Cohorts and their meaning

***First, an update on the status of the alpha release — It is imminent!! We hit a few snags, but will have you authorized to start entering data this week.***

What are cohorts? 

Cohorts are groups of individuals who share a set of similarities.

How can we exploit this type of grouping?

Lets say we want to offer advice to an individual (lets call this person, A) on how he/she can alter training/nutrition to perform better. One way to do this would be to randomly pick a training protocol/nutrition system and ask the person to follow it for a month and see what happens. The probability that this will be successful is small.

How do we increase the probability that we provide advice that works?

We find a group of individuals who approximately 30 days ago (+/-) were very similar to  similar to A, in multiple categories. We then narrow this group down to those individuals who are similar to A and also improved their performance output over the past 30 days. As we are all interested in improving overall work capacity, a max effort lift, or some specific movement/skill, this information would be very useful to individual A. Now — what did this group of people do over 30 days to improve their performance? Its very likely that implementing these changes could have a significant effect on individual A’s performance.

How do we determine who is in a cohort?

We use what’s referred to as a ‘graphical model’ to determine similarity between individuals and to assess what the commonalities are between/among these groups of highly similar people. Graphical model analysis will compare large groups of individuals and find those who share many edges with individual A. Read: those who are similar to individual A in many aspects. The thicker the edge (i.e: the closer the values are) the more alike the individuals may be. See the figure below for an illustration.

We compare individual A (highlighted by red arrow) to the entire group, with respect to multiple variants (work capacity, muscle group bias, height, weight, race, age etc etc). We find that he/she is more similar to about 30 people within the group (circled) than to the other ~500 people. This allows us to focus in on this group and identify changes they have made to improve. We can then use this as a starting point to make suggestions to individual A.

Cohort analysis = Accurate advice 


Work and other metrics

I was going to post some analysis on muscle group involvement, movements and how to gauge training versus overtraining of certain muscle groups. But, some pressing questions have been raised by several readers.

**Important Note:  If something seems off or I just haven’t explained things clearly enough, please leave comments on here.** Unfortunately I don’t get to talk to each and every one of you on a daily basis and won’t get to answer your questions if I don’t know what you are thinking.

Question: What are the metrics you are going to measure and how are you going to measure it?

Answer: This is a very important question that I should have addressed at the outset. I would like for each one of you to understand exactly what we are doing so you can challenge our rationale and thought process if you see something wrong.

Work done: we have spent a significant amount of time reading and researching papers and measuring movements in multiple individuals to figure out formulas for the work done in moving both the centre of mass of the individual and the moved mass (barbell, KB, med ball etc)

Muscle group involvement (MGI): We have also broken all oly lifts, crossfit movements, running, rowing etc into the discrete major muscle groups involved. In order to simplify it, we are currently using a binary system where the muscle group is either used or it isnt. There are other ways to do this (i.e: how much each muscle group is contributing to the overall muscular activity in each movement). We will continue to experiment with this as we go through the pilot. At the moment, no other analytical software is doign this and we think that this would be a good place to start.

Power generation/VO2max/Agility/Heart rate: There are once again many ways to measure this and we will be tweaking this measurement. But currently we can pull some of this from your 500m row sprints. Additionally, we would love for you guys to do a 30sec all out sprint on the erg and give us some benchmark numbers. You can select whether or not this would work for you below.

• When you log in, you will also be asked to answer a quick set of 5-7 questions (this will allow us to add in more variables to the overall picture in order to get a better understanding of each days training session/performance):

  1. Any change in weight?
  2. Hours slept (eventually this will become something that we can automatically track using our mobile app)
    2a. how well did you sleep? (1-5)
  3. describe energy level (1-5)
  4. water intake for the day
  5. mood (1-5)
  6. soreness (1-5)
  7. any sickness? (yes or no.. and if yes  a description)
  8. appetite (less than normal, normal, more than normal)
So I have tried to detail the major metrics we will be tracking for your training. In addition, we will be tracking all kinds of stuff from your nutrition (including supplementation). That part of the web tool is still a little preliminary. But we are getting there.
Once again, leave questions on here or reach out to me personally —