James Gleick in his new book, “The Information” says that the basis of the universe isn’t matter or energy. It’s data. This is quite a profound and magical statement when you begin to think about it and how we interact with data changes our lives. It changes our cycling lives and our life in general from your iPhone to your connection to the internet and knowledge from all parts of the world. Data is just strings of bits, but whether or not it contains information, depends on what you do with the data and how you learn to interpret it. Interpreting data into useful information is a key skill that we all need to improve in all facets of our lives. The more information that we have, the more we can understand the role it plays in our lives and how we can become better cyclists and citizens in the world around us.
Using a power meter is one of the main ways that you can collect data in your cycling training and racing. A power meter can collect the data, but you have to turn that data into information that can be interpreted and used to make changes in your cycling. Your power meter collects this data at one second samples and it can be up seven different channels of data like speed, cadence, elevation, torque and even GPS. The key is that we turn that data into information and that is done through software analysis in a program like TrainingPeaks WKO+ and also education in articles and books so that you can understand this data and information. In this world of cycling in which you are immersed and inside this amazing magazine full of information, we need to discuss the different categories of data. Each category can give us some insight into a part of our cycling that we can improve or just learn about for a better experience down the road. Of course using a power meter on your bike is really our only meaningful data capture device we currently have available in our world. A meaningful data capture device to me means that it has the ability to help you make changes in your training; it gives me the information I need to decide whether or not one of my athletes should do a workout or not, or do 8 hill repeats or 12 hill repeats, or whether they should train their threshold power or their anaerobic capacity and this information makes my job more precise and efficient.
There are seven main categories of data:
1-Point related data, you look at the power or cadence or HR at specific moment in the ride. This can help to determine if the interval or exercise was executed correctly. This is the simplest of the data you are capturing and here you are drilling down to the minutiae so that you can determine if you held just enough watts for the required period of time. I look at point related daily with my clients’ files, and this is something that I learn many things from how many watts an athlete cracked out for the interval to whether or not they paced themselves correctly and even if they created the watts correctly using the right balance of force and cadence
2-Warning system Data. Data can be used as an early warning system. This data is comprised of many, many smaller data sets and we need to look at this data over a longer period of time. Unfortunately, in order for this warning system to ring the warning bells, you need a large data set of your rest days, your hard days, your races and all your rides no matter how easy or hard they are. This is a critical part of the warning system and if you are missing data because you didn’t use your power meter in a race or because it had to be sent back for repairs then you really compromise the integrity of the warning system. My warning bells can tell me if a client is doing too much training too quickly and overtraining could occur. Another warning could be that you might see a drop in your threshold power suddenly and unexpectedly. While out on a ride doing intervals you could use your power meter to tell you when to stop doing intervals, as your power has decreased below optimal in creating the right training stress.
3-Detector Data. Data can be a detector. When you cracked out your best 20 minutes, how fresh were you? When you blew on the big climb, what happened in the 5 minutes before it? 10 minutes before it? In post analysis of your data, you can use your data to better understand your failures and your successes. When you succeeded, what exactly did you do in order to succeed and when you failed, why did that happen? Was it the 10th hill that crushed you or was it the violent attacks up the 10th hill that crushed you?
4-Instanteous Data. Data can give you instant feedback. During a workout, you continually watch your powermeter to stay within required limits for optimal training. This is where your power meter can help you in pacing. Cycling is a sport of pacing, and you must pace yourself in a breakaway, in a long road race, in a short criterium and in a century ride or gran fondo. Pace your effort on the hills and pace yourself with your nutrition and hydration as well. These are all key fundamentals to your success as a cyclist and one of the beauties of using a power meter: the data is instantaneous. You push down on the pedals, and you see the number on the screen instantly. There is no lag time, there is nothing to wait for or download later, it’s right there and it happens immediately.
5- Investigative Data. Data can help you be a detective. If a problem occurs, then that’s when you can use the data to help you detect the problems. Sometimes you have to dig deeper into the issue surrounding a success or failure and reviewing the data maybe the way you discover the true underlying cause of your performance. I spend a lot of time being a detective when I analyze an athlete’s data, asking myself questions like: “How many times did he have to attack and how many watts were in each attack before he was able to get away?” or “As this athlete fatigues, does she choose a bigger gear because they have more natural strength than endurance or do they just not have enough muscular endurance to begin with?”
6- Explanation Data. Data can explain why you are faster or slower. You have to understand what information the data is trying to tell you. You have to translate it. Like James Gleick said, “Data is only a string of bits and has nothing to do with information. The information comes from understanding and that is our job to understand it.” Why were your watts lower than yesterday? Is it because you are tired and couldn’t physically produce the watts? Was it because you tried to test up a steep climb and you are better as a flat time trialist? Was it because you had your arch-nemesis to chase therefore you were pushing harder than ever to beat them? This type of data is similar to the data you get from investigative data, but explanation data provides a quicker insight into the information you need.
7-Incorrect data or biased Data- This is worse than no data at all. Sometimes you can correct for incorrect data from your past experiences. Other times you have to throw it away. Incorrect data is easy to identify in most cases, but biased data is much harder to discern. Fortunately, our power meters are not biased (I hope!) and therefore we rarely have to consider biased data, but often our data can be incorrect and that can pose many problems in analysis.
The data is always clear as a bell to see, but it’s not clear whether or not it explains the problem.
You must first prepare the data in order to identify the problem and this is what turns data into information. To achieve the right interpretation of the data, you need experience and a gift for joining the dots together in one picture or just good computer software….. I do believe that you need to have a personal connection to the data and understand this information first for yourself and then you can understand it for others. I have seen too many coaches trying to coach athletes with a power meter, but they have never used a power meter themselves, so have no understanding of what 300 watts feels like to them or what 1000watts feels like. This data, this information that we capture on a power meter has the unique aspect in that we can associate it with a feeling and learn that sometimes our feelings are incongruent with the data and other times feels exactly how it appears.
The experience and a basic knowledge of riding and racing a bicycle are essential. You are creating a harmony between man and machine. You are looking to optimize what your body is telling you about how it feels and what the data is telling you about how you feel. Relying solely on the data is dangerous and doesn’t tell the whole picture, but the information we gather from the different categories of data can help us to improve as cyclists and citizens of this world of data.
Hunter Allen is a is a USA Cycling Level 1 coach and former professional cyclist. He is the coauthor of “Triathlon Training With Power”, “Training and Racing with a Power Meter” and “Cutting-Edge Cycling,” co-developer of TrainingPeaks’ WKO software, and CEO and founder of Peaks Coaching Group. He and his coaches create custom training plans for all levels of athletes.