International Journal of Sports Physiology and Performance, 2010, 5, 394-405
© Human Kinetics, Inc.
Australian Football Player Work Rate:
Evidence of Fatigue and Pacing?
Robert J. Aughey
Previous research has suggested elite Australian footballers undertake pacing strategies to preserve high intensity activity later in matches. However, this research used
GPS with slow sample rates, did not express performance relative to minutes played
during games and used lowly ranked players. Methods: Therefore in this study
movement was recorded by GPS at 5 Hz. Running performance was expressed per
period of the match (rotation) divided into low-intensity activity (LIA, 0.10 to 4.17
m⋅s–1); high-intensity running (HIR, 4.17 to 10.00 m⋅s–1) and maximal accelerations (2.78 to 10.00 m⋅s–2). All data were expressed relative to the first period of
play in the match and the magnitude of effects was analyzed with the effect size
(ES) statistic and expressed with confidence intervals. Results: The total and LIA
distance covered by players did not change by a practically important magnitude
during games (ES< 0.20). High intensity running was reduced in both rotations
of the second quarter, Q3R2 and both rotations of the fourth quarter (ES −0.30 ±
0.14; −0.42 ± 0.14; −0.30 ± 0.14; −0.42 ± 0.14; and −0.48 ± 0.15 respectively).
Maximal acceleration performance was reduced in Q1R2, and each rotation of
the second half of matches. Conclusion: When expressed per minute of game
time played, total distance and low intensity activity distance are not reduced by
a practically important magnitude in AF players during a match. These data are
therefore inconsistent with the concept of team sport players pacing their effort
during matches. However, both high intensity running and maximal accelerations
are reduced later in games, indicative of significant fatigue in players.
Keywords: motion analysis, functional performance, physical performance, sport
physiology
Recent research on the match demands of elite Australian Football (AF)1,2
has seemingly agreed with previous findings in soccer that players fatigue during
matches3–5 and therefore adopt a pacing strategy to mitigate the fatigue experienced
later in matches.1,2 However, there are a number of methodological issues in recent
studies that must be addressed before accepting these findings.
The recent AF studies relied on 1 Hz global positioning systems (GPS) for the
recording of running activities of players during matches.1,2 As most high intensity
Robert J. Aughey is with the Institute of Sport, Exercise and Active Living, School of Sport and Exercise Science, Victoria University, Melbourne, Australia, and with the Western Bulldogs Football Club,
Melbourne, Australia.
394
Work Rate in Professional Australian Football 395
activities in team sports are of a very short duration,3,6,7 it is unlikely a 1 Hz sample
rate offers sufficient resolution to accurately measure high intensity, and thus match
activity.8 When directly compared with data with a 5 Hz sample rate, 1 Hz data less
reliable and less valid for measuring distance in a variety of team-sport specific
movement patterns.9 GPS technology is heavily used in AF,1,2,10,11 commercially
available units now sample at 5 Hz,10–12 which may enhance the ability to measure
short duration high intensity activities.8,12
Australian Football is different to soccer with unlimited substitutions allowed
during matches. This means that individual players may get significant periods of
recovery during matches. It is therefore not uncommon for players to have two periods
of play within each quarter of a match, with each team having up to one-hundred
substitutions during matches (Aughey, unpublished observations). In AF the terminology applied to this is player rotations. Therefore, players may have rotations during
match play of varying durations, and all movement data should be standardized per
unit of time to allow comparisons to be made. Merely reporting the absolute distance
covered by players during a full,3 half,1–3 or quarter1 of a match may misrepresent the
actual work rate or suggested pacing of players during individual rotations of AF.
The data in two recent AF studies1,2 was sampled from a team ranked in the
lower 25% of the competition during the 2005 to 2007 seasons. It is possible that
the profile of running in this team was different to more successful teams. As the
authors of that recent AF study point out,1 less successful soccer teams have a higher
activity level than more successful teams and are less efficient at some technical
skills.13 It is therefore possible that the data presented is skewed due to the level of
ability of the participants in that study.
While the idea of team-sport athletes pacing efforts early in a match is an
attractive hypothesis, if similarly true to strategies adopted by individual athletes,
the highest work rate of players should be achieved in the final periods of a match,
as described by the “end spurt” phenomenon.14,15 There is no evidence to date of
team sport athletes achieving this end-spurt.
Finally, there is increasing evidence that the running demands of AF players
have increased in the past few years, with a 7% increase in both the mean running
velocity and steady-state running over 8 km⋅h–1 from the 2005 to 2008 seasons.16
Therefore, findings from matches sampled during the 2005 to 2007 seasons may
no longer be relevant.
The aims of this study were therefore to: (1) quantify player work rate in AF
with 5 Hz GPS devices; (2) express player work rate per unit of game time played;
(3) analyze results per rotation; and (4) sample players from a team ranked in the
top 25% of the competition.
Methods
Participants
Eighteen elite Australian footballers (age 25.9 ± 3.5 y; height 188.4 ± 7.8 cm; body
mass 90.6 ± 8.8 kg at commencement of the study (mean ± SD) gave informed
consent to participate in this study. The study conformed to the Declaration of
Helsinki. Participants were all registered players of an elite Australian Football
club, ranked in the top 25% of the elite Australian Football League competitions
in the 2008 and 2009 seasons.
396 Aughey
Data were collected from the eighteen players between 1 and 17 occasions from
29 individual matches during the 2008 and 2009 seasons. Files were only included
if the following criteria was met: (1) Players played ≥ 70% of total game time; (2)
players were rotated twice per quarter; and (3) each rotation was at least 5 min in
duration. A 75% game time minimum criteria as recently described1 was not used
in this study, as it would have excluded approximately 15 match files that were
representative of common game times for those players. A total of 147 individual
match files were included for analysis.
Player Work Rate
Traditional Time Motion Analysis. Player work rate was measured via a small global
positioning system (GPS) sampling at 5 Hz (MinimaxX Team Sports 2.0, Catapult
Innovations, Melbourne, Australia), using proprietary software (Logan Plus, v4.1,
Catapult Innovations, Melbourne, Australia). The devices were worn in a custom
pocket in the player uniform, located between the scapulas. The player movement
variables analyzed, expressed in meters and distance per unit of game time (m⋅min–1)
were total distance; low-intensity activity (LIA, 0.10 to 4.17 m⋅s–1); and high-intensity
running (HIR, 4.17 to 10.0 m⋅s–1).3 All movement data were expressed per quarter
and per rotation. That is, in AF players are often rested, or rotated to the bench during
quarters of play. A rotation equals a period of play within a quarter of football that
a player is on the field. All rotation data were compared with the first rotation in the
first quarter, which should have had the highest work rate.1 Periods were numbered
Q1R1, Q1R2, Q2R1, Q2R2, Q3R1, Q3R2, Q4R1 and Q4R2 for individual rotations.
Changes in Velocity. The number of maximal (2.78 to 10.00 m⋅s–2) changes in
velocity (accelerations) were calculated from GPS data using the manufacturers
software (Logan Plus, v4.1, Catapult Innovations, Melbourne, Australia). In
piloting the reliability of these GPS units to measure these accelerations, the CV
was large at approximately 50% (Varley and Aughey unpublished observations).
To enhance the ecological validity and reliability of this measure, our software
rules required two consecutive measures (ie, 0.4 s) at the same rate of change in
velocity to classify as acceleration. The statistical method we employ here can also
account for this uncertainty in measurement.17 The definition of accelerations here
differs from the only other studies to use acceleration data from GPS. One study
counted accelerations of greater than > 1.11 m⋅s–2 as moderate accelerations16 and
another counted accelerations > 4 m⋅s–2 as maximal accelerations.11 World-class
100 m sprinters accelerate at a rate of approximately 6 m⋅s–2 in the first second
of a race, and subsequent to that first second acceleration occurs at a maximum
rate of approximately 2 m⋅s–2. Further, elite team sport athletes accelerated from a
standing start at a maximal rate of approximately 3 m⋅s–2.18 In recent pilot testing,
trained but subelite team sport athletes accelerated maximally at a rate of between
2.5 and 2.7 m⋅s–2 measured by laser (Varley, Fairweather and Aughey unpublished
data). Finally, these elite AF players only accelerate maximally in matches from
a moving start.19 It is, therefore, likely that 4 m⋅s–2 is too high a threshold for elite
team sport athletes,18,20 and a rate of between 2.7 and 3 m⋅s–2 is appropriate. Based
on this, and the observation of >1000 GPS files from elite AF matches and training
sessions, this researcher believes 2.78 m⋅s–2 is an appropriate threshold for maximum
acceleration in elite AF players.
Work Rate in Professional Australian Football 397
Statistical Analyses
Variables were log transformed to reduce bias due to nonuniformity of error and
analyzed using the ES statistic with 90% confidence intervals (CI) and percentage change to determine the magnitude of effects using a custom spreadsheet.17,21
Magnitudes of change were classified as a substantial increase or decrease when
there was a ≥ 75% likelihood of the effect being equal to or greater than the smallest worthwhile change estimated as 0.2 × between subject standard deviation, and
classified as small 0.2 to 0.6; moderate 0.6 to 1.2; large 1.2 to 2.0; and very large
2.0 to 4.0. Effects with less certainty were classified as trivial and where the ± 90%
CI of the ES crossed the boundaries of ES −0.2 and 0.2, the effect was reported
as unclear.17
Results
The mean movement and acceleration data for players across whole matches are
presented in Table 1.
Length of Playing Periods
Players were on the field of play for 101.91 ± 9.80 min in matches sampled. This
represented approximately 85% of available game time for these matches. The
second rotation was shorter than the first in each quarter played, but there were
no differences between the first rotation of the first quarter and the first rotation in
subsequent quarters. The length of individual rotations was 15.22 ± 6.68, 10.77
± 3.83, 15.50 ± 7.41, 11.52 ± 4.14, 16.22 ± 7.12, 11.21 ± 4.14, 15.91 ± 8.09 and
11.44 ± 4.27 min in chronological order.
Table 1 Movement and acceleration data (mean ± SD, n = 147) for
whole matches, expressed in absolute and relative to time on field
terms
Variable
Unit
Mean ± SD
Distance
Total (m)
12734 ± 1596
127 ± 17
m⋅min–1
LIA Distance
Total (m)
m⋅min–1
HIR Distance
Total (m)
m⋅min
Maximal Accelerations
–1
Total (#)
accel⋅min
–1
9011 ± 1137
89 ± 11
3334 ± 756
34 ± 9
96 ± 41
0.99 ± 0.39
Note. LIA is low intensity activity performed at a velocity between 0.01 and 4.17 m⋅s–1; HIR is high
intensity running defined as running performed at a velocity between 4.17 and 10.00 m⋅s–1; maximal
accelerations were defined as a change in velocity of between 2.78 and 10.00 m⋅s–2.
398 Aughey
Total Distance
There was a moderate reduction in total distance in absolute meters traveled in the
second rotation of each quarter when compared with Q1R1 (ES −0.78 ± 0.19; −0.63
± 0.19; −0.72 ± 0.20; and −0.75 ± 0.20 respectively, Figure 1A). When compared
with Q1R1 and expressed per minute of game time, total distance was, however,
maintained in subsequent periods of play (Figure 1B).
Figure 1 — Total distance per rotation expressed in meters (A) and meters per minute of
game time (m⋅min–1, B). Periods were named for the quarter of play they occurred in, and
the sequential number of the rotation in that quarter (Q1R1; Q1R2; Q2R1; Q2R2; Q3R1;
Q3R2; Q4R1; and Q4R2 respectively). Magnitudes of change were classified as a substantial increase or decrease when there was a ≥ 75% likelihood of the effect being equal to or
greater than the smallest worthwhile change estimated as 0.2 × between subject standard
deviation, and classified as small 0.2 to 0.6; moderate 0.6 to 1.2; large 1.2 to 2.0; and very
large 2.0 to 4.0. * Denotes a small reduction from Q1R1. All data are mean ± SD, n = 147.
Work Rate in Professional Australian Football 399
Low Intensity Activity (LIA) Distance
As for total distance, there was a moderate reduction in LIA in the second rotation
of each quarter when expressed in absolute terms (ES −0.71 ± 0.19; −0.54 ± 0.19;
−0.63 ± 0.20; and −0.67 ± 0.20 for Q1R2, Q2R2, Q3R2 and Q4R2 respectively).
However, when compared with Q1R1 and expressed per minute of game time, LIA
distance was maintained in subsequent periods of play (90.83 ± 17.74; 93.01 ±
17.76; 91.32 ± 14.65; 94.63 ± 18.41; 88.22 ± 17.89; 92.60 ± 14.44; 89.91 ± 15.95
and 89.65 ± 14.52 for Q1R1, Q1R2, Q2R1, Q2R2, Q3R1, Q3R2, Q4R1 and Q4R2
respectively).
High Intensity Running (HIR) Distance
When examined per rotation and expressed in absolute terms, HIR was reduced
by a moderate magnitude in the second rotation of each quarter (ES, −0.78 ± 0.20;
−0.72 ± 0.19; −0.82 ± 0.20 and −0.80 ± 0.20 for Q1R2, Q2R2, Q3R2 and Q4R2
respectively. Figure 2A). However, when expressed in relative terms, HIR was
reduced by a small magnitude in both rotations of the second quarter, Q3R2 and
both rotations of the fourth quarter (ES −0.30 ± 0.14; −0.42 ± 0.14; −0.30 ± 0.14;
−0.42 ± 0.14; and −0.48 ± 0.15 respectively, Figure 2B).
Maximal Accelerations
When the absolute number of maximal accelerations was expressed per rotation
relative to Q1R1, there was a moderate reduction in Q1R2, Q2R2, Q3R2, and Q4R2
(ES −0.75 ± 0.20; −0.60 ± 0.20; −0.75 ± 0.20 and −0.71 ± 0.20 respectively, Figure
3A) and a small reduction in Q4R1 (ES −0.27 ± 0.18; Figure 3A). When expressed
relative to game time, small reductions were evident in Q1R2, and each rotation
of the second half of matches (ES 0.28 ± 0.20; 0.27 ± 0.17; −0.33 ± 0.20; −0.46 ±
0.18; and −0.34 ± 0.20 respectively, Figure 3B).
Discussion
This study uses 5 Hz GPS for the first time to quantify match performance of elite
AF players. The first major finding of this study was that total distance covered by
elite AF players was maintained throughout matches when expressed relative to
game minutes played. Similarly, players maintained the amount of LIA throughout
matches when normalized for game time. The second major finding of this study
was that there were small reductions in high intensity running in the latter part of
matches, even when playing time was accounted for. For the first time we have characterized the number of maximal accelerations players undertake during matches,
and reported a decline in this ability in the latter stages of a match.
The findings on total distance covered by players in this study differ from the
two recent studies using GPS technology to measure AF player work rate.1,2 In
both of the previous studies, the authors have reported a reduction in total distance
covered by players in the last part of matches. There are at least three possible
explanations for the differences reported here. The first possible explanation is
that these players may have had a higher level of conditioning than those in the
previous studies. Players used here were from a team ranked in the top 25% of
Figure 2 — High intensity running (HIR) distance per rotation expressed in meters (A) and
meters per minute of game time (m⋅min–1, B). Periods were named for the quarter of play they
occurred in, and the sequential number of the rotation in that quarter (Q1R1; Q1R2; Q2R1;
Q2R2; Q3R1; Q3R2; Q4R1; and Q4R2 respectively). Magnitudes of change were classified
as a substantial increase or decrease when there was a ≥ 75% likelihood of the effect being
equal to or greater than the smallest worthwhile change estimated as 0.2 × between subject
standard deviation, and classified as small 0.2 to 0.6; moderate 0.6 to 1.2; large 1.2 to 2.0;
and very large 2.0 to 4.0. * Denotes a small reduction from Q1R1. † Denotes a moderate
reduction from Q1R1. All data are mean ± SD, n = 147.
400
Figure 3 — The number of maximal accelerations defined as a change in velocity of
between 2.78 to 10.00 m⋅s–2 expressed in absolute terms (A) and per minute of game time
(accelerations per minute, B). Periods were named for the quarter of play they occurred
in, and the sequential number of the rotation in that quarter (Q1R1; Q1R2; Q2R1; Q2R2;
Q3R1; Q3R2; Q4R1; and Q4R2 respectively). Magnitudes of change were classified as
a substantial increase or decrease when there was a ≥ 75% likelihood of the effect being
equal to or greater than the smallest worthwhile change estimated as 0.2 × between subject
standard deviation, and classified as small 0.2 to 0.6; moderate 0.6 to 1.2; large 1.2 to 2.0;
and very large 2.0 to 4.0.* Denotes a small reduction from Q1R1. † Denotes a moderate
reduction from Q1R1. All data are mean ± SD, n = 147.
401
402 Aughey
the competition, rather than the bottom 25% in the previous studies.1,2 It is well
documented that players at a higher level of competition have superior physical
capabilities. Evidence of this is presented in comparisons of athletes of different
levels on team-sport specific tests such as the Yo-Yo Intermittent recovery test.22
Indeed, international standard soccer players performed approximately 10% better
than other elite players playing at a lower level on this test.22 Further, in elite AF,
players selected to commence on the field have an approximate 27% greater Yo-Yo
IR2 performance than nonstarters.23 Finally, players in this study had a relative total
distance approximately 14% higher than the previous study.1 Taken further, it is
reasonable to assume that players of a higher level may also have a higher level
of fatigue resistance than there less successful counterparts. The second possible
explanation is that the higher ranked players used in this study did not have to run
as hard, as they were more technically proficient, as noted in elite soccer players
in the Italian Serie A competition.13 Finally, AF players get ample opportunity to
rest during and between quarters of games. When analyzed per rotation, rather than
over a whole quarter of play and expressed per minute of game time played, it is
easier to measure peaks and troughs in player work rate.
It has been postulated that players regulate the amount of low-intensity activity
undertaken to preserve the important high-intensity components of running during
matches.2 The players in this study had unchanged low-intensity activity over the
course of the game, in disagreement with the concept of pacing. Indeed, individual
athletes tend to lower work rate early in races14 to allow an “end-spurt”14,15 or
enhanced performance during matches. Australian Football matches are played
over a period of approximately 120 min, but the exact duration cannot be known in
advance by AF players, as it is dependent on how much extra time is added due to
stoppages in play and strategic considerations. Further, players do not always know
in advance how long each rotation will be during a match, and therefore pacing
and subsequent performance are altered by the accuracy of feedback provided.24
In agreement with previous findings in elite team sport athletes, high intensity running of the elite AF players in this study was lowered in the latter part of
matches.1–5,25–28 The mechanisms underlying this reduced performance are likely
to be multifaceted, and were not examined in this study. However, fatigue may be
caused by reductions in available substrate,29,30 disturbances in electrolytes across
the muscle membrane,31 impaired calcium release from the sarcoplasmic reticulum,32 or central factors.33
For the first time we present evidence of a reduction of the ability of players to
accelerate maximally during matches. It is perhaps not surprising that this ability
is impaired in these athletes, as to accelerate is extremely physically demanding,
even from low commencement velocities and therefore likely to induce significant
fatigue. Further, accelerations are associated with key elements of the game, including the ability to accelerate toward an opponent to lay a tackle, accelerate away
from an opponent to evade opponent tackle or move to space to receive the ball
from a team-mate. Notwithstanding that the measurement of accelerations using
GPS is less reliable than the measure of total or HIR distance,9 this may reflect an
important indicator of fatigue. In this study, the measurement of normalized maximal
accelerations was able to detect fatigue later in games similar to normalized HIR
distance. However, subtle differences in the magnitudes of fatigue and the time
course between these two measures points to the importance of measuring different
Work Rate in Professional Australian Football 403
fatigue qualities in these athletes. Further, to neglect the rapid and common changes
in velocity that occur in team-sports probably underestimates true high-intensity
activities of players in matches.34
Practical Applications
Player work rate must be expressed in relation to a unit of time played in AF, as
players can be substituted regularly during matches. When considering performance
in AF, it is likely that the most high intensity actions such as sustained high-velocity
running, or hard changes in velocity will be impaired in the second half of matches.
To improve this performance later in games, careful management of players through
regular rotations and implementation of recovery strategies during games should be
undertaken. However, in the absence of data on the capability of GPS to accurately
and reliably measure accelerations, care must be taken when interpreting data on
this practically important parameter.
Conclusions
When expressed per minute of game time played, both total distance and lowintensity activity distance are not reduced by a practically important magnitude
in elite AF players during a match. This data are therefore inconsistent with the
concept of team sport players pacing their effort during matches. However both
high-intensity running and maximal accelerations are reduced later in games,
indicative of significant fatigue in players. Further work is needed to characterize
the reliability and validity of GPS for measuring these accelerations.
Acknowledgments
The author acknowledges the players and coaches of the Western Bulldogs Football Club,
and especially Cameron Falloon and Bill Davoren for facilitating data collection. Finally, the
author thanks James Zois and Matthew Varley for assistance with manuscript preparation.
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