Right before the COVID-19 pandemic completely changed the world, I was training for my first marathon. During that process, I started to upload my data to a training platform called Training Peaks. This tool, popular amongst both amateur and professional triathletes is designed to ingest workout data and provide an estimate of overall training load. The goal of the platform is to build sustained consistency and fitness while attempting to prevent over training.

A key feature of training peaks is the performance management chart (PMC). While the PMC is a premium feature behind a paywall, I was fortunate enough to get a trial of its power this past few weeks. This was especially cool because every single workout that I had logged on my Garmin watch has been passively uploading to their system since January 2020. AKA a data nerds literal Christmas morning. When I realized this, I got irrationally excited and started to buzz around the house and show Ellie all of my stats for hours on end. In one chart, it captured everything that has happened to my fitness level for the past 2.5 years. This was especially cool because I had some serious ups and downs health wise these past couple of years. So... let's dive in to the chart!

Now, there is a lot going on here, so let me first orient you to the different colored lines. The one that is most informative to this conversation is the blue line with the shaded area. This data is called (CTL) or chronic training load. It's a proxy for my overall-fitness, and is a function of time spent working out at a specific intensity level. Generally you want that number to increase over time, but at a controlled rate (i.e ramp rate). The pink line is a measurement of my fatigue levels that results from the workouts i'm doing. You can see that it's correlated with the chronic training load (blue line). The more training I do, the higher my fatigue gets. Lastly, the yellow line is a measurement of how well my body is able to absorb the training that I am doing. The more negative the number, the less my body is handling the work. The higher the number, the more ready my body is. 

I annotated this plot with key events in red that occurred over the past few years. You can see that the build up to the marathon in 2020 (left side of the plot) was going fairly well and when the pandemic hit I essentially stopped working out, loosing a lot of the fitness gained. We had just completed a 17 mile training run and got the email that the race was cancelled... and that was enough for me to say screw this I'm done.  Later that summer we started to do a long distance walking challenge with my parents and walked 3 to 5 miles every day... which increased my overall fitness quite a bit, really more than I expected to be honest! (Caveat: this is relative fitness though, because I wasn't developing speed, just time on my feet.)

In 2021 I started to build up to an olympic distance triathlon but about a week before the race, I had a complete collapse of my thyroid hormones which landed me in the E.R. and unable to compete. Looking back it's hard to say what exactly caused my thyroid to quit on me, but based on my fatigue levels, my way too high ramp rate of training, and probably some other factors like acute viral sickness (not covid), I think my body wasn't put in a good position to absorb that training load. Essentially I was pretty depleted despite thinking I was "race ready".

It took several months for me to recover from the thyroid problems, but in the spring of 2022 I started to build back some fitness. We ran the Edinburgh half marathon, which I fully admit I wasn't well trained for it, but got through it with peer pressure from Ellie and Ellen. The data agrees with my feeling of under-preparedness. Next, by July 2022 I gained a bit more fitness and set a PR at the Boilermaker, which we were pretty excited about. 

Looking retroactively at this data has me pretty excited because while I wasn't chasing any specific fitness CTL score or anything like that, it perfectly captured the dynamics of my fitness over the past 2.5 years. More so, it also illustrates one of the chronic problems in my overall fitness and training -- lack of long term consistency and building. Each year I built up to a race, and then either got hurt, sick, or stopped training for months on end after the race. This has led to long term failure to build true fitness. Seeing this in the data really hits home, as i'm very much a data-first kind of person. The goal moving forward is to change up my typical pattern and try to build month to month consistency over the span of a year, or two, or three. 

Let me know what you think, or if you have any questions about the plot or data points or how it is all calculated!