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Assessing the usefulness of submaximal exercise heart rates for monitoring cardiorespiratory fitness changes in elite youth soccer players

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Aim: This study aimed to assess the value of monitoring fitness in elite youth soccer players (U15 to U19 age groups) by analyzing the concomitant changes in heart rate at submaximal intensity (HR12km/h) and the velocity at a lactate concentration of 4 mmol/l (v4mmol/l). Methods: Players were tested by means of an incremental treadmill test on two occasions during the summer pre-season in two consecutive seasons. Based on data from a total of 170 test comparisons from the U15 (n = 48 test comparisons), U16 (n = 40 test comparisons), U17 (n = 46 test comparisons), and U19 (n = 36 test comparisons) age groups, the agreement between substantial changes in HR12km/h and v4mmol/l was analyzed using the threshold combination of HR12km/h = 4.5% and v4mmol/l = 6.0%. Results: Results revealed 2% full mismatches, 36% partial agreements, and 62% full agreements for the whole sample in terms of fitness change interpretation between both variables. The respective values for the U15 to U19 age groups ranged between 0% and 5% full mismatches, 28-44% partial agreements, and 56-68% full agreements with no meaningful differences between age groups. Conclusion: In conclusion, our findings confirm the practical value of using HR12km/h to monitor fitness changes in elite youth soccer players when lactate sampling during incremental tests is not possible.
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Science and Medicine in Football
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/rsmf20
Assessing the usefulness of submaximal exercise
heart rates for monitoring cardiorespiratory
fitness changes in elite youth soccer players
Stefan Altmann, Ludwig Ruf, Rainer Neumann, Sascha Härtel, Alexander
Woll & Martin Buchheit
To cite this article: Stefan Altmann, Ludwig Ruf, Rainer Neumann, Sascha Härtel, Alexander
Woll & Martin Buchheit (2022): Assessing the usefulness of submaximal exercise heart rates for
monitoring cardiorespiratory fitness changes in elite youth soccer players, Science and Medicine in
Football, DOI: 10.1080/24733938.2022.2060520
To link to this article: https://doi.org/10.1080/24733938.2022.2060520
Accepted author version posted online: 29
Mar 2022.
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Publisher: Taylor & Francis & Informa UK Limited, trading as Taylor & Francis Group
Journal: Science and Medicine in Football
DOI: 10.1080/24733938.2022.2060520
Assessing the usefulness of submaximal exercise heart rates for
monitoring cardiorespiratory fitness changes in elite youth soccer players
Submission Type:
Short Communication
Authors:
Stefan Altmann1,2
Ludwig Ruf1,4
Rainer Neumann2,3
Sascha Härtel4
Alexander Woll5
Martin Buchheit6,7,8,9
1TSG ResearchLab gGmbH, Zuzenhausen, Germany
2Department for Performance Analysis, Institute of Sports and Sports Science,
Karlsruhe Institute of Technology, Karlsruhe, Germany
3Institute of Movement and Sport, University of Education Karlsruhe, Karlsruhe,
Germany
4TSG 1899 Hoffenheim, Zuzenhausen, Germany
5Department for Social and Health Sciences in Sport, Institute of Sports and
Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
6HIITScience, Revelstoke, BC, Canada
7Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia
8Kitman Labs, Performance Research Intelligence Initiative, Dublin, Ireland
9French National Institute of Sport (INSEP), Laboratory of Sport, Expertise and
Performance (EA 7370), Paris, France
For submission to: Science and Medicine in Football
Submission Date: October 26, 2021
Corresponding Author:
Stefan Altmann, PhD
TSG ResearchLab gGmbH
Horrenberger Str. 58, 74939 Zuzenhausen, Germany
Phone: +49-7261-9493-170
Email: stefan.altmann@tsg-researchlab.de
Monitoring fitness changes in soccer players 2
Running Head: Monitoring fitness changes in youth soccer players
Abstract Word Count: 212
Word Count: 1,990
Tables: 2
Figures: 1
Keywords:
youth soccer; player monitoring; fitness; heart rate; lactate; aerobic
Monitoring fitness changes in soccer players 3
Abstract
This study aimed to assess the value of monitoring fitness in elite youth soccer
players (U15 to U19 age groups) by analyzing the concomitant changes in heart
rate at submaximal intensity (HR12km/h) and the velocity at a lactate concentration
of 4 mmol/l (v4mmol/l).
Players were tested by means of an incremental treadmill test on two occasions
during the summer pre-season in two consecutive seasons. Based on data from a
total of 170 test comparisons from the U15 (n = 48 test comparisons), U16 (n =
40 test comparisons), U17 (n = 46 test comparisons), and U19 (n = 36 test
comparisons) age groups, the agreement between substantial changes in
HR12km/h and v4mmol/l was analyzed using the threshold combination of HR12km/h =
4.5% and v4mmol/l = 6.0%.
Results revealed 2% full mismatches, 36% partial agreements, and 62% full
agreements for the whole sample in terms of fitness change interpretation
between both variables. The respective values for the U15 to U19 age groups
ranged between 0–5% full mismatches, 28–44% partial agreements, and 56–68%
full agreements with no meaningful differences between age groups.
In conclusion, our findings confirm the practical value of using HR12km/h to monitor
fitness changes in elite youth soccer players when lactate sampling during
incremental tests is not possible.
Monitoring fitness changes in soccer players 4
Introduction
Youth soccer players cover up to 8–9 km per match, consisting of
moderate- and high-intensity running bouts interspersed by low-intensity
movements and breaks. These match-running characteristics increase with age,
thereby placing marked demands on the cardiorespiratory system of the players.1
Therefore, testing cardiorespiratory fitness plays an integral role in the overall
monitoring process of such players. While multistage incremental tests with heart
rate (HR) and blood lactate measures are considered a gold standard method in
this regard,2,3 this method has several drawbacks (e.g., time-labor, poor player
buy-in, expensive equipment for data collection and analysis) which limits its use
for regular testing during the competitive season. As a result, monitoring exercise
HR during a submaximal run in the field has emerged as an easy-to-implement
method in this setting.4 Indicated by large correlations between the changes in
exercise HR and maximal (aerobically-oriented) performance, the validity and
sensitivity of this simple practice have been confirmed in a number of studies.4–11
In this context, Buchheit et al.10 analyzed the change in HR at a running velocity
of 12 km/h (HR12km/h) and the corresponding change of the running speed at the
anaerobic threshold (i.e., blood lactate concentration of 4 mmol/l; v4mmol/l), both
determined during incremental treadmill tests during two testing occasions. They
found that substantial individual changes in HR12km/h were associated with
similarly substantial changes in v4mmol/l in more than 90% of the 23 test
comparisons in a professional soccer team. Based on a large sample (225 test
comparisons in professional soccer players), Altmann et al.11 replicated this
methodology and reported that substantial changes of the two abovementioned
parameters match in 60–78% of cases, depending on the context (e.g., timing
during the season).
However, these studies were conducted in adult soccer players and whether
these results could be generalized to youth players of different age groups
remains to be confirmed.
Therefore, the aim of this study was to assess the value of monitoring changes in
fitness in elite youth soccer players (U15 to U19 age groups) by analyzing the
Monitoring fitness changes in soccer players 5
concomitant changes in HR at submaximal intensity (HR12km/h) and the velocity at
a lactate concentration of 4 mmol/l (v4mmol/l).
Materials and Methods
Design
Observational, cross-sectional.
Population
A total of 170 test comparisons from the male U15 (age = 14.2 ± 0.3 years; n = 48
test comparisons), U16 (age = 15.3 ± 0.3 years; n = 40 test comparisons), U17
(age = 16.0 ± 0.5 years; n = 46 test comparisons), and U19 (age = 17.7 ± 0.7
years; n = 36 test comparisons) age groups of three professional German soccer
teams competing in the highest division of their respective age groups were used
for the purpose of this study. Data were collected during the routine fitness
assessments of the teams so that ethical approval was not required.12 The
players provided informed consent prior to participating in the fitness
assessments. All players were free from injuries at the time of testing and did not
train the day before testing.
Methodology
All players were tested by means of an incremental treadmill test on two
occasions during the summer pre-season in two consecutive seasons.
The incremental treadmill test (Woodway GmbH, Weil am Rhein, Germany)
started at 6 km/h and increased by 2 km/h every 3 min until volitional exhaustion
of the players (vmax). Rest between stages was passive and lasted for 30 sec. HR
(H7 and H10, Polar Electro Oy, Kempele, Finland) was measured during and
blood lactate (capillary blood samples from the earlobe, Biosen C-Line Sport,
EKF-diagnostic GmbH, Barleben, Germany) collected after each stage.13,14
Data Analysis
The HR at a running velocity of 12 km/h (% of maximum HR; HR12km/h) and the
running velocity at a lactate concentration of 4 mmol/l (as an indicator of the fixed
Monitoring fitness changes in soccer players 6
anaerobic threshold; v4mmol/l) were used for further analysis. V4mmol/l was
automatically determined using the Ergonizer Software (K. Roecker, Freiburg,
Germany); for a graphical illustration, see Buchheit et al.10 Regarding HR12km/h,
the average HR during the last 30 s of the 12-km/h stage was used. Between-
testing session percentage changes in HR12km/h and v4mmol/l were calculated.
Lastly, the changes in HR12km/h and v4mmol/l of a single player over a 3.5-year
period (case study; n = 10 test comparisons) were also examined. For this player,
not only pre-season data were used but also data obtained at different moments
during the competitive season (e.g., summer pre-season, autumn in-season,
winter pre-season, spring in-season).
Statistical Analysis
The data were analyzed using SPSS statistical software version 26.0 (SPSS,
Chicago, USA) and Microsoft Excel (Microsoft, Redmond, USA).
The agreement between changes in HR12km/h and v4mmol/l was analyzed for the
whole sample, each age group separately as well as for the case study on the
individual player. First, Pearson product-moment correlations with 95%
confidence intervals (95% CI) were applied to analyze the relationships between
the change in HR12km/h and v4mmol/l. Moreover, the concomitant changes in both
variables were examined using the following classification:
- Full agreement (e.g., improved () fitness from HR12km/h / improved ()
fitness from v4mmol/l)
- Partial agreement (e.g., unclear change () in fitness from HR12km/h /
improved () fitness from v4mmol/l)
- Full mismatch (e.g., impaired () fitness from HR12km/h / improved () fitness
from v4mmol/l)
Based on the recommendations of Altmann et al.,11 the threshold combination of
HR12km/h = 4.5% and v4mmol/l = 6.0% was used to indicate substantial changes in
the respective variables. Data of all variables were normally distributed.
Monitoring fitness changes in soccer players 7
Results
For the U15 age group, v4mmol/l and vmax were 13.7 ± 1.2 km/h, 95% confidence
interval (CI) 13.6–14.2 km/h and 16.7 ± 1.2 km/h, CI 16.4–17.1 km/h, respectively.
For the U16 age group, v4mmol/l and vmax were 14.0 ± 1.4 km/h, CI 13.4–14.2 km/h
and 17.1 ± 1.3 km/h, CI 16.5–17.2 km/h, respectively. For the U17 age group,
v4mmol/l and vmax were 14.4 ± 1.2 km/h, CI 14.0–14.7 km/h and 17.7 ± 1.1, CI 17.3–
18.0 km/h, respectively. For the U19 age group, v4mmol/l and vmax were 14.2 ± 1.2
km/h, CI 13.6–14.3 km/h and 17.5 ± 1.1 km/h, CI 16.9–17.6 km/h, respectively.
Pearson correlations and 95% CI between changes in HR12km/h and v4mmol/l for the
whole sample, each group, and the case study are shown in Table 1. All response
classifications between changes in fitness from both variables (HR12km/h: threshold
of 4.5%; v4mmol/l: threshold of 6.0%) can be found in Table 2. Absolute values as
well as percentage changes for HR12km/h and v4mmol/l for a single player over a 3.5-
year period are illustrated in Figure 1.
+++ Please insert Tables 1–2 and Figure 1 about here +++
Discussion
The aim of the present study was to assess the agreement between changes in
HR12km/h and v4mmol/l to estimate changes in fitness in elite youth soccer players
(U15 to U19 age groups).
The correlation regarding between-season changes in HR12km/h and v4mmol/l was r
= -0.40 for the whole sample and ranged between r = -0.31 and -0.48 for the U15
to U19 age groups (Table 1). Using the threshold combination of HR12km/h = 4.5%
and v4mmol/l = 6.0% for analyzing concomitant changes in both variables, we found
2% full mismatches, 36% partial agreements, and 62% full agreements for the
whole sample. The respective values for the U15 to U19 age groups ranged
between 0–5% full mismatches, 28–44% partial agreements, and 56–68% full
agreements (Table 2).
Monitoring fitness changes in soccer players 8
While the magnitude of correlation provides an overall impression on the
agreement between changes in HR12km/h and v4mmol/l on a team level, the ability of
the two variables to determine substantial fitness changes at the individual level is
likely what coaches and practitioners are most interested in as these information
can be used to inform decisions about the training process (e.g., return-to-play
programs, fitness top-ups). The full agreements of 62% in the present study for
the whole sample are somewhat lower than the 71% reported by Altmann et al.,11
who also compared changes between two consecutive seasons. Since in the
latter study, we investigated adult professional soccer players, the present results
might indicate that the practical value of HR monitoring to assess fitness changes
during short submaximal runs could be slightly reduced in youth as examined in
the present study. In this specific population for example, Buchheit et al.7 showed
changes in HR12km/h to better reflect true improvements than decrements of
physical performance. However, there is no evidence that exercise HR should be
less reliable or less indicative of fitness changes in youth players per se.7,15 A
possible explanation for the present finding could rather be related to the
proportion of substantial fitness changes observed (as indicated by changes in
v4mmol/l) in relation to the overall changes comparisons, which was greater in the
present study (i.e., 34% (57 out of 170 comparisons) vs 23% (8 out of 35
comparisons) in the study of Altmann et al.11). In fact, since the level of full
agreement is lower within this specific change category (42% and 38% of
agreement in the current vs the previous study, respectively) than for all the other
test comparisons (i.e., unclear changes, 62% and 71% of full agreement), the
young players of the present study displayed a “mechanically” reduced level of
overall agreement.
Of note, the higher proportion of substantial fitness changes (which were
predominantly improvements) of the U15 to U19 players in our study reflect the
different training foci between youth and adult soccer. In youth soccer, the main
aim is to develop (physical) performance levels of players in order to optimally
prepare them for the increased demands of adult soccer.16 As a consequence,
physical performance (in our case cardiorespiratory fitness) might frequently
change, both in adaption to targeted training programs17 and biological maturation
Monitoring fitness changes in soccer players 9
towards adulthood.18 By contrast, in adult soccer, the main aims are to maintain
the players’ already developed physical performance levels and to prepare for or
recover from weekly matches.17
We also sought to identify patterns in terms of agreement between changes in
HR12km/h and v4mmol/l across the four age groups investigated. However, no clear
age-related trend was evident. We also believe that the slight between-group
differences in terms of full agreements (i.e., 54% (U15) and 68% (U17)) might only
stem from other influencing factors of HR12km/h and v4mmol/l such as time of day,19
load over the previous days,20 hydration4 or nutritional status21 (that were not
systematically controlled in our study). Importantly, full mismatches between
changes in HR12km/h and v4mmol/l were very uncommon for all age groups (0–5%; 3
out of 170 comparisons). Consequently, coaches and practitioners are very
unlikely to misinterpret changes in a player’s fitness based on the threshold
combination used in this study.
Lastly, we included a case study in our analyses where an individual player was
monitored 11 times over a 3.5-year period from the age of 14.6 to 18.1 years
(Figure 1). The results (correlation of r = -0.68; 0% full mismatches, 20% partial
agreements, and 80% full agreements) are higher than those of the whole
sample. Indeed, only one substantial fitness change as indicated by v4mmol/l
occurred within this time period which facilitates the high proportion of full
agreements (see explanation regarding proportion of substantial fitness changes
above). However, while the changes from the first to the second testing occasion
are less comparable (large increase in v4mmol/l by 13.2%, rather small decrease in
HR12km/h by -3.0%), the changes in both variables follow a similar pattern for all
following testing occasions.
Given that these analyses also included within-season tests, where influencing
factors of HR12km/h and v4mmol/l are commonly even less controlled,11 the results of
the case study confirm the practical value of monitoring HR12km/h on an individual
basis.
Monitoring fitness changes in soccer players 10
The findings of this study should be interpreted in light of its limitations. As
previously mentioned, influencing factors of HR12km/h and v4mmol/l were not
systematically controlled for. In addition, all data were obtained on a treadmill in a
laboratory, and therefore the transfer of the findings to the soccer pitch remains to
be investigated.
Practical Applications
Based on their specific purpose and a cost-benefit approach, coaches can decide
if the 62% of agreement between changes in HR12km/h and v4mmol/l are high
enough. For example, incremental tests with HR and blood lactate sampling
together should be preferred, if they aim to prescribe lactate-threshold based
training intensities and are not only interested in the direction of possible changes
in fitness but also their magnitude. When using HR12km/h only, coaches can on
average expect a 6.0%-change in v4mmol/l to yield a 1.0-km/h change in vmax for a
given player.11 Such a change commonly leads to the assignment to a different
player group for HIIT drills.
Conclusions
Our study showed that between-season changes in HR12km/h (threshold of 4.5%)
using a simple 3-min run match changes in v4mmol/l (threshold of 6.0%) in 62% of
the time in elite youth soccer players with no meaningful differences between U15
to U19 age groups. Moreover, opposite interpretations are extremely unlikely to
occur. Taken together, these findings confirm the practical value of using HR12km/h
to monitor fitness changes in this population. To further interpret the agreements
or mismatches between changes in HR12km/h and v4mmol/l, future research could
benefit from investigating influencing factors of these two variables. In doing so,
longitudinal measurements using within-subject correlations seem promising.22
Monitoring fitness changes in soccer players 11
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Monitoring fitness changes in soccer players 13
Disclosure of interest
All contributing authors declare that they have no conflicts of interest relevant to
the content of this study.
Figure Legends
Figure 1. Absolute HR12km/h and v4mmol/l values (upper graph; n = 11) as well as
percentage changes in HR12km/h and v4mmol/l (lower graph; n = 10) for a single
player over a 3.5-year period. The smallest worthwhile changes (SWC) are shown
with grey (HR12km/h) and light grey (v4mmol/l) areas. Error bars represent the typical
errors (TE) of each variable. To be considered as substantial (i.e., positive, +, or
negative, -, estimated change in fitness), changes had to be greater than the
SWC + TE. Unclear changes in the lower graph are indicated with an “u”.
Twitter Handle
@StefanAltmann3
@RufLudwig
@mart1buch
Monitoring fitness changes in soccer players 14
Acknowledgments
The authors would like to thank Christian Kloss and Frederik Nockemann for their
support during data collection.
Tables Captions
Table 1. Pearson correlations and 95% confidence intervals (95% CI) between changes
in HR12km/h and v4mmol/l regarding the whole sample, all age groups, and the case study.
Table 2. Response classifications between changes in HR12km/h and v4mmol/l along with
full mismatches, partial agreements, and full agreements regarding the whole sample,
all age groups, and the case study.
Monitoring fitness changes in soccer players 15
Table 1. Pearson correlations and 95% confidence intervals (95% CI) between changes
in HR12km/h and v4mmol/l regarding the whole sample, all age groups, and the case study.
Pearson's r (95% CI)
Whole sample (n = 170) r = -0.40 (-0.26 to -0.53)
U15 (n = 48) r = -0.48 (-0.31 to -0.62)
U16 (n = 40) r = -0.32 (0.03 to -0.70)
U17 (n = 46) r = -0.41 (-0.19 to -0.60)
U19 (n = 36) r = -0.31 (0.01 to -0.60)
Case study (n = 10) r = -0.68 (-0.38 to -0.98)
Table 2. Response classifications between changes in HR12km/h and v4mmol/l along with
full mismatches, partial agreements, and full agreements regarding the whole sample,
all age groups, and the case study.
Whole Sample (n =
170) U15 (n = 48)
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
HR12km/h
6 17 3
Full
mismat
ch
2
%
fitness
from
HR12km/h
1 8 0
Full
mismat
ch
0
%
fitness
from
HR12km/h
10 82 20
Partial
agreem
ent
3
6
%
fitness
from
HR12km/h
3 21 6
Partial
agreem
ent
4
4
%
fitness
from
HR12km/h
0 14 18
Full
agreem
ent
6
2
%
fitness
from
HR12km/h
0 4 5
Full
agreem
ent
5
6
%
U16 (n = 40) U17 (n = 46)
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
HR12km/h
1 4 2
Full
mismat
ch
5
%
fitness
from
HR12km/h
4 5 1
Full
mismat
ch
2
%
fitness
from
HR12km/h
2 21 3
Partial
agreem
ent
2
8
%
fitness
from
HR12km/h
3 23 4
Partial
agreem
ent
3
3
%
fitness
from
HR12km/h
0 2 5
Full
agreem
ent
6
8
%
fitness
from
HR12km/h
0 3 3
Full
agreem
ent
6
5
%
U19 (n = 36)
Case Study (n =
10)
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
v4mmol/l
fitness
from
HR12km/h
0 0 0
Full
mismat
ch
0
%
fitness
from
HR12km/h
1 1 0
Full
mismat
ch
0
%
fitness
from
HR12km/h
2 17 7
Partial
agreem
ent
3
9
%
fitness
from
HR12km/h
1 7 0
Partial
agreem
ent
2
0
%
fitness
from
HR12km/h
0 5 5
Full
agreem
ent
6
1
%
fitness
from
HR12km/h
0 0 0
Full
agreem
ent
8
0
%
Monitoring fitness changes in youth soccer players 17
Monitoring fitness changes in youth soccer players 18
FIG 1
Article
Full-text available
Purpose: This study aimed to examine the responsiveness of commonly used measurement instruments to a short training camp by examining the time course of psychophysiological responses in high-level youth soccer players. Methods: Monitoring was carried out in 14 U15 male soccer players of 1 professional youth academy. Players provided data 3 days prior to (D - 3), during (D2-D4), and 1 (D + 1) and 4 days (D + 4) after the camp: 4 items for the Short Recovery and Stress Scale (SRSS), a countermovement jump (CMJ), and a submaximal run to assess exercise heart rate and heart-rate recovery. Training load during the camp followed an alternating low-high pattern, with lower training loads on D1 and D3 and higher training loads on D2 and D4. Results: Changes in SRSS physical performance capability, emotional balance, overall recovery, muscular stress, and overall stress were small to moderate on D3 and moderate to large on D + 1, while changes were trivial on D + 4. Some CMJ parameters related to the eccentric phase were slightly improved on D3, and these parameters were slightly impaired on D4. Changes in CMJ parameters were trivial on D + 1 and D + 4. After a moderate decrease in exercise heart rate on D3, there was a small decrease on D + 4 and a moderate increase in heart-rate recovery. Conclusion: Measurement instruments such as the SRSS and submaximal runs can be used to monitor acute psychophysiological responses to load, while the CMJ may provide little insight during periods of intensified training load.
Article
Full-text available
Purpose: To assess the value of monitoring changes in fitness in professional soccer players, using changes in heart rate at submaximal intensity (HR12km/h) over the velocity at a lactate concentration of 4 mmol/L (v4mmol/L). The authors reexamined (1) a range of threshold magnitudes, which may improve detecting substantial individual changes and (2) the agreement between changes in these 2 variables. Methods: On at least 2 occasions during different moments of the season, 97 professional soccer players from Germany (first, second, and fourth division) completed an incremental test to determine HR12km/h and v4mmol/L. Optimal thresholds for changes in HR12km/h and v4mmol/L were assessed, using various methods (eg, smallest worthwhile change + typical error [TE], successive reiterations approach). Agreement between both variable changes was examined for the whole sample (225 comparisons), 4 different subgroups (depending on the moment of the season), and in an individual over 6 years (n = 23 tests). Results: Changes of 4.5% and 6.0% for HR12km/h and v4mmol/L, respectively, were rated as optimal to indicate substantial changes in fitness. Depending on the (sub)groups analyzed, these thresholds yielded 0% to 2% full mismatches, 22% to 38% partial agreements, and 60% to 78% full agreements in terms of fitness change interpretation between both variables. Conclusions: When lactate sampling during incremental tests is not possible, practitioners willing to monitor adult professional soccer players' (Germany; first, second, and fourth division) training status can confidently implement short, 3-minute submaximal runs, with 4.5% changes in HR12km/h being indicative of true substantial fitness changes, with 60% to 78% accuracy. Future studies should investigate the potential role of confounding factors of HR12km/h to improve changes in fitness prediction.
Article
Full-text available
The purposes of this study were: (i) to analyze the variations of maximal oxygen consumption (VO2max), maximal heart rate (HRmax), heart rate rest, acceleration, maximal speed, agility, anaerobic sprint test (RAST) of peak power (RPP), RAST of minimum power, RAST of average power (RAP), and RAST of fatigue index (RFI) during the competition season, using maturation status (MS) and accumulated training load (ATL) as covariates; (ii) to describe differences between responders and non-responders in relationship with baseline levels. Twenty-three elite players of the same team competing in the national under-16 competitions were evaluated for 20 weeks in period 1 (P1= Before league), middle (Mid= mid league), and period 2 (P2= After league). Significant improvements were noticed in VO2max, RPP and RAP between P1 and Mid, with small, moderate and trivial effect sizes, respectively. Between Mid and P2 and in the entire period of evaluation, increases in maximal speed, RAP (both with small effect sizes), RPP and RFI (both with moderate effect sizes) were registered. When analyzing responders and non-responders, only HRmax (between P1 to P2) showed no differences between those groups. All these variables seemed to be influenced by ATL and MS, since when included as covariates, the differences were vanished. Additionally, almost all variables presented differences between responders and non-responders highlighting the individual responses to training.
Article
Full-text available
Purpose: To describe individual sleeping patterns and nocturnal cardiac autonomic activity of National team female soccer players during an international tournament. Materials and methods: Twenty elite female soccer players (aged 25.2±3.1 years) wore wrist actigraph units and heart rate (HR) monitors during night-sleep throughout 9 consecutive days (6 day-time training sessions [DT], 2 day-time matches [DM], and 1 evening-time match [EM]) of an international tournament. Training and match loads were monitored using the session-rating of perceived exertion (s-RPE) and wearable 18-Hz GPS (total distance covered [TD], training and match exposure time, and highspeed running [HSR]) to characterize training and match loads. Results: Individually, s-RPE, TD, exposure time, and HSR during training sessions ranged from 20 to 680 arbitrary units (AU), 892 to 5176 m, 20 to 76 min, and 80 to 1140 m, respectively. During matches, s-RPE, TD, exposure time, and HSR ranged from 149 to 876 AU, 2236 to 11210 m, 20 to 98 min, and 629 to 3213 m, respectively. Individually, players slept less than recommended (<7 hours) on several days of the tournament, especially after EM (n=8; TST ranging between 6:00-6:54 h). Total sleep time coefficient of variation (CV) ranged between 3.1 and 18.7%. However, all players presented good sleep quality (i.e., sleep efficiency ³75%; individual range between: 75-98%) on each day of the tournament. Most of the players presented small fluctuations in nocturnal cardiac autonomic activity (individual nocturnal heart rate variability [HRV] ranged from 3.91-5.37 ms and HRV CV ranged from 2.8-9.0%), while two players presented higher HRV CV (11.5 and 11.7%; respectively). Conclusion: Overall, this study highlights the substantial individual variability in sleep and HRV measures, suggesting the adoption of an individual approach to monitor sleep, training and match loads and recovery, to better understand how players cope with highly demanding competitions.
Article
Full-text available
Background: To date, athletic performance has been extensively assessed in youth soccer players through laboratory and field testing. Only recently has running performance via time-motion analysis been assessed during match-play. Match running data are often useful in a practical context to aid game understanding and decision-making regarding training content and prescriptions. A plethora of previous reviews have collated and appraised the literature on time-motion analysis in professional senior players, but none have solely examined youth players. Objective: The aim of the present systematic review was to provide a critical appraisal and summary of the original research articles that have evaluated match running performance in young male soccer players. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement, literature searches were performed in four databases, namely, PubMed, ISI Web of Science, SPORTDiscus and SciELO, using the descriptors “soccer”, “football”, “young”, “youth”, “junior”, “physical performance”, “running performance”, “match running performance”, “movement patterns”, “time-motion analysis”, “distances covered”, “activity profile”, “work rate”, “match analysis”, and “match performance”. Articles were included only if they were original articles written in the English language, studied populations of male children and/or adolescents (≤ 20 years of age), were published/ahead of print on or before December 31, 2017, and showed at least one outcome measure regarding match running performance, such as total distance covered, peak game speed or indicators of activities performed at established speed thresholds. Results: A total of 5801 records were found. After removal of duplicates and the application of the exclusion and inclusion criteria, a total of 50 articles were included (n = 2615 participants). Their outcome measures were extracted and findings were synthesized. The majority of the reviewed papers covered the European continent (62%) and used global positioning systems (GPS) (64%). Measurement error of the tools used to obtain position data and running metrics was systematically overlooked among the studies. The main aims of studies were to examine differences across playing positions (20%), age groups (26%) and match halves (36%). Consistent findings pointed to the existence of positional role and age effects on match running output (using fixed running speed thresholds), but there was no clear consensus about reductions in activity over the course of match-play. Congested schedules negatively affected players’ running performance. While over 32% of all studies assessed the relationships between match running performance and physical capacity, biochemical markers and body composition, ~70% of these did not account for playing position. Conclusions: This review collated scientific evidence that can aid soccer conditioning professionals in understanding external match loads across youth categories. Coaches working with youth development programs should consider that data derived from a given population may not be relevant for other populations, since game rules, match format and configuration are essentially unstandardized among studies for age-matched players. Despite limited evidence, periodization training emphasizing technical-tactical content can improve match running performance. Occurrence of acute and residual impairments in the running performance of young soccer players is common. Prescription of postmatch recovery strategies, such as cold-water immersion and spa treatment, can potentially help reduce these declines, although additional research is warranted. This review also highlighted areas requiring further investigation, such as the possible influence of environmental and contextual constraints and a more integrative approach combining tactical and technical data.
Article
Full-text available
Purpose: To examine the reliability of heart rate (HR) measures obtained during a 6-min Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1), and following a 3-min passive recovery, within a group of highly trained youth soccer players Methods: Eight players completed three separate 6-min Yo-Yo IR1 tests, with a passive recovery, over a 2-week period. Measures of absolute heart rate (bpm) and relative HR (%HRmax) were obtained at the 3rd and 6th min of the test, with measures relative to the end HR (%HRend) 10, 20, 30, 60, 90, and 180 s, during the 3-min passive recovery. Variability in HR measures were assessed across successive trials (trial 1 vs. 2 and trial 2 vs. 3) and across all three trials, using the intraclass correlation coefficient (ICC), coefficient of variation (CV) and typical error (TE). Results: HR measures obtained during the 6-min Yo-Yo IR1 test displayed good levels of reliability (ICC: 0.95–0.98, CV: 1.1–1.3% and TE: 0.96–2.44). Results, display a potential learning effect, with lower levels of variability between trial 2 and trial 3. Examination of %HRend obtained during the passive 3-min recovery demonstrated an increased variance, as the passive-recovery period progressed. Conclusion: The 6-min Yo-Yo IR1 test presents a novel and potentially practical approach to regularly assessing youth soccer players’ physical response to intermittent exercise. Practitioners and researchers should, however, consider the need for appropriate familiarisation when undertaking this test.
Article
Full-text available
Background. The purpose of this study was to analyze the relationship between performance test parameters and match-related physical performance in professional soccer players. Methods. To determine physical capacity, 28 male soccer players underwent several performance tests at the start of the seasons 2013/2014, 2014/2015, and 2015/2016. The following parameters were assessed: maximum running velocity (vmax), fixed (v4mmol/l) and individual anaerobic threshold (vIAS) during an incremental treadmill test; 30-m sprint time in a linear sprint test (LS30m); in a repeated-sprint test, the 30-m sprint time (RST30m) and performance decrement (RSTdecr); and countermovement jump height (CMJ). Match physical performance was quantified during the first ten official matches of each season using a computerized, camera-based tracking system. The following measures of match physical performance were considered: top running speed (TS), mean running speed (vØ), total distance covered (TD), number of sprints (SP), number of high-intensity running (HIR), and aerial duels won (AD+). Pearson correlation coefficients were used for statistical analysis. Results. Moderate to very large correlations were found between the majority of performance test parameters and match performance variables, with a variability of correlations across the three seasons. Large relationships across all three seasons were only observed between vmax and TD, vmax and vØ, LS30m and TS as well as RST30m and TS. Conclusion. This study demonstrates the relationship between several performance test parameters and match-related physical performance in professional soccer players, thereby supporting the test parameters’ criterion validity. vmax, LS30m, and RST30m seem to be the most consistent parameters. +++ Link to full-text view-only version +++ https://rdcu.be/Mi0X
Article
Full-text available
Purpose: The aim of the present study was to examine the reliability and usefulness of a proposed 4-min individualised submaximal shuttle run test (SSRIndiv) in elite rugby league players. Materials and methods: Twenty-two elite rugby league players competing in the National Rugby League competition (23.2 ± 3.4 years, 186.8 ± 5.4 cm, 100.2 ± 8.5 kg) performed the SSRIndiv twice, seven days apart (test–retest design). The SSRIndiv was prescribed as 75% of the average speed during a 1500-m time trial. Exercise heart rate was calculated as the average heart rate (HR) over the final 30 s (HRex). Seated HR recovery (HRR) was recorded at 1- (HRR60) and 2-min (HRR120) post-exercise. Data were analysed with magnitude-based inferences. Results: Test–retest typical errors were moderate for HRex (1.2 percentage points; 90% confidence limits: 1.0–1.7), HRR60 (3.4; 2.7–4.6) and HRR120 (2.9; 2.3–3.9). Intraclass correlation coefficients were extremely high for HRex (0.91; 0.78–0.94) and very high for both HRR60 (0.80; 0.61–0.90) and HRR120 (0.84; 0.69–0.92). Thresholds for an individual change that would be likely small and greater than the typical error were ±1.8 (percentage points), ±4.6 and ±4.1 for HRex, HRR60 and HRR120, respectively. Conclusions: The SSRIndiv demonstrates acceptable reliability in the assessment of HRex and HRR, thus demonstrating its potential usefulness for monitoring fitness and fatigue in elite rugby league players.
Purpose: To compare between-tests changes in submaximal exercise heart rate (HRex, 3 min, 12 km/h) and the speed associated with 4 mmol/L of blood lactate (V4mmol) in soccer players to get insight into their level of agreement and respective sensitivity to changes in players' fitness. Methods: A total of 19 elite professional players (23 [3] y) performed 2 to 3 graded incremental treadmill tests (3-min stages interspersed with 1 min of passive recovery, starting speed 8 km/h, increment 2 km/h until exhaustion or 18 km/h if exhaustion was not reached before) over 1.5 seasons. The correlation between the changes in HRex and V4mmol was examined. Individual changes in the 2 variables were compared (>2 × typical error considered "clear"). Results: The changes in HRex and V4mmol were largely correlated (r = .82; 90% confidence interval, .65-.91). In more than 90% of the cases, when a clear individual change in HRex was observed, it was associated with a similar clear change in V4mmol (the same direction, improvement, or impairment of fitness) and conversely. Conclusions: When it comes to testing players submaximally, the present results suggest that practitioners can use HRex or V4mmol interchangeably with confidence. However, in comparison with a field-based standardized warm-up run (3-4 min, all players together), the value of a multistage incremental test with repeated blood lactate samplings is questionable for a monitoring purpose given its time, labor, cost, and poorer player buy-in.
Article
Purpose To examine differences in weekly load between the first (FT) and the under 19 team (U19) within a professional football setting. Methods: Data were collected in 11 FT and 9 U19 players during one season (2016-2017). FT data was divided into two week types, with (FT-M1) or without (FT-M0) a mid-week match. Indicators were total distance (TD) and distances covered at 12-15, 15-20, 20-25 and >25 km‧h⁻¹. All indicators were analysed as weekly external load (m), intensity (m‧min⁻¹) and load monotony (a.u.). Results: TD-based external load was higher for U19 compared to FT-M0 (very likely moderate; mean difference = 4180m; 90% compatibility limits ±1508m) and FT-M1 (likely large; 4684m; ±1320m). However, the difference in the higher velocity zones was substantially less (trivial to possibly small), with TD >25 km‧h⁻¹ being lower than FT-M0 (very likely moderate; -118.3m; ±56.4m) and FT-M1 (likely small; -78.7m; ±61.6m). All external intensity indicators were lower for U19 (likely small to almost certainly large). External load monotony was higher compared to FT-M1 (possibly small to almost certainly very large). Compared to FT-M0, monotony was higher for TD (possibly very large; 0.25 a.u.; ±0.08 a.u.) and TD >25 km‧h⁻¹ (possibly moderate; 0.19 a.u.; ±0.16 a.u.) but lower for TD 12-15 (possibly small; -0.06 a.u.; ±0.07 a.u.) and 15-20 km‧h⁻¹ (likely moderate; -0.11 a.u.; ±0.06 a.u.). Conclusions: Despite higher weekly external loads at low velocity for elite youth players, external intensity and within-week load variation increase substantially when these players may transition to professional football.
Article
Purpose: To determine the validity and reliability of a submaximal intermittent running (SIR) test in elite Australian rules football (ARF) players. Methods: Validity: heart rate (HR) responses of 38 elite ARF players to both the SIR and yoyo intermittent recovery 2 (YYIR2) tests were compared over two trials. Linear regression analysis was used to examine the relationship between SIR test HR responses and YYIR2 test performance. Reliability: HR responses of 25 elite ARF players to the SIR test were monitored over three trials. Day-to-day reliability was determined using intra-class correlation coefficient (ICC), typical error of measurement (TE), coefficient of variation (CV) and smallest worthwhile change (SWC). Results: Validity: large inverse correlations were reported between two, three, and four minute HR during the SIR test and YYIR2 test distance (r = -.58 - -.61, P < 0.01). Heart rate recovery (HRR) after two and three minutes of the SIR test was moderately correlated to YYIR2 distance (r = .32 - .35, P < 0.05). Reliability: strong correlations for ICC (r = .90 - .97) and low CV (1.3 - 9.2%) were reported for all HR variables. Conclusions: and practical applications: Monitoring HR during the SIR test is a valid and reliable indicator of YYIR2 test performance in elite ARF players. These findings support the use of the SIR test as a regular and non-fatiguing indicator of intermittent running capacity. Copyright (C) 2016 by the National Strength & Conditioning Association.