Wko+ for simpletons

After my last blog entry, my buddy Jaakko advised me to use my skills in translating the complex math of wko+ into terms that the layman can understand, to write a book on wko+ for Dummies. In fear of copyright infringement, I elected to go with today’s title :-)

There is also a little hidden meaning to today’s title. Truth is, there is no negative intent to my use of the word simpleton (or Mr Gump). Au contraire, I deeply admire simplicity in all senses of the word.

As much as I love to deal with numbers and complex theories, the truth is, I abhor complexity. Whenever looking at a data set or a new theory, my driving motivation is to reconcile it with my current view of the simple truth, i.e. to break down complexity into simplicity.

We are all familiar with the term ‘paralysis through analysis’. The corollary to this would be ‘action through simplicity’. In other words, those who most embody action (and who, consequently, generate results) do so through a simple approach – a focus on spending their time DOING the essentials rather than analyzing the inessentials. So, this brings us to today’s blog.

Somebody whose approach I deeply respect is athlete, Tim Luchinske. It seems that the bulk of Tim’s actions are put in place with the aim to bring the essentials more into focus and I’m not talking along the lines of what logbook he selects. Check out his blog to get a feel for what I mean.

In fact, it was reading his blog over the last couple of weeks that partly prompted this post. I want to distance myself from my recent posts that seem to suggest that fulfilling your potential in sport is a mathematical problem. It is not. In order to actually ‘do the math’, requires tuning out the noise and tuning into your passion throughout the day, throughout your life. So, I write this post with that intent.

That said, there are some simple key essentials that have been known to elite coaches for decades and recently confirmed by (and elaborated within) the studies on mathematical modelling of the training process on which wko+ is based. These key principles are so key, in fact, that I have witnessed, on numerous occasions, very passionate, action oriented athletes who fail to observe them consistently perform below their potential.

So, in this post, I want to provide some of the key ‘take home points’ that I have learned from wko+ that can be applied to all athletes, irrespective of whether their training log consists of a docking port for every speed and power measuring device known to man or a writing pad sitting on your bedside table.

1. Every individual athlete has an optimal ‘chronic training load’ for any one season that is the result of their training base and constitution, not their aspirations.

In other words, every athlete has a limit to the training load that they can absorb at any one point in the training season. It is important to note/realize that this number, of what the athlete can absorb over a long term period is significantly less than what the athlete can do over a short term period. It is only through long term monitoring of large scale workload, e.g. month to month workload that a reasonable assessment of optimal training load can be made.

This optimal load will also change over the year as the athlete’s base improves. While a 50hr month may make an athlete tired in the prep period. At the end of the base period, the athlete may be able to absorb a 70hr month with no problem.

Irrespective, the take home message is to stick to one given training load until you have proven that you can absorb it (6 weeks or more) before deciding to up the ante.


2. Every individual athlete has an optimal ‘ramp rate’ to build training load towards this optimal level. Exceeding this rate results in failed adaptation (overtraining)

There are 3 basic scenarios that can arise from the application of a training load:

a) Too much load



If the athlete digs too deep a hole for themselves at the start of the season, by ramping up the volume/intensity too quickly, they will exceed their adaptation reserves and fail to supercompensate, i.e. too much load will make the athlete slower rather than faster

b) Too little load



If the athlete digs too shallow a hole for themselves at the start of the season by ramping up the volume/intensity too gently, they will receive full benefit from the load very early in the training season, i.e. they will ‘peak too soon’. Obviously this is preferable to the first option as it is much easier to maintain a given level of fitness through to competition than it is to shed fatigue, get healthy and get fit if too much load is undertaken.

c) “Just right” load.



Optimal load will have the athlete arriving at maximal fitness shortly before their peak race of the year, with just enough time to taper and freshen prior to the competition.

Fitter athletes (athletes with a stronger consistency base) will generally be able to tolerate more aggressive ramp rates. However, the only way to not risk the fitness that you have accrued in the last block is to plan very moderate volume jumps from month to month until you have a proven baseline ramp rate that you have sustained over the course of a season.

3. Every individual athlete has an optimal season length before load makes them more tired rather than more fit. Exceeding this optimal season length results in failing adaptation (overtraining).

The other time of the season that the athlete risks failing adaptation is in a season that extends too long. When performance begins to drop late in the season in spite of maintained/increasing load, it is time to shut her down and take a worthwhile break. This optimal length also depends on the base of the athlete and how deep the initial hole is dug. Generally, this time period will be in the vicinity of 3-7 months.

4. It’s a lot easier to get fast by getting ‘fresh’ than it is by getting ‘fit’.

While the seasonal gains that an athlete can expect from appropriate tapering are less than those that the athlete can expect from training, the relative benefit makes allowing time for an optimal taper a key inclusion within the training plan. In a wko+ sense, an athlete can, under a good case scenario, expect a 10-20% improvement in fitness (CTL) from month to month. However, freshness (TSB) can improve almost 200% within 1 month of reduced training! This is worthwhile remembering when considering ‘doing a little more’.

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Wko+ is a tool that enables athletes and coaches to reconcile the relationship between training load and relative performance. It is especially useful as summary statistics for those athletes who experience frequent fluctuations in training load to keep track of expected fitness and to forecast what load modifications will lead to the best result. However…..

For the serious athlete, controlling variables should always be a higher priority than measuring them.

Train Smart,

AC

Benchmarks and Forecasting

I woke up this morning and looked out the window to find a good accumulation of snow on the ground. I was a little surprised. I didn’t remember my local Fox meteorologist, Crystal Egger (pictured) saying anything about an upcoming snow storm. Usually, she gets it pretty right. In fact, if I think back a couple of decades to my childhood, it sure seems that weather forecasting has improved a whole lot. It seems that back in the day, it was a running joke that the weather that we would wind up with was basically the opposite of what the meteorologist would predict.

Of course, like most things, I am sure technology has played a part in the improved accuracy of weather forecasting. Scientists are now able to sample, minute by minute, a myriad of benchmark #’s, from barometric pressure to humidity to minor fluctuations in temperature and furthermore, they are able to summarize this data to create accurate computer models to predict future weather behavior.

If you’re reading this blog, chances are that you’re seeing where I’m gonna go with this.. there are parallels between weather forecasting and performance forecasting in the world of athletics. Similarly, there are those who are understanding and embracing these new technological tools to better forecast their athletes’ performances and there are those who still see this new science as ‘hit and miss’ at best. I want to chat a little, in this blog, about how to go about selecting appropriate benchmarks and how to use them to accurately forecast and plan improvements in performance.

Regular benchmarking is necessary and useful for a number of reasons on a number of levels….

1. Is the training program working?

Clearly, from peak to peak, we want and expect an improvement in performance from the preceding training program. It would be a foolish athlete who would commit to a multi-year training plan without some ‘checking in’ along the way to make sure the program is working. This ‘check in’ may take the form of racing or testing but it is clearly an important component of the feedback loop when it comes to training. You would probably be surprised by the number of athletes that I come across who don’t have regular effective ‘check ins’. It is common for Ironman athletes to race much less frequently than short course athletes, focusing more on work than testing out whether the work is working  Additionally, athletes will often choose different events from year to year in the name of variety and miss the benefit of having a standard check-in at a local event at a given point in each training year. The problem is compounded by the fact that many athletes do not undergo regular field or lab testing.

Clearly, this represents the first and most important level of feedback for the athlete. Are they getting better? In my meteorological metaphor, this level of understanding as akin to having a general sense of what the weather is like in a given region of the Country. When I first moved from Florida to Colorado, I had a sense that the weather would be considerably colder than what I was used to, however, I had limited experience or information to understand how the differences may manifest over the course of a year or to predict the specific temperature on a given day. Which brings us to the second level of understanding…..

2. Is the athlete where they need to be in the context of the training cycle?

Better coaches will have a good general understanding of where they expect their athletes’ performance to be through the course of the training year. This is an important upgrade on the first level of understanding.

Experience has taught us that it is necessary to get ‘unfit’ at certain points in the season in order to get ‘more fit’ at other points. This ability represents a critical distinction between very good coaches and most self-coached athletes. On a lot of levels, many self-coached athletes expect continuous, steady improvement. They do not understand the performance ebb and flow that comes with the training seasons. Good coaches have a good general idea of how ‘out of shape’ they want their athletes to get and what level they expect their training sets to be at through the course of a training season.

It is really important that the athlete and coach establish seasonal benchmarks that are best correlated to their peak performance.

In weather terms, this level of understanding is akin to having local knowledge of the annual weather. For example, when I spent my first year in Colorado, I learned just how warm it would be in Summer, just how short the Spring and Fall seasons could be and just how varied the winter could be, from 60 degrees and Sunny one day to a 2 day snow storm the next. Even with this local knowledge, however, my ability to forecast the actual temperature on any one day is limited at best. Which brings us to the third level of understanding…

3. How can we ‘forecast ahead’ to determine the performance effect of different training strategies – different work:rest cycles, different peak training loads, different season structures.

If an “old school” coach wants to determine if an alternative training strategy is beneficial, they do so via long term trial and error. I have been fortunate to work with a number of truly world class coaches over the course of my career and, to a man, they are very structured, methodical individuals who rarely stray from the well tracked path. Occasionally, however, they will conduct an ‘experiment’ and will slightly modify their core training plan in accordance with the result. I remember during my coaching apprenticeship with Ian Thorpe’s coach, Doug Frost, Doug decided to change from Ian’s usual 3:1 work:rest cycles to a 2:1 structure. I asked him how he would determine whether this strategy was effective and he simply said – by Ian’s race results at the end of the season.

Simply put, the example above illustrates just how limited is the number of ‘experiments’ that the coach can conduct. Best case, an athlete may work with a given coach for 10 years. At most, this represents 10 or so alternative experiments that can be tailored to the individual. What if, however, we had a specific understanding of the fitness and fatigue dynamics for each individual athlete? What if we could predict relatively accurately how a given athlete will respond to a 2 week taper vs a 4 week taper without throwing away a whole season in the name of an experiment? What if we could determine whether an increase in load of 2hrs a week would lead to a new PR or overtraining for a given athlete, without compromising their health and athletic career in the process?

By assessing the performance dynamics of an athlete over the course of their training, we are able to get a firm handle on how quickly a given athlete acquires and loses fitness in response to a given training load.

I have presented the following figure a number of times now – Selye’s GAS curve.



Usually when this curve is referenced, it is done so in a general, theoretical sense of how a general athlete responds to training stress. However, like any curve, we can generate an actual, real world, mathematical expression for the curve and by using criterion performances, or Benchmark tests, we can change the constants of the formulae to create a curve that best fits the athlete’s specific response to training load.

When this is done, we can provide a relatively accurate performance forecast for a given athlete in response to different training protocols.

However, generating an accurate performance curve for the athlete demands that we have a good number of accurate criterion performances or ‘benchmarks’ for each athlete. We have a couple of options on this front (each with it’s own strengths and weaknesses):

a) “Flat Out” Criterion Performance Tests

In ‘pure’ terms, it is hard to beat regular races or time trials to answer the first of the questions listed above: Am I getting better?

However, there are a couple of problems with the use of time trials that compromise their effectiveness in answering the other questions. The first of these is assessing fitness at various points in the season. While theoretically possible to run time trials throughout the training year, many coaches prefer a progressive ramp up in the preparatory phase before including any ‘flat out’ work. It can be biomechanically and physiologically risky to throw a time trial in in the very early season. Therefore, we can miss out on assessing how fit the athlete is when ‘kicking things off’, or more importantly, how much fitness has been maintained and carried across from last season.

Additionally, the frequency that would be demanded to create sufficient samples for an accurate forecast model is prohibitive if the athlete wants to actually perform some training in addition to the testing trials. Or, put another way, flat out tests tire you out and wind up compromising total training load.

b) Critical Power/Pace monitoring.

Wko+ provides the weekly and monthly metrics of power and pace ‘bests’ for a given duration. IMHO, using these as a benchmark is a mistake because they do not take into context whether these were a 100% effort, an 80% effort etc.

Take for example, an athlete who performs a regular 2x20min session at a moderately-hard effort on a weekly basis. This is prescribed as a session at roughly the power than the athlete could sustain for 3-5hrs. Week after week, the athlete completes a pretty standard basic week, with a tolerable load and a similar (though slightly increasing) power level for this session. Then, 8 weeks out from their peak for the year, the coach decides to up the ante and rapidly increase the load, in addition to adding some races. With the addition of more load, the athlete’s fatigue #’s go through the roof (and their TSB sinks to -50) but, with the addition of a flat out race, they experience their highest 20min power for the season. A less than astute coach may attribute the highest power of the season to the increased training load, when in fact the 20min power best is actually the result of a change in training content rather than fitness.

Of course, the coach could include a critical power ‘best’ set each week however this brings with it the same issues as the ‘flat out’ time trial mentioned above.

c) Power or Pace vs. Heart Rate.

My preferred primary method of benchmarking is using power or pace vs heart rate for given aerobic sets throughout the training week.

The primary advantage to this method is the pure frequency of sampling. Several times per week I can look at the power:HR relationship for a given set and I can establish an improvement curve without compromising or affecting total training load. Additionally, I can assess performance throughout the training year, testing at times of fatigue as well as peak form to establish both fatigue and fitness components of performance with respect to a given training load.

Of course, this method has it’s shortfalls also. Heart rate is a physiological measure that is affected by many non-training related environmental factors. However, when it comes down to it, the pure number of data samples that I am able to accumulate with this method outweighs the standard error associated with the method.

A couple of key sessions that I like to use for the Bike and Run:

Run (Track Workout):
2mi Easy (@130bpm)
2mi Steady (@140bpm)
2mi Mod-Hard (@150bpm)
Record 400m splits for all.

Bike (Long Workout)
1hr on the trainer (30min easy w/up, 30min @ 135bpm) Record power
2-4hrs on the road
1 hr on the trainer (30min @ 135bpm, 30min cooldown) Record power

As mentioned, these workouts should be done regularly and during hard weeks as well as easy weeks so that the both the athlete’s fitness and fatigue responses to a given training load can be determined

Stay tuned in coming weeks for more on how you can use your training benchmarks to ‘calibrate’ your CTL and ATL constants in wko+

Train Smart.

AC

Do work, Son!

I had to include a pic from one of my favorite shows from last year, Rob and Big, when I decided to write a post on that 4 letter word – work. Big Black had a recurrent catch phrase on the show – “Do work, Son!” that I thought was particularly relevant to this post. So there you go. This one’s for Rob and Big.

It can be tempting in this world of relative measures to lose sight of the absolutes. This is just as true in triathlon training as in any other field. Doing your best is great but in the world of competition, being the best is better.

I had an interesting question from one of the athletes that I work with that went along the lines of,

“Coach, I just had a look at Joe Blow’s performance manager chart from last year (Joe Blow is a top AG athlete). I almost put in the same amount of work as him. Our CTL #’s were almost identical but our performances were a world apart. What gives?”

And so, in one key sentence in the above passage lies the problem, “I almost put in the same amount of work..”. The problem is that TSS may be a measure of stress, but it is not a measure of work. CTL, ATL and all of the other metrics associated with TSS management are relative, rather than absolute measures related to each individual’s personal functional threshold pace or power. Just because you deposit a similar TSS workload to the pro of your choice doesn’t entitle you to withdraw a similar race result. No, if you want a similar result you need to compare apples and apples, i.e. absolute measures. Or, put another way – Do work, Son!

I could see that my explanation wasn’t entirely satisfying my athlete who was still of the mind set that 120 TSS/d for one guy is the same as 120 TSS/d for another. So, I pulled up the wko #’s of the other athlete in question and we looked at another number – kilojoules of work.



Athlete A experienced almost the same training stress (~5%) less than athlete B but experienced a performance that was ~35% slower than athlete B. Coincidentally, he did ~33% less work than athlete B. Hmmmm.

My point is not that Athlete A should have ‘sucked it up’ and done more work (irrespective of the fact that matching Athlete B’s workload would have probably take him an additional 5 hours a week, not to mention burying him in the process), but rather that, when comparing across athletes, the absolute work is ultimately more of a determinant to performance than the relative training stress.

Relative training stress for a given session may not change a whole lot over the course of an athlete’s development. However, total work will. A long ride of 250TSS (5hrs at an IF of 0.71) will represent a total workload of 2500kj to a newbie athlete with an FTP around 200, however this same session will represent a total work of over 3500kj for a top AGer. For this reason, when planning long term TSS, it is not always necessary to ‘up the ante’. Providing the athlete is improving, the ante will be uped quite naturally.

All of this is not to say that an increase in CTL should not occur from year to year. Because CTL is ‘carried over’, if the season is timed appropriately, a slow and steady increase in the athlete’s CTL over the course of their development should be noted. However, this is a function of appropriate recovery and consistency within the sport, rather than a conscious choice to increase training stress. Increasing training stress is, well, stressful and is not conducive to the long term, steady progression that those seeking to discover their potential in the sport should adhere to (for more on Long Term Athletic Development, check out my article on Xtri.com)

However, when you’re consistently seeing high TSS weeks and the frustration starts creeping in that you’re not ‘keeping up with the Joneses’, it is worth remembering that there is really only one number that counts and one way to the top (for a very long period of time) – Do work, Son!

Train smart.

AC