2011 Afl Gps Report

8/2/2019 2011 Afl Gps Report

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QUANTIFYING CHANGES INAFL PLAYER GAME DEMANDS

USING GPS TRACKING

Ben Wisbey (FitSense Australia),David Pyne (Australian Institute o Sport)

and Ben Rattray (University o Canberra)

2011 AFL SEASON


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CONTENTS

Introduction

03 Executive Summary04 Introduction

Part One: Long Term Comparison o Movement Patterns07 Work Rate

08 Movement Pattern Prole

10 Time In Speed Zones

Part Two: Player Workload and Perormance13 Intensity and Rotations

14 Elite Midelders15 Teams and Rotations

17 Workload, Team and Success

19 Top 4 Teams v Bottom 4 Teams

19 Player Workload and Perormance

20 Workloads Across The Season

Conclusions22 Conclusions

Appendix A: Methods and Further Results24 Methods

26 Statistical Analysis

27 GPS Variables by Position

29 GPS Variables by Ground

30 Quarter By Quarter

Appendix B: GPS Analysis Defnitions33 Work

34 Movement Pattern Prole

34 Time In Speed Zones

Reerences36 Reerences

This study was conducted by FitSense Australia as a unded project by the AFL Research Board.

FitSense Australia thanks the Australian Football League and the AFL Research Board or their assistance during this

project. Thanks also go to those AFL teams and their sta who committed to this project. Without their assistance

this research would not have been possible.

The FitSense Australia researchers can be contacted on +61 2 6161 0810 or [email protected].

FitSense Australia Pty Ltd, 2011.


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FitSense Australia Quantiying Change in AFL Player Game Demands Using GPS Tracking - 2011 AFL Season 03

INTRODUCTION

Executive Summary

This research extends previous investigations into the physical demands o playing Australian Football

League (AFL) based on GPS data collected since 2005.

In 2011, all seventeen AFL Clubs participated in this research with a total o 1653 GPS game les captured

rom 377 players. Data was captured rom GPSports (n=567) and Catapult (n=1086) GPS devices.

For the rst time since the research started in 2005, there has been a decrease in playing intensity (3.1%).

This reduction was associated with an increase in playing duration o 4.4%.

The workload prole o players has changed with less accelerations, more time at sub-maximal speeds, less

time at maximal speeds, more steady state running and shorter eorts at maximal speeds.

The changes in player workload in 2011 is one o the largest year to year variations observed since the

research program began in 2005.

As in previous years, there was a moderate relationship between game intensity and rotations with those

players rotated more oten able to maintain a higher game intensity (r=0.33, p


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AFL teams have been early adopters and heavy users o GPS technology in both game and training environments.

In 2005, eight o the sixteen AFL teams were using GPS to monitor player workloads. This level o activity has

increased to all seventeen teams using GPS on a regular basis in 2011. In-game use has expanded quickly as

teams continue to benet rom the technology and the AFL grants unlimited use within games. In 2011, approxi-

mately 50% o all players in all games were monitored during the home and away season; while all this data was

available or this research report, a large number o les were discarded due to poor quality.

Previous research1,2,3,4,5,6,7 established AFL player game demands. This longitudinal retrospective research pro-

gram has documented seasonal trends and substantial changes and dierences in player demands over the last

six seasons.

Key ndings o the GPS analysis or the six preceding AFL Seasons (2005-2010 inclusive) were:

The intensity o work has been gradually increasing during the course o the research period. This increase

was initially associated with reduced playing time, but in 2009 and 2010 both intensity and playing time in-

creased;AFL is a highly intermittent game interspersing lower and higher intensity eorts and this prole may be a

key actor in atigue, recovery and injuries;

The size and shape o AFL grounds had no substantial relationship with the running requirements o players

during a game;

The most successul teams have lower player workloads across the season than their less successul op-

ponents;

Players who are rotated more oten were able to maintain a higher game intensity, and thereore increased

use o the interchange is associated with a subsequent increase in average player speed, and time spent at

the highest speeds.

At the beginning o the 2011 AFL Season, a rule change was implemented which reduced the number o

interchange players rom our to three, and introduced one substitute player. This was done on the basis o 1)

Congestion, 2) Fairness, and 3) Injuries11. One o the key objectives o the rule change was to prevent the speed

o the game rom reaching a new level11, and thereore the GPS report is a key piece o inormation in illustrat-

ing the impact o the rule on the physical demands o the game.

The aim o the 2011 GPS research report was to investigate the ollowing relationships in the physical demands

o AFL ootball:

Changes in player speeds and demands rom previous years;

The impact o rotations, and the new interchange rule, on player demands, player work rate and team suc-cess;

Player perormance and work rates.

In 2011, a total o 1653 usable game les were used or the results in this report. These results are presented in

two parts:

Part 1 A long term comparison o movement patterns;

Part 2 Player workload and perormance.

Introduction


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Further details including methods, urther results and analysis methods can be ound in Appendix A and B.

Throughout the report, exertion index is used as a key measure o player work rate. The exertion index is an

estimate developed by the researchers to quantiy the level o physical work completed by players. Details are

shown in Appendix B.

The inormation presented in this report provides specic inormation to three key reader groups:

The AFL and those involved determining the impact o the rules o the game Trends o player demands o

the past six years are presented in Part 1;

AFL coaches, tness sta and sports scientists An analysis o player workload, perormance and team

success is presented in Part 2, while Part 1 oers a summary o game demands;

Members o the public with an interest in AFL A summary o key game demands are presented in Part 1.


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Part One

Long Term Comparison o

Movement Patterns


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Work Rate

The 2011 data exhibits a number o changes rom previous years. There has been an increase in playing duration

which has in turn resulted in increased distance covered. However, exertion index per minute has decreased by

3.1%; this is the rst decrease in work rate since monitoring started in 2005.

Table 1 shows data captured in 2011 compared to 2010 and 2009.

Work Variable

2011 Mean

Values

(n=1653 fles)

2010 Mean

Values

(n=1177 fles)

2009 Mean

Values

(n=1642 fles)

Dierence 2010 to

2011

Total Time

(min:s)109:53 14:47* 105:14 14:38 106:56 14:45 4.4%; small

Total Distance

(km) 13.43 1.99* 13.04 2.01 13.19 2.04 3.0%; small

Average Speed

(km/hr)7.35 0.64* 7.45 0.63 7.42 0.64 1.3%; trivial

Exertion Index 137.3 25.1 135.5 24.8 135.8 25.3 1.3%; trivial

Exertion Index

per Minute1.25 0.18* 1.29 0.18 1.27 0.18 3.1%; small

Table 1. Comparison o main work rate variables between Seasons rom All data (mean SD).

* Signicantly dierent rom 2009 and 2010 (p


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Comment

These changes are some o the most substantial we have seen since monitoring began seven years ago. Contrary

to the increased work rate observed in previous years, 2011 showed the rst decrease in playing intensity. The

increase in playing duration appears to have resulted in players being unable to sustain the same level o inten-

sity throughout the game, or possibly a consequence o reduced number o rotations.

A seasonal comparison o movement pattern variables (i.e. acceleration characteristics, steady state running and

longest continuous eorts) is presented in Table 2.

The 2011 data shows a number o distinct changes rom the previous seasons. This includes a moderate reduc-

tion in all acceleration and deceleration measures with reductions ranging rom 37-56%.

Signicant changes were also observed in the length o eorts above various running speeds. This work involved

longer eorts at sub-maximal speeds, yet shorter eorts at maximal speeds.

A moderate increase o 19% was also evident in the volume o steady state running undertaken.

Movemement Pattern Profle

Variable2011 Mean Values

(n=1653 fles)

2010 Mean Values

(n=1177 fles)

2009 Mean Values

(n=1642 fles)

Dierence 2010 to

2011

Accelerations over

4 km/hr in 1sec233 119* 402 194 322 135 42%; Moderate

Accelerations over

10 km/hr in 1sec 11.0 11.5* 25.4 19.3 17.3 14.4 56%; Moderate

Decelerations over

4 km/hr in 1sec232 146* 369 180 275 109 37%; Moderate

Decelerations over

10 km/hr in 1sec14.4 14.4* 26.8 15.2 20.4 10.6 45%; Moderate

LCT over 13 km/hr

(sec)32.1 102.6* 23.5 51.1 22.6 6.3 36%; Trivial

LCT over 15 km/hr

(sec)25.8 90.8* 19.2 41.2 18.8 5.9 34%; Trivial

LCT over 17 km/hr

(sec)20.6 78.4* 15.6 27.5 15.7 5.5 32%; Trivial

LCT over 20 km/hr

(sec)10.2 3.2* 11.2 4.2 11.9 5.3 9%; Small

Steady State Time

above 8 km/hr

(min:s)

30:30 7:11* 25:36 5:36* 27:15 5:26 19%; Moderate

Table 2. Comparison o movement pattern variables between seasons or all GPS data (mean SD).

* Signicantly dierent rom 2009 and 2010 (p


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Comment

While the 19% increase in steady state running is partially a result o a 4% increase in total playing duration, the

magnitude o the change also highlights that the nature o the game has changed. This change, combined with

the reduction o acceleration requency indicates that the running demands o AFL have altered substantially in

the 2011 season.

Further highlighting this change is the length o eorts. Maximal speed eorts have decreased in length while

there has been an increase in the length o eorts at sub-maximal speeds. This is likely a result o an increase in

steady state sub-maximal running.


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A seasonal comparison o speed zone proles is presented in Table 3.

In 2011, there was a signicant increase in the time spent at walking speeds below 8 km/hr. Time in most other

speed zones also changed with an increase in the time spent in sub-maximal running speed zones and less time

spent at maximal speeds, despite the increase in playing duration.

Figure 2 shows the percentage o total playing time spent above 16km/hr and 18km/hr in the 2010 and 2011

seasons. A signicant dierence (p


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Comment

A number o changes are evident in the speed zone prole o players when compared to 2010. Increases oc-

curred at walking and sub-maximal running speeds, however there was a reduction o time spent at high running

speeds.

When accounting or the increase in total playing duration, Figure 2 shows a substantial reduction in relative

times at high running speed in 2011. This reduction may relate to the longer playing durations, greater steady

state running and resultant atigue which means players are unable to sustained high running speeds as they

have done in previous years.

Figure 2. Percentage o total playing duration speed above 16km/hr and 18km/hr in

the 2010 and 2011 seasons.


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Part Two

Player Workload and Perormance


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Intensity and Rotations

Results

A moderate relationship existed between the average intensity o a player and the number o rotations that a

player had during a game in the 2011 season. As the number rotations increased, so did the exertion index per

minute (r=0.33, p


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Six rotations per game appears to be the ideal requency to enable to players to sustain maximal playing intensity

while also maximising on-eld playing duration. While more rotations than this will not see a reduction in average

speed, it will likely reduce the playing duration, and potentially the impact a player can have.

A moderate number o rotations will allow higher intensity on eld playing periods, although other contributors

play a greater role in game intensity (e.g. players own tness).

Elite Midfelders

In order to compare the impact o the new interchange rule in 2011, twenty midelders were compared across

the 2010 and 2011 season. This group o twenty players was selected based on players with the highest work-

loads and most possessions.

Results

Table 4 shows a comparison o data rom a group o elite midelders in 2010 to 2011. This highlights an 8% re-

duction in rotations along with a reduction in a number o workload variables. The largest reductions in workloadwere the percentage o game time spent above 18km/hr (-29%), exertion index per minute (-7.7%) and average

speed (-3.7%).

There was also a 9% increase in the volume o steady state running.

Work Variable2011 Mean Values

(n=138 fles)

2010 Mean Values

(n=141 fles)Dierence 2010 to 2011

Total Time (min:s) 113:29 12:18 109:01 10:57 3.9%; Small

Total Distance (km) 14.23 1.85 14.18 1.75


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Teams were divided into two groups: those that had a change in rotations rom 2010 to 2011 and those that

had no change. Dierence in rotations between seasons was assessed using the eect size method, with teams

showing a trivial change being classied as having no change. Those with a small or moderate change in rota-

tions were classied as having a (substantial) change.

Results

Table 5 shows the change in exertion index and average speed or teams that displayed a change in the number

o rotations rom 2010 to 2011. A minimal change in the exertion index was evident while there was a small

decrease in average speed.

Table 6 shows the change in exertion index and average speed or teams that displayed no change in the number

o rotations rom 2010 to 2011. A small increase in overall exertion index combined with only a minimal increase

in average speed is shown.

These results are displayed graphically in Figures 4 and 5.

Those teams that changed substantially the number o rotations went rom an average o 5.94 rotations per game

in 2010 to 5.55 in 2011. For those that showed minimal change, the average went rom 5.75 in 2010 to 5.77 in

2011

Teams and Rotations

Work Variable2011 Mean Values

(n=1182 fles)

2010 Mean Values

(n=755 fles)Dierence 2010 to 2011

Exertion Index 136.5 24.7 137.1 24.4


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Comment

Not surprisingly, those teams that had a substantial reduction in the number o rotations, also had a substantial

reduction in the average player speed. Teams who had less rotations in 2010, did not have a reduction in the

number o rotations or 2011. While their average player speed was lower in 2010, they were able to sustain this

in 2011 and given the longer playing durations, their overall workload increased.

Figure 4. Exertion Index comparison rom 2010 to 2011 or teams who had a substan-

tial change in rotation between seasons and those that had no change.

Figure 5. Average Speed comparison rom 2010 to 2011 or teams who had a substan-

tial change in rotation between seasons and those that had no change.


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Determining why a team is successul is dicult as perormance outcomes are based on many actors. In this

section we investigate selected relationships between team success and player work rate.

The exertion index or and against each team is presented in Table 7. Figure 6 shows a graphical representation

o each teams exertion index prole.

The only relationships between the position a team nished on the ladder and that teams workload was with

steady state running volume. This weak relationship indicated that poorer perorming teams undertook a greater

volume o steady state running (r=0.16, p


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Figure 6. Box and Whisker o Exertion Index by AFL Team. The order o teams has been

randomised to maintain condentiality o results. The median value is indicated by the

thick black line, the standard deviation by the box, the mean or all teams by the red

line, and the range by the vertical error bars.

Comment

As per last season, in 2011 there were no strong relationships between a teams success and GPS variables

across the entire season. However, the small relationship that was observed indicated that the more successul

teams are likely to complete less steady state running. This may be dictated by the more successul teams orc-

ing their opposition to continually run as they control the tempo o a game.

Throughout the last three seasons, there has been no consistent relationship between team perormance and

player workload based on GPS.


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The relationship between team success and work rate was also investigated by evaluating data rom the rst our

teams versus that o the bottom our teams at the end o season Premiership season (Table 8).

Minimal dierences were evident between top 4 and bottom 4 teams. The most substantial dierence was the

lower volume o steady state running completed by top 4 teams.

Top 4 Teams v Bottom 4 Teams

Variable Top 4 Bottom 4 Dierence

Exertion Index 141.2 23.3 140.9 26.7


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To examine changes in workload during the season, the 2011 Premiership Season was divided into ve stages:

rounds 1-6, 7-12, 13-18, 19-22 and nals. The average exertion index o each was analysed (Figure 7).

No substantial changes were evident in the workload o players across the season. Additionally, there were no

substantial changes in intensity measures throughout the season either.

Workloads Across The Season

Comment

The ndings o 2011 dier to that o 2009 and 2010. In 2010, workload remained steady across the season, with

the exception o rounds 18-22 which displayed a lower overall workload. In 2009, the opposite trend occurredwith the latter part o the home and away season displaying the highest workloads. This discrepancy between

seasons may be related to the certainty o teams making nals, thus impacting the workload in the last quarter

o the season. The 2011 season is also the rst season where workloads have been sustained across the season

as players attempted to maximise perormance with the increased on-eld playing time.

Figure 7. Box and Whisker o Exertion Index Across the AFL Season. The median value

is indicated by the thick black line, the standard deviation by the box, the mean or all

teams by the red line, and the range by the vertical error bars.


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Conclusions


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Since the rst GPS report or AFL in 2005, substantial changes in player workloads have been observed. The

increase in player intensity, estimated as the exertion index per min, increased 17% between 2005 and 2010.

However, 2011 showed the rst reduction in this measure with a 3.1% reduction rom 2010.

The reduction playing intensity is also associated with a number o changes to the workload prole o players.

The game was less intermittent in 2011 with less accelerations and decelerations and a greater volume o steadystate running. The ongoing running in the game has also seen a reduction in the length o maximal speed eorts

and the amount o total time spent at these speeds.

A moderate relationship existed between game intensity and rotations. This outcome is similar to previous years.

Further highlighting this relationship were the reductions in average speeds and time spent at high speeds by a

group o elite midelders compared rom 2010 to 2011.

Possibly the strongest evidence that the interchange rule had an impact was the observation that teams with a

substantial reduction in the number o rotations rom 2010 also had a substantial reduction in average speed,

while those teams with a similar number o rotations had minimal change in average speed.

Previous years have shown mixed relationship between team success and team workload. In 2011, the only

substantial relationship showed that better perorming teams undertook a lower volume o steady running.

On an individual player level, players completing a greater volume o work had a greater number o possessions

and also had a better perormance according to the Champion Data player rating. Moreover players who could

sustain a higher game intensity also obtained more possessions.

For the rst time over the last three seasons, workloads remained relatively stable throughout the year, with little

change in the nal stages o the home and away season or during the nals.

Conclusions


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Appendix A

Methods and Further Results


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Elite AFL ootballers (n=377) rom AFL clubs were tracked using two dierent GPS systems (GPSports, Canberra,

Australia and Catapult, Melbourne, Australia) during the 2011 AFL Season. Players were assigned to three major

positional groups nominated by their respective clubs i.e. xed orwards, nomadic and xed deenders.

GPS units were tted to the upper back o each player using a purpose-built supportive harness. In total, 1653

usable game les were captured. A le was considered usable when it was captured during the PremiershipSeason and included a playing period o greater than 60 minutes without substantial data errors or missing data.

Upon receiving the GPS game les (n=1653), the data was categorised according to the type o GPS device used:

GPSports (n=567) or Catapult (n=1086). Data captured rom both units had a mixture o logging requencies,

both 5Hz and 10Hz.

Comparisons were made to data rom previous years. Details o the methods used in these years can be ound in

previous reports submitted to the AFL1,2,3,4,5,7.

Each participating club was responsible or tting the units to players, and downloading and orwarding data tothe researchers. Data was imported into custom built GPS sotware (Sports Tracker Analysis v2.0, FitSense Aus-

tralia). All GPS game data was stored with accompanying demographic data or each player. This data was made

up o individual player game possession statistics (rotations, kicks, handballs, marks, and total possessions),

player position, team, opposition, venue, and date and time o game. All playing time was analysed. Non-playing

periods (quarter and hal-time breaks and interchange periods) were omitted rom the analysed data.

To ensure consistency between les, two rules were employed to categorise objectively the data into one o two

groups - playing period and non-playing period. These same rules have been applied since 2008. These rules

were:

1. A non-playing period was triggered when the average speed was less than 3 km/hr or 2 continuous min-utes; and

2. A playing period was triggered when the average speed was greater than 5 km/hr or 2 continuous minutes.

Figure 8 shows an example o how these triggers applied.

Methods


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Figure 8. Line graph o the 2 minute rolling speed average showing how a playing period and non-playing period

was triggered.

All game les were analysed using a number o steady state and movement pattern variables:

Total distance (km)

Average speed (km/hr)

Exertion index

Exertion index per minute

Time spent in speed zones (min:sec)

Longest continuous time above specied speeds (seconds)

Acceleration / deceleration prole

A brie explanation o each variable (including the exertion index ormula) is shown in Appendix B.


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Statistical Analysis

Statistical analysis was perormed with the SPSS sotware package (v16.0). A Pearson two-tailed correlation

was used to assess the relationship between variables with a signicance o p


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The ollowing section compares key GPS variables by position (Table 9). For comparison, Table 10 presents this

same data during the 2010 season.

Nomadic reers to all players who are not classied as either a xed orward or xed deender, this includes mid-

elders and ruckman. Nomadic players played or signicantly less game time than orwards (~4.5 min less) and

deenders (~8 min less). Despite the reduced playing time, nomadic players completed a greater amount o workas measured by exertion index. This outcome was associated with a higher average game intensity by nomadic

players compared to both orwards and deenders.

The volume o steady state running and high speed running that dierentiated nomadic players rom players in

other positions. Similar conclusions about nomadic players were presented in previous seasons.

GPS Variables By Position

Work VariableForward

(n=94)

Nomadic

(n=1396)

Deender

(m=163)

Total Time (min:s) 113:25 14:50 108:52 14:36* 116:37 14:50

Total Distance (km) 12.89 1.89 13.46 2.00 13.50 1.88

Average Speed (km/hr) 6.83 0.52 7.43 0.62* 6.97 0.61

Exertion Index 124.2 22.1 139.0 25.1* 130.6 22.6

Exertion Index per

Minute1.10 0.15 1.28 0.18* 1.12 0.17

LCT over 20 km/hr

(sec)9.12 2.18 10.32 3.32 9.77 2.57

Steady State Time

above 8 km/hr (min:s) 25:28 5:17 31:07 7:05 28:07 7:20

Time Over 18 km/hr

(min:s)4:18 1:08 5:35 2:19* 4:20 1:44

Table 9. Work variables by position or All GPS Data (mean SD).

* Signicantly dierent rom all other positions Signicantly dierent rom orwards (p


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Comment

Substantial dierences were evident between playing position. The most apparent dierence in 2011, as with

previous years, was the higher game intensity o nomadic players. Intensity was ~16% higher or nomadic play-

ers compared with orwards and ~14% when compared to deenders. This pattern o dierences maybe associ-

ated with nomadic players generally getting rotated at a higher requency and thereore having greater o-eld

recovery.

Deenders and orwards displayed similar work proles and worked at similar intensities.

Work VariableForward

(n=88)

Nomadic

(n=1036)

Deender

(m=53)

Total Time (min:s) 108:56 14:55 104:28 14:28 113:58 13:52

Total Distance (km) 12.50 2.16 13.08 2.00 13.08 2.00

Average Speed (km/hr) 6.89 0.81 7.52 0.58 6.93 0.58

Exertion Index 122.2 27.2 137.0 24.3 127.08 23.09

Exertion Index per

Minute1.13 0.23 1.31 0.17 1.12 0.17

LCT over 20 km/hr

(sec)9.62 2.88 11.35 4.32 10.00 4.03

Steady State Time

above 8 km/hr (min:s)22:52 5:28 25:54 5:33 24:16 5:23

Time Over 18 km/hr

(min:s)5:09 1:40 6:29 1:49 5:17 1:36

Table 10. Work variables by position or all GPS data in 2010 (mean SD).

LCT = Longest Continuous Time.


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A summary o key GPS variables or each ground are presented in Table 11.

Some signicant dierences were observed between grounds total workload but not intensity. The stand-out di-

erences include longer playing durations, and thus a greater volume o work and steady state running at Subiaco

Oval when compared to most other grounds.

GPS Variables By Ground

Work

Variable

AAMI

Stadium

(n=194 fles)

GABBA

(n=140 fles)

MCG

(n=547 fles)

SCG

(n=89 fles)

Skilled

Stadium

(n=115 fles)

Subiaco

Oval (n=354

fles)

Dimensions

(m)165 x 133 156 x 138 160 x 141 149 x 136 170 x 115 176 x 122

Total Time

(min:s)

111:45

14:00

108:15

13:52

107:28

14:56

109:36

13:45

107:52

14:51

115:50

12:23

Total Dis-

tance (km)13.87 2.01 13.21 1.86 13.04 1.97 13.26 1.65 13.06 1.82

14.26

1.73

Average

Speed (km/

hr)

7.47 0.73 7.33 0.54 7.30 0.62 7.28 0.47 7.29 0.57 7.40 0.57

Exertion

Index142.5 26.0 134.9 22.7 133.6 24.6 135.2 19.4 133.1 22.6

145.3

22.6

Exertion

Index per

Minute

1.28 0.20 1.25 0.16 1.25 0.18 1.24 0.14 1.24 0.17 1.26 0.17

Steady StateTime above

8 km/hr

(min:s)

31:54 7:39 30:48 6:41 29:24 6:53 29:10 5:23 27:41 5:0732:01

6:57

Table 11. Work variable by AFL venue (mean SD).

Signicantly dierent rom all other grounds except AAMI (p


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Table 12 and 13 provides the key work variables rom each quarter during the 2010 and 2011 seasons respec-

tively. Both seasons show reductions in work rate rom the 1st to the 4th quarter, with the decreased work rate

being most evident in the percentage o time at high running speeds (above 16 and 18 km/hr).

The reduction in average speed across the game is shown in gure 9, which illustrates a similar rate o decline

in both seasons although the speeds in all quarters are lower in 2011.

Quarter By Quarter

Work

Variable

Q1

(n=935 fles)

Q2

(n=999 fles)

Q3

(n=959 fles)

Q4

(n=932 fles)

Eect Size

From Q1 To Q4

Total Time

(min:s)26:05 4:12 25:24 4:36 24:47 4:33 25:00 4:40 4%; trivial

Total Distance

(km)3.35 0.59 3.18 0.64 3.09 0.63 2.99 0.64

11%;

moderate

Average Speed

(km/hr)7.74 0.77 7.53 0.77 7.50 0.79 7.20 0.84

7%;

moderate

Exertion Index 35.5 7.5 33.1 8.0 32.0 7.7 30.1 7.815%;

moderate

Exertion Index

per Minute1.37 0.22 1.30 0.22 1.29 0.22 1.21 0.23

12%;

moderate

% Time Above

16km/hr10.76 3.11 9.77 2.84 9.82 2.84 8.68 3.06

24%;

moderate

% Time Above

18km/hr6.86 2.40 6.17 2.15 6.20 2.13 5.37 2.39

28%;

moderate

Table 12. Comparison o main work variables between quarters in 2010 (mean SD).

Work

Variable

Q1

(n=501 fles)

Q2

(n=507 fles)

Q3

(n=519 fles)

Q4

(n=504 fles)

Eect Size

From Q1 To Q4

Total Time

(min:s)26:21 4:07 25:37 4:50 24:54 4:50 25:28 4:34 4%; small

Total Distance

(km)3.27 0.57 3.09 0.64 3.00 0.63 2.94 0.59 11%; small

Average Speed(km/hr)

7.47 0.78 7.25 0.76 7.24 0.74 6.94 0.768%;

moderate

Exertion Index 33.6 7.3 31.1 7.6 30.0 7.5 28.7 7.117%;

moderate

Exertion Index

per Minute1.28 0.22 1.22 0.22 1.21 0.21 1.13 0.21

13%;

moderate

% Time Above

16km/hr9.23 3.00 8.45 2.92 8.30 2.68 7.35 2.67

26%;

moderate

% Time Above

18km/hr 5.59 2.10 5.03 2.04 4.89 1.92 4.31 1.8830%;

moderate

Table 13. Comparison o main work variables between quarters in 2011 (mean SD).


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Figure 9. Line graph o the average speed across each quarter in the 2010 and 2011

seasons.


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Appendix B

GPS Analysis Denitions


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Total DistanceMeasures the total distance travelled during the playing period. Measured in kilometres.

Average SpeedTotal distance divided by total playing duration in hours. Measured in kmhr-1

Total TimeThe total on eld playing duration. Measured in minutes.

Exertion IndexExertion index is a quantiable level o physical load developed by FitSense Australia. This measure allows a

relationship to be drawn between game load, atigue, and the total load between players. The exertion index

used to assess GPS data in this project was based on the sum o a weighted instantaneous speed, a weighted

accumulated speed over 10 seconds, and a weighted accumulated speed over 60 seconds. This ensures both

short sharp eorts, and long sustained eorts are analysed equally. The weighting is based on a polynomial rela-

tionship in which high speeds achieve a higher exertion value than lower speeds. Exertion index is measured inarbitrary units. The ormula to determine exertion index was:

Exertion Index = (Sum o EI1 + Sum o EI10 + Sum o EI60)/300

Where:

EI1 = (v4 x 0.000009) - (v3 x 0.001) + (v2 x 0.0356) - (vx 0.0596) - 0.0172

EI10 = (V104 x -0.00003) - (V103 x 0.0004) + (V102 x 0.0477) - (V10 x 0.0476) + 0.1056

EI60 = (V604 x -0.00003) - (V603 x 0.0004) + (V602 x 0.0477) - (V60 x 0.0476) + 0.1056

v= speed in kilometres per hour captured at 1 Hz. Where data was captured at 5 Hz, it was averaged to create

a 1 Hz sample.

V10 = average speed in kilometres per hour o the last ten 1 Hz speed samples.

V60 = average speed in kilometres per hour o the last sixty 1 Hz speed samples.

Exertion Index Per MinuteThis is a measure o game intensity and is determined by dividing exertion index by playing time.

EfciencyA measure o the work requirements or game involvement and game impact. Measured by dividing exertion

index by total number o possessions.

Maximal SpeedThe maximal speed reached or a one second sample period. This measure is likely to be lower than the actual

maximal speed achieved by the player due to the sampling rate and resolution o the GPS system.

Work


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Number o Accelerations (Acceleration > x kmhr-1 in 1sec):The number o times the speed increases by more than x kmhr-1 in a 1 second time period. This gives an indica-

tion as to the accelerations undertaken and how requently these occur. Accelerations are categorised as moder-

ate (4 kmhr-1) or rapid (10 kmhr-1).

Number o Decelerations (Deceleration > x kmhr-1 in 1sec)The number o times the speed decreases by more than x kmhr-1 in a 1 second time period. This gives an indica-

tion as to the decelerations required and how requently these occur. Decelerations are categorised as moderate

(4 kmhr-1) or rapid (10 kmhr-1).

Longest Continuous Time above a Specifed Speed (LCT > x kmhr-1)The longest period o time the player stays above this speed, without dropping below this speed. Time is recorded

even when the player enters a higher speed zone. Provides an indication o the longest continuous eort at vary-

ing speeds.

Time At Steady State > 8 kmhr-1 (Steady State Intensity Time)Any time at a speed above 8 kmhr-1 where the players velocity does not alter by more than 1.5 kmhr-1 within a

1 sec sample period. This gives an indication o time spent at continual running speeds.

Movement Pattern Profle

Speed Zones (x y kmhr-1)

Time spent between the speeds o x and y kmhr-1

. Provides inormation on the dispersion o speed throughoutthe session.

Time In Speed Zones


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Reerences


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1. Wisbey B. and Montgomery P. Quantiying AFL Player Demands Using GPS Tracking - 2005 Season. AFL

Research Board Report, 2005

2. Wisbey B. and Montgomery P. Quantiying AFL Player Demands Using GPS Tracking - 2006 Season. AFL


3. Wisbey B., Montgomery P. and Pyne D. Quantiying AFL Player Demands Using GPS Tracking - 2007 Season.

AFL Research Board Report, 2007

4. Wisbey B., Rattray B. and Pyne D. Quantiying AFL Player Demands Using GPS Tracking - 2008 Season. AFL


5. Wisbey B., Rattray B. and Pyne D. Quantiying AFL Player Demands Using GPS Tracking - 2009 Season. AFL


6. Wisbey B., Montgomery P.G., Pyne D.B. and Rattray B. Quantiying movement demands o AFL ootball using

GPS tracking. J Sci Med Sport. 2010; 13: 5

7. Wisbey B., Rattray B. and Pyne D. Quantiying AFL Player Demands Using GPS Tracking - 2010 Season.AFL


8. Hopkins W. 2000 - Measures o reliability in sports medicine and science. Sports Med 2000 Jul; 30 (1): 1-15

9. Jennings D., Cormack S., Coutts A.J., Aughey R.J. The validity and reliability o GPS units or measuring

distance in team sport specifc running patterns. Int J Sports Physiol Perorm. 2010 Sept; 5(3): 328-41

10. Petersen C., Pyne D., Portus M., Dawon B. Validity and reliability o GPS units to monitor cricket-specifc

movement patterns. Int J Sports Physiol Perorm. 2009 Sept; 4(3): 381-93

11. Anderson A., Memo to AFL Clubs dated 4 October 2010, Laws o the Game 2010 Premiership Season

Reerences

Documents

2011 Afl Gps Report