To view results on the Crickles Navigator you are now required to provide your Date of Birth. This enables us to run heart rate analysis based upon age and is needed for some of the features that we plan to introduce.
More immediately, it gives you the ability to compare your Navigator analytics with those of people who are close in age. To do this, simply pick Closest in age from the Group dropdown. This then compares your results to those of the athletes who are are closest in age to you:
The number of athletes who appear in light blue will depend upon the number who have signed up and disclosed their dates of birth at the time (as well, of course, upon the selection algorithm, which may change). The label in the top left of the chart shows the percentage of the Crickles population that are included in the Group selection. This now appears for all Group choices apart from All.
The Closest in age comparison applies to all of the tabs for which the Group choice is generally relevant. At the time of writing this is the first four, viz: Relative CSS, Relative profile, All-in and Summary. For each of these you can now compare your values with those of age-similar peers on Crickles.
For example, on the Summary tab when I select Closest in age I can see that my Current LTHR is at the 81st percent for my age group, whereas it’s only at the 59th percentile for the overall Crickles population (not illustrated here but can be seen by setting Group to All):
The identity of the athletes who are picked out as close in age is not disclosed on any o the tabs, nor is your identity disclosed to others when you appear as a comparison for them.
The Planner introduced a version of the Fit-Fat charts that, rather than looking backwards, projects forward into the future. Since its purpose is to assist with fitness planning, the Planner introduces High Fatigue warning lines to show when a proposed training load would push the athlete to a level of Fatigue that would be high for the athlete and/or high for the entire Crickles cohort.
This presentation of Fitfat charts is now available on Fit-Fat itself. Here’s an example with a Date range from 1/Nov/2017 to 7/Apr/2018:
This works well with short to medium Date ranges. Over a longer Date range the Fatigue, Form and Fitness lines can become unhelpfully overlapping. Also, the High Fatigue lines become somewhat redundant: in the limit, if you sample all of your available data by pushing the start of the Data range back to 1/Jan/2015 you get a very good view of how your current Fatigue compares to its historical levels without the need for the warning lines. Accordingly, for longer Date ranges the Fit-Fat display reverts back to its previous form. The cross-over occurs at around six months. In the example above, we can see this happen if the Date range is nudged one month further back:
Over this time horizon of around six months there’s not much to choose between the two views. The more stripped down format works better as the length of the Date range increases and the new format taken from the Planner works better over shorter horizons at which you lose the long-term picture.
I have been in the 48:30s for my 10Ks so far. Mo Farah can sleep soundly in his bed. My fastest 10K, according to Strava, came during the Bristol Half Marathon last year (surprisingly). On Tuesday night, in my Nike’s I ran 46:31. About 2 minutes faster. So the shoes are better in the real world too. Frustratingly I can’t remember my previous best – and Strava doesn’t give you a list for some unknown reason.
Looking back at some of the segments I have run repeatedly during the route, I was a few percent faster consistently. What really surprised me was that I had done a run in the morning, and an hour and a half on the turbo too, doing intervals, so I was far from rested.
The shoes are not going back. I’m amazed. If you buy a TT bike and a speed suit and a helmet, and spend time in the wind tunnel, you expect some time back “for free”. But I had never expected that shoes could make so much difference to running.
What is written below correctly describes the Planner functionality but there are a couple of new updates since this was written, namely:
Forecast method. For athletes for whom Crickles has uploaded at least a year of data there are two new Forecast methods for projecting your exercise load. The method described in the post below is now called Average based on Date range. The first new method is called Trend. This takes your average CSS per day from exactly one year before the forecast period (which is from now to your chosen Target date) and scales this up or down according to your current v. last year prior exercise load. The advantage of this over the Average method is that it accounts for both seasonality and year-to-year trend, which are typically very significant factors. Like the Average method, this generates ‘per day of week’ exercise load that you can adjust to suit your training programme. The second new method is called Repeat block from the past. When you choose this you’re prompted to enter a Start date to repeat from. Given this, the actual exercise loads that you incurred from that start date are projected forward from now to your Target date. For this method the adjustable per day of week levels do not appear. This enables you to see exactly how your Fitness, Fatigue and Form will evolve between now and race day if you repeat a training block from the past.
Taper periods. The default taper periods described below were taken from analysis of the tapers of successful marathon runners prior to a marathon. These allow for a substantial amount of recovery and lead to very high Form levels on race day at a cost to Fitness (which is the point of tapering). These defaults have been changed to levels that are recommended for (and typical of cyclists) – a two week instead of a three week taper and of more modest extent. Of course, you can freely set the Taper levels as you see fit and this only affects the defaults.
The Crickles Fit-Fat tab shows you how your Fitness, Fatigue and Form have evolved based upon the Crickles model for Cardiac Stress. Now, you can also use the new Crickles Fitness Planner to anticipate how Fitness, Fatigue and Form will respond to a training programme geared towards an event. This is accessed on the Planner tab.
Entering the data
When you first visit the Planner you’ll see that the sidebar changes to the following:
Target date defaults to today + 3 months. You should change it according to your fitness planning horizon – say the date of your next significant athletic event. (It won’t accept a date less than one month into the future.)
The Sundays to Saturdays fields in the CSS Regime section are populated with your average CSS (actually your ‘extended CSS’ or XSS) for each day of the week sampled over the Date range. In this screenshot, I’ve extended my Date range back to 01/01/2015 to get a longer-term sampling period. You should adjust these numbers to reflect your planned training programme over the period up to your event. It’s best to do this using typical observed CSS values from the Activities tab. For example, in my case my usual park loops on a Wednesday or a Saturday park run will each score me about 40 CSS points; an hour on the turbo will typically get me 80; and a weekend club ride or equivalent might score about 320. Of course, if I want to increase my Fitness I’ll have to do more than I’ve done in the past!
The three Taper period fields enable you to specify how you plan to step down your exercise in the three weeks leading up to the target date. The fields are pre-populated with typical percentages – e.g. a reduction to 70% of a normal training week in the third week before the target date – and you can change these if you wish.
As you change all of these values the charts will change accordingly.
What you should aim for
The general aim of a Fit-Fat-Form training programme can be summarised in three principles:
Add training volume to increase Fitness
Taper before your event to flush out Fatigue and hence increase Form
Don’t take on so much exercise load that your Fatigue gets to unhealthy levels.
Of course, there are many other important factors too such as working on strength and flexibility, managing any medications you may be taking, and balancing non-exercise factors such as diet, workload, travel and sleep; these lie outside the scope of this tool.
There is no established science on correct or optimum levels for Fitness or Fatigue. However, you can see if your own Fitness is increasing, staying flat or falling. Regarding Fatigue, the charts show you two useful levels as horizontal dashed red lines:
What is a high Fatigue level for you. This is calculated from your 90th percentile of Fatigue over all of your data on Crickles.
What constitutes a high Fatigue level for all of the athletes on Crickles. This is calculated from the 90th percentile of the 90th percentiles of each Crickles athlete.
Each of these two levels is marked on the Planner chart. As a fact of statistics, most of us will find our own high Fatigue level lies at a smaller absolute value than the high Crickles Fatigue level. When you train hard and do tough sessions you will occasionally push yourself beyond your own high Fatigue level. However, when planning a training programme if you see that your Fatigue levels are sustained for several days at a greater negative level than your high level, and especially if they are also sustained beyond the Crickles high level, it would be prudent to build in more recovery days.
So with reference to the three aims of the Fit-Fat-Form programme given above, you want to see that:
Your Fitness at the target date is higher than it is today
Your Form at the target date is comfortably positive – ideally at levels of 25 or more for the days leading up to your event
At no point during the course of the programme is your Fatigue hanging for days on end below the high lines, and especially not below both lines.
The longer you give yourself to train, the easier it will be to meet all three of these training goals. Over three months it is certainly possible, and over a longer period it is easier. To take my numbers given on the input panel above as an example, if I project forwards based on no change except for a taper period I’ll find that my Fitness at the target date is lower than my Fitness now, while my Form will be much higher/better: both effects are simple consequences of the taper period. However, if I increase my average exercise load on Sundays from 131 to 250 while leaving all other values the same I’ll get this:
My Fitness increases by about 10%, my Form is nicely high leading up to the target date and although my Fatigue sometimes dips below my own “high level”, it never stays there for long; moreover, my Fatigue never falls below the “Crickles high fatigue” level set by our hardiest athletes.
A final thought
There are limitations to any model and, as I’ve noted, there are important health and fitness factors that are not addressed at all by this kind of model. However, the Crickles methodology for assessing cardiac stress is robust and can be applied consistently to any form of exercise (although the estimate quality is reduced when heart rate is not captured). Furthermore, if you set a CSS-based exercise programme using this approach and stick to it then – as a mathematical fact and not just with the vagueness of an estimate – your Fitness, Form and Fatigue on the target date will be exactly as they were projected to be at the start of the programme!
Last May I was struggling with lateral knee pain. For days after the Taunton half marathon I couldn’t walk down stairs. I had tried a few things and was about to spend a lot on a trip to a podiatrist. Instead I went to TriUK in Yeovil and had a go at their “Mizuno Running Solution”. They picked out some shoes for me and I haven’t looked back – I haven’t had knee pain since (I have had Achilles discomfort, lateral foot pain and posterior tibial tendonitis mind you – but nothing terrible). I’m on my third pair of Mizuno’s now. My wife and kids have pairs too.
I have been using the Wave Mujin 3 shoes over the winter. They have taken me through umpteen muddy fields and down paths as well as covered a lot of road miles. I have probably done 400-500Km in them. They have been through the washing machine umpteen times (I know…).
I thought it was time for some new shoes. The Nike app texted me last week to say that their new lightweight Epic React Flyknits were available. 5 minutes later I had ordered a pair and they arrived last Wednesday. They have a new type of foam in (“React”). It’s durable and returns energy to the runner. It’s no Zoom Vaporfly 4%, with no carbon fibre plate (as far as I know). But it’s not exorbitantly expensive and the shoes expected to be durable – 600 miles or so.
On Friday I took them for a spin. On a treadmill. My “fast” mile felt easier than ever – rather than feeling as though I was going to pass out at the end of it, I was increasing the speed and went on for 2Km.
Psychological? Possibly. I firmly believe in psychology. I have a degree in it, and my PhD was on “central fatigue” – the concept that your brain limits your exercise capacity. I spent a lot of time doing transcranial magnetic stimulation. It’s odd to see the resurgence recently in brain stimulation. There is no doubt that new kit gives you a boost. But certain parameters, such as heart rate don’t (shouldn’t) lie.
Last night I settled down for some science. I’ll need to replicate this again, probably next Sunday, but the bottom line is that the new shoes seem faster.
Some methods. I warmed up outside with a 3K run up and down our local hill. I then did 5 intervals on our treadmill: 800m at 11.3Km/h then 800m at 16.2Km/h then a brief rest (I let the treadmill run at 9Km/h for 400m – 160s). A total of 8K. That rest time allowed me to slow down, get off the treadmill and change my shoes and my footpod (Polar). I used a Polar H10 heart rate strap and recorded it on my Garmin 935. The first interval was with the Mizuno shoes. Then two intervals with the Nike’s. Then an interval with the Mizuno’s and then a final interval with the Nike’s. For reference I weighed the shoes – a single Nike weighs 234g, a single Mizuno weighs 388g – an important difference.
Note I can run “faster” on the treadmill than in real life. I have just managed a Sub 20 5K on the treadmill, but it’s still just over (by about 40s) on the local 5K park run. 11.3Km/h is the speed I target for endurance. Last year that kept my heart rate about 130-135bpm. 16.2Km/h is the fastest I can sustain for a mile. Because I wanted to see if the new shoes were faster I didn’t want to hit my maximum heart rate and plateau, so although I can go a (little) bit faster over 800m I kept it at this level.
What did it show?
Firstly, it felt way easier with the Nike’s. There is a definite squish and you can feel the shoe deforming on impact with your toes and forefoot sinking into the shoe. You don’t get that with the Mizunos. But was it physiologically easier?
It looks like it was. See figure 1. It has two traces on it. There is an actual speed (according to the treadmill) line to demonstrate the intervals and a heart rate trace. The orange intervals are when I have the Mizuno’s on. The Black intervals are when I have the Nike’s on.
Firstly, from left to right there is a gradual increase in heart rate. For me, running the 5 back to back intervals was hard. I’m also in a small, hot stuffy room. So I get tired and dehydrated.
But the interesting thing for me is that my peak heart rate is higher on interval 4 than interval 5, by just over 4 beats per minute. The trend would suggest it should be the other way around. Not much – but around 3%.
The really interesting thing is the speed data from the footpod though. The next chart (figure 2) shows the actual speed (calibrated – the actual data suggested I was much faster than I was!). As far as the footpod was concerned I was running more slowly (about 2Km/h) with the Nike’s on compared with the Mizuno’s, although the treadmill speed was the same.
I’m not quite sure why this is. Running in the Nike’s changed my technique though. I felt a bit more tipped forward and a bit more on my toes. I also noticed a bounce, and I would imagine I spent more time in the air, allowing the treadmill to travel further beneath me.
I have summarised the data in the table (table 1). I can go faster on the treadmill in the Nike’s. But am I faster in real life? I’ll try to answer that soon. As soon as the weather dries up anyway and I have some time to do some intervals outside. I don’t want to get my Nike’s dirty yet, and time is a bit tight at the moment. I also need to do a long run first to see if they are comfortable enough. The toe box is a bit small, and I don’t know how my knee will stand up to things. If I can’t get on with them, back they will go. Despite the treadmill times.
This morning I ran up Quakinghouse lane with the dogs and one of my kids. For about the first time in a while I enjoyed it. At the top of the hill the sun was rising, the wind had dropped, and I could see out over the vale of Taunton. There was a chance I would get home with warm, dry feet.
It’s been a long hard winter, and running up and down that hill hasn’t been pleasurable. But people who run (or cycle) are addicted to running (or cycling), and I am now a slave to it. And it is an addiction.
There is a long-running study looking at Ultra marathoners (the ULTRA study). It takes a little finding. There is a study on the treatment of fibroids known as Ultra, and project MKUltra is also known as the CIA mind control program – allegedly.
The signup for the study is here if you are interested. It’s an ambitious project to determine whether running long distances is healthy. If you are one of the many who has done an Ultra, then go and sign up.
But the interesting thing about people who do Ultras (people can enrol in the study if they have run an event of more than 50K) is that they don’t care if it’s healthy or not. Participants in the study were asked to answer “yes” or “no” to the question “If you were to learn, with absolute certainty, that ultramarathon running is bad for your health, would you stop your ultramarathon training and participation?” Of 1349 who answered the question, almost ¾ answered “no”. My guess is that this would hold true for cyclists and triathletes too. The Pubmed link is here if you want to read a bit more.
I see people with heart trouble every day of the week, that may be due to exercise. I haven’t stopped yet and won’t for as long as my health and my joints can keep going.
It absolutely p****d down as I ran down Quakinghouse lane. The shoes are on the Aga. I’ll be out again tomorrow.
Recently Strava’s API for getting Friends has stopped working. This hasn’t only affected Crickles: numerous other app developers are reporting the same problem. There is no information about this on the Strava developers site, which still reports the same protocol for accessing Friends data, so there is no way of knowing if it’s an unintended bug or a planned removal of functionality. Strava are not replying to Support queries on the topic.
Whether/how Friends-style comparisons will be supported if Strava don’t fix their API remains to be seen. Please let me know if you have views on its desirability.
UPDATE – Strava are not restoring this functionality hence the Friends groupings in Crickles are, for the time being, stuck with only the friends known as of the date before this was withdrawn.
It’s been one of those weekends which haven’t been full of joy. At one stage yesterday, with the rain pouring and the wind blowing, I asked myself what I was doing out running up a muddy hill with the dogs. The answer was of course to take my mind of the Bawa-Garba case.
For those of you who don’t know, Dr Bawa-Garba was found guilty of manslaughter and struck off by the GMC after the tragic death of a child under her care. She made a mistake – that is clear – and it had terrible consequences. But there were, as there usually are with mistakes, also problems with the system in which she worked. She had just returned from maternity leave, was working in an unfamiliar environment, the IT system was playing up and she had with junior doctors supporting her with little experience. It has been reported that she was covering for absent colleagues, including the consultant as well. Is it any wonder that a mistake happened?
This winter in the NHS has left many of us rushing around, managing a much higher number of patients than usual, and consequently making hurried judgements. But what is the alternative – to say you will only see a certain number of patients, or down tools if members of the team are off with flu? The case has made many of us feel vulnerable. All doctors make errors at times. We know we make more errors when under pressure.
The practice of medicine relies on judgement and intuition – which is why it is error prone. It is not an exact science, and never will be.
It is that very lack of hard data that inspired Crickles. I was asked “how much exercise is too much”, and I couldn’t give an exact answer. Crickles draws on the wisdom of the crowds. You can look at your exercise volume and see where you are relative to others. You can look at your fitness and fatigue levels. As of this evening, I am fatigued according to my data. So, it’s a day off training tomorrow, thank God, as the weather looks crap.
Prominent amongst the latest batch of enhancements to Crickles is the introduction of user credentials: you now need a password to access the Navigator. The log-in screen looks something like this
On your first visit, you’ll only see the Username (Strava ID): field at first. The Strava ID that is needed is not the email address or Facebook ID that you use to log onto Strava but the number that Strava uses to key your data. In my case, for example, it’s 301194, as in the figure. To find your Strava ID, go to the Strava website and find “My Profile”. On the Strava website, it’s currently found in the pull-down menu next to your photo on the top right of the screen.
Once you have selected this, the top of the browser window will look like this:
You can see from the figure that the Strava ID (301194 in my case) is at the end of the URL in the address bar.
Once you enter your Strava ID, if you haven’t yet authorised Crickles to access your Strava data a link will appear where you can do this. Alternatively, you can do so at:
Then, if you haven’t got a password yet, hit the Request password button. A password will be emailed to you and it should arrive more or less instantly.
If you wish, once you’ve logged on you can create your own password. As well as being potentially more memorable, this is also more secure. Although the password generated by Crickles is encrypted, it has necessarily passed through email servers en route to you, unlike a password that you choose for yourself.
You change password using this screen:
You get to it by checking the Change password? checkbox in the side panel. If you’re on the screen and decide that you don’t want to create a new password, simply uncheck the box. Once you’ve changed the password you’ll need to re-enter it to log in.
After you have logged in you should not usually need to do so again on the same device. (If, though, you have disabled all cookies in your browser you’ll need to log in every time.) The way that credentials are shared between devices, and whether and how passwords are cached, will depend upon your device, your browser and your settings.
Significantly, no one can now see your data on Crickles without logging in as you. Your Strava Friends who are also on Crickles can compare various aggregate CSS measures and compare charts of activities that have not marked as Private on Strava, but the detailed information that you can see is now just your own.