Category: handball

Virtual reality and Handball Training


I have been recently reading a lot about the use of virtual reality in sport, mainly because I strongly believe in the potential of using this technology in rehabilitation and training. While looking for specific articles, I found some interesting work conducted on Handball Goalkeepers by a French group.

The situation between a shooter and a goalkeeper in Handball is fundamentally a duel. The shooter wants to be beat the goakeeper and score a goal, the goalkeeper wants to beat the shooter and make a save!

In a duel between two players, previous research works demonstrated the role of the opponents’ motions. It means that elements in the opponent’s movements make the other player choose an appropriated reaction. The ability to utilise visual cues and “anticipate” what the shooter is doing is what makes a World class handball goalkeeper.

Endless hours of shooting training help goalkeepers in developing the appropriate strategies and moves, however one could argue that the ability for a goalkeeper to progress depends a lot on the quality of players providing him/her with “cues”. Form a coaching standpoint, a goalkeeper always facing shooters “easy to read”, would never progress further, so allowing him/her to train with more advanced shooters and a variety of shooters and situations can improve the goalkeepers’ ability to develop.

This is particularly true when we are thinking about progressing young goalkeepers and fostering talent. Having been in handball for many years I am still surprised about how old fashioned goalkeepers’ coaching still is.

There is a lot of emphasis on technique and position (all very important), virtually no work on eye movements and visual abilities, and virtually no work on advanced cues and anticipation (due to the limitations of the quality of shooters and drills). Virtual reality could be an innovative solution, and in the promising work of our French colleagues we might find a new way to progress goalkeeping to a whole new level.

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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.

Training team sports athletes: Periodization and planning strategies. Part 2


Time goes fast and I just realised how long ago I wrote the first part of this article. So, let’s try to start from where I left.

Monitoring training and avoiding mistakes was the topic I left the readers with. Generally speaking, technology in this field is moving very fast and in the very near future I envisage the ability to be able to monitor physiological and behavioural responses to training in team sport in real time, with the ability to make some sensible decisions to optimise training gains in team players.

Heart rate monitoring for example has become nowadays accepted standard practice in the team sports World and also in the Football/Soccer environment nowadays many training sessions are monitored to quantify the effort of the players and the characteristics of the drills employed by the coaches.

In order to quantify training intensity, due to the intermittent nature of team sports, time spent in various intensity zones is quantified. A simple classification is presented and it is based on defining zones with heart rate presented as a % of Heart Rate Max or Heart Rate Reserve.

Of course, in order to have a precise determination of such training zones it is important to measure Heart Rate Max rather then using the 220-age estimation.

Because of the linear relationship between the intensity of exercise and the perception of effort, a simple scale is proposed here:



Heart Rate measurements can be used to define not only the overall intensity of the training session, but also the intensity and demands of individual sessions. This approach allows the coach/S&C coach to develop a database of drills which can impose on the players similar demands in order to be able to change sessions and reduce the boredom factor.

By using Heart Rate based measures in combination with blood lactate it is in fact  possible to compare game-specific drills with more generic drills such as intermittent sprinting and/or repeated sprints and verify the demands on the same player of such activities.

In the following example we can see how intermittent sprint drills (10s activity-20s rest) provided a similar physiological response to 3 vs.3 in Handball players.



This suggests that when training time is limited, the use of well planned technical and tactical drills can represent a significant training stimulus. Of course, what is important to remember is the fact that game-like drills can be effective only if we know how demanding they are. The physiological responses to such drills depend in fact on the rules used in the drills, the space, the number of players and the quality of the players involved. Generalising data findings from other sources is not the way to plan training. In order to successfully implement game-like activities in your training programme requires accurate measurement of the physiological demands in your particular group of players.

In elite team sports athletes it is also effective to plan specific sessions in which game-like drills are combined with more generic repeated sprint drills. A practical example could be to alternate 10 minutes of a game-like drill with repeated sprint drills (such as shuttle runs etc.).

This approach can be very effective and can lead to improvements in aerobic capacity without the need to dedicate too much time to training activities which not involve technical and tactical elements. The following data are the yo-yo test distance scores of an elite handball team performing for one month training sessions characterised by game-like activities mixed with intermittent work.



This is of course only part of the picture. In team sports we want athletes to be able to perform high-intensity movements for the duration of the game, but we also want them to be fast, strong and powerful. Strength training and monitoring activities aimed at maximising gains in this area of the players’ fitness are very important and will be now discussed.

Strength and speed

First of all, we have to take into account what kind of variables we are interested in. Acute variable can help us in understanding how a session is going and how it is affecting the player.


Chronic variables can give us more information on how effective a period of training has been and where is our training programme leading to.


The use of measurement tools to analyse single sessions can be a very useful way to understand how the athlete is coping with the load we have imposed on him/her and also to understand how fatiguing is the session. If heart rate monitoring is important to understand the physiological demands of game-like drills, we need to use some form of monitoring to understand the responses to strength training sessions. Iso-inertial dynamometers are becoming more and more affordable and can provide a good solution. Monitoring strength training sessions offers the following benefits:


However the last point is the most important one: if your monitoring activity does not provide data which are useful to improve your training prescription you are just collecting data which will not impact on the quality of training!

The following is a typical example of monitoring a training session using a linear encoder during a Bench Press exercise. Two athletes are lifting the same weight, they both have similar 1RMs, however by measuring their power output during the set we can see how different fatigue patterns occur:


If the aim of the session/programme is to maximise power output, we need the athletes to be able to produce power within 90-100% of their maximum power for the given load. By monitoring how they respond (provided that they are encouraged to perform the concentric phase of the lift as fast as possible), we can improve our training prescription by dividing sets and reps to make sure the target power output is attained for the total volume of reps we want the athlete to perform in our programme.

Why such focus on power and speed of movement? Simple, it seems that during rapid movements an increased activation of fast motor units or decreased activation of the slow ones may occur. So, if we aim to improve power and speed in our athlete we should always ask them to perform the concentric phase as fast as possible. The work of Linnamo et al. (2002) can explain in justifying such approach. In their study, Linnamo and coworkers had 6 subjects with different fiber type composition characteristics:


This is what you would typically encounter in a team sports scenario. They asked the subjects to perform two types of sessions (explosive and heavy resistance):

[EE] 5 x 10 reps @40+ 6% of MVC

[HE] 5 x 10 reps @67 + 7% of MVC

MVC is the maximal voluntary contraction (measured isometrically).

image image

The difference in the median frequency of the surface EMG (after rectification and fast fourier transformation of the EMG raw signal) between the two modalities of exercise clearly suggest a difference in motor unit recruitment patterns when performing the two types of loading. Note that the sets and reps where the same, with a difference in external load and velocity of movement.

By measuring in real time such parameters it is possible to change the session while it is being performed (again, if the aim of such session is to improve power and speed). The following example from Lore Chiu and coworkers (2004) shows that if you are monitoring the speed of the barbell/weight stack and you observed a decrease in speed, of course by changing the external load you can make sure the speed of execution is increase and is matching what you planned for.


The key message here is that we should still plan sessions with sets x reps x load, but we should be able to measure the output in order to make sure the athlete is performing what we require in order to maximise the adaptations and make sure he/she is not wasting time in the gym!

Monitoring strategies to identify recovery and readiness to train

While everyone tends to accept the general adaptation syndrome paradigm, whereby a training stimulus challenges homeostasis and takes a certain amount of time to be recovered. Very few people actually measure what it means and if it is possible to track the various phases of responses to a single training session.


The following approach is an example conducted with an Handball team using vertical jumping tests (in this case the Counter Movement Jump [CMJ]) before, during and after a session of plyometrics (approximately 200 jumps in total). You can see that while the team average score seems to be recovered within 24 hours of such session, some individuals have recovered (BP) and some haven’t (SO). Individualisation should be a fundamental approach to team sports! But if you don’t measure anything…how can you individualise? While everyone talks about it, I still see scarce evidence of this actually occurring, where are the data?



Biochemical monitoring of training, long term monitoring of adaptations

I have already presented examples of monitoring training load and adaptations in some team sports showing that different approaches of periodisation can be used depending on the level and the performance goals of the team and both approaches can produce improvements in the players when it counts ( if you know what you are doing.

Testing modalities and ways of tracking individual and team progress have also been discussed here before. I will spend few words with regard to hormonal monitoring which is now becoming something everyone claims to be an expert in. I recently came across a lot of manufacturers which claim can sell devices able to measure quickly (almost realtime) salivary concentration of hormones (in particular Testosterone and Cortisol) and/or measure hormones in capillary blood.

I regret to inform all readers that to my knowledge there isn’t a single device which provides good reliability and validity of the measures taken, furthermore while measuring such things can be useful, it is still an expensive exercise which requires time and most of all real expertise not only in conducting the necessary assays to measure hormone concentration but also in understanding the validity and the meaning (and most of all the limitations) of the data collected.

To real make and impact, hormonal monitoring should be performed routinely, with many data points during the day, and following strict guidelines in terms of sample collection, storage, preparation and analysis. Collecting only baseline morning fasting hormonal measures might not help in explaining the bigger picture. In the example below, Cortisol levels are presented during the course of the day showing a clear circadian pattern. The Blue line represents “normal” patterns of cortisol secretion. The red and the black line represents alterations I have observed in some athletes following specific training periods. The red and black dots represent the single point, morning fasting sample. As you can see, having only 1 data point might mislead you….as clearly while the subject represented by the black line would appear to have lower cortisol values in the baseline sample, his cortisol pattern is different from normal and his cortisol values are actually overall higher during day and night suggesting some indications of overreaching/overtraining.


There is a clear message here. Beware of the so called experts…hormonal monitoring is an interesting field, but still no conclusive evidence on how it actually work, most of all, very few people understand it but many are out there selling all sorts of services and “expertise”. The use of testosterone and cortisol as biomarkers to understand training adaptations is an interesting field but requires the appropriate knowledge of physiology, techniques and limitations in order to be used to make the “right calls” when it comes to training prescription. In the last few weeks I have been working with my colleagues Blair Crewther, Christian Cook, Robert Weatherby and Paul Lowe on an extensive literature review addressing the evidence and implications of the short term effects of testosterone and cortisol on training adaptations and performance. I will keep the readers up to date when such paper is published (hopefully soon).



Writing training programmes is a mix of art and science. The scientific model should drive any inquisitive strength and conditioning coach in designing appropriate and effective programmes. Team sports are challenging in terms of trying to maximise performance with strength and conditioning programmes. They are challenging because of the different types of athletes involved in them, the complexity of the performance requirements and the difficulties of seasons with cups, playoffs etc. The only way to succeed is to approach training with an “evidence-based” attitude. Trying to put in place measurements and monitoring tools able to inform and guide the training process. The devil is always in the details. Group analysis should be followed by individual analysis in order to develop individualised programmes aimed at maximising performance in each single athlete of your team. Statistical procedures should be used to understand and treat the data better, but the attitude towards such approach should be to gain a better understanding of training adaptations rather then trying to find what is significant at P<0.05. As my friend Will Hopkins wrote some time ago:

If a treatment shows an improvement with P<.01 it means that there is a probability of 99% of the treatment being effective.


If you are terminally ill, would you take a pill that gives you 80% chances of surviving (P<.20)?

In athletics terms…if a training programme can give you 80% chances of a 2% improvement which could win you a gold medal…would you use it…or would you wait for P<0.05?