Author: marcocardinale

I am the Executive Director of Research and Scientific Support in Aspetar (Qatar). The aim of this blog is to present and discuss issues related to sport and sports science.
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New Technology: Polar RS800 SD

I want to use this blog also to present some innovative technology I come across or help develop as I think modern sports scientists need to be aware of novel technologies and be able to make informed decisions on which tools they need to do their work the best they can.

Of course It is not the intention of this blog to be some form of advertisement for products/methods/procedures. The aim of the blog is in fact to provide unbiased information. When a possible conflict of interest could be present I will clearly describe my relationship with any company.

The product I am presenting in this article is genuinely exciting and improves our ability to monitor running sessions. Hence the reason to present some information on this blog.

I had the pleasure in the past months to work with Polar Electro (www.polar.fi) on this innovative technology which will definitively help many sports scientists.

The Polar RS800 SD is a novel running computer that allows the measurement of Heart Rate and Heart Rate variability synchronised with running mechanics parameters (stride frequency/length/pace etc etc.).

 

Polar RS800 SD

This is really a great product, running distance is measured during each run using a very simple Stride Sensor without the need of GPS. This means you can measure your running efforts also indoor.

It is very precise and extremely reliable and valid as demonstrated in our study presented at the American College of Sports Medicine annual conference in New Orleans last May.

The combination of HR and mechanical information allowed the development of a novel running monitoring tool called Running Index, this index can be measured in each running session and can provide indications of how training is affecting both fitness and running mechanics.

image

Furthermore, the integration with Adidas in the Fusion system (clothing/shoes/running computer; www.adidas-polar.com) allows each athlete to use this technology attaching the chest receiver to t-shirts or bras and enclosing the Stride Sensor into the shoe insole.

 

fusion 

Finally with this technology a coach can email the athlete a training programme indicating not only Heart Rate zones, but also pacing strategies that the athlete can follow on the running computer.

Each training session can also be analysed looking at a combination of HR and mechanical data:

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All in all, a great tool to use for training planning and monitoring and also for research use. We will be publishing soon the results of our research studies validating and using this technology.

 

Disclaimer: The author of this article is a consultant to Polar Electro. 

data analysis, Strength testing, Strength Training

Testing team sports athletes and analysing data

Many strength and conditioning coaches and/or exercise physiologists are nowadays employed to work with team sports. Testing and monitoring training is now becoming standard practice and data analysis, data mining and the ability to produce meaningful reports is a necessary skill of the elite sports science support staff. I this short post I will not discuss the main aspects to consider when performing a test and/or the limitations of testing procedures. I will just present simple examples of reporting data using Microsoft Excel.

 Womens_Football_360x2701

When dealing with large squads, single athlete’s scores should be analysed and continuously monitored to make sure the athlete is progressing and improving. However, in order to profile areas of improvement it is important to compare the single athlete to the group or to a known group of elite performers.

A very simple way for doing this with excel is to collect all the data in a single sheet with the name of the athlete in the first column and all the tests scores in the following columns. Then, when the average values and the standard deviation for the team is calculated, all scores of each individual player can be transformed in Z-Scores. In Excel this is possible using the function STANDARDIZE which returns a normalised value from a distribution characterised by mean and standard deviation.

The syntax is the following:

STANDARDIZE(x,mean,standard_dev)

X   is the value you want to normalize.

Mean   is the arithmetic mean of the distribution.

Standard_dev   is the standard deviation of the distribution.

Once each score is normalised, spider charts can be used to see how each individual player scores as compared to the team scores. Two examples are given here. Zero is the team score, every score higher than zero means that the athlete scored better than the average value, every score below zero means that the athlete scored less than the average value.

Figure 1: This is an athlete that outscores the team average values in all tests

image

Figure 2. This is an athlete outscored team results only in sprinting.

image

When we plot the results in this way we can clearly identify areas where we need to make an impact with a training programme. So, while in athlete JL we need to put a lot of emphasis on sprinting abilities, on athlete H we need to do a lot of work on strength and power. With this approach we can then track not only athlete’s development in different areas but also how they evolve in comparison to his/her team scores. Individualization of training is the key aspect to take into consideration when working in team sports. Data analysis allows the coach, the physiologist and the sports scientist to profile each individual player and provide appropriate training interventions.

data analysis, Strength testing, Strength Training

Testing team sports athletes and analysing data

Many strength and conditioning coaches and/or exercise physiologists are nowadays employed to work with team sports. Testing and monitoring training is now becoming standard practice and data analysis, data mining and the ability to produce meaningful reports is a necessary skill of the elite sports science support staff. I this short post I will not discuss the main aspects to consider when performing a test and/or the limitations of testing procedures. I will just present simple examples of reporting data using Microsoft Excel.

 Womens_Football_360x2701

When dealing with large squads, single athlete’s scores should be analysed and continuously monitored to make sure the athlete is progressing and improving. However, in order to profile areas of improvement it is important to compare the single athlete to the group or to a known group of elite performers.

A very simple way for doing this with excel is to collect all the data in a single sheet with the name of the athlete in the first column and all the tests scores in the following columns. Then, when the average values and the standard deviation for the team is calculated, all scores of each individual player can be transformed in Z-Scores. In Excel this is possible using the function STANDARDIZE which returns a normalised value from a distribution characterised by mean and standard deviation.

The syntax is the following:

STANDARDIZE(x,mean,standard_dev)

X   is the value you want to normalize.

Mean   is the arithmetic mean of the distribution.

Standard_dev   is the standard deviation of the distribution.

Once each score is normalised, spider charts can be used to see how each individual player scores as compared to the team scores. Two examples are given here. Zero is the team score, every score higher than zero means that the athlete scored better than the average value, every score below zero means that the athlete scored less than the average value.

Figure 1: This is an athlete that outscores the team average values in all tests

image

Figure 2. This is an athlete outscored team results only in sprinting.

image

When we plot the results in this way we can clearly identify areas where we need to make an impact with a training programme. So, while in athlete JL we need to put a lot of emphasis on sprinting abilities, on athlete H we need to do a lot of work on strength and power. With this approach we can then track not only athlete’s development in different areas but also how they evolve in comparison to his/her team scores. Individualization of training is the key aspect to take into consideration when working in team sports. Data analysis allows the coach, the physiologist and the sports scientist to profile each individual player and provide appropriate training interventions.