Tag Archives: phdinleuven

Double observing run: done.

During the last three weeks I spent 17 nights working at the telescope. 11 nights at the 1.2 meter Mercator telescope on La Palma, and 6 nights at the 0.8 meter IAC-80 telescope on Tenerife (and I had one night in between, when I did not have to work). All these nights were clear, and though some were plagued by the Calima (dust from the Sahara blown above the Canaries), I managed to keep observing all the time, except for one hour, when the seeing got so bad, that I could not do anything anymore. It will be really hard to have a better observing run ;) It is not easy to admit that there are much better time-lapse movies than the one I made last year, but the video below really shows how beautiful my workplace is…

I still think that this is the best part of being an astronomer, but of course after so many days it is good to be back in the normal day-night rhythm, and on a lower altitude (almost sea level), where there is more oxygen ;) So after saying good bye to the view from the Observatory (see below – pretty, isn’t it?), I took a taxi down (to 2000 meters lower in elevation) to La Orotava.

I am staying at the Hotel Rural Victoria, and it is perfect. I have a quite big room, free wifi, an LCD TV (on a nice wooden work desk), a huge private terrace overlooking the city and the sea (with my own cacti :D), two big beds, separate bathroom and toilet, etc. And the dinner included in the half pension has three courses with some tidbits in between! Perfect for a tired cyclist, who does not want to look for food after a long day. I hope the breakfast will be as good too! (Update: it is damn good too! I have chosen the best hotel.)

Today I did not do anything special, just assembled my bike (for the 3rd time in three weeks…) while watching the Vuelta (I went on a ‘short’ 1.5-2 hour training on 5 out of 7 afternoons while I was working here on Tenerife, so today was a rest day), walked around the city for an hour (it is really nice, a bit like La Laguna), and got some cookies and chips for later. And a big bottle of water – the most important thing… Now I have 6 days to bike around the island (mostly up and down, not really around), and I made plans for 5. We will see how much I can handle. The rides are shorter (100-130 kilometers), but with a lot of climbing, so it is not at all easy… But the scenery is amazing, so it is definitely worth the struggling ;)

I will keep you updated on the rides! (If I have energy left to blog afterwards… :D)

The Performance Management Chart

Now that I can analyze and plot my workouts in detail, and I can estimate the Training Stress Score (TSS) of each ride, it is time to make use of all the statistics. It is nice to have numbers quantifying my trainings one-by-one, but how nice would it be to track my form and fitness during the season based on the volume and intensity of my rides. This is the concept behind creating the Performance Management Chart. I will write down (partly quote, or just rephrase) here the most basic things, but again, everything is based on the following two articles (take time to read them, they are very interesting):

What is the Performance Management Chart in TrainingPeaks WKO+?, by Hunter Allen
The scientific inspiration for the Performance Manager, by Andrew R. Coggan, Ph.D.

Andrew R. Coggan defines form as a combination of fitness and freshness (Form = Fitness + Freshness). You will have a really good day in the saddle when your fitness level is high, and when your fatigue level is low. Fitness is a response to training stress (or training load); the more you train the better you will be. Freshness is simply a result of rest. As TSS quantifies training load, knowing TSS values of workouts from the past enables us to determine the rider’s fitness in the present, and see how much training is needed in the future to raise this level higher.

The Performance Management Chart is based on Banister’s impulse-response model (see 2nd article for details), and we define the following components:

1) Chronic training load (CTL) provides a measure of how much an athlete has been training historically (chronically). It is calculated as an exponentially-weighted moving average of daily TSS values, with the default time constant set to 42 days. CTL can be viewed as analogous to the positive effect of training on performance in the impulse-response model. It is a relative indicator of changes in performance ability due to changes in fitness.

2) Acute training load (ATL) provides a measure of how much an athlete has been training recently (acutely). It is calculated as an exponentially-weighted moving average of daily TSS values, with the default time constant set to 7 days. ATL can be viewed as analogous to the negative effect of training on performance in the impulse-response model. It is a relative indicator of changes in performance ability due to fatigue.

3) Training stress balance (TSB) is the difference between CTL and ATL, i.e., TSB = CTL – ATL. TSB provides a measure of how much an athlete has been training recently, compared to how much they have been training historically. It can be viewed as an indicator of how fully-adapted an individual is to their recent training load, i.e., how “fresh” they are likely to be.

In the Performance Manager concept, an individual’s CTL determines their performance potential, but their TSB influences their ability to fully express that potential. Their actual performance at any point in time will therefore depend on both their CTL and their TSB, but determining how much emphasis to accord to each is now a matter of trial-and-error/experience, not science. (Really go and see more details in the original article.)

Some other interesting quotes before I tell you about my progress in the topic:

“The following approximate guidelines may prove useful when analyzing prior data: a TSB of less than ‑10 would usually not be accompanied by the feeling of very fresh legs, while a TSB of greater than +10 usually would be. A TSB of -10 to +10, then, might be considered neutral, i.e., the individual is unlikely to feel either particularly fatigued or particularly rested. The precise values, however, will depend not only on the individual but also the time constants used to calculate CTL and ATL, and therefore should not be applied too literally.”

“The optimal training load seems to lie at a CTL somewhere between 100 and 150 TSS/d. That is, individuals whose CTL is less than 100 TSS/d usually feel that they are undertraining, i.e., they recognize that they could tolerate a heavier training load, if only they had more time available to train and/or if other stresses in life (e.g., job, family) were minimized. (…) On the other hand, few, if any, athletes seem to be able to sustain a long-term average of >150 TSS/d.”

“In addition to the absolute magnitude of CTL, considerable insight into an individual’s training (and/or mistakes in training) can often be obtained by examining the pattern of change in CTL over time. Specifically, a long (e.g., 4-6 week) plateau in CTL during a time when a) the focus of training has not changed, and b) the athlete’s performance is constant is generally evidence of what might be termed training stagnation – that is, the individual may feel that they are training well, by being very consistent and repeatedly performing the same workouts, but in fact they are not training at all, but simply maintaining, because the overload principle is not being applied. On the other hand, attempting to increase CTL too rapidly, i.e., at a rate of >5-7 TSS/d/week for four or more weeks, is often a recipe for disaster, in that it appears to frequently lead to illness and/or other symptoms of overreaching/overtraining. Of course, since changes in CTL are driven by changes in ATL, this means that any sudden increase in the training load (e.g., training camp, stage race) must be followed by an appropriate period of reduced training/recovery, so as to avoid too great of an overload.”

So now that I have all my rides processed with my python script (even the indoor ones, so really all cycling workouts), I only had to write a script which grabs the TSS values from every statistics file (then calculates daily values if there were more rides on a given day), calculates the ATL, CTL and TSB values for every day in the given period, and plots them (plus saves the data as a table). This was not too hard ;) There is even an option to change the default time constants in the parameter file (the same parameter file which is used by the workout analyzer and plotter script), and to define a start date and end date for the plotting in the command line. Then after giving the

>python plotgarmintcx_makePMC.py 20101201 20110920

command (where the dates are optional and only affect the plotting limits, while the calculations are always done using all the data), you have your Performance Management Chart plotted and all the data saved in an ASCII file too. Let’s see how the result (with some additional comments photoshopped over in red) looks like (click and it will be bigger)!

You can see that I came into the season with some residual CTL (in blue) from last year, but one 1 hour trainer session per week was not enough to keep that on a steady level… Then as the spring was exceptionally warm and sunny I had some quite good trainings in March and April raising my CTL from 20 TSS/d to 55 TSS/d, which then dropped because of no training and very low training load during my observing run. Then the four hard days of cycling on La Palma gave a huge amount of training load (ATL in magenta), my CTL jumped from 45 TSS/d to 68 TSS/d, but my TSB (in yellow) fell to -87 TSS/d, which is extremely low, if you keep riding there then the chances are high that you will get an injury… It also resembles well that I was extremely tired after that week… Then, only after two days of rest, with a still pretty negative TSB I rode my personal best on the standard Leuven-Mechelen-Leuven route. Probably I should have waited a bit more, because another 4 days later I did a ride where I easily had a better average speed on 62 kilometers than my personal best on 48 kilometers from 2010. I was extremely surprised about my performance on that day. It is not such a surprise anymore when you look at this plot. My CTL was still very high, and as I was resting a lot in the days before, my TSB became almost zero. This is the perfect combination (high CTL, zero or slightly positive TSB – remember, actual form is a combination of fitness and freshness) for record breaking rides (or races), this is an example of a sweet spot on the Performance Management Chart. Unluckily after this really good period I could not ride for almost three weeks (work, work, and weather…), which had a huge impact on my CTL (dropping all the way down to 43 TSS/d). From this point, I started a quite systematic and serious training, as I wanted to finish July with at least 1000 kilometers. You can see that my ATL is almost always above my CTL, which leads to the increase of CTL. Then I crashed into a car just days before I was about to climb the Mont Ventoux, which gave me some time to rest (and a bit if pain in my right knee, which is missing from this chart…), so again I had a high CTL and an ~zero TSB when I went to France. And I was again very surprised how easy the first ride felt there, especially after an accident. But now from this chart, it is not so surprising anymore. My TSB was still only -13 TSS/d when I climbed the Mont Ventoux, so it was close to optimal, but I could have done better with a bit less riding on the first two days in France. It was also the day of my highest CTL with 71.3 TSS/d this year (till now). Then during my observing run, it dropped again (to 57 TSS/d), so now I am working on getting it back up to the region where is should be :) Next year I want to be at 100 TSS/d at this time. At least. Especially if I am serious about my plans for the summer…

As a conclusion, I think it is a very nice visualization and an extremely useful tool for a cyclist!

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Estimating cycling power and training load

Updated 1: I modified the script slightly to perfectly match the estimation method of Joe Friel (see below), and as this had a small but clearly positive effect on the results, I have also updated the last plot and the paragraphs describing it at the end.

Updated 2: I have also tested the power estimate on very low intensity efforts with known average wattages (check out the bottom of the post).

You might remember that I have written a python script earlier this year, to analyze my cycling workouts and besides the calculation of detailed statistics, also create all kinds of fancy (multidimensional) plots. If you do not remember, or you would like to refresh your memories, please click here before reading this post further.

The most important thing missing from my script was the ability to directly compare different workouts. Of course you can tell that a 150 km ride with 5000 meters of elevation gain is more difficult than an easy 50 km Sunday afternoon ride, but how much more difficult? And what about an easy 75 kilometer training and a short but hard interval session? How do these compare? How tired am I going to feel myself after these? I really wanted to create or find a metric which tells me how much I did on a training. Of course this is only a problem when you don’t have a power meter installed on the bike, because that would directly tell you the amount of work in SI units for every workout. But power meters are expensive, and most importantly I don’t have one. This situation might change in the future, but till then let’s see what can we do.

I kinda forgot about the problem (and I did not even start dealing with it earlier, I just simply made a note on my To Do list), but some days ago Strava (a similar site to Garmin Connect, but with competitive – social media based – extras, unluckily with basically no users in Europe, so it is not an alternative for me) introduced a so called suffer score on their website, basically giving a rating to every ride based on its intensity (estimated from heart rate – HR – data) and duration. I knew that the algorithm behind this will be quickly decoded on one of the blogs I frequently read, and indeed it did happen very quickly, go and have a look there. First I wanted to implement this into my script, but then I got some extra motivation from the post and the comments there, so I looked a bit into the literature, and thus I got to know about the Training Stress Score, or simply TSS (among others, but this is the most important thing for us right now). To save some space here, check out the following three sites, so I can skip retyping things which are already on the Internet.

Estimating Training Stress Score (TSS), by Joe Friel
Normalized Power (NP), Intensity Factor (IF), and Training Stress Score (TSS), by Andrew R. Coggan, Ph.D.
What does 100 TSS mean, and the connection to Functional Threshold Power (FTP)

Though TSS and all these metrics are used in and based on power measurements, you can see that it is possible to give a good estimate (as good as estimating the realtive power on climbs from the slope gradient and VAM, which my script already did before) of it from time spent in HR zones using the scaling values from Joe Friel. We have seen that by definition a TSS of 100 equals to a one hour ride at FTP (so as hard as you can go for one hour). This means that rides shorter than one hour can have a TSS/hour higher than 100, but longer rides will have a lover value. So the TSS value tells you how big the training load of a given ride was (and it is related to the amount of post-ride fatigue), and the TSS/hour value gives you the intensity of your workout. The way it’s calcualted, TSS varies by the square of intensity. That means if you’re only going at 90% for an hour then you’re only accumulating 81 TSS per hour (90% = 0.9, which squared is 0.81, then you multiply by 100 to get TSS). So from the TSS/hour you can calculate an intensity factor, which gives you your average power output in units of your FTP power for the whole workout. Given that you know your FTP power, you can have a good estimate of the average power of any of your training rides! Now that is pretty cool. So that is what I have built into my script, this way now the TSS, TSS/h, average power and total work estimate values are also given in the summary file. And I also performed some test calculations and comparisons – because you should never forget, these are estimates! You need to know your FTP, and your HR at FTP, and then you might even get a reasonable value…

First of all, I wanted to see what is the intensity factor of my personal best ride to Mechelen and back. It was an approximately 1 hour 20 min all out effort, and the script gave an intensity factor of 1.00, meaning that I was riding on FTP. Though the ride was a bit longer than one hour (when it should not be possible to ride on FTP anymore), but I had a small 10 min break between the two legs in Mechelen, so it might still be a valid approximation, but for sure it should be extremely close to reality. Also, though it was a very tough ride, because it was short, the TSS value is ‘only’ 135.0, meaning that in 24 hours I might have probably almost fully recovered. In comparison, a normal ride (in my terms, so an average of 32 km/h instead of the record 35.7 km/h) on the same route gives a TSS around 110, while a recovery ride is probably below 100, and my epic ride (147 km and a bit more than 5000 meters of elevation gain) climbing twice up from sea level to the highest point of La Palma had a TSS of 483.7, which – as you have already guessed it probably – is in the epic category. Just as comparison, the last short (46 km and 400 meters of ascent) and recovery paced ride from France had a TSS of 69.5 (which is approximately half the TSS of my personal best ride which was done on an almost equally long, but completely flat route, so this really shows how easy this French ride was). So as I got an IF (intensity factor) of 1.00 on a ride which is very close to the definition of FTP I was already quite happy with the result. (If for such a ride you get something like 1.05 or even higher as IF, then that is a sign that your threshold heart rate is now higher, so you should change it accordingly in the parameter file.)

As a second test I wanted to see how does this power estimate compare to the power estimate from VAM and average gradient, which is a widely accepted and used relation for climbing sections. If the power values from the two methods match, then it is OK to use the power estimate from the hourly TSS value on rides even with no climbing at all. So first I took my recent ride up to the Mont Ventoux, where I did 1 hour and 40 minutes of all out riding, so I expect to get an IF around 0.95 and of course I am very interested to see how the two different power estimates will differ from each other (if they will differ at all). So here is the statistics file (recent additions marked with a grey background):

So from the IF of 0.96 you can see that indeed I did all I could in this time frame. Now we can estimate the average power from my FTP, which is somewhere around 300 W (or maybe a bit more, but I have to admit I don’t have a recent measurement, so I can only guess this from my workouts on the trainer back in the first months of the year). The result from this is 288 W. What about the value from the other method? I was ~70.5 kg and my bike + drink and food + clothes is an extra ~11.5 kg, then with a total weight of 82 kg and the relative power estimate from the VAM and gradient you get an average power of 287 W. These values are surprisingly almost perfectly identical! This means that I can most probably trust the TSS based method, and use it for complete rides, while the VAM and gradient based method only works on climb sections. This is quite nice! Of course one measurement is not a measurement, so I wanted to check this on other climbs as well. Unluckily I don’t have to many climbs (as Flanders is pretty flat), but I still managed to put together a sample of 18 climbs from this year, mostly from my rides on La Palma in may, and some others from later (so there is a chance that my FTP was not the same at the time of the different rides, but I still calculated with the same value, while for my total weight – with equipment included – I could make small changes based on me having a backpack with 2 extra liters of water or not). The sample has climbs from short explosive hills to the long ascents of La Palma, steep climbs and not so steep climbs, climbs where I was really fit and well recovered, and also climbs where I was tired, to see what is the effect of these on the relation. So all these climbs are displayed on the plot below (the size of the circles is related to the length of the climb, while the colour resembles the steepness).

With a perfect 1:1 relation between the two different power estimates we expect the climbs to fall on the x=y linear (which is the grey dashed line here). The correlation is well visible, with of corse some noise, but the trend seems to be pretty clear. The biggest outlier is the Smeysberg on the top right, which is a very short (430 meter) but very steep (an average of 9.8%) climb, and the reason why it is an outlier is that it was a sprint effort well above threshold, but starting with a very low heart rate, so it took some time till my HR got up into the regime which really corresponds to the level of my power output, and this time was in the order of the full length of the effort, so of course the TSS based metric is lower. For such sprint efforts the heart rate based estimated TSS will be always lower than the power based, because 1) the already mentioned lag of HR behind the sudden raise of power output, 2) that much above FTP the HR will not get higher, it does not matter if you maintain 400 W or 600 W for 30 seconds, your HR will be probably stuck at you maximum HR value. But these problems only arise when you do very short above threshold sprints. This is also why one of the small blue dots is also a clear outlier. Still, in the region where most of my training rides are (~220 W to 300 W) the match is almost perfect. Fitting a linear [y = f(x) = mx + b] to all the climbs (solid grey line) or only climbs which were longer than 3 km (a.k.a. efforts where there was a significant heart rate lag were dropped, thick black line) gives the following equations:

a) m = 1.41±0.16, b = -99±41, but we don’t really care about this
b) m = 1.00±0.12, b = 0±31, which is a perfect 1:1 match (with some noise of course)!

The other problem with HR based power estimates, that your heart rate at, e.g., 250 W will not be the same for two workouts which were ridden in different conditions, as for example dehydration and the level of residual fatigue strongly affects the heart rate. So again, these can significantly change the resulting estimated power. Like in case of the medium sized light blue circle slightly above the 1:1 line in the bottom left – this was a very slow paced ride (I was not alone), but I was extremely fit (after more than 1000 km ridden already in the same month, but basically no hard workouts in the previous one week), so probably my heart rate zones were a bit shifted. On the other hand, the two other climbs where the difference between the two values is larger than 5% (the small blue circle and the larger dark blue circle slightly below the 1:1 line towards the bottom left) were the last climbs of my two hardest days on La Palma, so at those ascents I was already very tired, which led to the shift of my HR zones – but now to the other direction. (At least this is my explanation.) Furthermore, small ascending sections can effect the estimate from overall VAM and slope gradient, and to convert relative power to power you need to know your total weight with bike, clothes, and everything included. Taking all these factors into account it is easy to understand why there is a scatter around the 1:1 relation.

To see what happens when you go to lower power – so the region of true recovery workouts – I have modified the script to be able to handle TCX files which do not contain GPS position information (so files which contain indoor trainer workouts). I have only three rides where I maintained a constant power instead of doing intervals (where the heart rate based method is clearly off, but we know that already), but in case of these, I can compare the ‘real’ average power (from the Tacx Flow) to the estimate. So for these three rides, the real average power values were 156 W, 140 W, and 200 W, while the estimates for the same rides are 133 W, 136W, and 220 W (assuming an FTP of 290 W as these were done very early in the season). The difference between the measurements and the estimates is in the order of ~10% (of the trainer values), which is OK for an estimate.

Conclusions: we can say that indeed the TSS based method can be used to estimate the average power (and workload) of workouts (even from HR data) if they do not consist of (only) short sprint efforts (so sections where there is a significant lag in the change of heart rate compared to the power output), as it scales well with another widely used power estimation method, and as it is consistent with wattage data from indoor trainer workouts (though the latter is only tested for low intensities). As a second conclusion: I really need a power meter (to test these estimates, and to have real power data, damn it)…

And oh, this was my 500th post!

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Daily commute at the ORM

I am back again on La Palma at the Observatorio del Roque de los Muchachos (ORM) – for the 4th time already. I have 11 nights of work at the Mercator Telescope, then I will fly to Tenerife to continue there with another instrument. As always, I can only say that this island is amazing. Every time I take the taxi from the airport to the observatory, I can not stop staring out the window to look at the landscape. This is the first time I am here during summer, and I have to admit that the temperature is much nicer up here at 2300 meter, than it is in e.g. October. I don’t need my winter coat anymore, and I don’t need to put a kilogram of warm clothes (knee warmers, arm warmers, neck warmer, wind coat, rain jacket, etc.) on when I roll down with the bike on the morning, a simple jacket is enough. So during the day it is typically ~20°C (but it feels much more thanks to the Sun), while on the morning it is around ~15°C. Now again I took my racing bike with me (and I will have a week of cycling after my observing run on Tenerife), so already here I use it every day to commute between the Residencia and the Mercator Telescope.

I need to ride up once before dinner to start the calibrations (~5 PM), then I roll down to eat (~7 PM), and after a small nap I ride up to catch the sunset (which is around 9 PM) and start the observing night. Then I work till the Sun rises, and go down to sleep around 7:30 AM (and sleep from 8 AM to 4-4:30 PM). The ride itself is 2.65 km @ 6.9% with a maximum over 100 meters of 10.3% (a hard 3rd category climb in Tour de France terms), so it is not extremely difficult, but riding above 2000 m makes every climb a bit more challenging (click on the climb-plot and it will be bigger). But it is very good high-altitude training, and 3 times faster than walking! (I don’t even think about driving up with a car, that’s not my thing :D)

On the last afternoon I rode a new personal best up to the telescope, reaching the ‘summit’ in 11m 09s, which corresponds to a VAM of ~1000 Vm/h (yeah, I know it is not really a pro value, but who cares :D)! My previous bests from last October and this May were 12m 05s and 11m 36s, respectively, so the improvement is very clear. Oh, and these were ridden while carrying a backpack… After this record ride, I took the evening ride a bit easier and recorded the scenery (turn the volume down, if you don’t want to listen to my still quite hard breathing…). It is a nice place to work at ;)

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Riding up to the Mont Ventoux (and more)

There are iconic climbs in road cycling, and probably the most known ones are the Col de Tourmalet, the curvy road of Alpe d’Huez, and the vindy ascent of the Mont Ventoux. These are not the most difficult climbs (like the north side of the Roque on La Palma is way more difficult – steeper and longer -, and you can find the almost exact copy – in terms of steepness and length – of Alpe d’Huez also on the island) of the World, but these are usually decisive places on the Tour de France. The yellow jersey is won on these slopes. They have a long and exciting history.

As I already mentioned in the last post, I got invited by Valery (who is now a PhD student in Gent, but who finished her Master in Astronomy during the first year of my PhD in Leuven) to join them (her boyfriend and some family members) for five days in France, where one of the days would be a climb to the Mont Ventoux. How on Earth could someone say no to such a thing? :D

We left from Limburg around six on Monday morning, and I spent most of the ride sleeping, so the almost 1000 km to our residence near Grospierres went by relatively quickly. The apartment was a bit smaller than we expected, but we had no plans to spend a lot of time inside, so we did not make a big fuzz about it. On two of the evenings, we had the buffet dinner of the resort, which was really delicious, and usually made me almost unable to move ;) There were also several pools, so the children and the non-cyclist adults also had fun on the spot.

As the weather was not the best on the first days, but the weather forecast was really promising for Thursday and Friday, we scheduled the ascent of the Mont Ventoux for the second part of our stay. (Side note to myself: make a lot of money – or love, as a sub side note -, and forget this economy class flying, because it starts to be a bit annoying… We are somewhere between Madrid and La Palma while I am writing these, and there is absolutely no leg-space on this plane… But back to the story…) So after the first night, I decided that it was time to try out my knee, to see what I might still free from the accident I had on Saturday. I had a 47 km ride alone into the nearby gorge (which was really amazing, as at one point, the river flows below a magnificent arch of rock which connects the two sides of the valley), with an average speed of 33.4 km/h and basically no pain in my knee, so I was quite convinced that I won’t have any problems with it later that week (as such average would have been really good even on my flat Leuven – Mechelen – Leuven training route). Almost immediately after arriving back to the apartment, I went for another ride with Jurgen. It was a much more calm ride of 74 km to a relatively nearby bike store, where he could get the specific bike parts he needed, and I could buy a new rain (and wind) jacket, as my old one was torn in the accident (and that was not even windproof). Speaking of the jacket I made a very good purchase, because it was not only relatively cheep, but I made use of it immediately, as on the return leg we got quite some rain starting at the exact moment when we left the store ;) 10 km from home we caught Jurgen’s father, who was riding all the way from Belgium! On Wednesday Jurgen wanted to rest, so I went on a ride with his father. It was 68 km with an elevation gain of a bit more than 1000 meters (through a beautiful pine forest, with rocks and flowers on the ground level), but with low intensity climbing, as neither of us wanted to use too much energy before the big day. The roads (even the smalles ones) in this part of France are generally very good quality and quiet (especially the small mountain roads have very low amounts of traffic), so we enjoyed the ride very much despite the rain we got here and there. I hope I will be in the same shape as Jurgen’s father when I turn 67… On the descent I had the feeling that he took too much risk, as at a very curvy section I got dropped, but I preferred to take it slower especially because of the wet road (and because one accident per week is already more than enough). From the point where the road got straighter, I went back in front to lead the group (of the two of us). For the next day, we set the alarm clocks to 6:30 AM, as we wanted to do the climb before it gets too windy and hot on the afternoon.

As the holiday resort is situated a bit more than a 100 km from Bédoin (the village where the most difficult of the three ascents of the Mont Ventoux starts), we still had to spend two hours in the car before we could start the ride. After one hour the Mont Ventoux started to became visible, as a huge pyramid standing high above the vast plains between the Alps and the Massif Central. It was a majestic sight. We hopped on the bikes 20 km from Bédoin to have a proper warm-up before the hardcore part of the day. One hour later (and already ~250 meters higher) we arrived to the start line, which is literally an old line made out of stones across the road – the 0 km mark of this legendary climb (some people start 400 meters further out at the Bédoin road sign, that’s why the official distance from the Tour de France in 2009 is ‘only’ 21.1 km). We had enough time to think about the climb (at least that’s what I did) during this warm-up section, as the rocky, deserted peak stood high in front of us all the time, getting higher and higher as we approached the start… Here we discussed the strategy for the support car (as Valery and Jurgen’s mother was our support car staff for the climb, which was pretty nice), filled our bottles, prepared our replacement bottles, energy bars, and everything we might have needed later on. Then around noon, we started the climb (see photo of me crossing the start line, while starting the recording of the climb on my Garmin cycling computer – precision is very important). The data of the ascent is here, while the descent is here.

My plan was 1 hour and 40 minutes, as this was the time Tijl had when he did the climb before his PhD defense. Of course I wanted to be faster ;) He was not in his best shape back then, but now I was less then one week from a quite serious accident. I did not want to look at the time (that’s frustrating), so I had not have it displayed on the GPS, but I just wanted to give the maximum effort I could, and see the resulting time only on the top. So the only thing I had to concentrate on was to keep my heart rate around 180 BPM. That’s the maximum I can keep for such a long time, above that I start producing too much lactic acid in my muscles, which makes you tired and slow pretty quickly. As you can see it on the elevation profile (click for larger version) the ascent consists of 4 main sections.

The first 5.5-6 km is very easy, so the plan here was to go as fast as possible (ok, basically this was the plan on all sections, but still, people tend to not pedal really hard before the climb gets really serious). Then from the first switchback (and the first checkpoint with the support car – where they did not expect me that early, so they were not yet standing on the side of the road when I arrived there…) to Chalet Reynard, kilometer 7-15 through the forest is really difficult with an average gradient of 9.2% for 9 kilometers, and with kilometer 9 being 10.5%, this stretch of the route is really something to survive.

You can see it on the plot below that on such steep climbs I can not keep up my cadence in the optimal ~90 RPM zone, so on the easiest gear I have much lower cadences too. In the first section I could just keep my optimal cadence and shift gears according to the gradient, that’s why you see the nice compact distributions along the different gears other than the easiest, where the distribution is elongated towards the lower values. (My earlier posts about these plots can be found here.)

We had the second checkpoint in the middle of this section, and the last at the Chalet Reynard, where I also put my jacket in my pocket, as I knew that because the support car has to wait for the last one of use, they will not be on the peak when I arrive there (and you don’t want to stand there in the cold wind without a jacket). The good thing was that I kept passing others and no cyclist passed me, though there was a guy with whom I went together for quite a while, and we really played the game of he dropping me and me catching him for kilometers (then on the last section he bonked, and I flew past him).

The third section comes after Chalet Reynard and lasts till the last 1.5 km, with gradients below 8%, and with a kilometer of only 5.8% around 1500 meters above sea level. Here it started to be a bit colder and the wind got stronger because at this point the road leaves the forests and continues through the rocky deserted yellowish grey landscape of the Ventoux. Also, the tower on the top stays visible till the end of the climb from this point. These kilometers – especially after the steep road of the forest – seemed to be really easy, so I had the feeling of going pretty well. Then the last 1.5 kilometer is again 9.6% and the steepest 100 meter section comes also here with a shocking 14.0%…

There were three points where photographers took pictures of basically every cyclists, and then gave you their business cards (with the time and date, or even a specific ID number printed on), so later it was possible to find the pictures, and purchase them online for a lot of money. Really, a lot. But they made really cool pictures, so I had to buy the ones above and below. (And thanks to Valery for the other pictures and the support!)

The last curve is very steep again, but then after 21.5 kilometers of climbing at an average of 7.3% (HC climb beyond any question), you arrive at the top of Provance. Which is extremely crowded… It’s like Mecca but for cyclists. I arrived on the top completely exhausted, and stopped the timer on 1:38:41, which was a bit more than 1 minute faster than the plan, so I was extremely happy. And tired. This was my fastest HC category climb till now.

On the peak it was very windy and cold, so I put on my new jacket and stood next to the building where the conditions were less harsh… At a point a guy asked if I was from Leuven, as it turned out he was the one I rode along with for a very long time on the Brabantse Pijl earlier this year. The World is a tiny little place, isn’t it!?! Then at the point where I really started to be cold the support team finally arrived (the others had a time around two and a half hours), so I could put on all my warm clothes (arm and knee warmers, etc.), before we started the descent. Now that was fun! I had an average speed of 50 km/h to Bédoin, following a Dutch car (but not in its slipstream). Then we rode back to where we started that morning. None of us had problems with sleeping that night ;)

On the last day we went for a shorter and only slightly hilly ride of 48 km. There was very strong (~40 km/h base with gusts up to who knows what) headwind for the last kilometers, but with my last energy reserves, I led the three of us home with ~30 km/h, which was quite well apreciated by Jurgen’s father. Then on Saturday we drove home, and luckily all the traffic jams were in the other direction, towards Marseille and the sea. With all this biking, July became my best month with 1256 km on the racing bike (so the cruising around Antwerpen with Elise on a Dutch bike on the last Sunday is not included :D). It was almost 400 km more than the previous best, and it was third af all the road cycling I had last year. It was a very nice month :)

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