A Case for Training Scientifically

As a coach, I am usually the person, or type of person, that someone comes to when they decide they want to start training more seriously. So I see a lot of people who are considering taking the step deeper into the world of cycling and all the factors that go into that choice. I’ve seen people decide to train seriously, and I’ve seen people who’ve decided that the serious training just isn’t for them. Obviously as a coach I believe that the best way to train is scientifically, but I also see the challenges. What I’d like to do in this piece is to make my case for scientific training, in the way that an academic might. What is the difference between training seriously and scientifically? What are the benefits of training scientifically, what are the problems and how do you deal with them? What role does the coach play and what role does the athlete play? Why a person might chose to train scientifically, and why might someone choose to avoid it?

First off some definitions. I’ll keep this short because it can muddy the water, but I also plan on posting more of these definitions later. Let’s start with what do I mean by “serious training”? Serious training is when someone is committed to their training at some level. It doesn’t mean it’s priority number one, but rather it means that it is a priority, it is on the list. When planning their life out, training and racing has a place in the conversation. The level of commitment can depend on everything from age, job, children, location, anything, but if training makes the list then you must care about it. And the level that you are committed is how serious you are. Now to train “scientifically” means to train by scientific principles. Just like seriousness, there are various levels here, but if you’re applying the basic ideas of science to your training you’re training scientifically. So that means if you have a method of testing and confirming results; and make training decisions and adjustments based on those results, you’re training scientifically. And the more exact you get, the more scientific you’re training. It’s important to keep these two separate in your mind I feel. You can train very scientifically, while also not being very serious, and you can train very seriously, without being very scientific about it.

So hopefully you’re seeing the difference already between serious training and scientific training. Everybody is different, but they all fall on a scale of seriousness and they all train at different scientific levels. But the difference is that seriousness deals with the commitment level, whereas training scientifically deals with the decision making process and the method used for answering the basic questions like how much should I ride and how hard?

I think it should be pretty obvious that the more committed a person is, the more improvement they will make. So the level of seriousness is directly tied to how well you’ll perform, but it is also directly tied to other things like time, life situation, life goals, and even cycling goals. So in most cases, a person will be as serious as their life allows them to be. Some may work to change the situation, but we train as hard and as seriously as we allow ourselves to. But on the other hand training scientifically is not linked to time, or life situation (at least not as much). Granted some are limited by money and cannot afford the equipment, and not everyone can work with a coach, and most don’t have the knowhow or the time to analyze data. But that doesn’t mean you can’t train scientifically. At the most basic level, training scientifically could simply mean that you take notes after each ride. How did you feel, how fast did you go, how many miles? It means that you’re recording some input and some output and looking for trends in how the input changes the output. The input might be you ate a cheese burger and the output might be you felt sick during your ride, but by noticing that when you didn’t eat a cheese burger and you felt better, and making sure that you don’t eat cheeseburger before you ride or race, you’re making a basic decision based on data. On the other end, you could be taking power, heart rate, RPE, and a whole bunch of other data. Your ability to make clear decisions increases, but you’re still making the choice based on inputs and outputs.

So what are the benefits? Why should you train scientifically? You should train scientifically because it allows you to make the most of your time. Let’s say for instance you start training with the purpose of racing cross country mountain bikes. You train 3 days a week and race 1 day. You have 2 hour on those 3 days. What should you do in that time? The most basic ride would be to just hop on the bike and ride. You would see improvement for sure. It would get easier to ride after a few weeks and you might even notice you’re going faster. But now let’s say you want to get faster, what do you do? You start taking water with you, you get clipless pedals, you take recovery drink. All these things will certainly make you faster, and so much so that you’d probably notice. But lets say you’ve been training for 2 years and you’re trying to get faster, but nothing seems to work? You tried some intervals and they didn’t seem to help, and you tried a new diet and it wasn’t doing anything as far as you could tell. The problem is that you have no way of knowing, long term, if something is working. Very few improvements in any sport once you’ve been training for a significant period of time are sudden and drastic, they are usually slow and steady. So you’ve hit a plateau not because you’re not still working hard, but you’ve lost your ability to make training decisions based on input and output. You no longer can learn from your training. It’s as much a mental issue as it is a physical issue. You can continue to make improvements by improving your ability to learn, but making your ability to observe better and more fine. This might mean a heart rate monitor, a power meter, but it could also mean rating each workout on a scale of 1 to 10 using RPE, and perceived performance. The key is to think about what works and what doesn’t.

So that all sounds incredible, but what are the problems with all this data and thinking. The biggest problem I’ve seen and run into myself is a problem of perspective. It’s very easy to lose sight of the big picture. Some things happen quickly, but most are slow increases and most improvements will start out as decreases in performance. So it becomes important to have the correct perspective and that largely comes down to experience, but also removing yourself from the situation, this is where a coach is the biggest help. The other big down fall is data overload! We have so many options for collecting data these days and it can a blast to keep track of it all, but it can also be overwhelming as well. If you’re overwhelmed by it all, it can cause you to look for the wrong trends, and look at the wrong performance parameters, and see the wrong things as the issue of the cause of success. Again, perspective is important here, but also clarity. The solution is to stick to the basics. The closer you can copy racing in training, generally the better. Race simulations are critical to both understanding the output of your training, as well as learning how to deal with the intensity of racing. Finally the biggest problem is not realizing your own individuality. While scientific studies are an awesome way to learn about how your body works and for getting new and interesting ideas on how to train, you have to remember it wasn’t tested on you. So get out there and test it before you just believe it.

I’ve already alluded to this, but what role does the coach play in all this? What about as an athlete, what is your role? Can someone just coach themselves? Having a coach has the obvious benefit of not having to think much about the data, your time is free to enjoy life and not have to wrangle data or worry about what you’re going to do next week for rides. But the coach can also do something that the athlete can’t. The coach can step out of the situation and look at the data much more objectively than an athlete ever can. It’s important for a coach to get inside the athletes head a little bit so they can draw from their own experiences, it’s also hugely beneficial for the coach to step outside the situation and look at the data for what it is. Of course the athlete has the role of actually pushing the on pedals, but I think the most important role the athlete can have is in thinking about how it felt. Basically like keeping a diary. I think of it like a car racing team. You have the car, you have the driver, and you have the mechanic. The mechanics have lap times and all sort of numbers coming from the car, but they can’t feel the car. Only the drive can feel the car. It’s the same thing with cycling. Only the athlete can feel their body and only the athlete can feel the effort, what it felt like and how it compares to before.

So why might someone want to train this way. By now I hope it’s obvious, the ability to get faster is much better when you start looking at what you’re doing and why you’re doing it. What effect does this have on that, what works and what doesn’t work. But beyond that a person can learn so much more about themselves when it comes to evaluating training objectively using data. A person can open up their capacity to work harder and smarter by know what works and what doesn’t, regardless of how it felt. So why might someone not want to train this way? Simple, it’s all about goals! If you want to get faster, you have to train hard and you have to train smart. But it takes some sacrifice and moreover it takes some focus. Often times you’re sacrificing fun rides with your friends to train specifically, and when cycling stops getting fun, it’s really not worth is. And this is all on a sliding scale, Just like you pay for commitment with free time or life responsibilities, you pay for training scientifically with training fun. For some it’s worth it, and for some it just isn’t.

Thanks for reading.