A week or so ago, I wrote a post up that reviewed a couple of years of my personal data in Training Peaks. Today, along the same vein, we dig into my lovely wife Ellie's data. For those of you who know Ellie, you are probably aware that she is probably the most consistently active person year round of anyone in the family. Signing up for weekly fitness classes at Sweat Society and Reform Fitness in Buffalo (evening getting on the wall of fame at Reform for the number of sessions completed!) to meeting up for casual runs with her friend group all summer long... the girl keeps after it! For these reasons, I thought her data might show and tell quite a different story from my own boom and bust cycling. I was not dissapointed!

Let's quickly acclimate everyone to the vast amount of data presented on the Training Peaks Performance Management Chart: The blue line with the shaded area is called chronic training load (CTL). It's a proxy for overall-fitness, and is a function of time spent working out at specific intensity levels. 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 fatigue levels that results from the workouts. Lastly, the yellow line is a measurement of how prepared the body is to absorb the training that you am doing. The more negative the number, the less the body is handling the work. The higher the number, the more ready your body is. 

Now, if you recall or tab back to my data, there were quite a number of really high peaks, and really low valleys. In Ellie's data however we see a very different story. After the 2020 Marathon Prep that was cut short due to the SARS-CoV-2 pandemic, me and Ellie's CTL pattern changes dramatically. While we were both building, in her data, she kept active after we got the notification that the race was off, maintaining a high level of fitness into the summer before reducing overall load slightly in the fall and winter. Me other hand? Straight up shut down and loss of fitness.

The other major feature that I see when comparing our two datasets are what I am referring to as "peak-to-valley" ratios. AKA from my fittest point to my lowest point, the difference is quite a bit higher then Ellie's peak-to-valley ratio is. She certainly builds up towards races just like me, but her starting points are always at a much higher level of base fitness than I am, and after races she doesn't decline in fitness nearly as far as I do. This is anecdotally accurate based on how our training for races typically goes as well. She is always in FAR better shape when we set out to prep for a race (like the Edinburgh Half). I spend much more time building back up my fitness to a reasonable level, where she starts off the training cycle with a solid base under her. By the end of the race training block, I historically blow up, get sick or injured and fall off, while Ellie continues on her merry way working out 4 to 5 days a week.

Based on how different our trends in activity patterns are, we would both benefit from making different adjustments to how we operate.  For me, it's all about consistency, day in and day out. For Ellie, it's going to be all about training with a bit more specificity. She's nailing the basics of consistency but in my opinion there is a huge potential for more structure in her workouts to start inching that performance needle upward. This is super exciting because I think that just means she has yet to reach her full fitness potential!

I hope you guys liked these two posts, I've always found fitness and tracking data to be super fascinating. Getting these two datasets loaded in training peaks has been super cool to see, and I'm excited to see how we can use this data moving forward.