Home Brewed Monitoring of Physical Readiness: Managing Data Streams

This is the 2nd post in a series detailing my jimmy-rigged athlete monitoring system. As I mentioned in the first post in this series, I don’t have the luxury of a fancy monitoring system and was forced to do something myself. The intent of the series will be more to feed thought and discussion on these matters rather than get in the technical bits behind it (which I’d be welcome to address at a later time).

Although this post will be on managing data streams, we should really talk about what data streams need to be managed. I’ve found this is somewhat of a compromise between what you’d really like to do and what you are logistically able to do with your man-power, equipment, and resources. In a nutshell, I had a couple criteria:

  • I wanted to measure acute mechanical load (~closely related to neuromuscular training stress), acute physiological load (~closely related to metabolic stress), adaptation, life stresses (travel, sleep, etc) for both practice and game scenarios.
  • Game scenarios are obviously very different than practice scenarios in terms of stress (psychological, physiological, etc) and I wanted this to be reflected.
  • I didn’t want to be dependent on any one data stream OR need to have all data streams. Expecting to have every data stream every day for every athlete would be foolish and impossible to actually achieve. I took the route of “some info is better than none and more info is better than some.” With this in mind, my model was built recognizing that on any given day I might not have or be able to obtain the same data sets for all athletes.
  • I wanted to weight data streams for importance when relevant.

So with these points in mind, and given my and the club’s limitations, I went with the following data streams grouped in to 3 categories and created a system around a 0-5 scale (although it’s possible to earn a daily value in excess of 6 under extraordinary circumstances).

  • Game stress:
    • Minutes played (converted to a 1-5 scale)…this value is ALWAYS available so it serves as the primary indicator for game stress. Reserves who don’t play = 1; 1-19 minutes = 2; 20-39 minutes = 3; 40-59 minutes = 4; 60-79 minutes = 4.5; 80-90+ minutes = 5. This recognizes the fact that athletes who sit on the bench but don’t play have still done something (warmup repeatedly) and the fact that the stress related to playing is not linear with minutes played.
  • Training Stress:
    • My own session rating (1-5 scale)…this value is ALWAYS available so it serves as our primary indicator for training load…not the same for every player on a given day. A day off would be a 0.
    • Survey data (1-5 scales) on fatigue, soreness and sleep quality…when taken I average it with the other points in this category.
    • Player session RPE (1-5 scale)…when taken, I average it with the other points in this category.
  •  Daily Modifiers:
    • Pro Zone stop-motion fitness data from games (when data is available it can modify the game stress value by +0.5 to +1 if the values are outside of norms for the player; unfortunately, we only have Pro Zone data from our home games and 3-4 other stadiums around the league).
    • Polar Team 2 Heart Rate data (+0, 0.5, +1 depending on Polar stress rating for a given player on that day).
    • Travel stress…under 4 hours of travel is worth +1 points and over 4 hours of travel is worth +2.0 (yes…I think travel can be that stressful).
    • Weight room session….a daily modifier of +0.5 or +1 depending on the intensity and duration of the session.
    • HRV….I don’t currently use but I have a place holder because we should be using it shortly. There’s a decent amount of research on HRV as an indicator for recovery and I look forward to implementing soon. It will be used as a daily modifier as above.

There are no hard and fast rules on these points, everything is modifiable at my discretion. For context, a daily stress of 0 would be a day off or a therapy day, a typical pre-game walk through would typically receive a value of 1 and a very taxing field training or game could receive a 5. Any given athlete could exceed a 5 depending on the modifiers.

Using this setup, I was able to meet the criterion laid out at the start of this post and keep things flexible and not overly complicated.

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Mike Young

Director of Performance at Athletic Lab
Mike is the Head Fitness Coach for the North Carolina Courage and North Carolina FC. He is also the owner and Director of Performance at Athletic Lab sports performance training center. He previously served as the fitness coach for the Vancouver Whitecaps and Carolina Railhawks. He has a PhD in Biomechanics, an MS in Coaching Science, and a BSS in Exercise Physiology and has coached Olympic and professional athletes in Skeleton, Track & Field, MLS and NASL Soccer, PGA Golf, NFL Football, MLB Baseball and Olympic Weightlifting. He has lectured around the world and authored 2 books and dozens of research and coaching articles.