Computer Supported Training

Analysis of the Environmental Conditions and Sports Performance

Roberto Bellasio

, Alessandro Pezzoli

2,3

Jacopo Padoan

, Matteo Moncalero

3,5

and Andrea Boscolo

Enviroware, Via Dante 142, Concorezzo(MB), Italy

DIATI, Politecnico di Torino, C.so Duca degli Abruzzi 24, Torino, Italy

MeteoSport, Sport Psychology Research Unit, Motor Science Research Centre, School of Motor and Sport Sciences,

University of Turin, P.zza Bernini 12, Torino, Italy

FLJ Sport Solution, Via Druento 208, Venaria Reale, Torino, Italy

DICAM, Alma Mater Studiorum, Università di Bologna, Via Terraccini 28, Bologna, Italy

1 OBJECTIVES

Environmental and meteorological conditions have

an important effect on outdoor sport performances.

Wind direction and wind speed are important, for

example, during marathons, rowing and sailing races

(e.g. Pezzoli et al., 2012a). Temperature is also very

important in long running events.

Considering marathons, the American College of

Sports Medicine has established guidelines for

preventing health effects due to extreme weather

conditions (Cantu and Micheli, 1991). The

guidelines are based on the wet bulb, globe,

temperature index (WBGT index) which is based on

the combined effects of air temperature, relative

humidity, radiant heat and air movement. For

example race cancellation or voluntary withdrawal

are recommended when WBGT > 28 °C. Recently

El Helou et al., (2012) found that air temperature

and performance are significantly correlated.

Water temperature, for example, is an important

factor in swimming during triathlon races. Indeed,

below 13°C, the maximum swim distance is usually

shortened (e.g. Rulebook of the British Triathlon

Federation). Moreover, at temperatures below 11°C

it is recommended that open water swimming does

not take place.

Beside meteorological variables, other

environmental variables play an important role, such

as, for example, pollution levels. It is well known

and demonstrated (Schwartz, 1996) that the air

concentration of particulate matter (PM10 and

PM2.5) has deleterious effects on the respiratory

functions, even if they persist only for short times.

The same statement holds for other pollutants.

Notwithstanding the conditions of the outdoor

environment are often not considered when

evaluating sport performances - as if they were not

important – the sport performances are strongly

related to the environmental conditions.

The authors believe that environmental data will

acquire increasing importance in analyse sport

performances in the next future. Of course, such an

analysis will require the assistance of a specific

software tool, of which the main features are

summarised in this document. The software tool

would be very useful for athletes and trainers.

2 METHODS

The software is able to load the training data, for

example time, position and heart rate, monitored by

specific tools that are widely used even among non-

professional practitioners (Garmin, etc.). The

software tool also loads the meteorological data, and

any other environmental data, measured by one or

more monitoring station of interest. Other important

data to analyse are those monitored on the athlete,

such as for example his/her skin temperature or

humidity (e.g. Pezzoli et al., 2012b). These last data

are important when testing the features of particular

clothing. All the above mentioned data are generally

measured at different positions and at different

times. In order to carry out the analysis all the

external data must be time interpolated in order to

get them on the same times at which the

performance is available (synchronization process).

In a similar way, when the meteorological data

are measured by more than one station, a spatial

interpolation is needed to estimate the values at the

same positions where the performance has been

registered. There are situations where it is not

correct to carry out the spatial interpolation, in such

cases it is possible to indicate a radius of influence

of each station, or to define areas of competence of

each monitoring stations.

Of course the spatial interpolation may be more

Bellasio R., Pezzoli A., Padoan J., Moncalero M. and Boscolo A..

Computer Supported Training - Analysis of the Environmental Conditions and Sports Performance.

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

reasonable in some situations than in other ones. For

example, if N stations are measuring wind speed and

direction during a sailing race over a relative small

water surface, the spatial interpolation is more than

reasonable. On the other hand, if the same number of

stations is measuring the same variables during a

cycling race over a mountain region, the simple

spatial interpolation might not be reasonable. In such

cases a diagnostic meteorological model (e.g.

CALMET) would do a better work, but it cannot be

easily incorporated in a software as the one

described here.

For other variables, such as temperature, specific

algorithms are available to carry out spatial

interpolation even in complex terrain (Bellasio et al.,

2005). Indeed, air temperature at the ground depends

on some variables, such as the altitude above sea

level, the air temperature vertical gradient and the

land cover type. The interpolation of sparse

measurements of temperature over the domain

should account for these parameters.

Other meteorological variables are calculated by

the software if not available among the

measurements. For example, solar radiation can be

estimated starting from the geographic location of

the athlete, which depends on the time, and on cloud

cover, which can be obtained, for example, from

METAR (Meteorological Aerodrome Report) data.

3 RESULTS

The software reproduces the training track on a map

(the Open Street Map database is used), and for each

point a lot of information is given as, for example,

wind speed and direction in a specific training

location, temperature, or important indices such as

the wind chill or the Net Effective Temperature

(Leung et al., 2008). Of course, each point is also

related to the training data, as for example, the time

elapsed from the start of the exercise, the total

distance, the average and instantaneous speeds, the

heart rate, etc. The user is also allowed to export the

track in KML or KMZ format in order to view it on

Google Earth.

The performances are also summarised in tabular

format, and the user is allowed to export the tables in

many formats in order to use them in presentations

or for further analysis.

The first version of the software is still being

developed as a desktop application for PCs. Future

versions could be available also for Android and iOS

tablets.

4 DISCUSSION

Generally the sport performance are analysed

without considering the environmental conditions

even if these are closely related to each other.

In this Abstract was presented an innovative

computer supported training system that takes in

account all the sport performance parameters and the

environmental conditions. This tool, not yet

developed in the Sport Technology, is useful for

both athletes and coaches because it represents, with

a synchronization process, the environmental and the

sport performance values. This new technology

“opens the door” to a new discussion because in the

“environmental sensible” sports, coaches and

athletes can record the sport parameters and compare

their own performance with the environmental

conditions in which this was carried out.

REFERENCES

Bellasio, R., Maffeis, G., Scire, J. Longoni, M. G.,

Bianconi, R., Quaranta, N., 2005. Algorithms to

account for topographic shading effects and surface

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Cantu R.C. and Micheli L. J. (1991) ACSM Guidelines for

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Impact of environmental parameters on marathon

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Leung, Y. K., Yip, K. M. Yeung, K. H., 2008.

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Pezzoli, A., Cristofori, E., Gozzini, B., Marchisio, M.,

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