Category: training

Monitoring training load in Team Sports: Quo vadis? #1

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






Very, Very easy






Somewhat Hard





Very Hard





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!

Handball and sports science….why so behind?

Handball (also known as team handball, Olympic handball or European handball) is a team sport in which two teams of seven players each (six outfield players and a goalkeeper) pass and bounce a ball to throw it into the goal of the opposing team. The team with the most goals after two periods of 30 minutes wins. Handball is by far my favourite sport. I played handball for many years in Italy (a bit more seriously) and for a couple of years in Scotland (for fun) and was a coach for few years and despite the fact I am not coaching handball anymore, I still cannot believe how old fashioned handball training is.

Handball is a professional sport in many countries. In Germany, Spain, Denmark and Norway and many other European countries (mainly in Eastern Europe) there are full time coaches, players and support staff. The European Champion’s League is televised on Eurosport and in some games you can see more than 15000 supporters watching the game! In few words…it is a serious business!

(The Croatian Ivano Balic….possibly the best player in the World for Men’s Handball)

(The Hungarian Anita Görbicz….possibly the best player in the World for Women’s Handball)

If you have never seen a game of handball….you can get some ideas of how it is played on YOUTUBE.

Handball is a sport which is growing very fast in terms of spectators and media coverage, and is one of the top sports in Europe in terms of employment opportunities for coaches and sports scientists. Handball is an Olympic sport since 1972 in its indoor version. However, despite all the media interest, the sponsorships and the fact that Olympic medals are at stake, very little is available in terms of sports science. Very few research activities have been conducted and there is a paucity of published literature. A simple analysis on pubmed using the keyword “Handball” provides 343 entries (with many papers on injury rates and/or on a different sport also called Handball and played mostly in the USA and Canada). A keyword search for Basketball presents 1734 papers, and volleyball presents 693. In simple terms, there is clearly a paucity of information on Handball.

When we then analyse the scientific literature available, we then realise how little has been published on training and performance aspects as most of the literature refers to injuries in Handball.

A very recent review from Ziv and Lidor (Ziv, Gal and Lidor, Ronnie(2009) ‘Physical characteristics, physiological attributes, and on-court performances of handball players: A review’, European Journal of Sport Science, 9: 6, 375 — 386) has summarised all the available literature on handball and highlighted how little is known about this wonderful sport.

I have previously discussed on this blog specific aspects of physical preparation of handball players. However I would like to point out again that little is known about physiological demands and most of all about physiological characteristics of elite handball players. Ziv and Lidor summarised in Table 1 of their paper what has been so far published:


From the paucity of data on elite performers, you can clearly see that elite handball players are bigger and have more muscle mass than non elite. When I worked in Italy we used to benchmark our youth national teams and seniors with the World elite and it was always clear that in order to be World leading in this sport you needed height and fat free mass in particular in some playing positions.

Endurance capacity has always been a matter of discussion in the Handball coaching community. Despite the fact that Handball is clearly an intermittent sport (played on a 40m court!), a lot of attention was always devoted to endurance capacity. However data clearly show that handball players have a VO2max of 50-60, indicating that probably endurance capacity per se is not the most important performance-limiting factor. This has been supported by one scientific paper published by Gorostiaga et al. In fact, they conducted a study that examined endurance capacity in elite and amateur handball players while running at 10, 12, 14, and 16 km/h found no differences in mean blood lactate concentration or in mean heart rate (Gorostiaga et al., 2005). The mean running velocity and heart rate that elicited a blood lactate concentration of 3.0 mmol. l-1 were similar in both elite and amateur players, suggesting that endurance capacity per se does not differentiate elite from amateur handball players. In addition, no significant differences in endurance running at 10, 12, 14, and 16 km/h were observed in elite players over the course of a season (Gorostiaga et al., 2006). Despite this, a lot of handball coaches still put emphasis on training endurance capacity mostly in the form of long steady state running. However, it is important to state that we don’t have data on the top 5 national teams in the World and we have no idea if they are really different from the rest. Also, considering how fast the game is now played, we should clearly reconsider how to train handball players as I suspect metabolic demands are a lot higher than the ones recorder in the early 80s.

The most recent work on motion analysis characteristics is the one published by Luig et al. (2008) which conducted time-motion analyses during nine games of the 2007 men’s World Cup. The analyses were conducted using a computerized match analysis system. Four movement categories were defined in this study: walking, slow running, fast running, and sprinting. Playing time was significantly higher in wings (37.37 +/- 2.37 min) and goalkeepers (37.11 +/- 3.28 min) than backcourt players (29.16 +/- 1.70 min) and pivots (29.3 +/- 2.70 min). Total distance covered was higher in wings (3710.6 +/- 210.2 m) than in backcourt players (2839.9 +/- 150.6 m) and pivots (2786.9 +/-238.8 m). As anticipated, goalkeepers covered the shortest total distance (2058.1 +/-90.2 m). The total distance covered by field players consisted of 34.3 +/- 4.9% walking, 44.7 +/-5.1% slow running, 17.9 +/- 3.5% fast running, and 3.0 +/- 2.2% sprinting. Compared with other players, wings covered significantly shorter distances while slow running but significantly longer distances while fast running and sprinting. The distances covered are a lot less of what was reported in the 80s and is possibly due to how the game has changed with a better use of substitutions during the game to make sure players can perform fast movements for almost 21% of the total distance covered. To date, no study has been performed on oxygen consumption during handball games, but it is quite easy to predict what to expect considering the fast pace of handball playing. Quite simply, there is no information on handball performance which can help coaches identifying what the real demands are in particular at the very elite end of performance. I am sure data exist possibly in languages I cannot read and understand, I would be in fact very surprised if the elite handball nations don’t have such data to identify what they need in order to win an Olympic medal.

More data exist on strength and power capabilities and how training can influence throwing speed:



Again, few data here, but it seems feasible to suggest that strength training can improve throwing speed at least in non-elite players. The effectiveness of strength training on improving throwing speed in World class players is debatable mainly because there are no data to support or disprove this possibility. However, considering that Gorostiaga et al found a significant correlation between total strength training time and standing throwing velocities (r=0.58), and with my group we always improved throwing speed in national team players following a strength training programme, it seems feasible to suggest that strength training can improve throwing speed even in elite players. Throwing speed is of course only one part of the story, as accuracy is needed in order to score a goal as well as the ability to “beat” the goalkeeper. Incredibly there is virtually no information on interventions able to improve accuracy in handball players….

Handball is quite a demanding sport and being a “contact” sport eposes the players to a relatively high risk of injuries. Data from Beijing Olympics (Junge et al. 2009) clearly shows the high injury rates observed in Handball. 92% of the injuries occurred in competition. Of course during the Olympics teams tend to lower the intensity of training sessions and minimise physical contact in order to avoid injuries. However, it would be interesting to investigate injury rates in training and competition to find out if training sessions are too far from the competition demands as I suspect this is the case in many countries.


Who is going to invest in research activities on handball performance? Which country will be able to identify marginal gains to produce better players? Which country will be able to identify nutritional strategies to maximise performance in handball?

Maybe in few years we will have an answer, in the meantime, we can enjoy the competitions and hope that more research activities will be published on peer reviewed journals and websites for the good of coaches and players.

Playing videogames and social networking….good news or bad news for sports people?


It has become a matter of discussion in recent years and most of all a matter of concern for most of us working in sport: video games. Athletes nowadays travel with their playing consoles around the World, spend a lot of time updating their social network sites and personal websites, watch DVD and do all sorts of things in their “downtime” which are totally different from the old times when they used to go out for a walk, play cards and/or read.

Times changes, habits and behaviours change and we are all totally taken by the fast advancements in technology which nowadays provides us also with entertainment tools so small that they are able to travel with us.

Image copyright (

While the use of such tools can be seen as a useful way to keep the athletes “indoor” and avoid the dangerous temptations of wondering outside the hotels and training camps facilities, we should have a more critical approach to the problem and try to understand how we can control the use of technology to make sure that it does not become “abuse” and it starts to impair performance.

I would like to discuss few examples and provide the rationale for my thinking. Ideally I would like to stimulate some discussion and possibly stimulate some research activities in this area, as I strongly believe it needs investigation as I have seen some quite spectacular effects of athletes playing all night with videogames and messing up their training and/or their competitions!

First of all then, let’s discuss video games. My suggestion to all athletes travelling to Beijing last summer and to all athletes travelling to Vancouver this winter is to avoid at all costs playing video games, watching DVDs, using computers at night if they wake up because of Jet Lag. My rationale is pretty simple. In order to quickly recover from Jet Lag we need to make sure that sleep occurs at the right time of the day-night cycle. Most of the times, some athletes don’t consider getting help from sleeping tablets and tend to tackle the issue with bed routines. However, when they wake up at 3 am with their body thinking it is time for lunch or dinner, they should make every possible effort to avoid using light sources and getting back to sleep. Why that? Playing a video game on a computer or game console, using a laptop for social networking and watching a DVD can expose you to up to 300 nits (unit of measure of luminance) of light.

Light exposure through the visual field has been shown in various studies to stimulate brain areas leading with circadian control and the pineal gland dealing with hormonal pulsatility. Circadian rhythms in physiological, endocrine and metabolic functioning are in fact controlled by a neural clock located in the suprachiasmatic nucleus (SCN).


(Image from “The New Genetics”, US Department of Health:

This structure is endogenously rhythmic and the phase of this rhythm can be reset by light information from the eye. It is therefore possible that if somebody is exposed to light of the intensity produced by laptops and similar tools coupled with physiological and psychological arousal generated by the interactive nature of the tools (e.g. video games and social networking chats) might delay adaptation to the new time zone. In simple terms, this is pretty much because light exposure is telling your brain it is time to wake up! In humans, bright light exposure early in the biological night delays circadian timing, while bright light exposure late in the biological night advances circadian timing (Khalsa et al., 2003). However, the levels of light exposure employed to shift the circadian clock have typically been fairly high, ranging from 2,500 – 10,000 lux (Crowley et al., 2003; Czeisler et al., 1990; Horowitz et al., 2001), far above the lighting received by a Laptop screen. However usually laptops and video games use is associated with physiological and psychological stress which could contribute to altered sleep patterns not only in jet-lagged subjects but also in athletes in a training camp that have not crossed any time zone.

Light is not the only concern then. Playing video games has been shown to have some interesting physiological effects. Children playing Tekken 3 (Namco Hometek Inc) where shown to have Significant increases from baseline for heart rate (18.8%; P<.001), systolic (22.3%; P<.001) and diastolic (5.8%; P=.006) blood pressure, ventilation (51.9%; P<.001), respiratory rate (54.8%; P.001), oxygen consumption (49.0%; P<.001), and energy expenditure (52.9%; P<.001). Effect sizes for these comparisons were medium or large. No significant changes were found from baseline to after video game play for lactate (18.2% increase; P=.07) and glucose (0.9% decrease;P=.59) levels (Wang & Perry 2003).



Children playing for 60 minutes Need for Speed—Most Wanted (Electronic Arts, Redwood City, CA presented impaired sleep patterns and a reduction in verbal cognitive performance (Dworak et al. 2007).

Despite the fact that a violent video game (Over 85% of games contain some violence, and approximately half of video games include serious violent actions [e.g., Children Now, 2001]) does not seem to determine an increase in cortisol levels (Ivarsson et al., 2009) it is clear that it is  capable to provide enough physiological and psychological disruption to a normal sleeping pattern.

The smaller video game literature has found that playing violent video games causes increases in aggressive behaviour, aggressive cognitions, physiological arousal, and decreases in prosocial behaviour (Anderson et al., 2004).

Ivarsson et al (2009) showed a strong influence of violent video gaming on heart rate variability indices. In particular total power and very low frequency of the r-r intervals was shown to be higher while playing a violent video game as compared to a non-violent one.

At the moment there is no study which has been looking at the effects of playing computer games at night on performance. However all the information I cited before seems to suggest some marked negative influences in particular if the athlete is travelling to a new time zone.

So, what is the advice then?

1) If your are travelling to train and compete and are crossing time zones, avoid using your laptop, DVD player, Ipod and similar tools and video games devices during the night. Get back to sleep!

2) If you are training and or competing the following day, avoid all of the above the night before such activities (training and competing) take place

3) Recovery time is meant to be for rest and piece. You don’t want to play street fighter with your best mate and have your blood pressure, heart rate and cortisol levels go sky high because you lose!

4) There is a time and place and most of all a duration for your gaming and computing activities, make sure you don’t negatively affect your performance because of that!