Emerald Hills Go-To Ride

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What is a Go-To Ride? Let me begin by apologizing for the name, it really should be Go-To Route, but I have already used the term Go-To Ride so often I don’t feel like I can change it now. But a Go-To Ride is, in fact, a route (or at least usually, see below.) Collections of good routes for cycling are very common, almost every bike club has one. One that was particularly useful to me when I moved to California was that of the Stanford University Bicycle Club. Often such routes include variations signaled with phrases like “If you want to extend this ride…” A Go-To ride is all of that but what distinguishes it is that it is a ride I do over and over again. My familiarity with such a route allows me to do a ride without having to think about where to go, a real advantage when my enthusiasm is low. I find that the variations of a Go-To Ride add some flexibility without significantly diminishing the advantage of not having to think too much about where I am going. However, there is one situation where I do try to minimize such variation, and that is when I use my speed on such a ride to assess my Form (my ability to ride long and/or fast.) Because I repeat my Go-To Rides so often, they are natural candidates for such a test, but only when ridden on the exact same route. Thus, for some of my Go-To rides I have one or more variations which I flag as “canonical” and it is those I use to assess my Form.

Although I did not use the term Go-To Ride back in Texas, I certainly had such routes. The ride which I have repeated most often by far was there. It was the Rice University Bicycle Track ride. Typically that ride would consist of two miles from my home to the track, 35 times (more or less) around that third of a mile track, and then two miles back home. I repeated that ride almost 600 times. (That works out to about 20,000 times around the track.) Now that was a Go-To Ride! When I moved to California in 2017 I missed those rides and coined the term Go-To Ride to help define what I needed to do to settle-in here.

To a large extent, Go-To Ride is a self-defining categorization - my Go-To rides are the ones I end up repeating over and over again independent of my expectations when I proposed them. In a post from a few years ago I said the following: “In my second post from California, I described my Go To ride, … the Alpine Ride. Since then, I have developed other Go-To rides which I can do depending on my training needs and mood.” Although the title of that post, “Go To Sprint” referred to one ride I named The Tamarack Sprint, the post also discussed another which I named The Neighborhood Ride. Interestingly, the first failed the “self-defining” criterion in that I only ever rode it six times, whereas the second, mentioned as an afterthought, ended up being the most frequent ride I did during the three years I lived in San Carlos. Here are the routes I rode most often while living in San Carlos:

Ride Name	Number of Rides
Neighborhood	250
Alpine	140
Alpine Cañada	30
Peninsula Bikeway	40
Tamarack Sprint	6

When I moved from San Carlos to Emerald Hills, I blogged, somewhat tongue in cheek, “My Go-To Rides Must Die!.”  What was not tongue in cheek was that my move meant a significant change in the rides that I did. Here are the most common rides I have done in the year and a half I have lived in Emerald Hills:

Ride Name	Number of Rides
Trainer	70
New Alpine	30
New Alpine Cañada	30
Emerald Hills	30
Lake Loop	15
Huddart	10

New Alpine and New Alpine Cañada are almost the same routes as the similarly named rides from San Carlos except that they are about a mile shorter and have about 100 feet less of climbing relative to the old routes because I no longer have to ride to the start of the route; I now live on the route. At the time I announced my need for new Go-To rides, I blogged “The move provided new opportunities for go-to rides. Shortly after the move, I went on a ride with my son (another advantage to living closer) and he showed me one of his go-to rides, a beautiful if hilly hour long ride that has now become a ride I do weekly.” That ride I named The Huddart Ride (because it went to Huddart Park) and although I did ride it 10 times, it turned out to be too hilly to ride every week. Lake Loop is a route/Go-To Ride I have already blogged about,  though perhaps I should say failed Go-To ride because I did not end up riding that route as much as I had expected. The problem was that it was not actually an easy ride. At the time, I described it as follows: “If I use the lowest gear on my Volpe and deliberately keep my pace as slow as I can, the ride home, while not effortless, is not too bad.” Not too bad, perhaps, but not easy enough as it turned out. The surprise winner of this schedule is not a route at all. Because I was unable to find a route that qualified as an easy, recovery ride, I set a trainer up in my bedroom for that purpose, so “Trainer” has become my most commonly repeated Go-To ride. Way back when I lived in Houston, Texas, I blogged about purchasing that trainer. My initial review of that trainer was not positive. I had no complaints about the trainer itself but because riding it was hot and boring, it failed to fulfill the role I had planned for it and for the first few years I only rode it only a handful of times. That changed a bit when my wife became ill. I dared not leave her alone to go for a bike ride but was able to maintain a bit of fitness with the trainer. However, it was only upon moving to Emerald Hills it really came into its own. The problems of boredom and overheating are less when it is used only in the context of providing an easy, recovery ride. 

That brings me, at long last, to the Emerald Hills ride, shown at the top of the post. I mentioned this ride in my last post. I described how, to accommodate my new all-carbon eBike,  “I developed a Go-To ride that stayed within walking distance of my home” mostly in case I got a puncture, something which, at the time, I was unprepared to fix on that bike. So that seems like an unpromising start to a Go-To ride. Now that I am comfortable repairing such a puncture, why would I continue with this ride? Because it is the prettiest of any route I have ridden. What started out as a route forced on me by my ignorance has become one of my favorites, but one I can only ride on my eBike; it is too hilly for me to complete routinely on any of my other bikes. Even with the assistance of the eBike, it is a fairly Intense ride, more Intense than my (New) Alpine ride, having the same amount of climbing in half the distance, with many of the climbs significantly steeper than anything on the Alpine ride. It is shorter than the Alpine ride, typically taking me about 65 minutes to complete compared to 110 minutes for the Alpine ride. All that said, it fills a similar role, what I call a Pace Ride, a general training ride, neither too easy nor too hard.

What makes the Emerald Hills route so pretty? I could just show pictures but frankly, I am not that good of a photographer of scenery (few people are) and my pictures would not do it justice, so words will have to do. Much of the beauty of this ride is a direct result of it being so hilly. Around almost every corner (and with the winding roads in my neighborhood, there are a lot of corners) there is a great view. One view so common it might be underappreciated is that looking east. From the relatively lower elevations at the beginning of this ride, Silicon Valley looks almost like a forest. From higher elevations, a view in that same direction becomes one of San Francisco Bay and the mountains of the East Bay, including Mount Diablo and Mount Hamilton. A landmark, nothing special compared to the Seven Wonders of the World but quite charming in the context of our little neighborhood, is the Easter Cross, a massive structure at the top of a hill. I see it twice, once from farther away and then again when I reach the highest point on the ride. As I continue, I reach the top of the ridge and now, rather than looking east, I am looking west, out over Portola Valley where, depending on which corner I am rounding, I see the beautiful valley itself, the local cyclists training on Cañada Road far down below, or Crystal Springs Reservoir. I go right by our neighborhood’s local winery, Clos de la Tech, whose ambition it is to use our hills to make the finest Pinot Noir in the world. Finally, I get a peek at the business side of the climbing rock of Handley Rock Park.

One additional advantage of this ride is its flexibility. There are plenty of opportunities to shorten the ride or reduce its hilliness on a day I find myself more tired than expected. One additional point: notice that right in the middle of the loop that makes up my route is Emerald Lake, the location of my Lake Loop Ride. Thus, the Emerald Hills ride might be thought of as the Lake Loop Ride on steroids. Finally, this for the pedantic: besides Emerald Hills this ride visits the cities of Redwood City and Woodside as well. All in all, despite its unpromising origins, the Emerald Hills ride has become one of my favorites.

My First eBike: an Orbea Gain

My new Orbea Gain, right off the truck, with no pedals and the seat too high. This post is by no means a review of the Orbea Gain. For reasons which may become apparent, I am in no position to provide that. Rather, this post is a description of my personal journey through a most unusual bicycle acquisition experience. 

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About ten months ago my son Michael decided I needed an eBike. Why, and why just then? From time to time Michael becomes aware of my mortality. (This is not a newsflash about my health, it's just that the Bible promises us 70 years and I am 72.) According to Michael, this was one of those times. His reasoning was as follows:

• I had just moved to Emerald Hills and because of those hills, was finding it hard to do easy rides.
• It would allow us to ride together, my electric assist making up for his younger age.
• It might be fun for me to try some modern, high end bicycle technology.
• Given my age, I did not have an unlimited number of years of riding ahead of me so if I was going to do this, I might as well do it now to make the most of those years.

Because of the pandemic and associated supply chain issues, bicycles were (and are) hard to come by. Michael had gotten on the Internet and found what he thought was the perfect bike for me, available for immediate delivery, an Orbea Gain. Because of the bike shortage, he didn’t want me to miss this opportunity so was eager for me to follow up quickly, much more quickly than I found comfortable. I trust both of my sons very much so despite my deep concerns about buying a bike online rather than from a store and my feeling that I had not had time to think about what kind of bike I wanted, I closed my eyes and pressed the “Buy” button. A few days later, the bike arrived at my door.

What kind of bike is an Orbea Gain? It is an eBike built on the platform of a high end, thoroughly modern gravel bike. I am partial to bicycles manufactured by Bianchi, a fact Michael knows, but Bianchi’s eBike offering, their Aria, is built off the platform of a road bike and thus Michael felt that as a result it was not as appropriate a bike for me as the Orbea. Compared to the Aria, the Gain has a more relaxed geometry, wider tires, and lower gears (50x34 in front and 11x32 in back.)

What do I mean when I say the Orbea is high end and thoroughly modern? Pretty much everything on the Orbea that can be, is made of carbon fiber. It has Shimano Ultegra electronic derailleurs. It has Shimano hydraulic disk brakes. All the cables and wires run inside the frame to minimize wind drag and to optimize appearance. It does not go out of its way to advertise that it is an eBike; the battery is hidden inside of a rather normal looking downtube and the motor is in the rear hub. Anyone knowledgeable who looks at it will be able to see it for what it is, but it does have the general appearance of a normal bike. As for the electric side of things, it has no throttle, it only provides pedal assist. If I don’t push, it doesn’t help. It has three levels of assist plus a fourth no-assist setting. This was by far the most expensive  bike I have ever purchased; inflation doesn't even begin to offset that.

How was it, buying a bike on the Internet? The vendor, Contender Bicycles, Inc., was terrific. They seemed to be surprised to get such a large order out of the blue and called to thank me for it and to assure me I could contact them any time for help, an offer on which I have taken them up. They suggested that I take advantage of a shipper they used that does nothing but transport bicycles, which I did. It meant I got the bike a few days later than I would have but guaranteed my new bike would be handled with the care it deserved. The truck arrived and when the driver opened the back, I could see that all the bikes were held in bike-specific racks. He carefully removed my bike, reattached the front wheel, and that was that.

My first reaction to this amazing new bike was overwhelming fear that I would do something to damage it. My new Orbea came with no paper manuals and the manuals I found online were insufficient in my view, at least to a modern carbon fiber novice like me. I called Contender and they confirmed that what I found was all that was available but again reassured me they would be there to help. One thing that the online manuals did tell me was the torque required for every nut and bolt on the bike, so I ordered a torque wrench set from Amazon. I had to call Contender to find out how to raise and lower the saddle. They warned me about the pitfalls I should watch out for when I did that; the invisible bolt that held the saddle, if loosened too much, could fall into the seat tube, creating an adventure that the kind folks at Contender assured me I did not want. It turns out that, because the frame is carbon, I cannot put this bike on the bike rack on my car, a rack that supports a bike by the frame’s top tube, nor can I put it on my repair stand; both the top tube and the seatpost where the stand would attach are carbon. Someone on the Internet suggested getting an aluminum seatpost to swap in just to work on the bike. Contender warned me not to do that, so no repair stand for me. Even absent a repair stand, I did get the seat height adjusted without incident and put some old, low-end SPD pedals on the bike so I could go for a test ride.

The first thing I noticed was that the front disk brake rubbed. I got on the Internet and figured out how to adjust it. This reduced but did not eliminate the rubbing; it still rubs for a few minutes after I apply the front brake or after I lean too hard into a turn, but that was the best I could do. (The back brake, by comparison, has never rubbed.) On the other hand, the brakes are AWESOME! I have never felt so in control on the steep, narrow, windy roads of my neighborhood. Could I now do an easy ride starting at my house? Sadly, no. The algorithm in the power assist requires I work before it will help. Also, even at the highest assist level, it took all of my strength and all of the eAssist to make it up the steepest hill in my neighborhood, a short (0.1 mile) hill that Strava assures me has an average grade of 23%. On the other hand, I did make it up that hill in the end so having this bike means I can ride anywhere I want in my neighborhood without checking that the grades are not too steep. Still, my fear that I was going to damage this bike and my ignorance about how to do basic roadside maintenance on it were causing me to ride it less often than I might have. One silly issue was ‘what if I got a puncture?’ I knew this bike was tubeless-ready, but was it tubeless or did it have tubes? The rims were carbon. Could I use my usual tire irons and techniques to change a punctured tube? In response, I decided to avoid straying too far so that I could walk the bike home if necessary. Finally, my one complaint with Contender is that they had mounted the front tire incorrectly such that it went ‘bump bump bump’ when I rode, tolerable on the rough roads in my neighborhood but annoying the two times I took it out on my smoother New Alpine ride.

At this point, Michael and I were getting a little discouraged. Was this bike a mistake, a bike I wouldn’t ride much? I really didn’t want that to happen so I developed a Go-To ride that stayed within walking distance of my home. By riding my new bike mostly for that ride I was able to use it on a fairly regular basis. I kept thinking that I ought to just take the bike to Gebhart at my LBS and pay him to help me with it, but I felt bad I had not purchased it from him so held back until the day the rear disk brakes started making a funny noise; I worried that if I ignored that I might damage the bike. By this point, my favorite bike, my Bianchi Volpe, was so badly in need of maintenance I could no longer ride it. Finally, for a variety of reasons Gebhart had been sitting on my Bianchi Specialissima for almost two years and I wanted to nudge him about that. All of these issues together pushed me over the edge and I gave him a call. “I’d love to see your Orbea!” he said. “Bring it in.” After much work, he got the front tire reseated, no more ‘bump bump bump.’ He straightened the disk for the front disk brake. When I got the bike home, that made no difference, the amount of rubbing was the same but at least I knew it was not something stupid I had done. He said the rear brake was fine, but put a bit of lubricant on the disk to take the noise away. The lubricant accomplished that but it also reduced its stopping power. However, by the end of the first ride the lubricant was gone, the brakes worked as well as before, and the funny noise was back, but again his reassurances meant I could ignore it. Finally, he assured me I had tubes and that my existing tube changing tools and techniques would work fine. Besides reseating the front tire, Gabhart had mostly just provided reassurance but that made all the difference. He sold me a water bottle cage that looked nice on this fancy new bike, I attached my pump to the second water bottle mounts, put the seat bag with my tools and spare tube under the seat, and I now have a bike as serviceable as any I own. Gebhart also ordered me some Ultegra SPD pedals that will be more suitable for this bike. (Since then, he has also overhauled my Volpe and he is making slow but sure progress on the Specialissima.)

In many respects (cost, technology, the electric power assist) my Orbea Gain is unique among my bikes, but in other ways, it fits right in. Since acquiring the Orbea, I have ridden it 37 times (28% of my rides) for a total of just over 400 miles. Two of those rides were over my New Alpine route which allowed me to compare it to most of my other bikes. Even from my new home, this is a route I can manage on a fair number of my bikes including my 1960 Bianchi Specialissima, my 2010 Surly Cross Check, my 2007 Bianchi Volpe, and my reborn 1967 Hetchins, so when I rode it on the Orbea, I did it with the power assist turned off. With the power assist on, low gears are less important but the Orbea does have a fairly low bottom gear of 29”, almost identical to my Surly at 28” but not as low as the Volpe at 22”. By comparison, the Specialissima and the Hetchins have low gears of 46” and 44” respectively, unimpressive low gears which are nonetheless adequate for the New Alpine route. Presumably the gravel bike from which the Gain is derived is quite light, but once you add a battery and motor, the Gain itself comes in at a hefty 29 pounds, only exceeded by the Surly at 30 pounds. The lightweights are the Specialissima and Hetchins at 24 and 25 pounds respectively leaving the Volpe in the middle at 27 pounds. (Given how overweight I am, the weight of the bike is probably pretty unimportant.) Is there something magic about the Orbea that, despite its weight, would make it especially fast? It would seem not, its speed on the two New Alpine rides was comparable to rides on the Volpe or Cross Check ridden a few days before or after.

I have already confessed that as wonderful as my new Orbea Gain is, it did not give me the easy ride for which I have been yearning*. In compensation, it opened up a new Go-To ride for me, one with some unique advantages (which I will discuss in a future post). It also allows me to keep up with my son Michael, either when it is just him on his non-electric road bike or when he is on his cargo eBike with his two kids. Finally, the Orbea has allowed me to try out the latest bicycle technology. The most important difference between my Orbea and the rest of my bikes is the electric assist feature which is absolutely game changing, but here I want to consider its other modern features. I have already commented on the hydraulic disk brakes, one of my favorite features of this bike. The electronic shifting is impressive indeed! It is stunning to shift the gears and hear the derailleurs adjust themselves to a perfect position. One thing I find slightly annoying about the index shifting on my Surly and my Volpe are that I cannot ‘tune’ the shifting like I can on my Specialissima and my Hetchins and so occasionally, in some gears, the derailleurs are positioned slightly suboptimally. The Orbea provides the best of both, the convenience of indexed shifting while providing an automated tuning to optimize derailleur position. As impressive as I find this, I have to say it is not game changing; neither the index shifting of my Volpe and Surly nor the manual shifting of my Hetchins and Specialissima bother me all that much. While it is true that the Orbea most definitely has the best shifting of all my bikes, it’s just that it does not make all that big a difference to me. There is something absurd about this bike in that it is constructed largely of lightweight carbon fiber, an advantage that is more than offset by its battery and motor. I can’t say that I find the ride experience of carbon all that different from the rest of my bikes, all of which have steel frames. The difference in ride quality between my Surly (which I like less) and my Volpe (which I like more) is vastly greater than any difference I feel with the Orbea. Finally, I want to talk about one component on this bike that surprised me the most: the saddle. I am a huge fan of old school Brooks leather saddles which I have on my Volpe, Hetchins, and Specialissima. By comparison, the more modern plastic saddle that came with my Surly is barely tolerable (though it is better than any other plastic saddle I had tried up until now.) Thus, I wondered what I was going to do about the plastic Fizik Aliante R5 saddle that came with the Orbea. The good news was that, because the Orbea is a gravel bike, the saddle was not as terrifyingly narrow as those found on most modern road bikes, but a Brooks it was not. Putting a Brooks on this bike didn’t seem like an option. Brooks saddles require long offset seatposts which are not compatible with the Orbea. I was thinking about some more modern leather saddles that do not require a special seatpost but figured I’d first give the Fizik a try. It felt hard compared to my Brooks saddles, but when I took the bike out on the longer New Alpine ride, I found that although this saddle felt a little less cushy at first, it didn’t become less comfortable with time the way the Surly saddle did; it was fine. Now that I am more comfortable taking the Orbea out on the road, I am eager to try this saddle on some even longer rides. In summary, although this clearly was not my most cost effective bicycle purchase, I am glad I have it and for me it was definitely worth the money.

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* As I will detail in a future post, I ended up solving the ‘easy ride’ problem by setting up my trainer to be used for such rides.

Modelling Fitness, Fatigue, & Form

Using Banister’s model^ to predict how Fitness, Fatigue and Form will change over time. To generate the above graph, a training schedule was defined consisting of a ride generating a Load of 1 (in arbitrary units) to be ridden for 200 days and then training is stopped. At first, Fatigue dominates Fitness and Form (the ability to perform on a ride) falls. Then, Fitness dominates Fatigue and Form increases. When training stops, because Fatigue decreases faster than Fitness, Form increases. This is the reason that the taper period right before an event is so common in training plans.

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In my last post I wondered if I had been training too hard. One way to avoid that would be for me to monitor my training load (hereafter Load) to see if it is increasing, decreasing, or staying the same. If treated with full rigor, measuring that Load would be an impossibly complex task, so we all find simplifications for estimating Load that are better than nothing, or over time, better than we were doing before. I have, in fact, gone the other way, partially out of necessity (the hills where I live make it harder to ride at a fixed intensity or to estimate the overall intensity of a ride) and partly out of an attempt to simplify my life (when my heart meter broke, I didn’t bother to replace it.) Now and again, however, I regret that and wonder if it would be worth the effort to better track my rides. At present, the only way I am estimating my Load is to record the minutes of duration of each ride. Even that is better than nothing, but when I wonder if the increasing hilliness of my new neighborhood is throwing off my estimates it makes me want to do more. The first step in doing more would be to acquire a power meter or a heart rate monitor. That device, along with some basic software would allow me to characterize a ride in terms of minutes in Zone 1, minutes in Zone 2, etc which is better than just total minutes. If I had been doing that over the last couple of years and had noticed that my total minutes of riding stayed the same after I moved but that the zone distribution moved to more time in higher zones, that would already tell me I had increased my Load. To make that quantitative rather than qualitative, I would need to estimate the relative Load produced by different zones, something I have blogged about a fair bit and thus feel like I know how to do. The purpose of this post is to discuss the next step after that, to model the competing impacts of my training load on Fitness and Fatigue and how they play out over Time.

The inspiration for this post came while I was preparing my post on Sweet Spot Training. I was listening to a podcast by Frank Overton, the person who coined the term Sweet Spot, and he talked about how motivating it was to use modelling software to track the accumulation of fitness resulting from his training. I am very motivated by tracking my training and I found the prospect of incorporating this new kind of tracking very tempting. In order to figure out how I might do that I began exploring the training models that are used to do so, and thus today’s post.

The reason training increases performance (Form) is because the Fatigue generated by training goes away faster than the Fitness generated by that same training. That is the basis of the training models I will be talking about. It is more complicated than that; there are different kinds of Fatigue and different stages in the recovery from Fatigue and the Fitness generated by training doesn’t appear immediately but only over time, thus the truism that you don’t get stronger during training but during the rest after training. The models I will be talking about simplify things by ignoring some of that complexity.

I am aware of two models for estimating Fatigue, Fitness, and Form, the model developed by Dr. Andy Coggan (available as part of the widely used Training Peaks commercial software package) and that developed by Dr. Eric Banister^. Both of these models do two things. First, they estimate the Load generated by a ride based on how much Time during that ride the athlete spends at different power output levels or heart rates (respectively) and then assigns to each of those an Intensity score. Higher power or heart rate corresponds to higher Intensity but not necessarily in a linear  way; a doubling of power or heart rate can result in a much greater than doubling of Intensity. Because I have blogged about the calculation of Intensity a lot, I won’t discuss it in this post. Rather, I will assume that given a power output level or heart rate an Intensity can be calculated. As just one example of how to do that, I offer the following equation* for calculating the Intensity of some of my rides from the Heart Rate (HR) measured on those rides:

Intensity = .000428 x e^{(.0656 x HR)}.

Load corresponds pretty directly to how tired the athlete is after a ride. If an athlete knows the  Intensity of a ride, converting that to Load is straightforward:

Load = Intensity x Time

For a ride at constant Intensity, it really is that simple. For a realistic ride during which Intensity varies, it is still pretty simple but there are a couple of different ways of making this calculation. The good news is that they all give pretty similar results, it is mostly about which is the most convenient. For example, back when I was tracking my rides with a Garmin heart rate monitor, a Garmin bike computer, and Garmin software, I could have taken the amount of time spent in each heart rate training zone provided by that software, use an average Intensity for each zone, and sum up the five Intensity x Time values to get a total Load for the ride. But how does Load relate to Form, Fitness, and Fatigue? Both Fitness and Fatigue result from the accumulation of Load over many days of training on the one hand and the reduction of both Fitness and Fatigue that occurs during the time after that training. In other words, Load pushes both Fitness and Fatigue up, Time pulls both Fitness and Fatigue down. Expressed as equations, the effects of Load and Time are:

Fitness = ( Fx(Load on Day 1, Time since Day 1) + Fx(Load  on Day 2, Time since Day 2) + … +
      Fx(Load on Day N, Time since Day N) )

Fatigue = ( Fy(Load on Day 1, Time since Day 1) + Fy(Load  on Day 2, Time since Day 2) + … +
      Fy(Load on Day N, Time since Day N) )

...where Fx() and Fy() are functions that reduce the impacts of Load on Fitness and Fatigue for older rides; that epic ride I did ten years ago isn’t doing me much good anymore. Fx() is slower than Fy() such that an athlete loses Fatigue faster than they lose Fitness. As a result, training eventually produces a net increase in performance.

Finally, the following equation is used to model expected performance (Form):

Form = Fitness - Fatigue

Note that Intensity, Load, Fatigue, Fitness, and Form have no natural units. However, due to the above equation, the units for Form, Fitness, and Fatigue all need to be the same. What is commonly done is to first assign some constant to relate Load to Fitness and Fatigue. In the Coggan model, one unit of Load is defined as producing one unit of both Fatigue and Fitness. In the Banister model, one unit of Load produces one unit of Fitness, but two units of Fatigue. In both models, one unit of Form, Fitness and Fatigue are defined to be equal.

The interesting part of both models is how Fitness and Fatigue decrease over time, the functions Fx(Load, Time) and Fy(Load, Time) in the above equations. I confess that I do not understand the Coggan model. Using equations available on the Web, I get nonsensical outputs. Thus, from here on out, I will focus on the Banister model. In this model, both Fitness and Fatigue decrease exponentially with Time as per this equation:

Fitness = M1 x Load x Time x e^{(-Time / T1)}

Fatigue = M2 x Load x Time x e^{(-Time / T2)}

...where:

M1 is the relative iMpact of a given Load on Fitness. By default, this is set to 1.

M2 is the relative iMpact of a given Load on Fatigue. By default, this is set to 2; the initial impact of a ride on Fatigue is assumed to be twice that on Fitness.

T1 is the Time in days it takes for the impact of a ride on Fitness to decrease to 37% of its initial impact. By default, this is set to 45 days.

T2 is the Time in days it takes for the impact of a ride on Fatigue to decrease to 37% of its initial impact. By default, this is set to 15 days.

Time is the time in days since the ride.

Let’s see what this model predicts for some hypothetical scenarios. The figure at the top of this post describes a very unrealistic scenario the point of which is to illustrate the main features of the model. In this scenario, a ride with a Load set to an (arbitrary) value of 1 is done every day for 200 days and then training  is stopped. The Banister Model correctly reproduces the premise behind periodized training: training increases both Fitness and Fatigue, and at first, performance (Form) decreases due to Fatigue, but over time, the Fitness dominates and Form increases. If training stops, at first Form increases because Fatigue is lost faster than Fitness. This is the rationalization for tapering (reducing training) before an event. So far, the model seems good, but let’s apply it to some more realistic scenarios. I have selected the training plans offered by Coach John Hughes to prepare for a first 200 kilometer long ride and then to allow repeating that ride every month. I have modified these plans to scale them down for a 100 kilometer (Metric Century) ride.

I have added a fourth curve to the above graph, one showing the Load generated by the training plan. The three biggest peaks on the graph are the three long training rides, each increasingly longer, used to get ready for the Metric Century. The graph stops the day before that event. We can see that each of the long rides produces a peak of both Fitness and Fatigue but because the increase in Fatigue is greater, Form decreases in the days after that hard ride. However, it increases thereafter because Fatigue goes away faster than Fitness. Training tapers (decreases) just before the Metric Century and we see that Fitness levels off but that Fatigue falls and as a result the all-important Form continues to increase, reaching a maximum just before the event. This is exactly what is expected for a well designed training plan, and again, the model seems to capture it fairly accurately.

The final curve is for the scenario I so laboriously derived on this blog some time ago, a training plan to maintain the Form to be able to ride a Metric Century every month:

In this graph I added trendlines in order to emphasize that this is a maintenance schedule designed to keep Form relatively constant between the monthly Metric Centuries, those Metric Centuries being not only the goal of but also a critical part of the training plan. I plotted three monthly cycles, starting the day after a Metric Century and ending two days after the third Metric Century. Once again, the model seems to reconstruct the intent of the training program fairly accurately.

In summary, the Banister model (at least) seems pretty good. Of course, it does not do everything. For one thing, it allows you to input training schedules that no sane person would design and that nobody but Superman could follow. There is no limit on the amount of Load that can be completed, the amount Fatigue that can be tolerated, nor the amount of Fitness that will theoretically result from such a suicide schedule. Similarly, it does not model the notion of working up to a goal, like the 20% biweekly increases in mileage I use to work up to a Metric Century. According to this model, an athlete can just jump right into the longest training ride, repeating that until enough fitness has been built up. I see these as reasonable and expected limits as to what the model was designed to do. I think what Banister had in mind when he created the model is that it is up to the coach to plan a good training schedule and that the model is just one more tool to be used judiciously by the coach in service to that effort. Finally, I assume that part of a coach using this model would be adjusting the parameters to fit the individual athlete.

I would like to mention one additional limitation of this model, a limitation that impacts this whole way of thinking about training. This limitation is that the model defines Fitness as a single thing when it is obvious that it is not. The world of road racing provides a clear example of this. Road racers can be classified as climbers, sprinters, time trialists, etc., each needing to build a different collection of different kinds of Fitness. Coach Joe Friel in his classic book “The Cyclist’s Training Bible” describes three basic and three advanced kinds of fitness, each one needing its own training plan to be developed. These are Endurance, Force, and Speed and then Muscular Endurance, Anaerobic Endurance, and Power, respectively. And all of this is just within the narrow specialty of Road Racing. Does this negate everything above? I hope not! What I hope and believe is that the approach I am outlining here applies similarly to all these different kinds of Fitness, and that in fact they may be interchangeable. That is, a coach builds a training plan to address all the different kinds of Fitness a particular cyclist needs to meet their goals but common to them all is the tradeoff between Fitness (of any kind) and Fatigue described by me in this post and modelled by Banister.

I would like to end by explaining how I imagine this tool could be useful. Although it is far from clear I will ever do this myself, I will nonetheless use myself as an example to explain how I think this might work. Right now, I am only tracking ride time. This completely ignores the possibility that one 60 minute ride might be much harder (generating both more Fitness and more Fatigue) than another. If I were to purchase a heart rate monitor and/or a power meter, I could calculate the Intensity of those rides allowing me to account for such differences; I might find that one 60 minute ride generated twice the Load as another, for example. What would still be missing is the effect of Time. Have I rested long enough to recover from a hard ride? Have I rested too long so that I have lost the fitness that ride gave me? The value of Banister’s model would be to help me answer such questions. Will I ever do this? I have no idea, stay tuned.

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^ “Modeling Elite Athletic Performance” by Banister, Eric W. in “Physiological Testing of the High-Performance Athlete, Second Edition” 1982, Published by Human Kinetics Publishers (UK) Ltd. Rawdon, England. ISBN 0-87322-300-4

* I derived this equation by using Google Sheets to plot the Intensity values for Hughes TRIMP, described in my most recent post on intensity and then to fit them to an exponential function. This is the equation Google Sheets fit to the plot. 

My Recent Training

My recent training schedule showing reduced mileage. The last column labelled “ave min/wk” is my  minutes per week averaged over the last year. My heart broke when that sank below 300. Note that the last time I rode my 33 mile "New Alpine-Cañada" ride was on 6/30/2021.

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Four months ago, I posted "One change I am making, at least for the moment, is to ride a bit less in general and to relax what had been my fierce determination to ride at least 300 minutes a week and at least 4 rides a week." That decision was based on my tentative conclusion that my declining performance was due to an accumulation of fatigue, that my previous training schedule produced more load than my body could tolerate. How did that go? In short, the jury is still out, but I did learn enough that I thought it was worth an update.

Let me start by acknowledging an elephant in the room. I am a very bad patient of my medical care team, missing many office visits and diagnostic screenings. Thus, my poor performance could well be due to an illness that has not been diagnosed due to this negligence. However, I have nothing useful to say about that at this juncture, if I ever drag my negligent ass to the doctor, I will tell you what I find out. Short of that, if not an illness, what is it that is holding back my performance?

“What is holding back my performance” might be a combination of things, so the following list should not be seen as exclusive, a mixture of them might be the culprit. That said, here is my list:

1. Because of the hills where I live, I might be training harder than I think I am and thus training too hard.
2. Instead, the opposite might be true; I might be giving up too quickly and not training hard enough.
3. My performance might not actually be decreasing, or perhaps not as much as I think. What I am looking at might just  be normal variation.
4. Maybe I am just getting older.

My latest training was designed to both test and respond to possibility 1, the hypothesis that I have been training too hard. The changes I made were 1) to stop riding my longest ride, a 33 mile/160 minute ride with 1,600 feet of climbing and 2) to listen to my body and either not ride or do easier rides when my legs feel tired, even if that means failing to reach my previous goal of 300 minutes of cycling each week. I do confess that letting go of the 300 minute a week minimum for minutes per week of cycling has been both heartbreaking and discouraging but the logic for doing so is that the hills around my new home make my average ride closer to the vigorous intensity aerobic exercise of the Medical Community than to the moderate intensity I had been assuming so that what I should be shooting for, now that I am riding from my new home, is a minimum of 150 minutes a week.

Earlier, I had made a third change, not in response to this latest slump, but one which is helping me respond to it. That change is to set up my trainer in my bedroom. When I first moved into my new home I noted that finding an easy ride was difficult. My first solution was riding laps around a local recreational lake, a ride I call the Lake Loop. Although that ride is easier than some of my other rides, getting to and from there still involved some significant hills. Looking back at my training log I noted that I rode my last Lake Loop ride on December 1 of 2020 and my first Trainer ride on December 11. Thereafter, 30 minutes on my trainer (boredom prevents anything longer) has replaced 60 minutes of laps around the Lake as my easy ride. These new easy rides are much easier and thus have much less risk of contributing to overtraining.

How is my new, easier schedule working? It is probably too soon to tell, at least with any certainty, but one preliminary data point suggests that overtraining was at least a factor in my recent slump. I first noticed this slump in May of this year when I could not complete the training plan I had devised to prepare to ride the Art of Survival Metric Century. (I will comment on the wisdom of that training plan later in this post.) After taking it a bit easier during June, July, and August, my times on my benchmark Alpine-Like rides increased from below average to just above average in September. In October, an out of town trip and a cold severe enough to keep me off the bike meant I had too few Alpine-Like rides to judge, so I have no confirmation of that improvement. A warning against overinterpreting this one good month comes from the fact that I also had a good month the previous April for no reason I can fathom. Was April a statistical outlier? If so, could September be one also? It definitely could, which is why my caution in coming to a conclusion, but I did find my September results encouraging.

What should I do now?

1. Confirm that by reducing my riding I am improving my performance.
2. Continue at a reduced level of riding until my accumulated fatigue is gone.
3. Develop a schedule I can maintain from my current home.
4. Develop a schedule to prepare for metric centuries.

I have been giving some thought to item 4. Some time ago I devoted a whole post to working from a schedule given in “Distance Cycling” by John Hughes and Dan Kehlenbach to allow riding a century or 200K "every month of the year” and modifying it for a metric century a month, taking into account the rides I can actually do here in the hills of California. One step in that conversion was to increase the mileages I initially calculated to make sure I maintained 300 minutes a week of riding. Now that I am questioning that number, it may be time to reconsider those increases and similarly for the somewhat different schedule to get ready for the first metric century of the season. When I looked back on the actual preparation I had done for metric centuries in the past, it was less than I had remembered and less than the plan I had so laboriously developed, another reason for cutting back a bit on my metric century preparation schedule. Of course, if my recent problems preparing for a metric century resulted from illness or old age, then none of this will be effective. Back when I reviewed my last 40,000 miles of riding, I considered a more general version of that possibility and I asked the following question: "Will the Zombie make it to 50,000 miles, and if he does, what cycling adventures will he have enjoyed?" Stay tuned to find out.

What Is Sweet Spot Training?

This is the classic Sweet Spot diagram. It is not a presentation of experimental data but rather it is a cartoon illustrating the concept of Sweet Spot. That is, training at higher intensities provides increased benefit per minute but cannot be sustained as long. The concept (which remains to be demonstrated) is that the combination of these two results in a “Sweet Spot” of intensity where the total benefit is at a maximum. 

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Polarized Training and Sweet Spot Training are sometimes seen as competing training philosophies. Dr. Stephen Seiler coined the term ‘Polarized Training’ and Frank Overton the term ‘Sweet Spot Training’ but in both cases many others have adopted these philosophies so there is considerable variation in the actual training plans that are derived from each of them. That said, I am going to concentrate on Seiler’s and Overton’s versions of these philosophies. Back in the blog post where I described my discovery of Seiler I also mentioned that my first exposure to Seiler was my first experience getting training information from a podcast and that this medium had a number of advantages as a source of learning. So, in addition to concentrating on Seiler and Overton, I am going to rely primarily on their podcasts because these tend to be more flexible and realistic, giving me, I feel, a better sense of what these different philosophies are in the real world. I am not going to attempt to reference each point I make, rather, I am going to give a couple of general references to Overton podcasts at the end of this post^. (I have previously referenced Seiler podcasts.) Finally, there is a third name I need to mention, Dr. Andrew “Andy” Coggan. Dr. Coggan was one of the pioneers of the use of power meters in training and back around 2004 gathered together a group of athletes, coaches, and scientists to develop systems for using power meter data, a group including Overton, and it was the discussions of this group that Overton used to develop his concept of Sweet Spot Training.

The first thing we need to consider is the similar, specialized audiences for these two philosophies. What these audiences have in common is that they are bicycle racers, road racers in particular. (Later in this post I will discuss some differences in their audiences.) I realized this when I attempted to map these philosophies onto the training advice of the coach I use, Coach John Hughes. To my surprise, I couldn’t do it. What I realized is that Hughes writes mostly for participants in distance challenges, century riders and randonneurs for example. Training for these riders is much more about building endurance than speed. It is not that speed does not matter, but rather that speed is secondary to endurance and that the relevant speed is steady state speed, jumping to join a breakaway or having a sprint at the end of the ride is unlikely to be useful to the riders Hughes coaches. This results in very different training plans than those used by road racers.

So what is Sweet Spot? I have mentioned it before as an Intensity Zone used by Coach Hughes. His basic definition of intensity zones divides intensity levels into seven zones. On top of that basic system, he defines Sweet Spot as extending from the very top of his basic Zone 3 through the bottom half of his basic Zone 4. (For the remainder of this post, when I refer to an intensity zone, I am going to be using the Hughes seven zone system.) Overton defines the intensity level of Sweet Spot more broadly, as 84% to 97% Functional Threshold Power (FTP) which translates to the top half of Zone 3 and almost all of Zone 4 in the Hughes system. Coggan has an even broader definition which includes everything from the top of Zone 2 through the very top of Zone 4.

Sweet Spot is an intensity zone but it is also something more. To put this “something more” into context, both the Sweet Spot and Polarized philosophies have in common a firm commitment to periodized training. A minimal version of race-directed periodization is a Base phase during which aerobic fitness is developed followed by a Build phase during which specific racing adaptations (speed, power) are developed followed by a Taper phase in which a small amount of Fitness is sacrificed to substantially reduce Fatigue in order to maximize performance (Form) followed by the race followed by recovery. The period in this process where the difference between the Sweet Spot and Polarized philosophies is important is during the Base phase. The simplest description of the difference between Sweet Spot and Polarized training is that Polarized training recommends many hours of Zone 2 riding during the Base phase whereas the Sweet Spot philosophy recommends fewer hours of the more intense Sweet Spot intensity training during the Base phase. Both are intended to build an aerobic base and the primary argument between these philosophies is which of these intensities is better at doing that.

In a podcast, Coggan generalized this question in a way I found helpful. He opined that between somewhere in Zone 2 through the top of Zone 4, all that mattered was the product of time and intensity. That is, if Zone 4 has twice the intensity of Zone 2*, 1 hour in Zone 4 has almost exactly the same training effect as 2 hours in Zone 2. My impression (again, from podcasts) is that Seiler would disagree. To explain why, I have to talk about blood lactate levels. What makes doing so confusing is that blood lactate can be used as the basis for an intensity zone system that is very different from the Hughes seven zone system I am using in this post. For that reason, I am going to refer to these as Lactate Brackets rather than Zones.

There are three Lactate Brackets, Bracket 1, 2, and 3  corresponding to low, medium, and high levels of blood lactate and thus intensity. Zone 2 lies in the low Lactate Bracket 1 whereas Zone 4 lies in the medium Lactate Bracket 2 and thus I think Seiler would argue that there is likely to be fundamental physiological differences between them. One consequence of such differences would be that a ride in the Lactate Bracket 2 will produce much more fatigue than a ride in Lactate Bracket 1, thus limiting the amount of training that can be done. Assuming Seiler is correct, given unlimited time to train, an athlete would be able to build up much more aerobic fitness riding in Zone 2 than they could riding in Zone 4 because fatigue would limit the Zone 4 rides long before it will limit Zone 2 rides.

One confounding factor in comparing Sweet Spot and Polarized training is that there tends to be a difference in the intended audience for Polarized and Sweet Spot training. Advocates of both will argue that theirs is the best approach for almost all racers but their primary targets seem to be different subsets of racers. Seiler mostly coaches full time athletes who have almost unlimited time to train. Many of the clients of Overton are amateur athletes who have to fit their training in around a job and family responsibilities. It may well be that Sweet Spot training is better if you have a limited time to train but that Polarized training is better if you have unlimited training time. Also, we must never forget individual variation. It is possible that one athlete may reach a higher peak performance with Sweet Spot whereas another may do so with Polarized Training.

So which is better, Sweet Spot or Polarized? I am far from an expert on the training literature, but so far I have not come across a study that answers that question in a way I find convincing. In a podcast, Dr. Coggan, who is an expert on the training literature, said more or less the same thing. In the first place, it is not even clear what the question is. Is it that which provides the greatest benefit if there are no constraints (e.g. if there is no limit on training time)? Is it that which provides the greater benefit to the greater number of athletes? Is it that which might be problematic for many athletes but which, if applied to the most gifted athletes, would produce the highest level of fitness? How long should the experiment run? For a year? For multiple years? For the length of an athlete’s career? In the second place, the chances of getting the resources needed to do the right experiments are effectively zero. So unless the differences are dramatic we will probably never know the answer. 

While investigating Sweet Spot training for this post, I noticed one additional, relatively unrelated aspect of Overton’s approach to training and that is extensive use of a training load model developed by Coggan. This model is most easily available as part of the commercial “Training Peaks” software package. This specific training load model is designed to use power meter data. However, Coggan’s model was originally based on the heart rate-based model of Dr. Edward Bannister, so it should be possible to do the same kind of tracking using heart rate data. As I listened to Overton, I became very jealous of how he could use this model to track the projected impact of each ride on his Form, Fitness, and Fatigue. Was there some way I could do the same thing? If so, would I have to purchase a power meter and the Training Peaks software or could I use a less expensive heart rate monitor and publically available software? As I looked at Coggan and Bannister’s models more closely, I found parts of them with which I disagreed and/or where my age and genetic background would require different parameters than these racer-targeted models used. Could I also customize these models? Although I had originally planned that this would be the last post in this series, I am now planning on writing one more post on these models at some point. Stay tuned.

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^ https://fascatcoaching.com/blogs/training-tips/how-i-invented-sweet-spot-training
   https://fascatcoaching.com/blogs/training-tips/sweet-spot-training-with-dr-andy-coggan

* As I have previously blogged, I think the difference between Zone 4 and Zone 2 is greater than two-fold, but for the purposes of this illustration, it doesn’t matter, the principle is the same.

VO2max, Health, and Fitness

An athlete improved his VO2max by 40% after changing his distribution of training intensities. In yellow is his old (bad) distribution. In red is his new (improved) distribution.

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In the first post in this series, I made the argument that all of the most common measures of ride intensity: heart rate, power, blood lactate, oxygen consumption, even relative perceived exertion; were all different ways of measuring calories burned per hour. Perhaps one of the most direct measures of the rate of calories burned is oxygen consumption. Because oxygen is a gas, usually the best way to measure it is by volume, how many liters of oxygen are consumed per minute, a metric known as VO2 which stands for the Volume of O2, with 02 being the chemical symbol for the gaseous form of oxygen that we breathe. At rest, one consumes less oxygen and fewer calories per minute than when exercising. Of particular interest has been the maximum amount of oxygen it is possible for an athlete to consume when they are exercising as vigorously as possible. In the exercise community, this metric is named VO2max. In the scientific community, this exact same metric is sometimes referred to as VO2peak. This reflects the rigor of the scientific community, it recognizes that the value for VO2 measured can depend on how the measurement is made so that it is not really possible to know the maximum oxygen consumption but only the peak oxygen consumption measured in a particular experiment. (The MET, a metric popular in the health community, is more or less the same thing as VO2 and the equivalent of VO2max is max METs.) In the exercise community VO2max is often interpreted as “engine size”, the higher the VO2max an athlete has, the larger an “engine” they have. While it certainly is the case that an endurance athlete with a relatively low value of VO2max is unlikely to be competitive at the highest levels of their sport, it is also the case that the athlete with the highest VO2max will not necessarily win the race, other factors matter as well. In fact, more recent discussions deprecate the importance of VO2max in favor of other parameters such as threshold power, ability to quickly recover from a hard effort, etc.. In the health community, VO2max (aka VO2peak aka max METs) is often used as a stand-in for aerobic fitness; e.g. to conclude that subjects with higher VO2max live longer than those with lower VO2max.

Given the importance of VO2max, it has been a source of discouragement to the exercise community that it seemed very difficult to significantly improve VO2max by training. It seemed that every athlete was born with more or less the level of VO2max they are going to have throughout their lives. There is some variability from athlete to athlete in the trainability of VO2max . Some athletes cannot improve their VO2max at all, others can, but it is rare to find an athlete who can improve their basic VO2max by more than 15% or so. But how is this trainability determined? In my last post in this series, I mentioned the intensity of exercise traditionally used to improve various skills that an athlete might want to improve. According to the coach I used as an example, Coach John Hughes, Zone 6 of his 7 zone system is the intensity he recommends for improving VO2max. Specifically, he recommends working up to 2 to 4 repeats of 2 to 3 minutes at a heart rate greater than 105% of an athlete’s lactate threshold heart rate as a routine for improving VO2max. Thus, a typical experiment used to determine the trainability of VO2max is to measure VO2max on all subjects, have them engage in a training routine like that recommended by Coach Hughes for 6 weeks or so, and then measure it again. And this brings us to the very anecdotal, very problematic report which is the subject of this post.

Simplifaster is a company that makes exercise equipment. It stands to reason that they would prefer that athletes believe that training, in particular, training with Simplifaster’s equipment, improves performance. If it did not, why would anyone buy their equipment? Thus, a report on their website claiming that, with the right training, VO2max can be increased not just by 15% but by 40% would appear to present a conflict of interest. And yet, such a report is just what I am going to talk about. Worse yet, it describes an experiment on just one athlete, what would be called a “case study” in the medical community. Given these reservations, why am I blogging about it? It is because it is thought-provoking. Maybe we should not believe this report without confirmation, but maybe we should be inspired by it to question the conventional wisdom about the trainability of VO2max more than we have to date. The article is here.

The author of the article, Alan Couzens, is both an exercise scientist and a coach. Most of the article is a case study of one athlete he coached with the rest being some discussion about how typical this one athlete might have been. This athlete’s event was the Ironman Triathlon. His goal was to qualify for the Ironman World Championships. Qualifiers for that event typically have a VO2max of 65-70 ml/kg/min. This athlete trained by doing a lot of high intensity interval training at the intensity normally recommended for improving VO2max, and fully trained, he never exceeded a VO2max of 53 ml/kg/min. It might be argued that no further increase in VO2max was possible since he was already fully trained, but even assuming an improvement was possible by changing his exercise plan, a 15% increase, normally considered the maximum possible, would only give him a VO2max of 61, below typical qualifiers. At this point I want to be clear as to the relevant question. To the athlete, it is ‘Can I qualify for the World Championships?’ However, for the purposes of this post, the relevant question is ‘How much can this athlete improve his VO2max?’ This is a related but different question. What this coach did is exactly what most coaches would do, to replace some of this athlete's high intensity VO2max training with a large volume of relatively low intensity aerobic training and to maintain this program for three years. In year 1, his VO2max improved by 22%. In year 2, his VO2max improved by an additional 12%. In year 3, his VO2max improved by an additional 6% for a total improvement in his VO2max of 40% over three years. His final VO2max was 74.6 ml/kg/min, higher than the typical triathlon national champion, and in fact, he was able to qualify for the national championships. Finally, the author of this study noted that this athlete was not average, very few of the athletes he has coached improved their VO2max by 40%, but on average, they improved their VO2max by 24%, still significantly more than the 5-15% conventional wisdom would predict.

So, is Coach Hughes wrong about the benefit of Zone 6 training for VO2max? The author does not say that. Rather, he says that after an athlete has completed a long period of high volume/low intensity training, a small additional increase in VO2max can result from a brief period of high intensity (e.g. Zone 6) training. For the athlete who was the subject of this case study, the author suggests that the first 32% of improvement came from the large volume of low intensity training and the remaining 8% came from the small volume of high intensity training which was only done at the very end, after the low intensity training.

There is nothing new about the training plan that Couzens recommends, it is basically the same plan that every coach I have ever read recommends. Is it polarized training? For some time now, I have been following Stephen Seiler, the exercise scientist who coined the term polarized training, and I get the sense from him that what is of proven value in polarized training is less the high intensity side of that polarization and more the low intensity side. Thus, both polarized training and the training plan recommended in this report mostly just support the conventional wisdom of the coaching community that large amounts of low intensity exercise are an essential part of training for endurance sports.

Before switching focus from Fitness to Health, I need to insert a caveat. Everything up to this point has considered athletes whose current training program may not be optimal but who are relatively fit to begin with. This is very different from the situation faced by  the public health community who are interested in the benefits of exercise for health. Their studies are often on subjects who start out not exercising at all. Might such a person, one starting from a much lower level of fitness, have a greater potential for increasing their VO2max? I don’t have an answer to that question, but I do think about it while I am considering these health-oriented studies.

One health oriented study I have considered multiple times on this blog is one I call Gillen et al.  This study claimed that the health benefits of 1 minute of high intensity interval training (Zone 7) was equal to those of 45 minutes of low intensity aerobic exercise (Zone 2.) At the time I first reviewed this publication I had the following reservation:

“Am I convinced that HIIT [High Intensity Interval Training] provides as much benefit as moderate exercise in extending longevity and improving health? … Not yet [because, although] after twelve weeks, HIIT and moderate exercise produce the same changes in VO2max, glucose tolerance, and muscle mitochondria, ... would these changes be equally maintained if the experiment were extended to a year or ten years?”

The report which is the subject of this post would argue that my concerns are very justified, that if the experiment had been extended from 12 weeks to 3 years the results might have been very different, the low intensity group might have increased their VO2max much more than the high intensity group.

This report has different implications for another study I reviewed. This study compared over 100,000 patients who had taken treadmill “stress tests” as part of their medical care. These subjects were grouped by their max MET scores (equivalent to VO2max) and their risk of dying was followed over the next 4 to 13 years. The astounding result obtained was that the fittest 2.3% of the patients had a greater than 5-fold lower risk of dying than the least fit 25%. Compare this to the decrease in risk obtained by not smoking which is only 1.4-fold. Because this was an observational study, it was not possible to determine how much of that fitness was genetic and thus is out of the patient’s control and how much was the result of exercise. One hint as to the answer to that question came from a second paper I considered in that post which also looked at over 100,000 subjects and which was also an observational study but which asks its subjects how much they exercised. In this study, those who exercised the most had a 1.5-fold lower risk of dying, suggesting that much of fitness is genetic. Another way to ask this same question is to assume that VO2max can typically be increased by about 25% by exercising. How much would that help the treadmill scores of subjects with low fitness? In the treadmill study patients were put into five groups; the 25% with the lowest fitness, the next 25% with below average fitness, the next 25% with above average fitness, the top 25% with high fitness, and then a subset of this last group, the 2.3% with the highest fitness. In general, improving VO2max/max METs by 25% would move a subject up 1 group. This would decrease their risk of dying by about 1.4-fold. Thus, both of these approaches, an observational study that looked at exercise rather than fitness and a theoretical approach based on studies which measure how much VO2max can be improved provided very similar results; exercise can reduce risk of death about 1.5-fold whereas genetic factors that impact fitness can reduce risk of death by about 3-fold. This is a very weak conclusion based on a shaky chain of logic, but it is intriguing and to my mind begs for follow-up.

In the final post in this series I am going to look at the major competing theory to Polarized Training, and that is Sweet Spot training, a theory that seems to recommend the exact opposite to Polarized Training. Rather than avoid exercise which is in between low intensity and high intensity, such medium intensity training is the focus of Sweet Spot. Stay tuned.

TRIMP, Intensity, and Fatigue

TRIMP, which stands for TRaining IMPulse, is a measure of training load, the amount of fatigue a ride generates. The longer the ride, the greater the fatigue. The more intense (harder, faster) the ride, the greater the fatigue. TRIMP is calculated by multiplying the length of a ride in minutes times a measure of intensity of that ride. The different curves shown above above illustrate different ways of estimating intensity. Lucia, Edwards, and Banister TRIMP are well known and are well described in the literature. Gillen and Hughes are defined by me and thus essentially unknown. I defined Gillen intensity in a previous post, and Hughes intensity in this post. The point of this post is to argue that I the well known versions of TRIMP significantly underestimate the amount of fatigue generated by high intensity rides. (Note that the above scale is a log scale; the differences illustrated are quite large.)

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“It Ain’t What You Don’t Know That Gets You Into Trouble. It’s What You Know for Sure That Just Ain’t So” - Anonymous

How does one estimate the amount of fatigue a workout generates? The standard metric used by many coaches and academics is a metric known as TRIMP, which stands for TRaining IMPulse, a term that means training load. As is well known, training load produces fatigue in the short term and, when combined with recovery, increases fitness in the long term. In this post, I will only be considering the fatigue impact, and in that context, TRIMP is also synonymous with fatigue. 

TRIMP is not a single metric but rather a collection of different metrics. A TRIMP score is calculated by multiplying the minutes of exercise by the intensity of that exercise, which just kicks the can down the road: how does one determine intensity? The difference between the various TRIMP metrics comes from their use of different estimates of intensity. I wrote my previous post in this series, “​​Training Zones, Calories, Oxygen, and Power”, to provide the background needed to understand where estimates used by the more common versions of the TRIMP protocol come from; they come from the closely related metrics of heart rate, blood lactate, power, and the training zones derived from these metrics, all of which ultimately relate to calories burned per minute. In the absence of any information to the contrary, is it a reasonable guess that fatigue might be directly related to the rate at which calories are burned? Sure, why not? However, it is just as reasonable to guess that that it is not. What I am going to argue here is that there is information to the contrary, that the advice commonly given by coaches based on their real world experience provides a very different estimation of how fatigue relates to intensity than would be predicted by the amount of calories rides of different intensity consume. 

How do the common versions of TRIMP estimate intensity? Edwards TRIMP is based on a heart rate-based five zone system and uses the zone number as the measure of intensity. Lucia TRIMP uses a blood lactate-based three zone system and again uses the zone number as the measure of intensity. Banister TRIMP does not use training zones but rather  uses heart rate directly. In addition, it adds an exponential adjustment which reportedly was included to make it match lactate levels more closely. The effect of this correction is relatively small, however. There is also something called individualized TRIMP. I believe this represents a family of estimates with one source even using the term to to refer to Banister TRIMP^. The purpose of this post is for me to provide my own estimate of intensity which can be used in my own version of TRIMP, an estimate based on the actual training plans provided by Coach John Hughes.

This is not my first attempt to provide a different measure of Intensity. My first attempt was based on the paper I refer to as Gillen et al. This estimate was based on a 7 zone system, and I suggested that Zone 7 produced not 3.5 times the fatigue of Zone 2 but 45 times as much, that the estimates of intensity for Zone 2 and Zone 7 should be not 2 and 7 but 1 and 45. I think that fatigue generation and intensity is most definitely more complicated than that, that there may not even be a single number that fully represents each zone, but in the interest of not allowing the best be the enemy of good, such a single number representation is what I will be developing in this post not because I think it is perfect but because I think it is better than the other more commonly used estimates. To put this into perspective, in my last post I essentially used a multiplier of 1 for all zones because I lacked the zone data to do better. Had I been able to use the zone number multiplier I am now disparaging, that would have been better than what I did. I think this is why coaches sometimes recommend a zone number multiplier, it is simple so that their athletes might actually do it and it is better than nothing. In that spirit, I think there is an even better multiplier that coaches could add to their training zone charts that would be, if not perfect, an improvement over zone number (and just as simple). In fact, I think that multiplier is implicit in their more detailed training advice, and what I am going to do in this post is to tease that out for one publication of one particular coach, the one coach I am currently following, Coach John Hughes. The main theme of this post is going to be to compare what Coach John Hughes recommends to what he would recommend if it were true that Intensity was proportional to Training Zone Number (e.g. Load = Minutes x Zone Number.) 

Let’s imagine a healthy, young athlete who is a randonneur specializing in 200K brevets. Let’s imagine they select "Distance Cycling" by John Hughes and Dan Kehlenbach (hereafter referred to as Distance Cycling) as their training guide. This is the plan for preparing for a 200K brevet from Distance Cycling:

The numbers are the length of each day’s ride in minutes. The Green rides are ridden in Zone 1, the Yellow rides are ridden in Zone 2, and the Blue rides are ridden in Zone 3, but in what Zone should the red rides be ridden? To answer that question, our randonneur turns to another publication of Coach Hughes, “Intensity Training for Cyclists” (hereafter referred to as Intensity Training.) That book describes 6 training zones named Zone 1 through Zone 6. In addition to these six numbered Zones, it talks about 2 other zones named “Sweet Spot” and “Sprints”. Sweet Spot overlaps with the top of Zone 3 and the bottom of Zone 4 and Sprints are even more intense than Zone 6, they are a Zone 7 if you will. (This last point has confused me in the past so in some of my earlier posts I refer to Zone 6 when I should have referred to the Sprint zone, Zone 7.)  The imperfect but (hopefully) useful approach I will take is to look at how long the various workouts recommended by Coach Hughes are and from that, infer how much Fatigue per minute ridden Coach Hughes thinks are produced in each zone. There are some leaps in logic required to do that, and I will take you through those. To do so will require knowing a bit more about Coach Hughes’ training plan.

Intensity Training describes a periodized training plan consisting of fairly typical divisions into Pre-Season, Base, Build, and Main Season periods. The training plan diagrammed above describes the Build period which is what I will be focusing on in this post. This book is designed to be flexible, to adjust to a variety of riders and goals. Our hypothetical randonneur has the ambition of riding a 200K brevet as fast as possible and so uses the Coach Hughes’ “Performance Rider” plan which includes rides in all 8 zones. All rides between Sweet Spot and Zone 6 are done one day of the week, on the “red” day. Sprints (Zone 7) are interspersed within other rides, on any day except for rest (no ride) or active recovery (“green,” Zone 1) days. Rides in different training zones are designed to develop different cycling abilities. Which intensities your hypothetical randonneur will ride during their weekly “red” ride will depend on what abilities they are attempting to improve. Those abilities (along with the maximum recommended total time for each workout) are as as follows:

Sweet Spot: Increase Power                       Longest Workout: 40 minutes

       Zone 4: Increase Lactate Threshold     Longest Workout: 30 minutes

       Zone 5: Increase Racing Speed           Longest Workout: 20 minutes

       Zone 6: Increase VO2max                   Longest Workout: 15 minutes

       Zone 7: Improve Economy                   Longest Workout: 2.5 minutes

When our randonneur starts doing these higher intensity workouts, Coach Hughes conventionally has them start with fewer, shorter repeats and work up to more, longer repeats. the length of the workout is (the number of repeats) x (the length in minutes of each repeat). For each zone, he has a maximum number of minutes that an athlete reaches at the end of that progression. Since these Zones are swapped in and out of the same ("red") day in the schedule, one might infer that the maximum minutes, which is different for each zone, represents the same training load. Since Load = Intensity x Minutes, one can infer the relative Intensity by dividing the constant Load by the variable Minutes (e.g. Intensity = Load/Minutes). But is it true that all of these zones have an equivalent load? Here is what Coach Hughes says:

“The harder the intensity, the more days of recovery you need between sessions. You may do two days of tempo workouts in a row if you can do a quality workout the second day. Allow at least one recovery day between sweet spot workouts and at least two days between sub-threshold, super-threshold, VO2 max and sprint workouts.” - Coach Hughes, in Intensity Training

Thus, taking Hughes at his word, it takes twice as long to recover from a Sweet Spot workout as it does from a Zone 3 workout and three times as long from Zones 4 through 7. The good news is that, by inference, the Zone 4 through 7 workouts each adds up to the same training load. The difference in recovery times between Sweet Spot (Zone 3.5, if you will) and Zone 4 is small and I will ignore it. (If I did include it, it would only increase the already large trend I am suggesting.)

What about Zones 1, 2, and 3? Zone 1 is only used for recovery rides, the goal of these rides is not to increase fatigue but to reduce it. The bad news is that means my approach cannot be used to estimate the fatigue generated by Zone 1 recovery rides. The good news is that there is no need to to do so, Zone 1 rides can be ignored as a source of fatigue. 

The Zone 3 ("blue") ride occupies a different slot in Coach Hughes training plan than the higher intensity ("red") rides so there is no reason to expect that it will generate the same amount of Fatigue as they do. The one clue we have is Coach Hughes statement that Zone 3 rides can be ridden two days in a row whereas the higher intensity rides require two to three days recovery between them. From that, we might conclude that the higher intensity ("red") rides generate two to three times the total fatigue as the Zone 3 ("blue") ride. The longest Zone 3 ride, both in Distance Cycling and in Intensity Training, is 90 minutes. If I were to argue that these 90 minutes generated only half the fatigue as the 40 minutes of total Sweet Spot (Zone 3.5, "red") ride, then I would have to conclude that the Intensity (Fatigue per Minute) of the Sweet Spot ride was 90 divided by 40 time 2 = 4.5 times as that of the Zone 3 ride. Compare this to the conventional TRIMP estimates that they are at most 1.25 times greater. At this point, I want to reiterate that I am aware of how tentative my argument is. I feel very strongly that the conventional TRIMP estimates significantly underestimate the Intensity of higher intensity rides but am much less sure exactly how much they do so. Thus, to be conservative, I am ignoring the two-fold multiplier and suggesting that a Sweet Spot ride has 2.25 times the Intensity as a Zone 3 ride.

The weakest link in my argument concerns the relative Intensity of Zone 2 (long, "yellow") rides and the higher Intensity rides. Again, they occupy a separate spot in Coach Hughes training plan so there is no basis for assuming they generate the same amount of Fatigue as the higher Intensity rides. I don’t know how to fix that so won’t try; for no good reason, I will assume that the long (“yellow”) ride generates the same amount of total Fatigue (Intensity x Time) as the Zone 3 (“blue”) and higher intensity (“red”) rides. The longest Zone 2 training ride Hughes recommends is 210 minutes.

The intensity I am calculating is relative. For convenience, I set the intensity of a Zone 2 ride equal to 1* and for each of the higher zones, the intensity given is how much harder that ride is per minute than a Zone 2 ride. Thus, for each zone, I calculate the intensity as the length of the longest ride at that intensity divided by the length of the longest Zone 2 ride and this is the results of that calculation:

In the first column is the training zone number. I have never seen a case where rides in Zone 1 are used to build fitness, and as noted above, this means I will not be using Zone 1 in my estimation, it will start with Zone 2. In the next column, I have given the relative Intensity implied by the recommendation that training load (which by definition equals Time multiplied by Intensity) be determined by multiplying ride time by zone number. It is useful to arbitrarily set Zone 2 to have an Intensity of 1 and thus Zone 4 will have a relative intensity of 2 and so on. That implied intensity is given in the next column, Zone Intensity. In the third column, named Hughes Minutes is the maximum number of total minutes in a workout (day) Coach Hughes suggests for each zone. Using my logic, I then convert this into a relative implied Intensity by arbitrarily setting Zone 2 to an intensity of 1 and then multiplying that by the ratio of minutes in Zone 2 / minutes in the Zone. Thus, for Zone 4, Hughes recommends a maximum of 30 minutes. In his overall training plan to prepare for a 200 kilometer long ride, he suggests a maximum ride length of Zone 2 rides of 400 minutes. 400 divided by 30 gives an intensity relative to Zone 2 of 13.3, much higher than the zone-number based estimate of 2. In a previous post, I used the data from Gillen et al. to do a similar estimate, and, for comparative purposes, that is shown in the final column. Gillen et al. only looked at Zone 2 and Zone 7 and so I put n.d. In the remaining positions of the table to indicate that the value was Not Determined.

Am I guilty of the straw-man fallacy? Does anyone actually estimate ride load by multiplying zone number times minutes? Every single scientific paper I have read that considers ride intensity uses one of the common versions of TRIMP to estimate that intensity. In a perfect world, those papers would have justified use of that metric, but in my opinion, they do not. Some studies do go as far as to show that TRIMP scores are going in the right direction and are better than nothing, points I do not dispute, but then go on to use them in a way that relies on them being quantitatively accurate which has not been demonstrated and which I believe is not true. As just one example, consider the publication, Vermeire et al. I reviewed about a year ago. That publication concluded that polarization of training was more important than training volume because they found that improvements in performance correlated with degree of polarization but not with TRIMP scores. (They looked at Banister, Edwards, Lucia, and individualized TRIMP.) Perhaps there would have been a correlation with TRIMP scores had they used a more quantitatively correct version of TRIMP.

In contrast, coaches give TRIMP very little if any attention. Rather, they provide concrete training suggestions, how long an intense effort should last (20 seconds, 1 minute, 10 minutes...) and how many times that effort should be repeated. What I am arguing for is to connect the scientific community with the wisdom of coaches. This is an approach that Dr. Seiler (father of periodized training) has adopted. He argues that laboratory studies are limited in what information they can provide and thus need to be supplemented with studies of the training approaches used by successful athletes and their coaches. 

If I were reviewing this post, my biggest complaint would be the lack of any experimental evidence that my approach is helpful. My response is to concede the point but then to note that this post is not intended as proof for anything but rather as a reality check and suggestion for future research. If the actual recommendations of coaches (the recommendations of Coach Hughes I used in this post are pretty typical) do not match the TRIMP protocols we are using, should we not worry about that? In short, I think coaches do not need improvements to TRIMP but rather can provide suggestions as to how to improve it. Exercise research scientists, on the other hand, often use TRIMP and thus would benefit from the improved versions of TRIMP that coaches can provide, based on their experience.

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^ I confess that I understand individualized TRIMP least well of all of these and if you feel like you do understand it, please tell me about it in the comments. 

* Because of the way Banister TRIMP is calculated, and because that calculation generates a value of 0.9 for Zone 2, a value very close to 1.0, I didn't bother to correct Banister TRIMP numbers.