Kinematic Analysis in Official Soccer Matches: Preliminary Results

GPS Analysis in Soccer Matches

Gabriele Mascherini

1,2

, Andrea Cattozzo

1,2

, Giorgio Galanti

and Stefano Fiorini

Sports Medicine Center, University of Florence, largo Brambilla 3, Florence, Italy

Italian Football Athletic Trainers Association, via D’Annunzio, Florence, Italy

Keywords: GPS, Match Analysis, Soccer.

Abstract: Soccer match analysis was initially establish by coach to evaluate tactical aspects, after this approach was

used for physical effort. Previously this assessment has been done by video interpretation of the matches.

The aim of this study was to analyze the official matches in adults athletes for the first time with a wearable

device as GPS. Five official games of sixth division of Italian Football League were assessed with GPS

system. Parameters represented the volume of physical activity as Total Distance covered and Relative

Distance derived directly from the instrument, while the values of intensity as speed, acceleration and

deceleration have been indexed respect to the maximum individual of each athletes. Was also made a

tactical analysis respect the roles of players. Values of volume shows lower values than previous studies,

while the values of intensity confirm the data present in the literature. Tactical analysis shows

predominantly low speed for defenders, medium for midfielders and high speed for forward. Acceleration

not differ significantly between the roles. Decelerations are predominantly for midfielders. These are the

preliminary results of a larger study involved for the first time soccer official matches assessed with a

wearable system. In addition a new approach has been used in order to individualized threshold for speed,

acceleration and deceleration.

1 INTRODUCTION

Video analysis of matches was introduced into

soccer to check the roles assigned to each player and

the real tactics performance decided by the coach.

Soccer federal laws prevent players from wearing

any technological devices, therefore video analysis

is the only method allow to evaluate official

matches. This method was also used for physical

performance through parameters as “total distance

covered”, “speed” and “acceleration” (Mohr M,

2003; Bangsbo J., 1994).

Recently many studies were conducted in order

to find an uniform values on the metres covered by

athletes during a match. At present there are still

differences in “speed” and

“acceleration/deceleration” of soccer players in

official matches (Cummins C., 2013).

Respect “speed” values in a soccer match, the

researchers agreed to create six areas of intensity,

but the identification and the description of these is

still unclear.

At present there are few studies on the evaluation

of “acceleration” and these were made by sprint tests

during a training session (Castagna C, 2009; Bucheit

M, 2010).

Recent studies have introduced the use of the

Global Positioning System (GPS) as a tool for

analyzing the performance of athletes (Gray AJ,

2010).

Studies with GPS system in sports show a

growing attention to an individualized assessment.

One method is to identify the maximum value of

each athlete of team regard his performance of

“speed”, “acceleration” and “deceleration” (Abt G,

2009)

A second approach is to analyze tactical aspects

of each role in team sports (Di Salvo V, 2007).

The first aim of the study was to, for the first

time, report kinematic values of soccer performance

of five official matches with a wearable device. This

data will be compared with the ones present derived

from video match analysis.

The second aim was regard tactical aspects, in

order to verify any possible differences of physical

effort according to role of each soccer player.

205

Mascherini G., Cattozzo A., Galanti G. and Fiorini S..

Kinematic Analysis in Ofﬁcial Soccer Matches: Preliminary Results - GPS Analysis in Soccer Matches.

DOI: 10.5220/0004995402050209

In Proceedings of the 2nd International Congress on Sports Sciences Research and Technology Support (icSPORTS-2014), pages 205-209

ISBN: 978-989-758-057-4

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

2 METHODS

Observational Study

An Italian Soccer team playing in Campionato di

Eccellenza (sixth division) was analyzed.

According with the Regional Committee of the

Italian Soccer Federation, players wear GPS devices

during all official matches of the regular season

2013/2014.

10 soccer players, (age 23.1±2.1 years, weight

73.7±5.3 kg, height 176.5±11.9 cm) wore under

their official shirts the GPS (K-Sport - Italy,

sampling frequency of 10 Hz), and kept on the

device on for the time they played during first five

matches of the season.

During the week before the first official match

tests were carried out to determine the maximum

value of speed, acceleration and deceleration of each

team member.

Every athletes, wearing the appropriate GPS

equipment, complete:

- three 50 m all out sprints to determine their

maximum speed,

- four 20 m all out shuttle sprints to determine their

maximum accelerations and maximum

decelerations.

Therefore during the regular season, at the end of

each match, GPS device was downloaded and the

data were analyzed, values were tabled and divided

into the following categories:

- time played (T, min);

- total distance covered (TD, m);

- relative distance - defined as the ratio between

total distance and time (RD, m/min).

In addition to these it tabled the values of speed,

deceleration and acceleration were divided into

zones:

- speed, divided into 6 zones (S1, S2, S3, S4, S5,

S6, m/sec);

- deceleration, divided into 4 zones (D1, D2, D3,

D4, m/sec

);

- acceleration, divided into 4 zones (A1, A2, A3,

A4, m/sec

Each division was estimated considering the

individual maximum value of speed, acceleration

and deceleration.

For the division of speed there is still no

consensus, however we chose the six zones present

in literature (Barbero Alvarez J, Hill-Haas SV,

2008), choosing the interval from 0% to 20% for S1

and then every 16% up to 100%, in order to have a

uniform percentage breakdown.

This is the first work with a threshold approach

for values of acceleration and deceleration, therefore

the four categories were chosen for every 25%.

The primary aim of the present study was to describe

the physical activity of soccer player for the first

time with the use of a wearable system, this being an

observational study no statistical analyses were

performed for this purpose.

The roles of the players for the tactical analysis

was decided to divide the 10 players in:

- 2 Full Back

- 2 Central Defender

- 3 Midfield

- 2 Lateral Forward

- 1 Forward

Averages and standard deviations were calculated

into a new subdivision, and then tested by the Anova

Test to establish any significant differences between

five different samples.

After five competitive games have been downloaded

from the GPS, 50 players who played at the start, we

eliminated from the statistics all the players replaced

during the match so that it does not interrupt the

minutes and the meters of complete match.

They were therefore excluded 10 athletes:

3 lateral defender, 2 central defender, 3 midfield, 1

lateral forward, 1 forward.

3 RESULTS

The average of maximum values obtained from tests

before the season are:

 9.14±0.32 m/sec for speed

 7.46±0.84 m/s

for acceleration

 -8.06±0.95 m/s

for deceleration.

Therefore six zone of speed (S) are:

S1 = from 0 to 1.74±0.06 m/sec (6.3 km/h)

S2 = up to 3.13±0.11 m/sec (11.3 km/h)

S3 = up to 4.53±0.16 m/sec (16.3 km/h)

S4 = up to 5.92±0.21 m/sec (21.3 km/h)

S5 = up to 7.31±0.26 m/sec (26.3 km/h)

S6 = maximum is 9.15±0.32 m/sec (32.9 km/h)

The zone for acceleration (A) and deceleration (D)

are:

A1 = from 0 to 1.78±0.20 m/s

A2 = up to 3.55±0.40 m/s

A3 = up to 5.33±0.60 m/s

A4 = up to 7.46±0.84 m/s

D1 = from 0 to -1.92±0.23 m/s

D2 = up to -3.84±0.45 m/s

D3 = up to -5.76±0.68 m/s

D4 = up to -8.06±0.95 m/s

Results obtained during the matches are reported in

table 1.

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Table 1: values of “total distance covered” (TD), “relative distance” (RD) and “metres covered in different zones” of speed,

acceleration and deceleration during four official matches. The percentage in the right column is given by the ratio between

the different zones of T.

Mean ± SD % of TD

TD (m) 9591.9 ± 898.4

T (min:sec) 93:58

RD (m/min) 102.0 ± 7.9

S1 (m) 3552.2 ± 429.5 37.0

S2 (m) 2710.7 ± 392.7 28.2

S3 (m) 2188.3 ± 566.4 22.8

S4 (m) 828.2 ± 185.2 8.6

S5 (m) 262.3 ± 92.3 2.7

S6 (m) 50.2 ± 35.1 0.5

A1 (m) 4112.7 ± 455.2 42.8

A2 (m) 501.3 ± 69.3 5.2

A3 (m) 72.3 ± 14.9 0.7

A4 (m) 16.2 ± 4.3 0.2

D1 (m) 4089.1 ± 329.4 42.6

D2 (m) 422.1 ± 95.8 4.4

D3 (m) 65.8 ± 23.7 0.7

D4 (m) 11.2 ± 5.4 0.1

88% of total distance covered was below of

threshold of S3 corresponding at 16,3 km/h (52% of

maximum speed): only a small portion of the game

was played at high speeds.

95% of TD was ranged from -50% to 50% of speed

variation: therefore around 480 m was in

acceleration or in deceleration upper than 50% of

individual maximum.

The results reported for tactical aspects are

reported in table 2. The players who ran more meters

were midfielders (TD = 10102,1±629,1 m) and

lateral forwards (TD = 9759,3±889,6m).The speed

analysis shows that the majority of high speeds are

attributable to the forward, average speeds for

midfielders, and low speeds for defenders. The

evaluation of the acceleration showed no significant

differences in roles, while the deceleration show an

increased workload of midfielders at all intensities.

4 DISCUSSION

For a reliable data it is requires a larger number of

matches, in fact soccer has variables intrinsic in the

game such as opponents, pitch, match result,

weather and more.

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Table 2: values of “total distance covered” (TD). “relative distance” (RD) and “metres covered in different zones” of speed.

acceleration and deceleration during four official matches for each role.

ROLE Lateral

Defender

Central

Defender

Midfield Lateral

Forward

Forward Anova

TD (m) 9058.9±469.2 8571.2±635.5 10102.1±629.1 9759.3±889.6 9031.4±729.3 <0.01

(m/min)

96.9±4.7 90.2±6.9 106.2±7.3 105.4±23.9 98.7±2.4 <0.001

S1 (m) 3251.1±348.4 3548.7±336.4 3227.8±318.1 3921.7±789.1 3537.2±521.1 <0.05

S2 (m) 2815.7±165.1 2332.4±161.0 2876.4±346.2 2551.1±774.8 2288.1±30.1 <0.05

S3 (m) 1985.1±168.8 1739.1±284.8 2754.7±362.1 2030.2±674.1 1754.7±286.2 <0.001

S4 (m) 769.1±117.1 699.3±128.7 977.1±185.9 888.7±287.1 912.4±103.7 <0.05

S5 (m) 223.2±50.1 215.2±80.1 210.6±53.1 325.1±110.1 421.3±111.7 <0.01

S6 (m) 20.9±10.8 51.7±41.4 25.2±22.1 65.3±30.1 118.7±86.9 <0.01

A1 (m) 3960.7 ±225.9 3710.1±332.1 4530.2±407.7 4270.3±579.2 3959.0±179.2 NS

A2 (m) 510.6±65.4 479.1±67.1 492.5±77.3 566.1±177.1 495.1±13.1 NS

A3 (m) 75.7±14.9 76.4±15.2 73.1±21.2 82.1±23.2 74.1±11.4 NS

A4 (m) 13.1±2.8 13.3±5.3 16.7±2.9 18.7±8.7 17.4±5.2 NS

D1 (m) 4074.2±224.5 3910.4±279.4 4365.8±288.7 4278.1±568.1 4131.7±443.1 <0.05

D2 (m) 384.7±76.5 352.7±42.4 506.9±94.1 464.1±121.1 320.1±30.9 <0.001

D3 (m) 51.1±20.1 52.70±8.8 87.1±28.7 85.7±21.4 37.2±7.7 <0.001

D4 (m) 7.1±3.2 7.4±2.1 13.7±6.1 13.2±3.2 2.4±2.1 <0.01

This study has the principal finding to investigate

the kinematic data as speed, acceleration and

deceleration in soccer players. Therefore the present

results are to be considered as preliminary results

that allow researchers to improve their evaluation of

larger series.

This is first study with data analysis directly

from GPS instrument in an official game of soccer

(Larsson P, 2003).

The approach to the analysis follows the trend of

recent major studies on sports match analysis: before

to evaluate the matches were performed test in order

to establish maximum values of speed, acceleration

and deceleration. Setting the maximum values of

speed, acceleration and deceleration is limited to

recording artefacts due to too high values for a given

athlete (Abt G, 2009).

The zones of percentage of speed, acceleration

and deceleration have been set according a scale for

each athlete: a standardized values cannot represent

the real intensity of the individual player.

A limitation of the present study is the

comparison of the parameters related to the

performance of athletes of Italian sixth division, and

the international top level generally found in

previous studies.

The results obtained from tests completed before

the start of the regular season showed high values of

maximum speed, but the data regarding the

maximum values of acceleration and deceleration

was the most interesting: the maximum values of

acceleration and deceleration are similar and very

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high. These maximum values are reached during the

games in fact only for negligible periods of time

within the ninety minutes.

Tactical analysis shown how the speed is specific

for different areas of the field, defenders and

forwards must therefore have high speed abilities to

be able to meet the demands of the game.

In addition particular attention is for the

deceleration in midfielders.

5 CONCLUSIONS

Sports science in soccer is constantly changing as

well as the methods used during the training in this

sport (Randers M, 2010). Initially in match analysis,

the most common

parameters were “total distance”

and “relative distance”: the first one only provides

information about the volume of physical effort; the

second one can be considered a simple parameter

estimating the intensity of physical activity.

The presence of ball in sports game influences

the physical engagement with sudden accelerations

and decelerations, recent studies show these as the

main parameters to be evaluated the intensity in

team sport, leaving at relative distance less value in

this particular evaluation (Di Salvo, 2009).

Video match analysis can considered a risk

factor in the estimation of athletes movements in

order to assess speed, acceleration and deceleration

only indirectly: the use of tools such as wearable

GPS in this evaluation should lead to a reduction of

estimation error.

If it compare the results between this study with

a wearable systems in sixth division and studies

reported with video analysis of top level athletes,

you may notice a greater volume of workload at high

levels (9591.9 ± 898.4 m versus 10950±1044 m), but

the characteristics of intensity is comparable

(Osgnach C., 2010).

On average every player:

 runs approximately 1140 m with a speed

above 21.3 km/h,

 along 88 m above the acceleration 3.5 m/s

 along 77 m below the -3.84 m/s

The study of the physical effort following a tactic

division by roles can provide interesting ideas on

how to improve training methods according to the

different natures of physical demand in sport games

such as soccer.

ACKNOWLEDGEMENTS

The authors did not receive any financial support for

doing this analysis and presenting it in this report.

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