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Yo-Yo Intermittent Recovery Test Performance in Sub-Elite Gaelic Football Players from Under 13 to Senior Age Groups

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Gaelic football is indigenous to Ireland and has similar locomotion profiles to soccer and Australian Football. Given the increasing attention on long-term player development, investigations into age-related variation in Yo-YoIR1 performance may provide useful information in talent identification, programme design, and player monitoring. Therefore, the aim of this study was to evaluate Yo-YoIR1 performance across Gaelic football age groups. Male participants (n = 355) were recruited from division one, Gaelic football teams. Participants were allocated to one of seven groups according to respective age groups from under 13 (U13), under 14, under 15 (U15), under 16 (U16), minor, under 21 (U21), to senior age groups. Total Yo-YoIR1 distance (m) increased progressively from U13 (885 ± 347 m) to U16 (1595 ± 380 m) equating to a rate of change of 180.2%. In comparison to U13, total distance at minor (1206 ± 327 m) increased by 136.4%. Subsequent increases were observed in U21 (1585 ± 445 m) and senior players (2365 ± 489). Minimum (800-880 m) and maximum (2240-2280 m) total distances were comparable for U15, U16, and U21 players. Differences in total distance (m) for all age groups were statistically significant when compared to U13 players (p<0.002). In comparison to U13 players the magnitude of differences between age groups for total distance were deemed to be large (ES >0.8). Similar trends were observed for maximum velocity and estimated VO2max. The evolution of Yo-YoIR1 performance in Gaelic football players from adolescents to adulthood highlights how maturation may influence sport-related running ability. Changes in Yo-YoIR1 performance should be closely monitored to optimise interventions for individuals transitioning across age groups.
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YO-YOINTERMITTENT RECOVERY TEST PERFORMANCE
IN SUBELITE GAELIC FOOTBALL PLAYERS FROM
UNDER THIRTEEN TO SENIOR AGE GROUPS
MARK ROE
1,2
AND SHANE MALONE
2,3
AU2
1
Health Sciences Centre, School of Public Health, Physiotherapy and Sports Science, University College Dublin, Belfield,
Ireland
AU3 ;
2
Gaelic Sports Research Centre, Department of Science, Institute of Technology Tallaght, Tallaght, Ireland; and
3
Tom
Reilly Building, Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Henry Cotton Campus,
Liverpool, United Kingdom
ABSTRACT
Roe, M and Malone, S. Yo-Yo intermittent recovery test
performance in subelite Gaelic football players from under
thirteen to senior age groups. J Strength Cond Res XX (X):
000–000, 2016—Gaelic football is indigenous to Ireland and
has similar locomotion profiles to soccer and Australian Foot-
ball. Given the increasing attention on long-term player devel-
opment, investigations on age-related variation in Yo-Yo
intermittent recovery test level 1 (Yo-YoIR1) performance
may provide useful information in talent identification, program
design, and player monitoring. Therefore, the aim of this study
was to evaluate Yo-YoIR1 performance across Gaelic football
age groups. Male participants (n= 355) were recruited from
division one, Gaelic football teams. Participants were allocated
to one of the 7 groups according to respective age groups
from under 13 (U13), under 14, under 15 (U15), under 16
(U16), minor, under 21 (U21), to senior age groups. Total
Yo-YoIR1 distance (m) increased progressively from U13
(885 6347 m) to U16 (1,595 6380 m) equating to a rate
of change of 180.2%. In comparison to U13, total distance
at minor (1,206 6327 m) increased by 136.4%. Subsequent
increases were observed in U21 (1,585 6445 m) and senior
players (2,365 6489). Minimum (800–880 m) and maximum
(2,240–2,280 m) total distances were comparable for U15,
U16, and U21 players. Differences in total distance (m) for
all age groups were statistically significant when compared
to U13 players (p,0.002). In comparison to U13 players,
the magnitude of differences between age groups for total
distance was deemed to be large (effect size .0.8). Similar
trends were observed for maximum velocity and estimated
V
_
O
2
max. The evolution of Yo-YoIR1 performance in Gaelic
football players from adolescents to adulthood highlights
how maturation may influence sport-related running ability.
Changes in Yo-YoIR1 performance should be closely moni-
tored to optimize interventions for individuals transitioning
across age groups.
KEY WORDS intermittent aerobic capacity, field testing,
maturation AU4
INTRODUCTION
Gaelic football is indigenous to Ireland and is
governed by the Gaelic Athletic Association
(GAA). The sport has an amateur ethos super-
imposed on a professional work ethic (6). Dur-
ing competitive match-play, 2 opposing teams compete
over a 60-minute period separated by a 15-minute half-
time interval. Each team has 15 players and can make 5
substitutions. Th AU5
e aim is to outscore the opposition as with
H-shaped goal posts, 1 point is awarded for striking or
kicking the ball over a crossbar and 1 goal (3 points) is
awarded for striking or kicking the ball over under the
crossbar past a goalkeeper. Intercounty competition repre-
sents the elite level of Gaelic games, whereas club compet-
itions represented subelite levels.
Activity profiles of Gaelic football match-play follow
an intermittent pattern (12). Reilly et al. (21) reported
that underage players (15 60.7 years) cover a mean dis-
tance of 5,732 61,047 m with 14.8% (851 6297 m)
covered at high speed ($17 km $h
21
). Adult players have
been reported to cover average total distances of 8,815 m
with 10.3% of distance covered at high speed (1,695 6
1,047 m). The Yo-Yo intermittent recovery test level 1
(Yo-YoIR1) has significant correlates to total distance
(r= 0.62) and high-intensity distance (r= 0.73) within
underage team sport athletes (9). As underage develop-
ment pathways seek to optimize early detection and
physical development of talented players, assessment of
sport-related running ability across age groups may
improve talent identification and long-term training
interventions (7,14,21).
Address correspondence to Mark Roe, mark.roe@ucd.ie.
00(00)/1–7
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The Yo-YoIR1 has been assessed for validity in intermit-
tent field sport players (3,9) and is considered a valid field
test to assess changes in aerobic fitness within Gaelic football
populations (17). The Yo-YoIR1 evaluates an athlete’s ability
to repeatedly complete short, high-intensity running efforts,
which elicit maximal aerobic responses while significantly
stressing the anaerobic energy system (3). Thus, Yo-YoIR1
induces physiological demands similar to those experienced
during match-play (3,9,20).
Despite the popularity of the test, there is little informa-
tion about the potential role of the Yo-YoIR1 to discriminate
the aerobic performance across age profiles within Gaelic
football. An understanding of how Yo-YoIR1 performance
develops across age groups could be of practical value to
practitioners developing talent identification and profiling
procedures in Gaelic football. Therefore, the aim of this
study was to evaluate Yo-YoIR1 performance differences
across under 13 to senior age groups within a Gaelic football
population.
METHODS
Experimental Approach to Problem
In this cross-sectional study, we applied a between-subjects
design to examine the group differences in the Yo-YoIR1
performance among young and adult Gaelic football players.
All testing took place on a rubber-based third-generation (3
G) synthetic turf pitch (dimensions: 143 386 m; grass
length: 55 mm) with a 50.8-mm shock pad underneath a syn-
thetic grass carpet.
Subjects
Male participants (n= 355) were recruited from division one,
Gaelic football teams. Participants were allocated to one of
the 7 groups according to respective age grades, that is,
either under 13 years (U13) (12–13 years, 48.4 610.2 kg,
145.1 63.4 cm), under 14 years (U14) (13–14 years, 52.4 6
10.2 kg, 155.1 68.4 cm), under 15 years (U15) (14–15 years,
61.9 610.5 kg, 162.5 67.7 cm), under 16 years (U16) (16–17
years, 70.9 69.5 kg, 174.5 68.7 cm), minor age grade (17–19
TABLE 1. Yo-YoIR1 total distance (m) per age group.*
Sample size Mean 6SD Minimum Maximum 95% CI pCohen’s d
Under 13 63 885.1 6347.3 320 1,920 801.91–974.57
Under 14 41 1,326.0 6494.9 440 2,280 1,213.71–1,444.51 0.000 1.031
Under 15 62 1,470.9 6372.2 880 2,240 1,361.53–1,574.32 0.000 1.627
Under 16 53 1,595.0 6380.7 880 2,240 1,468.75–1,713.72 0.000 1.948
Minor 52 1,206.8 6327.3 600 1,840 1,109.27–1,313.17 0.002 0.953
Under 21 32 1,585.4 6445.3 800 2,480 1,426.15–1,755.31 0.000 1.753
Senior 52 2,365.4 6489.6 1760 3,400 2,178.58–2,551.52 0.000 3.487
*Pairwise comparisons reveal a statistically significant (p#0.05) mean difference between (a) U13 compared with all age groups
except minor, (b) U14 compared with U13 and senior, (c) U15 compared with U13, U21, and senior, (d) U16 compared with U13,
U21, and senior, (e) minor compared with U15, U16, and senior, (f) U21 compared with U13 and senior, and (g) senior compared with
all age groups.
Age range for players: minor group (17–19 years) and senior group (19–33 years).
TABLE 2. Yo-YoIR1 maximum velocity (m$s
21
) per age group.*
Sample size Mean 6SD Minimum Maximum 95% CI pCohen’s d
Under 13 63 4.24 60.27 3.89 5.22 4.17–4.30
Under 14 41 4.49 60.39 3.89 5.5 4.40–4.58 0.001 0.745
Under 15 62 4.61 60.34 4.2 5.4 4.52–4.70 0.000 1.205
Under 16 53 4.82 60.38 4.17 5.42 4.69–4.94 0.000 1.759
Minor 52 4.30 60.14 4.03 4.58 4.26–4.35 0.948 0.278
Under 21 32 4.90 60.39 4.19 5.67 4.75–5.10 0.000 1.967
Senior 52 5.54 60.42 5.03 6.44 5.39–5.71 0.000 3.682
*Pairwise comparisons reveal a statistically significant (p#0.05) mean difference between (a) U13 compared with all age groups
except minor, (b) U14 compared with U13, minor, and senior, (c) U15 compared with U13, minor, and senior, (d) U16 compared with
U13, minor, and senior, (e) minor compared with all age groups except U13, (f) U21 compared with U13, minor, and senior, and (g)
senior compared with all age groups.
Age range for players: minor group (17–19 years) and senior group (19–33 years).
Yo-YoIR1 Performance Across Subelite Gaelic Football Age Grades
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years, 76.3 67.6 kg, 180.1 64.6 m), under 21 years (U21)
(20.5 61.5 years, 72.9 69.5 kg, 179.5 69.7 cm), or senior
age grade (24.5 66.5 years, 78.8 63.6 kg, 180.4 66.2 m).
Inclusion criteria were no injury or illness within the pre-
vious 6 months and playing experience greater than 18
months. Data on goal keepers were excluded for analysis.
Participants were informed of the investigation aims, testing
procedures, and withdrawal process before providing written
consent. Written consent was obtained from parents and
guardians for participants less than 18 years. Ethical approval
was granted by the institutions’ human research committee.
The study conforms to the Code of Ethics of the World
Medical Association (approved by the ethics advisory board
of Swansea University) and required players to provide
informed consent before participatio
AU6 n.
Procedure
This study was performed over a one-month period. All
participants undertook a familiarization test of the Yo-YoIR1
in the 2-week period before testing. Testing was administered
during the 2014–15 season. Participants were instructed to
consume their usual diets before testing. Testing was then
completed in line with the procedures described by Bangsbo
et al. (3). This included participants completing a 15-minutes
dynamic warm-up involving multijoint and running activities
of progressive intensity. The Yo-YoIR1 consists of 2 320 m
shuttle runs at increasing speeds, interspersed with a 10-
second active recovery (controlled by audio signals from
a compact disc player). Failure to complete a shuttle resulted
in a verbal warning with participants being withdrawn on
a second failure. Total distance and corresponding maximum
speed at the final completed shuttle were recorded. Esti-
mated V
_
O
2
max was completed using the following formula
by Bangsbo et al. (3). V
_
O
2
max (ml$min
21
$kg
21
) = Yo-YoIR1
distance (m) 30.0084 + 36.4.
Statistical Analyses
All data were analyzed using SPSS (version 21.0; IBM, Inc.,
Chicago, IL, USA). Descriptive statistics were used to report
performance markers per age grade. Data are presented as
mean 6SD with 95% confidence intervals. Minimum and
maximum data per age grade are also presented. Quartiles
TABLE 3. Yo-YoIR1 estimated V
_
O
2
max (ml$min
21
$kg
21
) per age group.*
Sample size Mean 6SD Minimum Maximum 95% CI pCohen’s d
Under 13 63 44.7 62.6 41.4 49.2 43.97–45.69
Under 14 41 48.5 64.2 41.4 55.6 46.96–50.14 0.000 1.087
Under 15 62 49.8 62.7 45.1 55.2 48.83–50.9 0.000 1.924
Under 16 53 50.8 62.6 46.5 55.2 49.76–51.83 0.000 2.346
Minor 52 46.2 62.9 41.4 51.9 45.11–47.28 0.002 0.544
Under 21 32 49.7 63.7 43.1 57.2 48.38–51.15 0.000 1.563
Senior 52 56.3 64.1 51.2 65.0 54.76–57.94 0.000 3.379
*Pairwise comparisons reveal a statistically significant (p#0.05) mean difference between (a) U13 compared with all age groups
except minor, (b) U14 compared with U13 and senior, (c) U15 compared with U13, minor, and senior, (d) U16 compared with
U13, minor, and senior, (e) minor compared with U15, U16, and senior, (f) U21 compared with U13 and senior, and (g) senior
compared with all age groups.
Age range for players: minor group (17–19 years) and senior group (19–33 years).
TABLE 4. Yo-YoIR1 total distance, maximum velocity quartiles, andAU11 estimated V
_
O
2
max quartiles.*
Total distance (m) Maximum velocity (m$s
21
) Estimated V
_
O
2
max (ml$min
21
$kg
21
)
Quartile 1 Quartile 2 Quartile 3 Quartile 1 Quartile 2 Quartile 3 Quartile 1 Quartile 2 Quartile 3
Under 13 600 840 1,120 4.03 4.17 4.31 41.44 43.46 45.81
Under 14 960 1,285 1,660 4.17 4.44 4.72 44.46 47.19 50.34
Under 15 1,180 1,480 1,720 4.31 4.53 4.89 46.31 48.83 50.85
Under 16 1,240 1,660 1,920 4.53 4.91 5.14 46.82 50.34 52.53
Minor 940 1,200 1,460 4.17 4.31 4.44 44.30 46.48 48.66
Under 21 1,190 1,620 1,945 4.53 4.89 5.24 46.40 50.01 52.74
Senior 1,910 2,280 2,720 5.13 5.47 5.86 52.44 55.55 59.25
*Age range for players: minor group (17–19 years) and senior group (19–33 years).
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were used to report 25th, 50th, and 75th percentiles for Yo-
YoIR1 metrics. One-way between-groups analysis of vari-
ance with Tukey post hoc was used to investigate mean
differences using U13 performance as the dependent vari-
able. Significance was set at ap#0.05. Effect size (ES)
was assessed according to Cohen. An ES of 0.02, 0.5, 0.8,
or 1.3 was considered small, moderate, large, or very large,
respectively. Significant pairwise differences between age
groups are also reported.
RESULTS
Total distance, maximum velocity (meter per second), and
estimated V
_
O
2
max obtained during the Yo-YoIR1 per age
grade are presented in Tables 1–3, respectively. Quartiles
are presented in Table 4. Rate of change (percent) relative
to U13 players is presented in Table 5.
Total distance (meter) increased by 180.2% from 885.1 6
347 m in U13 players to 1,595 6380 m in U16 players (p,
0.001, ES = 3.49). In comparison to U13, total distance
at minor age group (1,206 6327 m) increased by 136.4%
(p= 0.002, ES = 0.95). Subsequent increases were observed
in U21 (1,585 6445 m) and senior players (2,365 6489 m)
(F1Figure 1). Minimum (800–880 m) and maximum (2,240–
2,280 m) total distances were comparable for U15, U16,
and U21 players. Confidence intervals and quartiles reveal
overlap for total distances between U14 and U21 players
(Table 4).
Differences in total distance (meter) for all age grades
were statistically significant when compared with U13
players (p,0.002). Differences in maximum velocity
(meter per second) for all age groups, except minor
(p=0.948),werestatisticallysignicantwhencompared
with U13 players (p,0.001). In comparison to U13
players, the magnitude of differences between age groups
for total distance was deemed to be large (ES .0.8).
Maximum velocity was largely different (ES .0.8) for
all age groups when compared with U13 players;
however, ES for the minoragegroupwasdeemedto
be small (ES ,0.5).
Estimated V
_
O
2
max progressed from 44.7 62.6
ml$min
21
$kg
21
in under 13 players to 56.3 64.1
ml$min
21
$kg
21
in senior players (p,0.001, ES = 3.4). How-
ever, estimated V
_
O
2
max seemed
to decline in minor players
when compared to under 14–
16 players.
Pairwise comparisons for
Yo-YoIR1 total distance reveal
a statistically significant (p#
0.05) mean difference between
(a) U13 compared with all age
groups except minor, (b) U14
compared with U13 and
senior, (c) U15 compared with
U13, U21, and senior, (d) U16
compared with U13, U21, and
senior, (e) minor compared
with U15, U16, and senior, (f)
U21 compared with U13 and
senior, and (g) senior com-
pared with all age groups.
Figure 1. Yo-YoIR1 total distance (m) across age grades.
TABLE 5. Yo-YoIR1 total distance rate of change relative to under 13 players (%).
Sample size Mean 6SD (%) Minimum (%) Maximum (%) 95% CI lower limit 95% CI upper limit
Under 13 63
Under 14 41 149.81 655.92 50.00 258.00 136.2 163.51
Under 15 62 166.19 642.05 99.00 253.00 154.3 177.45
Under 16 53 180.21 643.01 99.00 253.00 164.0 194.19
Minor 52 136.35 636.98 68.00 208.00 124.8 148.14
Under 21 32 179.12 650.32 90.00 280.00 160.9 196.67
Senior 52 267.25 655.32 199.00 384.00 247.1 288.97
Yo-YoIR1 Performance Across Subelite Gaelic Football Age Grades
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Pairwise comparisons for Yo-YoIR1 maximum velocity
reveal a statistically significant (p#0.05) mean difference
between (a) U13 compared with all age groups
except minor, (b) U14 compared with U13, minor, and
senior, (c) U15 compared with U13, minor, and senior, (d)
U16 compared with U13, minor, and senior, (e) minor com-
pared with all age groups except U13, (f ) U21 compared
with U13, minor, and senior, and (g) senior compared with
all age groups.
Pairwise comparisons for Yo-YoIR1 estimated V
_
O
2
max
reveal a statistically significant (p#0.05) mean difference
between (a) U13 compared with all age groups
except minor, (b) U14 compared with U13 and senior, (c)
U15 compared with U13, minor, and senior, (d) U16 com-
pared with U13, minor, and senior, (e) minor compared with
U15, U16, and senior, (f) U21 compared with U13 and
senior, and (g) senior compared with all age groups.
DISCUSSION
This is the first investigation on the evolution of Yo-YoIR1
performance in male Gaelic football players from adoles-
cents to adulthood. Interestingly, several between-age group
differences were observed. Yo-YoIR1 distance increased by
276 655% between under 13 (885 6347) and senior players
(2,365 6490) (Tables 1 and 5). However, subsequent dec-
rements in total distance were observed in minor (1,207 6
327) and U21 players (1,585 6445) (Figure 1) as evident
by all descriptive statistics used (Tables 1 and 4). Cullen et al.
(13) reported Yo-YoIR1 total distances of 1,446–1,503 m in
16- to 17-year-old elite Gaelic football players. Although
greater scores were observed in this study for such age
groups, differences may relate to decrements specific to sea-
sonal cycles during these years. However, the cohort inves-
tigated by Cullen et al. (13) was participants in school
competitions and not elite per se, given that they did not
entirely consist of intercounty players. Furthermore, inves-
tigations on a single age group fail to challenge the current
finding of Yo-YoIR1 decrements associated with various age
groups. Variations in training load and maturation between
age groups have yet to be described in Gaelic football. Thus,
it is unclear whether such decrements reflect ineffective
training interventions, overtraining by excessive exposure
to training and match-play, or biological maturation.
Results of the current investigation differ from studies on
adolescent soccer (11), rugby league (22), and Australian
football (AFL) cohorts (8) in that aerobic performance dur-
ing late-adolescent declined in this Gaelic football cohort.
Although a novel finding, whether this impacts running per-
formance during training and match-play remains to be
investigated. The current results are at odds with longitudi-
nal investigations of match-play locomotion profiles. For
instance, high-intensity running has increased by 30% (890
6299 vs. 1 ,151 6337 m, p,0.001, ES: 0.82) in English
Premier League soccer match-play between 2006 and 2013.
Similarly, meters per minute (m$min
21
) during under 18
AFL match-play have increased by 5.2% (113.07 617.1 vs.
118.94 614.13 m, p,0.036, ES: 0.37) from 2003 to 2009
(8). Greater increases in match-play demands were observed
among senior AFL players (121.19 614.74 vs. 134.02 6
12.09 m, p,0.001, ES: 0.95) during the same period (8).
Studies have previously shown large correlations between
Yo-Yo performance and match-play activity profiles (3) with
improvements in Yo-Yo performance correlating to
increased match-play running.
Studies have shown that junior AFL players with high
aerobic capacity have greater countermovement jump scores
and lower creatine kinase concentrations after match-play
despite having experienced greater internal and external
loads (16). Additionally, superior Yo-YoIR1 performance
(.1,516 6182 m) was also shown to have a protective effect
on under 19s rugby league players by reducing injury risk
(10). Therefore, the impact of Yo-YoIR1 performance in
altering injury risk in Gaelic football should be further
investigated.
Similar to previous studies conducted in soccer (7), age was
associated with superior aerobic capacity as marked by esti-
mated V
_
O
2
max between under U13 (44.70 62.60
ml$min
21
$kg
21
) and senior level (56.30 64.10
ml$min
21
$kg
21
) in Gaelic football players. The increase in
this study across aerobic profiles was similar to previous stud-
ies (3,24). Interestingly, AFL players with greater estimated
V
_
O
2
max based on 20-m multistage fitness test performance
were reportedly more likely to be selected for competitive
match-play (ES = 0.2) (24). In addition, these players had
more ball possessions during match-play (ES = 0.5) (24).
Therefore, the link between aerobic capacity and match per-
formance needs to be assessed in Gaelic football populations.
In this study, estimated V
_
O
2
max increased linearly
throughout adolescents with a noted decreased at minor
and under 21 age grades. The data highlighted within this
study may be used by coaches to analyze the development of
aerobic capacity among Gaelic football cohorts. Indeed,
among elite senior soccer players, a V
_
O
2
max of 62–64
ml$min
21
$kg
21
seems to suffice senior competition with
no statistically significant differences between international,
division one, or division 2 players (23). Such results suggest
that this threshold of aerobic capacity is highly desirable in
sports similar to Gaelic football, yet that pursuit of gains
beyond this threshold may not advance performance.
This study is the first to report the rate of developmental
change across Gaelic football players for Yo-YoIR1 shuttle
performance (Table 5). The authors propose this as a meth-
odology of highlighting potential performance improve-
ments across developmental cycles. One of the interesting
findings of this study relates to the age group decline in Yo-
YoIR1 performance at the minor and under 21 age groups.
To the best of our knowledge, this is the first article high-
lighting a decline in Yo-YoIR1 performance across certain
age groups. Indeed, the current finding is a surprising one
as 4 different team sports report consistent V
_
O
2
max increases
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with advancing pubertal development, suggesting increased
metabolic capacity during adolescents (5). Therefore, future
research should investigate influences of training loads dur-
ing maturation on program responses. For instance, a change
in the threshold or activities required to stimulate physiolog-
ical responses, advantageous to Gaelic football performance,
may differ across various stages of maturation.
Discussions into such decrements are limited as this is the
first investigation highlighting this trend in Gaelic football.
Future research should investigate whether such findings
may impact the transition of players to senior ranks, affect
tolerance to training and match-play demands, impair
execution of technical and tactical skills, and thereby
increase the risk of deselection. Furthermore, investigations
into increased susceptibility to fatigue-induced performance
decrements and injury are warranted. As a result, the authors
advocate multiple testing periods for underage players across
competitive seasons to fully understand the seasonal change
in aerobic capacity. Gathered data may guide programme
design as aerobic power development can be impaired by
motor control and anthropometrical characteristics during
maturation in adolescent soccer players (14).
Several limitations must be considered when reviewing
this study. Participants were grouped by chronological age.
Thus, the biological maturity of the players was not taken
into account. Additionally, the impact of relative age is an
important factor not taken into consideration in this study.
Previous investigations have identified relative age as an
important issue within Gaelic football (18); therefore, its
impact on performance should be investigated in further
studies. In addition, no identification of muscle mass differ-
ences among players impacts the value of this data set as
muscle mass, not whole-body mass, impacts functional
capacity of athletes (1).
PRACTICAL APPLICATIONS
This study describes the cross-sectional evolution of Yo-
YoIR1 performance in Gaelic football players throughout
developmental age groups (U13 to senior). This study
demonstrates that the Yo-YoIR1 is of value at identifying
aerobic differences across age groups. Therefore, practi-
tioners should appreciate the diverse range of abilities within
each cohort as players transition between age groups. In
light of the presented findings, coaches and strength and
conditioning professionals should consider Yo-YoIR1 in
testing batteries. This is because (a) the Yo-YoIR1 test is
a valid, reliable, and easily available measurement tool of
a player’s aerobic capacity and (b) Yo-YoIR1 performance
represents a very important fitness component in Gaelic
football, which may be adversely affected during adolescents.
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Yo-YoIR1 Performance Across Subelite Gaelic Football Age Grades
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... 48 Gaelic football, unlike similar field sports such as soccer and rugby, has an amateur ethos, meaning that athletes may only receive expenses for playing. 32,55 Despite this, elite players often train up to five times per week and follow a serious training regime, which can consist of pitch and weight room-based sessions; they also attend team meetings and educational workshops focusing on subjects such as nutrition and player welfare. 2,38 The difference between elite and non-elite players is the participation at the county level. ...
... 14 The 'Yo-Yo Intermittent Recovery 1' (YYIR1) is considered a valid field test to assess an athlete's ability to complete short high intense running bouts within the sport of Gaelic football. 55 It has been noted that this test applies the same physiological demands as experienced during match play. 55 The test was originally designed to be a maximal aerobic test specific to soccer and has a high correlation with the 'gold standard' laboratory tests (r = 0.86). ...
... 55 It has been noted that this test applies the same physiological demands as experienced during match play. 55 The test was originally designed to be a maximal aerobic test specific to soccer and has a high correlation with the 'gold standard' laboratory tests (r = 0.86). 14 Better performances in the YYIR1 have been related to greater match play sprinting and high intensity running; therefore, it would be deemed wise to include such a measure in a Gaelic football testing battery. ...
Article
Gaelic football is a high-intensity Irish sport which requires a wide range of sporting abilities. In this article, we present the demands of participating in the sport and provide a testing battery, alongside a method of presenting these data. Training recommendations have also been provided in order to enhance performance and reduce injury risk in Gaelic football players.
... Studies have shown that it is associated with the high-intensity activities during a match and it informs about competition levels throughout the season (Bangsbo, Iaia, & Krustru, 2008;Mohr & Krustrup, 2014). Yo-YoIRT 1 has significant correlations with the total distance (r = 0.62) and the high-intensity distance (r = 0.73) of sports athletes in the underage teams (Roe & Malone, 2016). ...
... However, this decrease is worthy of notice. It is thought that some differences in the responses to the training loads during maturation can be observed (Roe & Malone, 2016). Significant increase at the end of the season compared to the beginning of the season in all groups may be due to the fact that the adaptation of the athletes to the training programs was positively affected by the development characteristics according to the age categories. ...
Article
Full-text available
Los estudios longitudinales que evalúan el cambio estacional en la capacidad aeróbica de los jugadores de fútbol jóvenes de diferentes categorías de edad son limitados. El objetivo de este estudio fue investigar los cambios estacionales del nivel aeróbico de los jugadores de la academia juvenil de un equipo de fútbol profesional. Esta investigación se realizó con un total de 51 futbolistas de las categorías U14, U15, U16, U17 y U18 de un equipo de fútbol de élite. Las capacidades aeróbicas de los atletas se midieron mediante la prueba Yo-YoIRT 1. En los análisis, las evaluaciones de distribución normal de los datos se realizaron con la prueba de Shapiro-Wilk y las homogeneidades de varianza se probaron con la prueba de Levene. Se utilizó la prueba ANOVA de una vía para analizar todos los datos paramétricos; todas las evaluaciones estadísticas se realizaron con la ayuda del programa SPSS 21. De acuerdo con la prueba Yo-YoIRT 1, se determinaron aumentos y/o disminuciones en las evaluaciones de pretemporada, mitad de temporada y final de temporada. Como resultado, los sujetos de todas las categorías aumentaron significativamente al final de la temporada en comparación con la pretemporada y la temporada media. Los grupos de edad U14 y U16 lograron una aceleración creciente a partir de la pretemporada. Sin embargo, en los grupos de edad U15, U17, U18, la aceleración disminuye en la mitad de la temporada y aumenta al final de la temporada. Se cree que se pueden observar diferencias en las respuestas a las cargas de entrenamiento durante el crecimiento y la maduración. Se puede sugerir que el incremento al final de la temporada respecto a la pretemporada, en todos los grupos, puede deberse a que la adaptación de los deportistas a los programas de entrenamiento se ve afectada por las características del desarrollo en cuanto a las categorías de edad a lo largo del tiempo.
... Studies have shown that it is associated with the high-intensity activities during a match and it informs about competition levels throughout the season (Bangsbo, Iaia, & Krustru, 2008;Mohr & Krustrup, 2014). Yo-YoIRT 1 has significant correlations with the total distance (r = 0.62) and the high-intensity distance (r = 0.73) of sports athletes in the underage teams (Roe & Malone, 2016). ...
... However, this decrease is worthy of notice. It is thought that some differences in the responses to the training loads during maturation can be observed (Roe & Malone, 2016). Significant increase at the end of the season compared to the beginning of the season in all groups may be due to the fact that the adaptation of the athletes to the training programs was positively affected by the development characteristics according to the age categories. ...
Article
Full-text available
Longitudinal studies evaluating the seasonal change of aerobic capacity in young soccer players of different age categories are limited. The aim of this study was to investigate the seasonal changes in the aerobic level of the youth academy players of a professional soccer team. This research study was carried out with a total of 51 soccer players in the U14, U15, U16, U17, and U18 categories of an elite soccer team. Aerobic capacities of the athletes were measured by Yo-YoIRT 1 Test. In the analyses, the normal distribution evaluations of the data were made with the Shapiro-Wilk test and the variance homogeneities were tested with the Levene’s Test. One Way ANOVA test was used to analyze all the parametric data. All statistical evaluations were performed with the help of the SPSS 21 package program. According to the Yo-YoIRT 1 test, increases or decreases were determined in the pre-season, mid-season and end-of-season evaluations. As a result, in the present study conducted to examine the seasonal changes of the young elite soccer players in the U14, U15, U16, U17, and U18 categories, Yo-YoIRT 1 values in all categories increased significantly at the end of the season when compared to the pre-season and the mid-season. U14 and U16 age groups gained increasing acceleration starting from the pre-season. However, in the U15, U17, U18 age groups, the case is that acceleration decreases in the middle of the season and increases at the end of the season. It is thought that differences can be observed in the responses to the training loads during maturation. It can be suggested that the increase at the end of the season compared to the pre-season in all groups may be due to the fact that the adaptation of the athletes to the training programs are affected by the developmental characteristics regarding the age categories over time.
... One factor that could explain this behavior is a greater movement economy (or running economy) in the O20 group, similar to the one found by Chamari et al. (2005), who reported a higher economy in senior elite soccer players when compared to juveniles. On the other hand, other authors reported a significant association between the velocity in the VT obtained in a treadmill continuous incremental test and the final distance covered in the YYIR2 (Roe and Malone, 2016). This suggests that the economy of movement seen as distance covered during VT, and its velocity, could be differentiating factors in performance in intermittent activities (Roe and Malone, 2016). ...
... On the other hand, other authors reported a significant association between the velocity in the VT obtained in a treadmill continuous incremental test and the final distance covered in the YYIR2 (Roe and Malone, 2016). This suggests that the economy of movement seen as distance covered during VT, and its velocity, could be differentiating factors in performance in intermittent activities (Roe and Malone, 2016). ...
Conference Paper
Full-text available
Purpose: The aim of this study was to compare the older players (O20) and the younger ones (U20) of the Colombian Professional National League 2015 champion team in cardiopulmonary responses and performance, using the Yo-Yo Intermittent Recovery Test level 2 (YYIR2). Methods: Nine O20 and nineteen U20 were voluntarily evaluated. All subjects were monitored for heart rate, and a continuous breath-to-breath recording was carried out while they performed the YYIR2. The Student T test and the Pearson correlation were used for the statistical analysis. Results: A significant difference in distance covered and speed in the ventilatory threshold between U20 players (280 ± 85,3 m) (16,6 ± 0,3 km.h-1) and O20 players (373 ± 113,1 m) (17 ± 0,3 km.h-1) was observed. Only in the U20 group, a significant correlation between the variables oxygen uptake in the ventilatory threshold (V̇ O2atVT) and performance in the test (Dmax), V̇ O2 at VT and maximum speed (Smax), peak oxygen uptake (V̇ O2peak) and Smax and V̇ O2peak and Dmax was observed. Conclusion: The only variables that differentiated the performance in the population was the analysis of the istance and the speed at the time of the ventilatory threshold. Key words: COLOMBIAN, SOCCER PLAYERS, AEROBIC FITNESS, YO-YO INTERMITTENT RECOVERY TEST.
... The GAA is the governing body for the sports of Gaelic football, hurling, camogie and handball. Gaelic football is an intermittent field sport, which has similar profiles to professional sports, such as Australian football and soccer (Roe & Malone, 2016). Gaelic football is played between two teams of 15 players. ...
Article
The aim of the current study was to assess if opposition quality influences the technical performance of lower-ranked Gaelic football teams. Over a three-year period (2016–2018), nine teams from Tier 3 were assessed on their technical performance levels over 50 matches. Teams were split into three groups according to team rating determined objectively using the Elo Ratings System for Gaelic football (Tier 1 (n = 14) (>1500 points, highest ranking), Tier 2 (n = 17) (1200–1499 points) and Tier 3 (n = 19) (<1200 points)). Teams in Tier 3 are of the same ranking as the “lower ranked teams”. A series of 1-Way ANOVA’s examined differences in technical performance comparing the lower ranked teams to all 3 tiers, where both significance and effect size were considered. There was a non-significant difference found when comparing the lower ranked teams with all three tiers for all variables (all P > 0.05). For both successful hand-passes (ƞ² = 0.140) and long kick-outs lost (ƞ² = 0.213), all tiers had a large effect. Between tiers, long kick-outs lost (d = 1.77) was the only large effect noted and occurred when the lower ranked teams played Tier 1 teams. The current study gives an insight to coaches of what parameters in the game are influenced by the opposition.
... Research in adolescent Gaelic footballers to date has explored external match and training loads with the focus on examining aerobic capacity using estimated VO 2 max (Roe & Malone, 2016) and monitoring heart rate and distance covered via GPS technology (Reilly et al., 2015). While external load monitoring may be useful, internal load measures can provide information on how the individual responds to imposed loads without the need for specialised costly equipment (Haddad et al., 2017). ...
Preprint
This study aimed to examine internal loads in male adolescent Gaelic footballers and their association with musculoskeletal injury. Written training diaries were completed by 97 male adolescent Gaelic footballers weekly and injuries, defined as any injury sustained during training or competition causing restricted performance or time lost from play, were assessed by a Certified Athletic Therapist. Daily load was determined for each player (session rating of perceived exertion by session duration) and summed to give weekly load. Univariate and multiple logistic regressions were conducted to determine the association with injury. Twenty-two injuries were recorded with match injuries significantly more common than training injuries. Periodic variations in weekly load and injuries were evident throughout the season. Univariate analysis identified weekly load (OR = 2.75; 95%CI = 1.00-7.59), monotony (OR = 4.17; 95%CI = 1.48-11.72) and absolute change in load (OR = 3.27; 95%CI = 1.15-9.32) greater than the team average were significant injury risk factors. Multiple logistic regression with 2-weekly and 3-weekly cumulative loads, absolute change, monotony, strain, ACWR and age as independent variables identified internal load measures (monotony, strain and absolute change) were associated with injury with high specificity (96.0%) but low sensitivity (25.0%). The findings highlight the need to monitor team and individual loads to avoid sudden week-to-week changes or excessive weekly loads. Open communication between players, parents, coaches and sports medicine clinicians enables effective load monitoring that can reduce injury risk and may subsequently minimise dropout, improve team success and overall sport enjoyment and promote life-long sports participation.
Article
Full-text available
Camogie (kuh$mow$gee) is a traditional , amateur Gaelic sport played by female athletes. This invasion-based field sport involves high-intensity intermittent physical demands. There is currently a dearth of available research in intercounty despite the prevalence of research in the male version of the game (hurling). The aims of this article are to provide strength and conditioning recommendations for the sport of camogie, specifically at intercounty level. These recommendations include considerations working with inter-county female camogie athletes, specific camogie injury epidemiology, physiological demands, and practical strength and conditioning for implementation by practitioners. Moreover, a sport-specific testing battery; development of physical attributes to enhance match-play performance; a proposed annual periodization cycle; and sample strength, speed and agility programs will be discussed.
Article
Full-text available
Camogie (kuh$mow$gee) is a traditional, amateur Gaelic sport played by female athletes. This invasion-based field sport involves high-intensity intermittent physical demands. There is currently a dearth of available research in intercounty despite the prevalence of research in the male version of the game (hurling). The aims of this article are to provide strength and conditioning recommendations for the sport of camogie, specifically at intercounty level. These recommendations include considerations working with intercounty female camogie athletes, specific camogie injury epidemiology, physiological demands, and practical strength and conditioning for implementation by practitioners. Moreover, a sport-specific testing battery; development of physical attributes to enhance match-play performance; a proposed annual periodization cycle; and sample strength, speed and agility programs will be discussed.
Article
Objectives To provide age- and sex-specific reference values of Yo-Yo tests in children and adolescents. Design Systematic review Methods A literature search for articles on Yo-Yo Intermittent (YYI) tests was performed in MEDLINE, SPORTDiscus, Web of Science and Google Scholar. Original reports on healthy children/adolescents 6-16 years of age were eligible. For each test, age- and sex-related reference values were calculated using global means and percentiles. Results Ninety-two studies (7,398 participants) fulfilled the eligibility criteria. The YYI tests most frequently used were the Yo-Yo Intermittent Recovery Level 1 test (YYIR1, 57.8%), Yo-Yo Intermittent Endurance Level 1 test (YYIE1, 14.7%), Yo-Yo Intermittent Recovery Level 1 Children’s test (YYIR1C, 12.7%), Yo-Yo Intermittent Endurance Level 2 test (YYIE2, 8.8%) and the Yo-Yo Intermittent Recovery Level 2 test (YYIR2, 5.9%). Of these, 71.6% reported test results of boys, 17.6% reported mixed test results and 10.8% reported test results of girls. Smoothed centile curves for the YYIR1 and YYIE1 over the entire age range were generated for boys, revealing constantly increasing performance with increasing age. Conclusions YYI tests values differ with respect to age and sex. In boys, development of YYIR1 and YYIE1 test values (6–16 years of age) was different, suggesting better applicability of the YYIR1 test for boys >13 years of age. The results may be used to rate YYI test performance for continuous screening and to identify children with low physical fitness. Since limited data was available of females, further research on YYI tests is needed with respect to sex-specific results.
Article
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Background: Although Yo-Yo intermittent tests are frequently used in a variety of sports and research studies to determine physical fitness, no structured reference exists for comparison and rating of test results. This systematic review of the most common Yo-Yo tests aimed to provide reference values for test results by statistical aggregation of published data. Methods: A systematic literature search for articles published until August 2017 was performed in MEDLINE, Web of Science, SPORTDiscus and Google Scholar. Original reports on healthy females and males ≥16 years were eligible for the analysis. Sub-maximal test versions and the Yo-Yo Intermittent Recovery Level 1 Children's test (YYIR1C) were not included. Results: 248 studies with 9,440 participants were included in the structured analysis. The Yo-Yo test types most frequently used were the Yo-Yo Intermittent Recovery Level 1 (YYIR1, 57.7%), the Yo-Yo Intermittent Recovery Level 2 (YYIR2, 28.0%), the Yo-Yo Intermittent Endurance Level 2 (YYIE2, 11.4%), and the Yo-Yo Intermittent Endurance Level 1 (YYIE1, 2.9%) test. For each separate test, reference values (global means and percentiles) for sports at different levels and both genders were calculated. Conclusions: Our analysis provides evidence that Yo-Yo intermittent tests reference values differ with respect to the type and level of sport performed.The presented results may be used by practitioners, trainers and athletes to rate Yo-Yo intermittent test performance levels and monitor training effects.
Article
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Reilly, B, Akubat, I, Lyons, M, and Collins, DK. Match-play demands of elite youth Gaelic football using global positioning system tracking. J Strength Cond Res 29(4): 989–996, 2015— Global positioning systems (GPS) technology has made athletetracking a convenient and accepted technique to specify movement patterns and physical demands in sport. The purpose of this study was to examine positional demands of elite youth Gaelic football match-play using portable GPS technology to examine movement patterns and heart rates across match periods. Fifty-six elite youth male Gaelic footballers (age, 15 6 0.66 years) fitted with portable 4-Hz GPS units were observed during 6 competitive matches (60 minutes). Data provided from the GPS unit included total distance, high-intensity ($17$km$h21) distance, sprint ($22 km$h21) distance, and total number of sprints. Heart rate was monitored continuously throughout the games. Players covered a mean distance of 5732 6 1047 m, and the mean intensity of match-play was 85% of the peak heart rate. There was a significant (p = 0.028) drop in the total distance covered in the second half (2783 6 599 m) compared with the first half (2948 6 580 m). In particular, there is a noticeable drop in the distance covered in the third quarter of the game (after half-time), which has implications for re-warming up at the end of the half-time interval. There was a highly significant (p , .001) difference in the distance traveled across the 5 positional groups with midfielders covering the greatest total distance (6740 6 384 m). The significant differences found with respect to positional groups support the implementation of individual, position-specific strength and conditioning programs.
Article
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This study examined the evolution of physical and technical soccer performance across a 7-season period in the English Premier League. Match performance observations (n=14700), collected using a multiple-camera computerised tracking system and controlled for season, phase of season, position and standard were analysed for emergent trends. Total distance covered during a match was ~2% lower in 2006-07 compared to 2012-13. Across seven seasons, high-intensity running distance increased by ~30% (890±299 vs 1151 ± 337 m, p<0.001; ES: 0.82) and high-intensity running actions by ~50% (118±36 vs 176±46, p<0.001; ES: 1.41). Sprint distance increased by ~35% across the timeframe (232±114 vs 350±139 m, p<0.001; ES: 0.93) with a concomitant increase in the number of sprints (31±14 vs 57±20, p<0.001; ES: 1.46). Mean sprint distance was shorter in 2012-13 compared to 2006-07 (5.9±0.8 vs 6.9±1.3 m, p<0.001; ES: 0.91), with the proportion of explosive sprints increasing (34±11 vs 47±9%, p<0.001; ES: 1.31). Players performed ~40% more passes (35±17 vs 25±13, p<0.001; ES: 0.66), with a greater percentage of successful passes in 2012-13 compared to 2006-07 (83±10% vs 76±13%, p<0.001; ES: 0.60). The increased number of short and medium passes followed a similar pattern to total passes (p<0.001; ES>0.6), whereas the number of long passes varied little between seasons (p<0.001; ES: 0.11). This data demonstrates evolution of physical and technical parameters in the English Premier League, and could be used to aid talent identification, training preparation and injury prevention.
Article
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The present study aimed to model the development of soccer-specific aerobic performance, assessed by the Yo-Yo IR1 in 162 elite pubertal soccer players, aged 11 to 14 years at the baseline. Longitudinal multilevel modelling analyses comprised predictors related to growth (chronological age, body size (stature and weight) and composition (fat mass, fat free mass)), motor coordination (three KTK subtests: jumping sideways, moving sideways, backward balancing) and estimated biological maturation groups (APHV, earliest (<percentile 33) and latest maturers (>percentile 66)). The best fitting model on the soccer-specific aerobic performance could be expressed as: -3639.76 + 369.86 x age + 21.38 x age + 9.12 x stature - 29.04 x fat mass + 0.06 x backward balance. Maturity groups had a negligible effect in the soccer-specific aerobic performance (-45.32 ± 66.28; p>0.05). The present study showed that the development of aerobic performance in elite youth soccer is related to growth, muscularity and emphasized the importance of motor coordination in the talent identification and development process. Note that biological maturation was excluded from the model which might endorse the homogeneity in estimated biological maturation status in the present elite pubertal soccer sample.
Article
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Purpose The purpose of this investigation was to quantify maximal aerobic power (VO 2max ) in soccer as a function of performance level, position, age, and time of season. In addition, the authors examined the evolution of VO 2max among professional players over a 23-y period. Methods 1545 male soccer players (22 ± 4 y, 76 ± 8 kg, 181 ± 6 cm) were tested for VO 2max at the Norwegian Olympic Training Center between 1989 and 2012. Results No differences in VO 2max were observed among national-team players, 1st- and 2nd-division players, and juniors. Midfielders had higher VO 2max than defenders, forwards, and goalkeepers ( P < .05). Players <18 y of age had ~3% higher VO 2max than 23- to 26-y-old players ( P = .016). The players had 1.6% and 2.1% lower VO 2max during off-season than preseason ( P = .046) and in season ( P = .021), respectively. Relative to body mass, VO 2max among the professional players in this study has not improved over time. Professional players tested during 2006–2012 actually had 3.2% lower VO 2max than those tested from 2000 to 2006 ( P = .001). Conclusions This study provides effect-magnitude estimates for the influence of performance level, player position, age, and season time on VO 2max in men’s elite soccer. The findings from a robust data set indicate that VO 2max values ~62–64 mL · kg ⁻¹ · min ⁻¹ fulfill the demands for aerobic capacity in men’s professional soccer and that VO 2max is not a clearly distinguishing variable separating players of different standards.
Article
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To examine the effects of body size on locomotor performance, 807 15-year-old French and 64 Qatari soccer players participated in the present study. They performed a 40-m sprint and an incremental running test to assess maximal sprinting (MSS) and aerobic speeds, respectively. French players were advanced in maturity, taller, heavier, faster and fitter than their Qatari counterparts (e.g., Cohen's d=+1.3 and + 0.5 for body mass and MSS). However, when adjusted for body mass (BM), Qatari players had possibly greater MSS than French players (d=+0.2). A relative age effect was observed within both countries, with the players born in the first quarter of the year being taller, heavier and faster that those born during the fourth quarter (e.g., d=+0.2 for MSS in French players). When directly adjusted for BM, these MSS differences remained (d=+0.2). Finally, in both countries, players selected in National teams were taller, heavier, faster and fitter than their non-selected counterparts (e.g., d=+0.6 for MSS in French players), even after adjustments for body size (d=+0.5). Differences in locomotor performances between players with different phenotypes are likely mediated by differences in body size. However, when considering more homogeneous player groups, body dimensions are unlikely to substantially explain the superior locomotor performances of older and/or international players.
Article
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The two major sports indigenous to Ireland are Gaelic football and hurling. Both are 15-a-side field games played on a pitch 40% longer than a soccer field. They are firmly linked to a nationalist tradition and have by far the highest participation rates in sports in the country. Both games make multiple demands on participants due to their free-flowing nature and quick movement of play from end to end of the pitch. Hurling calls for hand–eye coordination and skilled use of the hurling stick in hitting and blocking the ball. Fitness characteristics mirror game demands. Participants at elite level in both games display high aerobic power, the footballers tending to be stronger in the upper body and better in vertical jumping. Gaelic footballers in particular match the fitness characteristics of professional soccer players, except for sprinting speed. Less attention has been paid to female participants, especially in camogie, the female version of hurling. Despite their amateur status, and due to the popularity of the sports and the training regimens adopted by players, the games have garnered sports science support systems for elite performers. Support personnel benefit from a generic knowledge base as well as a burgeoning research agenda targeted at the Gaelic games.
Article
The two Yo-Yo intermittent recovery (IR) tests evaluate an individual’s ability to repeatedly perform intense exercise. The Yo-Yo IR level 1 (Yo-Yo IR1) test focuses on the capacity to carry out intermittent exercise leading to a maximal activation of the aerobic system, whereas Yo-Yo IR level 2 (Yo-Yo IR2) determines an individual’s ability to recover from repeated exercise with a high contribution from the anaerobic system. Evaluations of elite athletes in various sports involving intermittent exercise showed that the higher the level of competition the better an athlete performs in the Yo-Yo IR tests. Performance in the Yo- Yo IR tests for young athletes increases with rising age. The Yo-Yo IR tests have shown to be a more sensitive measure of changes in performance than maximum oxygen uptake. The Yo-Yo IR tests provide a simple and valid way to obtain important information of an individual’s capacity to perform repeated intense exercise and to examine changes in performance.
Article
Aim To provide an evidence-based review of muscle metabolism changes with sex-, age- and maturation with reference to the development of youth sport performance. Methods A narrative review of data from both invasive and non-invasive studies, from 1970 to 2015, founded on personal databases supported with computer searches of PubMed and Google Scholar. Results Youth sport performance is underpinned by sex-, age- and maturation-related changes in muscle metabolism. Investigations of muscle size, structure and metabolism; substrate utilisation; pulmonary oxygen uptake kinetics; muscle phosphocreatine kinetics; peak anaerobic and aerobic performance; and fatigue resistance; determined using a range of conventional and emerging techniques present a consistent picture. Age-related changes have been consistently documented but specific and independent maturation-related effects on muscle metabolism during exercise have proved elusive to establish. Children are better equipped for exercise supported primarily by oxidative metabolism than by anaerobic metabolism. Sexual dimorphism is apparent in several physiological variables underpinning youth sport performance. As young people mature there is a progressive but asynchronous transition into an adult metabolic profile. Conclusions The application of recent developments in technology to the laboratory study of the exercising child and adolescent has both supplemented existing knowledge and provided novel insights into developmental exercise physiology. A sound foundation of laboratory-based knowledge has been established but the lack of rigorously designed child-specific and sport-specific testing environments has clouded the interpretation of the data in real life situations. The primary challenge remains the translation of laboratory research into the optimisation of youth sports participation and performance.
Article
Purpose: To assess the relationships between player characteristics (including age, playing experience, ethnicity, and physical fitness) and in-season injury in elite Australian football. Design: Single-cohort, prospective, longitudinal study. Methods: Player characteristics (height, body mass, age, experience, ethnicity, playing position), preseason fitness (6-min run, 40-m sprint, 6×40-m sprint, vertical jump), and in-season injury data were collected over 4 seasons from 1 professional Australian football club. Data were analyzed for 69 players, for a total of 3879 player rounds and 174 seasons. Injury risk (odds ratio [OR]) and injury severity (matches missed; rate ratio [RR]) were assessed using a series of multilevel univariate and multivariate hierarchical linear models. Results: A total of 177 injuries were recorded with 494 matches missed (2.8±3.3 matches/injury). The majority (87%) of injuries affected the lower body, with hamstring (20%) and groin/hip (14%) most prevalent. Nineteen players (28%) suffered recurrent injuries. Injury incidence was increased in players with low body mass (OR=0.887, P=.005), with poor 6-min-run performance (OR=0.994, P=.051), and playing as forwards (OR=2.216, P=.036). Injury severity was increased in players with low body mass (RR=0.892, P=.008), tall stature (RR=1.131, P=.002), poor 6-min-run (RR=0.990, P=.006), and slow 40-m-sprint (RR=3.963, P=.082) performance. Conclusions: The potential to modify intrinsic risk factors is greatest in the preseason period, and improvements in aerobic-running fitness and increased body mass may protect against in-season injury in elite Australian football.
Article
Gaelic football is the second most popular team sport in Ireland in terms of participation. However, very little research exists on the nutritional considerations for elite male Gaelic footballers. Gaelic football is an intermittent type field game played by two teams of fifteen players. Although amateurs, elite players may train and compete 4-5 times per week and may play for several teams. Research suggests that elite footballers are similar anthropometrically and in fitness to professional soccer players. Work-rate analysis shows that footballers experience longer durations of high-intensity (HI) activity (5-7s) and shorter rest durations than soccer players. Recent data suggests that half-forwards/backs perform a greater amount of HI work during games than players in other positions. Fatigue is apparent between the first and second halves and the first and fourth quarters. The limited amount of nutritional studies conducted implies that footballers may be deficient in energy intake and may be at the lower end of recommended carbohydrate intakes to support training. A wide variety of sweat rates have been measured during training, demonstrating the importance of individual hydration strategies. Ergogenic aids such as creatine and caffeine may prove beneficial to performance, although data is extrapolated from other sports. Due to the lack of research in Gaelic football, further population specific studies are required. Future areas of research on the impact of nutrition on Gaelic football performance are examined. In particular, the creation of a test protocol mimicking the activity patterns and intensity of a Gaelic football game is warranted.