDeleteCheers,
Russell
Interesting .. though I wonder if you are putting too much weight on the Quadrant II analysis. Actually, statistically, I would't be surprised if these were effectively the same. The big difference in the rides is a shift from Quadrant III to IV, but the interpretation of this -- I'm not sure. Since Quadrant III appears to be the 'easy' riding area where you were free-wheeling with low pedal rate, but very low power input (e.g. turning the pedals over descending). So I wouldn't hang my hat on QII. (Or if you did, you'd actually have to call the ACE250 'harder' since the proportions are the same in QII but the ACE250 is a longer event, you are effectively spending longer there.)
ReplyDeleteInstead, I think the total effort expended is more appropriate. The effort expended in the FE is at a higher rate than that of the ACE250 (a simple calc on your data yields 743 vs 695 (kJ/hour)) but the ACE250 requires an additional 34min equivalent at the FE workrate.
So I think it is right to say that the FE would have felt 'harder' for the duration of the race, but the overall ask is still about 30min ('FE equivalent minutes') under what the ACE250 requires. Or put another way, finishing the FE after an additional 30min of similar riding would make it a dead-heat.
sangus
Hi Sangus,
ReplyDeleteWith respect to the quadrant analysis, I have placed more weighting to quadrant II due to it being atypical to what is experienced in a road ride (specifically an enduro ride). Typically, “quadrant II pedaling” occurs when climbing or accelerating, especially from a low speed. Racing off-road (i.e., cyclocross or mountain bike racing) also often involves a significant amount of such high force, low velocity pedaling. However, even a race held on pavement may require a large percentage of such pedaling, if the climbs are steep and/or the rider is overgeared.
Because AEPF is sufficiently high, pedaling in both quadrant I and quadrant II would be expected to entail significant recruitment of fast twitch fibers.
The shift from quadrant III to IV, I would think is a function of the nature of the downhill’s. FE doesn’t really encourage too much pedaling more of a tuck and hang on style where as ACE250 because of the corners requires frequent accelerations.
While the total time vs % time may shift things in the favour of the ACE250, this is not really the function of the quadrant analysis.
KJ is not an appropriate measure to “effort” because of the variable nature of power output on the road. To account for this Dr Andy Cogan developed an algorithm to calculate an adjusted or normalized power for each ride or segment of a ride (longer than 30 seconds) that is analyzed. This algorithm is somewhat complicated, but importantly it incorporates two key pieces of information: 1) the physiological responses to rapid changes in exercise intensity are not instantaneous, but follow a predictable time course, and 2) many critical physiological responses (e.g., glycogen utilization, lactate production, stress hormone levels) are curvilinear, rather than linearly, related to exercise intensity, By taking these factors into account, normalized power provides a better measure of the true physiological demands of a given training session - in essence, it is an estimate of the power that you could have maintained for the same physiological "cost" if your power output had been perfectly constant (e.g., as on a stationary cycle ergometer), rather than variable. Keeping track of normalized power is therefore a more accurate way of quantifying the actual intensity of training sessions, or even races.
Although normalized power is a better measure of training intensity than average power, it does not take into account differences in fitness within or between individuals. IF is simply the ratio of the normalized power to an individual’s threshold power.
While exercise intensity is clearly an important factor in determining the type and magnitude of physiological adaptations to training, exercise frequency and duration - which together determine the overall training volume - are important factors as well. However, there is obviously an interaction between intensity and volume. To quantify the overall load, Dr Cogan developed TSS (Training Stress Score), which is modeled after Dr. Eric Bannister's heart rate-based training impulse (TRIMPS), and takes into account both the intensity (i.e., IF) and the duration of each training session, and might be best viewed as a predictor of the amount of glycogen utilized in each workout.
This is why I used these three pieces of data rather than KJ expenditure alone.