‘No one can get inner peace by pouncing on it.’ Harry Emerson Fosdick
I can go to sleep carefree knowing that there are plates in the sink that need washing up, and I don’t have to lock-up the house in a certain order before I leave. I would say I’m free from the obsessive compulsive disorders that many people develop around their daily lives. The main reason for this lack of OCD is for many years I have been far too busy stressing about training.
In 2008, in my first year on a UCI team I was especially keen to start our first team training camp. I had brought my power meter, laptop and trainingpeaks software ready to continue the power based training I’d been doing for a couple of years. After each ride I would analyze my speeds, power, heart rate, cadence, time spent in the 7 training zones and numerous other measurements. Most importantly, I could look at the parts of the ride where I was riding at full intensity and then track my progress against other all out efforts that I had done previously. I was sure I was well ahead of everyone else at the time who had not been training scientifically, or who only used heart rate.
In contrast to the masses of data I was gathering, Russell Downing the team leader wrote down how many miles he did each day on a scrap bit of paper, not for any other reason than to brag to his training partners back home.
After the training camp I knew what my best power output for 1min, 5 min, 10min, and 20min, I knew how many calories I burned on each ride , I knew average speeds, cadences, and time riding in the 7 different heart rate zones; Russell knew he was riding faster than everyone else. That year I got glandular fever and hardly raced, Russell won everything.
I don’t think that the training methods were the only factor in the gap between our fitness and the way our seasons panned out. He is, and has been the one of the Britain’s best cyclists, and has done so without too much planning where training is concerned. He simply goes out and rides hard up hills, races for the 30 mph signs, repeats the next day, and rests when he needs to. Hard days and easy days. It is incredibly simple.
I have spent many hours creating training plans, and then re-done them days later after I read something about a pro who swears by some other magical training zone. I have laid in bed the night before a race wondering if I have done enough 4 hour rides, if my nutritional strategy for the next day is perfect, and what I’m going to do in the next few weeks to improve even more. Is this the ideal state of mind for an athlete who is competing the next day?
This post is not to discourage people from taking their sports seriously, or to stop you looking for ways to improve, but to make you aware of the stress that I and many others can create about their training. In the next blog post I am going to explain what I have done to simplify my training for 2013, why I have done it, and also give some observations of what I’ve found so far.
Conversely though, iv’e always just done what what i thought i needed to, when i could, as hard as i could and made no real improvement in results, i have since taken the step of following a dedicated plan, be interesting to see how it affects my results this season. ( haven’t got into the whole analyzing every ml of sweat iv’e produced yet).
lets put some science to this……….Your question is: Does complex or simple training plans produce the best results?
My answer is: It makes no significant difference
Why: one of the basic errors in human thinking is assumption of course and effect. Between any two variable that have a less than perfect correlation the outcome is far more likely to be due to chance than we are prepared to admit. A far more accurate way to predict result in the following year is to make sence of the statistical dater available, it this case your previous results. Given that your training volume will be about the same whichever plan you choose, complex or simple, your result will be likely to follow simple statistical rules than be as a result in the training methords.
How it works
If you plot your results year on year on a graph focusing on wins or podium places they will likely form a bell shaped curve, as most data sets do. Calculate your mean in say wins or podium places. You will see that most year your outcomes will fall within one standard deviation of that mean. Exceptional years both good and bad should be rarer and thus make up the opposite and of the curve. Following any exceptional result, in your case a good or bad session, the following year will almost always regress towards the mean, regardless of what you have done in training. This is a statistical fact that has been proven again and again in the literature across a vast array of data sets.
The beauty is, the larger the data set is the more accurate the effect will be. This is due to law of small numbers, and why experiment with small sample should be view with caution. This is because in a small samples, exceptional result are far more likely. In context this means that it is harder to predict a novice rider result, than an experienced one, simply due to lack of objective data. For you, because you have many years of results, it will be more reliable. It is also cool because your mean will change year-on-year the formula remains accurate, and will reflect your natural demise.
The mistake that you will make is that you will link you training methods too closely to your outcomes the following year. For example you will correlate you training methods of the previous winter to you following results. This will satisfy your need to establish course and effect but will be a flaw in your thinking. This will result in rejection of training plans that were succeeded by poor performance, rather than being safe in the knowledge that a poor season is likely to be followed by one closer to your mean. This improvement following a bad season (or decline following a good season) will due to regression to the mean, rather than a changing your methods. In fact the greater the difference from the mean you experience the stronger the regression to the mean will be.
Simple put, as long as you are training, it does not matter if it is complex or simple. The best predictor of you result will be you previous result. For you, this means, next year, your results will be of close to you average number of wins than this year relitivly poor seeason. That is my prediction and i am statisticaly more likely to be wrong right than wrong. if this interest you read thinking fast and slow by danial kahnaman