It is the beginning of the season for many team sports and it is the typical time when sports scientists start to struggle with manipulating the training load and making sure the players can survive a long season producing great performances.

I will try to analyse the current trends in the literature and provide some comments and some possible advice on how to put in place a meaningful and practical monitoring system to be able to inform the coaching process.

It is widely recognised that appropriate periodisation of training is fundamental for
optimal performance in sport. Until recently, it has been very difficult to quantify the
training loads (TLs) in team sports players due to the difficulty in measuring the various types of stress encountered during training and competition. Wearable sensors and well established psychometric tools as well as easy access to field-based biochemistry nowadays allow the collection of various data to be able to quantify and understand the training load as well as track the progression of the players’ performances. This can provide the basis for a critical assessment of the training process and feedback to the players and coaching staff of the progression.

Few comments before discussing the methods for data collection.

Training monitoring is becoming a standard operating procedure for many strength and conditioning coaches and sports scientists which is a good thing. However there are certain aspects that needs to be taken into consideration in order to understand the limitations of some training monitoring approaches as well as the potential of such methods to impact practice.

The latter is the most important aspect to be taken into consideration. Training monitoring becomes a useful thing to do ONLY if guides practice and informs the coaching process. Otherwise it becomes just a data collection exercise. I have seen many S&C coaches use a variety of tools and tests and despite the fact they have some nice continuous data it is clear that such data did not affect practice as training programmes continued in the same way despite the information available on training load and some effects.

So, first rule: training monitoring is a great way to understand how much work your athletes are doing and how they cope with it. Great thing to do only if it helps you in changing and evaluating your training plans.

The other aspect to consider is the limitations of what you measure, when you measure it and how many time  you measure it. All this information helps in understanding what the information tells you and what parameter of your training programme you should change according to the results observed.

Training monitoring needs two main parameters to be measured:

1) The amount of training your athlete is performing (the INPUT)

2) How the athlete is coping with the amount of training (the OUTPUT)

The INPUT can be measured in various ways and should contain some information on how much work the athlete has performed (such weights lifted in each session, distance covered in training and also the perception of how hard the session has been). The list can be more extensive, but frankly your ability to collect more and better data is limited by the equipment you have access to. Heart rate monitors, GPS and accelerometers, power meters in the gym are all available nowadays and allow a lot of measurements to be collected in team sports to help you gain more info on the intensity and the amount of training performed. I have presented few technologies in this blog and aim to do more in the future, so plenty of solutions for you to try.

However, not many people have access to technology (in particular the expensive software and hardware kits for more complex multisensor data collection). So, let’s discuss some simple training quantification methods and their applications.

This will require the use of spreadsheets to facilitate the calculations and the data collection as well as provide you the possibility to create reports and graphs. If you don’t have access to Microsoft ® Excel don’t worry! You can in fact download open office for free from here and have access to a free suite which allows you to have spreadsheets, graphs and presentations at no cost!

The Session RPE method

The session-RPE method of monitoring TL in team players requires each athlete to
provide a Rating of Perceived Exertion (RPE) for each exercise session along with a measure of training time (as suggested by Foster et al., 2001).

To calculate a measure of session intensity, athletes are asked within 30-minutes of finishing their workout a simple question like “How was your workout?” A single number representing the magnitude of TL for each session is then calculated by the multiplication of training intensity (RPE from Table 1) by the training session duration (mins).

Table 1. The modified RPE scale proposed by Foster et al. 2001

RATING	DESCRIPTOR
0	Rest
1	Very, Very easy
2	Easy
3	Moderate
4	Somewhat Hard
5	Hard
6
7	Very Hard
8
9
10	Maximal

Training Load = Session RPE x duration (mins)

For example, to calculate the TL for a training session 60-minutes in duration with the
athletes RPE being 5, the following calculation would be made:

TL = 5 x 60 = 300 AU (arbitrary units)

With a simple spreadsheet it is is therefore possible to track the training load of a team very easily just by recording the duration of training and making sure that each player at the end of each session provides you with the perceived exertion for that session.

Here is an example of what a score of a typical training period could look like:

The Black dotted line represents the average Session RPE for the team and each colour represents one of the players. In this way, it is possible to track how the overall training load is progressing and how each individual compares to the team.

The data can also be useful to track down the team’s session RPE and understand if overall the training load is going in the direction planned.

 

Further simple calculations of training ‘monotony’ and ‘strain’ can also be made from
session-RPE variables.

Training monotony is a simple measure day to day variability in training that has been suggested to be related to the onset of overtraining when monotonous training is combined with high training loads (see Foster, 1998).

Training monotony is calculated from the average daily TL divided by the standard deviation of the daily TL calculated over a week.

MONOTONY= DAILY TL/SD of TL over a week

Training strain can also be calculated as follows:

TRAINING STRAIN = weekly TL x monotony

The table below provides a simple example of a weekly training load in a semi-professional handball team with all the variables calculated.

Recent work conducted using RPE from 20 soccer players during 67 small sided-games soccer training sessions (Coutts, Rampinini, Castagna, Marcora, & Impellizzeri, 2007a) has shown that  the combination of blood lactate and HR measures during small-sided games were better related to RPE than HR or blood lactate measures alone. This work suggested that RPE is a valid method of estimating global training intensity in soccer. There isn’t such evidence in other sports, however nothing stops practitioners to try and see if it helps with their coaching process.

This is the first article of a series aimed at discussing the issue of monitoring training. I aim to present practical solutions to be able to start quantifying and understanding adaptations in team sports athletes.

Enough for now, time to get your spreadsheets sorted and start calculating what your players are doing so you are ready to apply the techniques presented in the next article!