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.
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!
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.
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.
Crickles Activity Charts has up until now (only) been available as a standalone app at charts.crickles.org. From today, Crickles Charts are integrated in the Navigator and the separate app has been retired. Here’s an example of how it looks now:
For the time being, this functionality joins HR Zones and Regularity as a beta feature and thus requires a log-in.
Functionally, the only significant change is that the set of Athletes whose activities you can choose to chart against your own is now picked from amongst your Strava friends who are on Crickles rather than the entire Crickles population. If you need a refresher, a description of the functionality as it was before is available here.
Hopefully, now that charts are integrated with the rest of the Navigator functionality, you’ll find it more convenient.
You may have noticed on Strava that there is quite an extensive list of Sports into which activities can be categorised. Here, for no reason other than curiosity, is a chart showing relatively how many of each activity we have on Crickles:
Since the number of activities in each Sport ranges from Rides, which is in six figures, down to Handcycles, for which we only have one, I’ve used a log scale.
Cardiac Stress Score can be calculated for any of these Sports in which a heart rate monitor is used (and estimated imprecisely even if one isn’t).
UPDATE: the algorithm for calculating CSS in the absence of heart rate data has been significantly enhanced since the time of writing.
There is a new feature on the Navigator for everyone on the BETA programme: you can now see your current training zones. The tab structure has been changed slightly so that when you’re not logged in the tab bar now looks like this:
Notice in particular the MORE option on the right. When you choose this you get the log-in screen that takes your BETA programme password screen. When you log in, the tab bar changes to this:
You can see that the HR Zones and Regularity tabs have appeared and I’ve selected the HR Zones tab. This shows my current training zones as calculated from the Crickles estimate of my current Lactate Threshold Heart Rate (LTHR). It also shows the date at which the zones were last changed – such changes are triggered from time to time in response to athlete activity data.
If you don’t yet have a BETA log in and would like one, please read this post and then, if you’re happy to proceed, send me an email requesting a password along with your date of birth.
Separately from the BETA programme, the standard Seasonal tab has also changed: Zone 5 was previously spilt into Z5a, Z5b and Z5c. These have now been consolidated for easier zone-to-zone and quarter-to-quarter comparisons:
The Relative CSS report – which is at the time of writing is the landing page on the Navigator – shows how the chosen athlete’s totalled Cardiac Stress accrued over the period defined by the Date range compares with others. This total CSS is a product of three factors:
The number of activities
The duration of each activity
The cardiac intensity of each activity.
The first of these is straightforward. Information on items 2 and 3 is available on the Relative profile report. Here’s how it now looks:
In this case “Athlete” is me. The chart on the left shows how the duration of my activities over the chosen period (the last six weeks) compares with that of others, with the y-axis being scaled in hours. I’m in green. The widest part comes at about half an hour, indicating that more of my activities have been of this duration than any other. By contrast, other athletes – the blue shape – are doing a far greater proportion of their activities over a period of 1-2 hours. Unlike others, I have no activities – zero width – around the two hour mark over this period.
It’s important to note that the number of activities (item 1 on the list of three factors above) is not reflected here at all – from this chart alone it’s impossible to know whether I’m doing three times as many or half as many total hours as others. This only shows the proportion of activities at each duration.
The chart on the right shows the distribution of cardiac intensity. Again, the chosen athlete (me again) is in green and others are in blue. From this I can see that for me the widest part – the intensity at which I most frequently exercised – is at about 87% whereas for others it lies at about 82%. On the other hand, some other athletes have exercised at over 100% intensity in this period and I haven’t. (100% is not a magic value – you can think of it, approximately, as exercising at or above your established Lactate Threshold Heart Rate.)
Like most of the reports on the Navigator, it responds to your choices for Athlete, Date range and Group – Group defines who is counted as “Others”.
This form of chart is likely to be unfamiliar to most people. However, compared to the old visualisation, it more clearly shows the relative distributions and has less risk of misleading at the extremes. Once you get used to it, it’s an intuitive plot that conveys its information nicely.