Welcome to Complementary Training Community! › Forums › Performance Analysis, Testing, Monitoring and Statistics › Training Volume and Session RPE
18/01/2015 at 18:21 #16061
I am a first time strength and conditioning coach for a professional soccer team (second division) in the US. We do not have a budget for player monitoring, at this time, yet I know the importance of monitoring and planning the volume of training within every period of the season. I know that recording session RPE and multiplying this number by total minutes of training can give me a full load that I can track over time, but do you have any recommendations on giving RPE to the entire team during training? For instance, is there an app that allows ease of use and tracking vs. writing it down on paper? Do you have recommendations on RPE scales to use, timing of giving the score, and any other necessary or advisable element of player monitoring under a small budget?
John18/01/2015 at 19:31 #16062
Yes, sRPE seems to be good measure to begin with. Collecting data is always tricky. I wouldn’t use a paper since you introduce “dependence” of the scores (player A sees what player B wrote and that affect his score). You can collect data using Google docs and/or Excel online, but not sure if you can identify the athlete unless they write the name.
Andrew Flatt wrote something about it here: http://hrvtraining.com/2013/09/21/reviewing-survey-monkey-as-a-free-tool-for-daily-wellness-questionnaires/
As for the apps, well nothing simple enough and cheap enough as far as I know.
Mladen18/01/2015 at 22:39 #16063
How do you think this survey approach effects results when the timing of the response is not directly after training? If they do not check their emails until several hours after training, for a response, would this not diminish the accuracy of the response?
Also, does a system like smartabase provide any features for surveys/or monitoring wellness?12/03/2016 at 15:15 #17570
John you can use our football monitoring system free if you let me know how you find it and provide feedback on the system.
We use session RPE x duration to calculate AU load and automatically the system will calculate training monontony and strain.
We provide monthly reports using latex and send them back to you in a download section.
You can track wellness, any fitness test, physical data , msk screening data
It also links all the medical data with this to create reports we are just in the process of designing a data dashboard to provide all key useful metrics for the target audience.
I am particularly interested in cohesion in teams and bringing medical science sports science conditioning together, one of the ways is to be more open with information and making data relevant in a dashboard12/03/2016 at 15:25 #17572
I appreciate your offering. We are, currently, using the Kinduct system for everything that you have mentioned. I have built this system with their help to organize and individualize exactly what our training environment needs. It sounds very similar to your product. If you are familiar with Kinduct, I would value any feedback on differentiators that you know of.
Thanks12/03/2016 at 17:18 #17574
Hi John I guess it will be very similar although we have approached it from a different perspective, as I am a Doc the system started out very medically oriented. We are only just entering the sports science domain, I guess you started from the other end and developed the sports science side first before the medical ? I doubt there will be major differences. I suppose it comes down to cost and usability.
What is the cost of Kinduct for one squad e.g a soccer team ?
Systems aside however the whole training load TSB injury risk thing fascinates me. I do like the acute on chronic workload issue, in Triathlon our athletes train 35 – 40 hours a week for several consecutive weeks. I think basing assumptions on TSB may come unstuck unless previous long term chronic training loads are also considered. An example would be an athlete who has a large training ” base ” gets injured. He has time off but because of the base is able to accommodate a high acute training load to get back to where he left off quickly.
So it needs a ” factor ” in the equation perhaps Mladen you have an opinion on this ?
best James13/03/2016 at 16:04 #17578
EXACTLY the problem I am “struggling with” in the current project. Coming from a history of running 60km/week and having a month off then ramping to that same 60km across 4 weeks will yield high Acute:Chronic ratios which might give “false positive” injury prediction. I guess the approach might need to be more “Bayesian” and take apriori data, or the chronic need to be much longer (>6 weeks) or longer than any break that athlete used to do.
Other option might be to include “baseline” in both acute and chronic measures. For example adding normal “out of sport” walking distances. This might decrease the ratio and make it less “jumpy” when coming from break.
I am playing with using Exponential Moving Averages (EMA) and tuning the “alpha” parameter to get the best prediction. Not sure why we use 7/42 or 7/28 for Acute and Chronic estimates in the first place. Maybe some other ratios can yield better predictions?16/03/2016 at 20:02 #17602
Your knowledge of stats is far beyond mine. However I think the formula has to look much further than 6 weeks especially in an endurance athlete.
Its not that simple though.
A major factor to consider is Injury patterns within a sport and also Injury risk of the actual athlete.
Here is an example
2 Endurance athletes female both have a large training base of chronic workload.
Both develop a Meta tarsal stress fracture and lets assume they return at the same time.
One however has a slight -ve energy balance as she did not want to gain weight while being off
the other gained a little weight
On return they start running and as they are training partners do the same volumes intensities etc
6 weeks in one breaks down the other does not
The TSB will be the same for both but another factor in this case energy balance is relevant and has lead to the increase risk of bone stress response.
So prediction of injury is multi factorial using the agile approach these factors can be recognised by the team and dealt with effectively, but more importantly the athletes themselves need to self manage. One girl did the other took an ill judged risk.
You must be logged in to reply to this topic.