What A Week Of Our Daily Dashboard Looks Like

A daily dashboard should be the place you can get an overview of the most important metrics in one quick glance. What is important to some teams, may not be as important to others.

We are using the Catapult GPS system and while I could create a bunch of different charts to see the same information, it would be a significantly larger report (probably 5-6 pages worth and a bit messy to look at). Considering the general rule of thumb of creating athlete reports, we wanted to keep this concise and to a single page. We have created a dashboard to see what we deem as important for the performance and health of our team.

I realize this only takes into account objective GPS measures and that subjective measures, such as questionnaires and RPE values, are very important as well. We use a separate platform for that data and we’re working on incorporating that info in some capacity on the daily report as well. We have also calculated monotony and strain, but I keep that on the side and off the report for right now and am waiting to include in the report if it ends up being a valuable metric to look at.

For the purpose of this blog, I not only wanted to give some insight to not only what our dashboard looked like, but some insight to the fluctuations of certain metrics within the training week. This is a full week of training and match play for us (note that MD-5 and MD-4 are sorted differently, but after that days are sorted alphabetically so you can follow a bit easier):

Monday [MD-5]
Tuesday [MD-4]
Wednesday [MD-3]
Thursday [MD-2]
Friday [MD-1]
Saturday [Match Day]
Sunday [MD+1 – Regen]
Starting from the left to the right, the “status” and “position” columns allow us to compare starters, to subs, to non-dress players, and athletes in the same position. For example, we can easily sort to see if substitutes are doing enough to stay ready for when they are ultimately called upon to step into a playing role. Sorting by position allows us to see if a practice constrained a certain position. If athletes in the same position were constrained in practice then maybe we can make adjustments in the conditions or size of the SSG or drill if we use it again in the future (I realize my position descriptions are general, but I do take into account central and outside players to make it more specific).

Moving across the chart, I have set up “total distance” and “high intensity distance” the same way. Each has a daily total column, a rolling 7 day total, a rolling 28 day total, and the athlete’s corresponding acute:chronic ratio for both categories of running. We use total distance as a volume metric and HI distance as an intensity metric. You’ll notice that they are conditionally formatted to allow for a quick review when necessary. We have formatted based off of this research, but have also adjusted these values a bit based on what our starters cover on a weekly and monthly basis.

In reference to the 7 day and 28 day totals and acute:chronic ratios the formatting is as follows:

  • Green means an athlete is in an appropriate range
  • Yellow means an athlete is potentially under-prepared
  • Red means an athlete is under heavy volumes and potentially overtrained or in the beginning stages of overtraining.

I say potentially because everything is in context. I don’t take one red cell as an automatic red flag. If I see a red cell, I’ll look a little closer and find out why that happened and if it’s something to be concerned with. The first thing I usually do is cross reference their wellness surveys and see if anything looks out of the ordinary and then again ask them in person how they’re feeling and coping with training. Getting feedback from the athlete also allows me to start to make these values a bit relative. I then can start to understand who can handle more load and who needs a bit more of a conservative approach. Again, these cells are formatted as absolute thresholds, but it should be viewed in context with other pieces.

There are a couple immediate red flags for me though:

  1. If athletes in the 18 have many red or yellow cells in their respective row as we get closer to match day.
  2. If many of the athletes in the 18 have red or yellow cells in the same column as we get closer to match day.
  3. If an athlete is in red or yellow 3-4 days days in a row (I look mostly at the “acute” column here).

In regards to the first two points, this means that either the loading was incorrect for the individual or incorrect for a majority of the team. In regards to the third point, I’m not overly concerned when we’re in red for one or two days and then come down and recover into green and for me this is actually ideal most weeks because that means we have actually loaded and potentially overloaded the athlete a bit. On that same point, I would actually be a bit worried if we never saw red and were always in green.

Essentially, we’re just paying close attention to the “loading” and “taper” phases to make sure the goal of the session(s) have been accomplished and athletes are prepared and fresh for match day.

I’ve also been using the common acute:chronic ratio along with the 7 day and 28 day accumulated loads. The athlete’s accumulated loads help to give context to the acute:chronic ratio. The acute:chronic alone can only tell us so much. Meaning, an athlete’s acute:chronic ratio can be in an appropriate range according to the research, but if an athlete’s general loads (especially HI distance) are too low to be able to meet the game demands it doesn’t do us any good. You can see a few examples of this in the reports above where the A:C ratio is in green, but distance and/or HI distance is in yellow. For this reason, I don’t believe that the acute:chronic ratio alone gives you enough information. You must put it into context for each individual athlete.

The final piece on this report is speed. I put a premium on speed in soccer. When I reference speed, in this case, I am referencing max velocity. I realize acceleration capabilities in field sports are probably more important as that is an activity that occurs far more frequently, but the occurrence of injury during an acceleration is far less likely than in a maximal velocity sprint. We want our players to be able to handle game demands and while we might have only a handful of maximal sprints in a game, we need to be prepared to do so. I’ve formatted our speed cells off of this research.

These cells are formatted a bit different than the others. These cells are relative to the individual’s top speed recorded in pre-season testing and changed when they hit new top speeds during training or games. In the “% Max Speed” column, green isn’t necessarily good and red isn’t necessarily bad. This is relative to the day of training. On MD-4, green may be good and red might be bad, but on MD-1, red is good and green and yellow are not so good since we don’t want our players in the 18 sprinting above 75-80% on a MD-1. Again, it’s all in context to the training day, how far away from a game we are, and what athlete is in the discussion.

This is just one of two to three other piece of info we take in to help manage our athletes. I hope to update this throughout the year with a more 360 degree view of our process and will continue to try to give some practical insight to our monitoring.

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