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Applications of the Session Rating of Perceived Exertion System in Professional Rugby Union


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Applications of the
Session Rating of
Perceived Exertion
System in Professional
Rugby Union
Tom Comyns, PhD
and Eamonn P. Flanagan, PhD, CSCS
Irish Institute of Sport, National Sports Campus, Co. Dublin, Ireland; and
Irish Rugby Football Union, Dublin, Ireland
Rugby union is an intermittent
high-intensity sport in which
activities that rely on maximal
strength, speed, and power are inter-
spersed with periods of lower intensity
aerobic activity and rest (13). It is a col-
lision-based field sport requiring high
levels of endurance, strength, power,
agility, and speed as well as proficiency
with rugby-related skills (1). These
components comprise the training
modalities used in professional rugby
union and the monitoring of such a vast
range of modalities is central to
Training for success is a balance between
achieving peak performance and avoid-
ing the negative consequences of exces-
sive training. Training volumes and
intensities that are not optimal do not
have the desired physiological adapta-
tions, whereas those that are excessive
increase injury risk and impair sporting
performance. An appropriate periodiza-
tion of the training stimulus applied to
a player is important to obtain optimal
sporting performance.
Numerous techniques and methods
are available to strength and condi-
tioning coaches to quantify the train-
ing stimuli to which rugby players are
exposed. These include heart rate
monitoring and time motion analysis
via global positioning satellite (GPS)
units (5). Although these equipment
and methods have proven to be accu-
rate and to provide detailed informa-
tion on the training stimuli, from our
experience, there are disadvantages
associated with their utilization (5).
These devices can be expensive espe-
cially with an extended training squad,
and the data analysis can be extensive.
Multiple data sets are also produced,
which can be difficult to interpret and
use by coaches.
An alternative method for quantifying
the training stimuli is the session rating
of perceived exertion (session RPE)
method developed by Foster et al.
(10). Session RPE is a simple, reliable,
noninvasive, and valid method based
on the Borg’s category ratio 10 (CR-
10) scale (2). The athlete rates the
intensity of the session using the CR-
10, and this value is multiplied by the
session duration to get a training load
(TL) score for the session. These session
load values are used to calculate 2 other
important variables—training monotony
and training strain. Research has shown
that the session RPE method is a reliable
and simple tool to assess TL in steady-
state aerobic training (9,10), intermit-
tent-aerobic training (9), and strength
training (6). The validity of the method
has been specifically investigated in
training sessions for collision-based field
training load; training monotony;
training strain; periodization;
tapering; training load management;
rugby union
VOLUME 35 | NUMBER 6 | DECEMBER 2013 Copyrig ht ÓNational Strength and Conditioning Association
sports (3). Recently, Clarke et al. (3) dem-
onstrated strong correlations between
session RPE and heart rate training
impulse and stated that the method is
inexpensive, practical, and accurately
measures individual’s response to field
training sessions. Anecdotally, it is
known that the session RPE is a widely
used method of quantifying training
intensity and volume in professional
rugby union.
The session RPE method monitors
training by examining simple markers
of both training volume and training
intensity. Foster et al. (8,9,11) devel-
oped the session RPE method based
on a RPE for a session and the duration
of the session. By using these 2 varia-
bles, both the volume (duration) and
the intensity (RPE) are factored into
this method of monitoring. To calcu-
late the measure of session intensity,
the player is asked to rate the intensity
of the session 30 minutes after comple-
tion of the session (9). This is under-
taken by asking them ‘How was your
workout?’ and having them rate it
against a modified rating of Borg’s
CR-10 (9) that can be seen in Table 1.
The delay in asking the player/athlete
to rate the intensity of the session is
done to ensure that the rating reflects
the global intensity of the session (9). If
the rating was taken immediately post-
session, a particularly difficult or easy
section at the end of the session could
dominate the player/athlete’s rating
(9). The RPE should reflect a single
global rating of the intensity for the
entire training session according to
Foster et al. (9). This RPE is then used
in conjunction with the entire duration
of the session to calculate the session
TL. TL is calculated by multiplying the
session RPE by the duration of the ses-
sion (Figure 1).
For example, if a rugby training session
lasted 85 minutes in length and the
player gave a RPE of 5 (hard) for the
session intensity, then the following is
the calculation of the TL for that session:
TL 585 35
By recording the session duration
and session RPE for each session dur-
ing a typical training week and calcu-
lating each individual session TL, 2
important monitoring variables can
be derived—training monotony and
training strain. To accurately calculate
these variables, each session load
should be calculated and rest days cal-
culated with a TL value of 0.
Training monotony is a measure of
day-to-day training variability during
a training week (7). McGuigan and
Foster (12) referred to monotony as
the variability of training for the train-
ing period. It is calculated by dividing
the mean session TL by the standard
deviation of the TL over a 1-week
period. If the TL is equally high on
each day of the week, the training
monotony value will be high. Alterna-
tively, if high and low load training
days are interspersed throughout the
training week, a moderate or low train-
ing monotony score will be derived.
Both the overall weekly TL score,
which is the product of all the individ-
ual session TL values throughout the
week, and the training monotony
score are used to calculate training
strain (7). Training strain is a value that
represents the overall stress that the
athlete was exposed to throughout
the training week. It is derived by mul-
tiplying the weekly TL (including the
game load) by the training monotony
score. A higher TL week together with
a high monotony score yields excessive
training strain values.
An electronic spreadsheet can be cre-
ated to calculate each individual ses-
sion TL, weekly TLs, and weekly
training monotony and strain. Table 2
illustrates an example of such a spread-
sheet. To use such a system, each play-
er’s session RPE and session duration
in minutes for each session must be
entered. For rest days on which no
training is undertaken, a TL value of
0 must be entered.
The primary use of the session RPE
method is to provide coaches with an
overview of workload for athletes (or
squads of athletes) across varying
training modalities over time. Coutts
et al. (4) described the periodization
of professional rugby league training
across a full training year using the ses-
sion RPE system variables of TL, train-
ing monotony, and training strain.
Higher TLs were completed in prepa-
ratory macrocycles of training and TLs
for strength training and conditioning
were reduced during phases with high
competition demands. Coutts et al. (4)
showed that a periodized approach can
be used in team sports and the authors
support the use of the session RPE sys-
tem as a practical method to guide and
assess periodized training programs.
We have used this method extensively
at 2 professional rugby teams. TL,
monotony, and strain are tracked from
week to week across periodized train-
ing blocks providing coaches with
a visual impression of the periodized
plan as experienced by the athlete
(9). Figure 2 displays a set of session
RPE data for a professional rugby team
across a 24-week period. These data
would represent a “fit to play” squad
that comprises fully fit players partici-
pating in all modalities of training.
Injured players or players on adapted
Table 1
The session RPE scale
Rating Descriptor
0 Rest
1 Very, very easy
2 Easy
3 Moderate
4 Somewhat hard
5 Hard
7 Very hard
10 Maximal
Strength and Conditioning Journal | 79
training plans are not included in this
data set. Each player’s weekly TL,
monotony, and strain is calculated
and then pooled into a squad average.
This period represented a preseason
phase leading into the first half of
a competitive season. Weeks 1–6 rep-
resent the early preseason phase.
Weeks 8–12 represent the late presea-
son phase. Weeks 7 and 19 represent
a holiday week for the athletes. The in-
season phase runs from week 13 to 24
and includes 1 competitive game in
each week. Graphically representing
workload in this manner allows the
coach to assess where heavy and light
weeks have occurred and whether or
not the athletes’ perception of training
is consistent with the periodized plan.
Our observations of periodized plan-
ning in professional rugby are that
greatest TLs are accumulated in the
early preseason phase with average
weekly loads of 2400–2600AU. In the
in-season phase, the weekly workload
notably reduces to values of approxi-
mately 1800–1900AU. These in-season
loads include loads accumulated in
competitive games. An example of
a within-week breakdown of the TLs
for the different components of train-
ing, for example, rugby team session, is
provided in Figure 3.
By plotting training monotony and
strain along with TL between weeks,
coaches can identify weeks in which
the TL has not been appropriately
managed and arranged within the
week. Weeks of high monotony (and
resultantly high strain) can be identified
and coaches can strive to organize
training in a more optimal manner to
maintain TLs but reduce training
monotony and training strain. An
example of this can be seen in weeks
2, 3 and 8, 9 where monotony rises
above 1.2 units and training strain in-
creases 30–40% above TL (see Figure 2).
Figures 4 and 5 demonstrate the effect
that within-week TL organization can
have on training monotony and strain.
In weeks A and B, Saturday represents
a game day overwhich coaches have no
control of load management.
Throughout both weeks, players accu-
mulate the same absolute TLs (2125),
but when the organization of training is
Figure 1. Training load is the product of session time and session RPE.
Table 2
An example of a spreadsheet layout for calculating training load, monotony, and strain
Day Session Session RPE Session duration (min) Session TL Daily TL
Monday Weights/strength 4 45 180 300
Speed 4 30 120
Tuesday Rugby training (units) 6 80 480 480
Wednesday Weights/strength 4 35 140 290
Conditioning 6 25 150
Thursday Rugby training (team) 5 65 325 325
Friday Rest day 0 0 0 0
Saturday Rugby game 8 65 520 520
Sunday Rest day 0 0 0 0
Weekly training load 1915
Average daily training load 274
Training monotony 1.32
Training strain 2533
Applications of the Session RPE System
monotonous from day to day it leads to
a suboptimal training plan and unnec-
essarily high training strains. Week A
alternates heavy and moderate days
and has an additional day off within
the week. Week B follows a more
homogenous TL across the week.
Although there is a tapering of TL
throughout the week toward the game
day, the result of this homogeneity is an
elevated training monotony that leads
to approximately 30% increase in train-
ing strain. Foster (7) has recommended
that alternating hard and easy training
days reduces training monotony and
strain and this balanced approach to
load management may help reduce in-
cidences of illness and overtraining (7).
A strong advantage of the session
RPE system is to allow coaches to
assess the impact of programmed
taper or “light” weeks. There is an
established need for periodic reduc-
tions in TL to treat and prevent over-
training (14). The technique of
systematically decreasing TL to facil-
itate physiological fitness is known as
An extensive review of the factors
involved in tapering is available (14).
Based on the scientific literature, when
an appropriate and successful taper is
implemented, athletes can expect
Figure 3. An example of a within-week breakdown of training load for the different components of rugby training.
Figure 2. An example data set of training load, strain, and monotony over the course of a 24-week period of a rugby season.
Strength and Conditioning Journal | 81
improvements in power, strength,
serum testosterone levels, and mood
state and decreases in muscle damage,
sleep disturbance, and cortisol levels
(14). From our experience in profes-
sional rugby union, tapering can be
achieved by reductions in training fre-
quency, duration, intensity, or volume
or a combination of these factors.
It has been recommended that for expe-
rienced athletes in anaerobic sports that
the key variable for manipulation when
tapering is overall training volume (14).
Recommendations have been made for
magnitudes of volume reduction based
on the duration of “normal” training car-
ried out up to the taper week. Volume
reduction in the context of controlled
training, such as strength training, is very
easy to assess and control via the number
of repetitions (reps 3sets) or volume
load (reps 3absolute load). However,
attempting to assess volume reduction
across all the aspects of professional
rugby training such as on-field training,
speed training, and conditioning is more
difficult and less measurable. The session
RPE method offers a unique opportunity
to assess tapering volume reductions
holistically across all aspects of training.
The session RPE systems allows coaches
to compare the overall TL across the
tapering week to previous “normal” train-
ing weeks and assess whether or not the
planned changes in TL have resulted in
a similar reduction to the actual TL. By
assessing the weekly TLs in this context,
it allows coaches to assess if the pro-
grammed reduction has had the desired
effect. In reference to Figure 2, planned
“download” weeks were implemented in
notably lower in these weeks. Our obser-
vations have been that athletes gener-
ally accumulate 70–80% of the TL in
download weeks compared with the
average of the other weeks in that train-
ing block. It has been our experience
that quite drastic reductions in pro-
grammed training volume are required
to have measurable appreciable effects
on TL perception by players. This may
include a significant reduction of num-
ber of exercises, sets and repetitions in
Figure 5. Week B—An example of a poorly organized training week that does not minimize training monotony and training strain.
Figure 4. Week A—An example of a well-organized training week that attempts to minimize training monotony and training strain.
Applications of the Session RPE System
strength training sessions (20–30% vol-
ume reduction), reduced on-field train-
ing time (10–15 minutes less per
session),and a reduction in overall train-
ing frequency through the elimination
of extra short-duration conditioning ses-
sions for some players.
The session RPE method can assist in
managing players with acute injury in
their return to full training. Players
with short-term acute injuries (4–6
weeks) or in the latter stages of long-
term injury are often capable of follow-
ing adapted training plans and are
often only restricted from performing
specific types of training such as full
contact rugby training. Coaches can
use the RPE system to help develop
injured players training to “mirror” full
team training even if some of their ses-
sions have to be adapted in nature. The
RPE system assists the returning player
in training in the same pattern of exer-
cise and recovery as fully fit players so
that when they can return to full train-
ing, they can adapt more readily and
their body is ready to exercise and
recover at the same frequency as the
full training squad.
The RPE system can also be used in
the management of chronic injuries.
Some players in the professional rugby
environment are unable to follow a full
weekly training plan due to chronic
injury management. Such players often
need to be managed in a week-by-week
or day-by-day manner depending on
their specific condition and symptoms.
In conjunction with medical staff,
strength and conditioning coaches can
track what type of loads (magnitude,
training frequency, etc) are associated
with increases in chronic injury symp-
toms. Coaches can develop a personal
profile of what loads and strains are tol-
erable. This can help with individual
planning and scheduling and assist in
making informed decisions as to the ses-
sions in which the player will participate
or whether or not they should have
time restrictions on their involvement
in specific sessions. Figure 6 demon-
strates the TLs of a player with a chronic
injury gradually returning from an adap-
ted training plan to a full training plan.
There are potential errors that need to
be avoided when using the session RPE
system in the professional rugby envi-
ronment. As with any data collection
system, consistency of data collection
must be as closely adhered to as possi-
ble. With the session RPE method,
consistency must be maintained in the
collection of RPE scores from players
and in the timing of sessions. As
previously stated, players should report
RPE scores within 30 minutes of the
cessation of training and should refer
to a consistent scale when giving these
Consistency is highly important when
timing session or game duration also.
Coaches should decide ahead of the
season’s data collection whether they
plan to include warm-up duration in
their overall session time and adhere
to this decision throughout the season.
The game-day warm-up presents a par-
ticularly unique problem in maintain-
ing data collection consistency. The
game-day warm-up is generally much
longer in duration than warm-ups used
in day-to-day rugby sessions. The
game-day warm-up typically lasts
20–30 minutes. It is also drastically dif-
ferent to the game itself and can be much
less in terms of intensity and physical
effort. Including the game-day warm-
up as part of the game duration can over-
estimate the TL of the game because the
respective RPE scores of both modalities
are generally much different. We recom-
mend omitting the warm-up phase from
the TL of the game or scoring it sepa-
rately and following this protocol for the
duration of the season.
We recommend using the actual time
players spend on the pitch rather
than the standardized game time of
40 minutes per half. With in-game
Figure 6. The training loads of a player with chronic injury returning from an adapted training plan to a full training plan.
Strength and Conditioning Journal | 83
stoppages, a half of rugby can often
last over 45 minutes. This actual
game time rather than an artificial
most accurate TL calculations.
Another common error associated with
using the RPE method in the team
sport environment relates to the inclu-
sion of 0 values on nontraining days.
On a nontraining day, a 0 value for
TL should be recorded, and these 0 val-
ues should be included in calculations
of weekly TLs, monotony, and strain.
The associated 0 TL values have a sig-
nificant effect on training monotony
and strain. If these 0 values are not re-
corded and included in the relevant cal-
culations, then training monotony and
strain will appear artificially high.
Coaches should exercise caution in
comparing raw TL, monotony, and
strain values between players. If a par-
ticular player is exhibiting a higher re-
corded TL, for example, than another
player, this does not necessarily mean
that he has accumulated a higher
actual TL. From our experience, some
players are simply “high raters” and
will consistently rate sessions of the
same work output on a higher level
to their teammates. This is likely due
to a differing individual subjective
interpretation of the RPE scale. It is
perfectly valid to compare raw time
scores between players, but in terms
of TLs, we suggest comparing individ-
ual players to the “fit to play” squad
average to assess individual differences
in trends of TL rather than in absolute
values. In Figure 6, an individual
player’s TL is plotted with respect to
the “fit to play” squad average.
Although we do not deem it valid to
compare the absolute values between
the player and the squad average, we
think this type of graphical representa-
tion is a useful method to compare the
individual’s trend of TLs to the squad
trend. This allows us to assess if the
individual has a similar outline of TL
from week to week to the squad average.
Has the player had taper weeks when
the squad has had taper weeks? Has the
overall outline of the player from week
to week matched that of the squad?
As previously stated, one of the com-
mon goals of using the session RPE
system is to establish weekly TLs
(and monotony and strain values) for
the playing squad. Calculating the
squad average data can be wrought
with errors and must be approached
with caution. Within the professional
rugby environment, players can often
be on adapted training schedules due
to acute or chronic injury or due to
involvement in alternative playing
squads. The inclusion of such players
in the weekly average calculations can
artificially reduce the squad data. At the
end of each training week, we recom-
mend the selection of a “fit to play
squad” or a “training squad.” This could
comprise players who have completed
the entire week’s training and playing
schedule. This should give coaches
a truer reflection of the TLs accrued
by the planned training schedule.
The session RPE system is a reliable
and valid measure to provide strength
and conditioning practitioners with
simple and subjective markers of overall
TL. The system can be used to provide
information on within-week and across-
week training loading within the profes-
sional rugby environment. Practitioners,
however, should be keenly aware that it
is a simple and subjective measure and
is best used in tandem with other mon-
itoring systems such as time motion
analysis via GPS of rugby training ses-
sions and volume load monitoring of
strength training sessions. These sys-
tems provide very detailed, objective,
and accurate markers of the external
loads experienced within specific train-
ing systems, whereas heart rate moni-
toring provides detailed and objective
information regarding the internal load
experienced during rugby training. This
is information that is beyond the ses-
sion RPE system. However, the ses-
sion RPE system provides subjective
information of the internal load expe-
rienced by players across all modali-
ties of training and helps bridge the
gap between objective internal and
external training monitors and players’
perception of TL.
Conflicts of Interest and Source of Funding:
The authors report no conflicts of interest
and no source of funding.
Dr. Tom
Comyns is
a strength and
coach for the Irish
Institute of Sport
and a consultant
lecturer in Sport
Science at the
University of
Limerick and Dublin City University.
Dr. Eamonn
Flanagan is
a strength and
coach for the Irish
Rugby Football
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... A distinct advantage of the sRPE is its validity and reliability across a wide variety of exercise modalities, including steady-state aerobic training (Foster et al., 2001), intermittent-aerobic training (Foster et al., 2001) and strength training Comyns and Flanagan, 2013). sRPE is also very commonly used in the practical setting likely due to its relative ease of implementation Akenhead and Nassis, 2016). ...
... This is further supported by the strong link between sRPE TL and injury risk above all other TL measures (Eckard et al., 2018). sRPE allows practitioners to monitor and adapt TL without having to use expensive equipment, such as HR or GPS systems (Comyns and Flanagan, 2013;Impellizzeri et al., 2004). ...
... A low training monotony represents a high variation within the programme, whereas a high training monotony is a result of consistently high or repetitive TL (Comyns and Flanagan, 2013;Piggott et al., 2009). For instance, a week consisting of same TL every day would result in a high training monotony. ...
Introduction: Amateur Rugby Union has an inherent risk of injury that is associated with detrimental effects on player welfare and team performance. The monitoring of players’ preparedness for, and response to, training has become an integral tool for coaches in injury risk management as it may aid in the prescription and design of training. A training monitoring system (TMS) should be both attainable and scientifically grounded, however, there is a paucity of information in relation to monitoring training at the amateur level and the inherent challenges this presents. Aim: The aim of this doctoral research was to explore the associations between subjective measures of training load (TL) and wellness with injury occurrence in match-play and training sessions in amateur rugby in Ireland. Fundamentally, this programme of research aimed to offer practical methods of monitoring training that has the potential to mitigate injury risk and, in turn, benefit the health and wellbeing of players. Methods: Five studies were conducted in this programme of research which: (1) systematically reviewed and critically appraised the existing relevant literature regarding associations between the acute:chronic workload ratio (ACWR), and injury in team sports (Chapter Three), (2) established the current training monitoring practices of practitioners working with in amateur Rugby Union clubs (Chapter Four), (3) developed and evaluated an online TMS (Chapter Five), examined methods of addressing missing TL using missing value imputation (MVI) (Chapter Six), and (5) explored possible associations between subjective self-reported measures of wellness, various training load metrics, and injury in amateur Rugby Union. Results: The findings of the systematic review support the association between the ACWR and non-contact injuries and its use as a valuable tool for monitoring TL as part of a larger scale multifaceted monitoring system that includes other proven methods. 72.7% of practitioners working with amateur Rugby Union clubs monitored training with the most common method being the session rate of perceived exertion (sRPE), used in 83.3% of monitoring systems. The 3 most prominent challenges to motoring training were found to be lack of player compliance, data inconsistency and match-day challenges. Practitioners should strive to keep missing TL data at a minimum, however imputing missing data with the Daily Team Mean (DTMean) was the most accurate MVI method of the twelve MWI methods examined. Lastly, logistic regression found significant, strong associations (odds ratio (OR) = 6.172, 95% CI = 0.254 – 0.473, p < 0.001) between the occurrence of injury and the summative score of overall wellness (0-day lag). Significant weak associations were found between the occurrence of injury and the majority of ACWR calculations when 3-day and 7-day injury lag periods were applied. Conclusion: The findings of this programme of research support the positive association between injury and both subjective wellness and TL. Monitoring training of amateur athletes has its own unique challenges and confounders (e.g., limited time with players, occupation of players, resources available). Practitioners must accept that due to the complexity of injury, a risk will always be present and instead focus on prescribing training that they deem will promote positive adaptations in a safe manner. However, a TMS consisting of subjective measures may mitigate injury risk in amateur Rugby Union by supporting decisions around training prescription.
... The most common method used to monitor TL in the current study was sRPE (91%). This method is administered easily and is an accepted method for monitoring TL. 9 Bourdon et al 6 stated that sRPE has the ability to quantify TL regardless of the training mode or location. Malone et al 28 stated that this method is cost-effective as well as having within-player validity, making this method effective in amateur sport. ...
... Subjective RPE data were collected following the completion of the match using a 0-10 scale, with athletes providing one RPE rating for the whole match [16][17][18]. Additionally, objective variables from ATDs, worn between the shoulder blades in a custom harness for each athlete, which collected athlete playing time and total distance covered in each match (Apex v.2.50, StatSports, Newry, UK), were available for potential inputs into imputation models. ...
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Rate of perceived exertion (RPE) is used to calculate athlete load. Incomplete load data, due to missing athlete-reported RPE, can increase injury risk. The current standard for missing RPE imputation is daily team mean substitution. However, RPE reflects an individual's effort; group mean substitution may be suboptimal. This investigation assessed an ideal method for imputing RPE. A total of 987 datasets were collected from women's rugby sevens competitions. Daily team mean substitution, k-nearest neighbours, random forest, support vector machine, neural network, linear, stepwise, lasso, ridge, and elastic net regression models were assessed at different missing-ness levels. Statistical equivalence of true and imputed scores by model were evaluated. An ANOVA of accuracy by model and missingness was completed. While all models were equivalent to the true RPE, differences by model existed. Daily team mean substitution was the poorest performing model, and random forest, the best. Accuracy was low in all models, affirming RPE as mul-tifaceted and requiring quantification of potentially overlapping factors. While group mean substitution is discouraged, practitioners are recommended to scrutinize any imputation method relating to athlete load.
... Rate of perceived exertion was collected using the OMNI, 0-10, a scale used regularly by subjects in their training and competition environments (39). Rate of perceived exertion data were provided by athletes following the completion of the match, cooldown, and debrief and rehydration or snack, approximately 30 minutes after the completion of the match (10,15). Athletes provided 1 rating for the whole match as the RPE value. ...
... Following these procedures, HR values were used to calculate HR monotony and sample entropy (SampEn). The monotony was calculated by dividing the players' average HR by the standard deviation of the HR over the game (Comyns and Flanagan, 2013;Mateus et al., 2019). SampEn was used to assess each players' HR regularity during the games. ...
This study aims to examine youth players’ physiological responses and technical-tactical performance when playing simulated 3x3 and 5x5 basketball games. Fifteen well-trained male basketball players (16.6 ± 0.2 years old) participated in scrimmage basketball games under two different conditions: 3x3 (half-court) and 5x5 (full-court). The players’ heart rate, muscle oxygen saturation and total hemoglobin data were collected and computed to describe physiological responses, while video analysis was used to characterize their technical-tactical performance. A Bayesian one-way analysis of variance (ANOVA) was used to quantify the predictive influence of both game conditions on the physiological and the technical-tactical variables. The results indicated that different game conditions influenced the players’ physiological responses slightly, as only hemoglobin sample entropy increased between the 3x3 and 5x5 game scenarios. Conversely, statistical differences in most of the technical-tactical variables were moderate and decisive in favour of the game condition model. Overall, this study emphasizes that playing 3x3 and 5x5 basketball games lead to relatively negligible differences in the players’ physiological response but pronounced variations in their technical-tactical performance. Therefore, important implications may be drawn to the applied field as the specificity of technical-tactical adaptations when playing 3x3 or 5x5 formats should be considered by basketball coaches to better design the training sessions for players that fall within our sample age category.
... Throughout the experiment, the internal training load of all participants was monitored using the session Rate of Perceived Exertion (Session-RPE) method as described by Comyns and Flanagan, 48 expressed in arbitrary units. Thirty minutes after training sessions, players were asked to rate the global intensity of the workout session using the French version CR-10 RPE scale. ...
Objective: This study aimed to examine the effects of spirulina supplementation on pro/antioxidant status, inflammation, and skeletal muscle damage markers immediately and 24h after exhaustive exercise in elite rugby players. Methods: Seventeen elite male Rugby Union players were randomly assigned to a Spirulina (SPI: n=9), or a placebo group (PLA: n=8) in a double-blind design. Subjects were supplemented with Spirulina platensis (5.7 g/d) or placebo (isoproteic and caloric) for 7 weeks. At baseline (W0) and after seven weeks of supplementation (W7), blood samples were obtained before (T0), immediately after (T1), and 24h after (T2) exhaustive exercise. The Yoyo Intermittent Recovery Test Level 2 was used as an exhaustive exercise to induce oxidative stress (OS), inflammation, and skeletal muscle damage. The studied parameters included Pro/antioxidant status markers (SOD, GPX, GSH/GSSG ratio, ox-LDL, and F2-Isop), inflammation markers (MPO and CRP), and skeletal muscle damage markers (LDH and CK). Results: Our results showed that F2-Isop, CRP, and CK levels significantly increased at T1 only in PLA group (p<0.05, p<0.05, and p<0.001 respectively) with no change in SPI group which reflects the effect of spirulina to prevent lipid peroxidation, inflammation, and skeletal muscle damage induced by exhaustive exercise. Moreover, spirulina supplementation accelerated the return to baseline values given that F2-Isop, CRP, and CK levels at T2 were significantly lower than at T0 in SPI group (p<0.05, p<0.01, and p<0.001 respectively). Conclusion: Based on the markers used in this study, our results report that spirulina supplementation potentially prevents exercise-induced lipid peroxidation, inflammation, skeletal muscle damage and may accelerate the recovery of some of these markers. Based on our findings, we recommend spirulina supplementation especially for athletes who do not achieve the recommended antioxidant dietary intake and who perform a high training load in order to reduce the magnitude of OS, inflammation, and skeletal muscle damage which could help to reduce performance losses and accelerate recovery after training/competitions throughout the season. This article is protected by copyright. All rights reserved.
... Variables such as monotony and strain were mentioned as being helpful. Training monotony is a measure of day-to-day training variability, while training strain is a value that represents the overall stress that the athlete was exposed to (Comyns & Flanagan, 2013). Finally, training impulse (TRIMP) which is a method of quantifying physical effort using training duration and heart rate during exercise (Halson, 2014) was also referred to. ...
Objective The purpose of this study is to identify the training load (TL) monitoring practices employed in real-world competitive swimming environments. The study explores data collection, analysis and barriers to TL monitoring. Design Cross-sectional. Setting Online survey platform. Participants Thirty-one responders working in competitive swimming programmes. Main outcome measures Methods of data collection, analysis, level of effectiveness and barriers associated with TL monitoring. Results 84% of responders acknowledged using TL monitoring, with 81% of responders using a combination of both internal and external TL, in line with current consensus statements. Swim volume (mileage) (96%) and session rate of perceived exertion (sRPE) (92%) were the most frequently used, with athlete lifestyle/wellness monitoring also featuring prominently. Thematic analysis highlighted that “stakeholder engagement”, “resource constraints” or “functionality and usability of the systems” were shared barriers to TL monitoring amongst responders. Conclusions Findings show there is a research-practice gap. Future approaches to TL monitoring in competitive swimming should focus on selecting methods that allow the same TL monitoring system to be used across the whole programme, (pool-based training, dryland training and competition). Barriers associated with athlete adherence and coach/National Governing Body engagement should be addressed before a TL systems implementation.
... The TM is a measure of day-to-day variations in training load, and it is calculated as the mean daily training load divided by the weekly standard deviation load, while TS is a product of TM and weekly training load [5]. More specifically, rather than performing an equal daily training load throughout the week, interspersing low and high loading days can help maintain lower or moderate monotony and strain [6]. Furthermore, quantifying weekly TM and TS may prevent overtraining syndrome and negative health consequences [7,8]. ...
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Abstract: The purpose of this study was to analyze the intragroup differences in weekly training monotony (TM) and training strain (TS) between starter and non-starter male professional soccer players at accelerometry based variables throughout the periods of a season. TM and TS of different accelerations and decelerations zones for twenty-one players were followed for forty-eight weeks. Regardless of group, players obtained the highest mean TM (starters = 3.3 ± 0.6, non-starters = 2.2 ± 1.1, in arbitrary unit, AU) and TS (starters = 1288.9 ± 265.2, non-starters = 765.4 ± 547.5, AU) scores in the pre-season for accelerations at Zone 1 (<2 m/s2). The results also indicated that both groups exhibited similar TM and TS scores in accelerations at Zones 2 (2 to 4 m/s2) and 3 (>4 m/s2) across the entire season. While the starters showed the highest TM and TS scores at deceleration Zone 1 (<−2 m/s2) in the end-season, the non-starters exhibited the highest scores at the deceleration Zone 1 in pre-season. It seems that in pre-season, coaches applied higher levels of training with greater emphasis on deceleration for non-starters. This tendency was reduced over time for non-starters, while starters presented higher values of deceleration Zone 1. These results highlight the variations in TM and TS across the different periods of a full season according to match starting status among professional soccer players, and the results suggest that non-starter players should receive higher levels of load to compensate for non-participation in matches throughout a soccer season.
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Mastering a speciality language as well as formation of world outlook and professional speech competence of future medical specialists begins at the higher educational establishment. Above all, the process of forming speech competence implies formation of stable students' motivation for improving their skills of professional communication; mastering the terminology of their future speciality. Good command of the professional language contributes to effective mastering special disciplines alongside with increasing performance efficacy and promoting establishment of business linkages. The article focuses on psychological and pedagogical aspects of the Latin language training of medical students, their speech competence being paid particular attention. Underlying Latin language training is a semantic aspect: understanding the meaning of the word and improvement of lexical basis, mastering the system of linguistic concepts in the field of grammar, speech culture, and connected monologue speech. All the speech aspects are developed and correlated in the process of recognizing language and speech phenomena. The prospects of today’s health-care worker can hardly be imagined without properly formed skills of professional speech, providing means of receiving and transferring information for its further use in the professional activity. Psychological features of communicative study organization and its effect on students’ cognitive motivation have been analysed, and a version of interpreting the experience of the Latin language training in view of psychological specifics of forming future medics’ speech competence have been attempted. Actualization of psychological conditions of forming future medical specialist's professional speech competence is achieved due to the stepby-step development of his linguistic capabilities, provided by the reliance on the independent study, capabilities and inclinations taken into account. Besides, these conditions are associated with the understanding of the social nature of professional activity and awareness of the role of Latin language acquisition for meeting professional challenges through communicating with the colleagues and world community.
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Zusammenfassung Aufgrund ihrer Einfachheit und Nutzerfreundlichkeit wird für die Erfassung der subjektiven Beanspruchungswahrnehmung in Training und Wettkampf bevorzugt die Category Ratio Scale (CR10-Skala) oder eine daran angelehnte Ein-Item-Skala eingesetzt. Die CR10-Skala stellt eine nicht-lineare, leicht positiv beschleunigte Funktion bezogen auf die Beanspruchung dar, die in der autorisierten deutschen Fassung mit „Anstrengungsempfinden“ übersetzt wird. Allerdings ist festzuhalten, dass die existierenden Skalen keine vollständigen Stufenbezeichnungen beinhalten und/oder die Stufenbezeichnungen Überschneidungen mit verwandten Konstrukten, z. B. Ermüdung zulassen. Die Anstrengungsskala Sport (ASS) zeichnet sich demgegenüber durch vollständige Stufenbezeichnungen und begriffliche Klarheit mit der komparativen Deklination des Adjektivs anstrengend aus. Auf der Grundlage einer rationalen Konstruktionsstrategie sowie einer systematischen Item-Analyse kann gezeigt werden, dass die Voraussetzungen für die Verwendung der ASS als Verhältnisskala gegeben sind, die eine zuverlässige und inhaltlich eindeutige Messung der Anstrengung gestattet.
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The cross-training (XT) hypothesis suggests that despite the principle of specificity of training, athletes may improve performance in one mode of exercise by training using another mode. To test this hypothesis we studied 30 well-trained individuals (10 men, 20 women) in a randomized longitudinal trail. Subjects were evaluated before and after 8 weeks of enhanced training (+10%/week), accomplished by adding either running (R) or swimming (XT) to baseline running, versus continued baseline running (C). Both R (-26.4s) and XT (-13.2s) improved time trial (3.2 km) performance, whereas C did not (-5.4s). There were no significant changes during treadmill running in maximum oxygen uptake (VO2peak; -0.2, -6.0, and +2.7%), steady state submaximal VO2 at 2.68 m.s-1 (-1.2, -3.3 and +0.2, velocity at VO2peak (+0.05, +0.25 and +0.09 m.s-1) or accumulated O2 deficit (+11.2, -6.1 and +9.4%) in the R, XT or C groups, respectively. There was a significant increase in velocity associated with a blood lactate concentration of 4 mmol.l-1 in R but not in XT or C (+0.32, +0.07 and +0.08 m.s-1). There were significant changes in arm crank VO2peak (+5%) and arm crank VO2 at 4 mmol.l-1 (+6.4%) in XT. There was no significant changes in arm crank VO2peak (+1.3 and -7.7%) or arm crank VO2 at 4 mmol.l-1 (+0.8 and +0.4%) in R or C, respectively. The data suggest that muscularly non-similar XT may contribute to improved running performance but not to the same degree as increased specific training.
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Athletic performance generally is thought to improve with increases in training load. However, few data exist showing the quantitative relationship between training load and performance. We followed 56 athletes (16 runners; 40 cyclists/speed skaters) during 12 weeks of training. We recorded index performances (3.2 km time trial or 5 or 10 km bicycle ergometry) after 6 weeks of baseline training and 6 weeks of a self-selected training increases. Training load was quantitated as the product of intensity (global rating of perceived exertion (RPE)) and the duration (time) of each training session. Load was expressed as the weekly average over the 6 weeks preceding each index performance. We also recorded the duration of high intensity training (RPE>5, hard) (inten). From 6 to 12 weeks, performance improved 12.95 +/- 3.83 to 12.66 +/- 3.00 min (p < .01). Training time (345 +/- 282 to 355 +/- 273 min/wk) and inten (61 +/- 88 to 71 +/- 91 min/wk) did not change significantly, although RPE (3.8 +/- 0.7 to 4.0 +/- 0.8) and load (1242 +/- 957 to 1386 +/- 978) increased significantly. No strong correlations existed between changes in performance and changes in any training measure (TIME, r = -0.031, RPE, r = -0.039, LOAD, r = 0.29, INTEN, r = 0.025.) Data suggest that improved performance in events of 7-20 minutes duration in response to intensified training is primarily dependent upon increases in total load and overall RPE during training and; that a 10-fold increase in training load may be associated with an approximately 10% improvement in performance. These data suggest the possibility of understanding the training responses of athletes on a quantitative basis.
The session-rating of perceived exertion (Session-RPE) method for quantifying internal training load (TL) has proven to be a highly valuable and accurate monitoring tool in numerous team sports. However, the influence of frequent impact during Canadian football on the validity of on this subjective rating tool remains unclear. The aim of this study was to validate Session-RPE application to a prolonged intermittent high intensity collision-based team sport through correlation of internal TL data collected using two criterion heart rate-based measures known as Polar Training-Impulse (TRIMP) and Edwards' TL. Twenty male participants (age = 22.0±1.4 years) from the competitive roster of the University of Saskatchewan Canadian football team were recruited. Session-RPE, Polar TRIMP and Edward's TL data were collected daily over the 2011 Canadian Interuniversity Sport pre- and competitive season (11 weeks; 713 total practice sessions). On average each player contributed 36 sessions of data to the analysis. Statistically significant correlations (p<0.01) between Session-RPE with Polar TRIMP (r range: 0.65-0.91) and with Edwards' TL (r range: 0.69-0.91) were found for all individual players. This study provides confirmation that Session-RPE is an inexpensive and simple tool which is highly practical and accurately measures an individual's response (internal TL) to Canadian football practice. Furthermore, when considering the number of individuals involved world-wide in collision-based team sports, this tool has the potential to impact a large proportion of the global sporting community.
summary: Monitoring the training load during resistance training is problematic. There is no universally accepted method of monitoring resistance training. Session rating of perceived exertion (RPE) can delineate intensities and may be a useful tool for strength coaches and athletes. (C) 2004 National Strength and Conditioning Association
The purpose of this study was to assess the magnitude of upper and lower body strength changes in highly trained professional rugby union players after 2 years of training. An additional purpose was to examine if the changes in strength were influenced by the starting strength level, lean mass index (LMI), or chronological age. This longitudinal investigation tracked maximal strength and body composition over 3 consecutive years in 20 professional rugby union athletes. Maximal strength in the bench press and back squat and body composition was assessed during preseason resistance training sessions each year. The athletes completed a very rigorous training program throughout the duration of this study consisting of numerous resistance, conditioning and skills training sessions every week. The primary findings of this study were as follows: (a) Maximal upper and lower body strength was increased by 6.5-11.5% after 2 years of training (p = 0.000-0.002 for bench press; p = 0.277-0.165 for squat); (b) magnitude of the improvement was negatively associated with initial strength level (r = -0.569 to -0.712, p ≤ 0.05); (c) magnitude of improvement in lower body maximal strength was positively related to the change in LMI (an indicator of hypertrophy; r = 0.692-0.880, p ≤ 0.05); and (d) magnitude of improvement was not associated with the age of professional rugby union athletes (r = -0.068 to -0.345). It appears particularly important for training programs to be designed for continued muscle hypertrophy in highly trained athletes. Even in professional rugby union athletes, this must be achieved in the face of high volumes of aerobic and skills training if strength is to be increased.
The current case study attempted to document the contemporary demands of elite rugby union. Players (n = 2) were tracked continuously during a competitive team selection game using Global Positioning System (GPS) software. Data revealed that players covered on average 6,953 m during play (83 minutes). Of this distance, 37% (2,800 m) was spent standing and walking, 27% (1,900 m) jogging, 10% (700 m) cruising, 14% (990 m) striding, 5% (320 m) high-intensity running, and 6% (420 m) sprinting. Greater running distances were observed for both players (6.7% back; 10% forward) in the second half of the game. Positional data revealed that the back performed a greater number of sprints (>20 km x h(-1)) than the forward (34 vs. 19) during the game. Conversely, the forward entered the lower speed zone (6-12 km x h(-1)) on a greater number of occasions than the back (315 vs. 229) but spent less time standing and walking (66.5 vs. 77.8%). Players were found to perform 87 moderate-intensity runs (>14 km x h(-1)) covering an average distance of 19.7 m (SD = 14.6). Average distances of 15.3 m (back) and 17.3 m (forward) were recorded for each sprint burst (>20 km x h(-1)), respectively. Players exercised at approximately 80 to 85% VO2max during the course of the game with a mean heart rate of 172 b x min(-1) ( approximately 88% HRmax). This corresponded to an estimated energy expenditure of 6.9 and 8.2 MJ, back and forward, respectively. The current study provides insight into the intense and physical nature of elite rugby using "on the field" assessment of physical exertion. Future use of this technology may help practitioners in design and implementation of individual position-specific training programs with appropriate management of player exercise load.
There is a great demand for perceptual effort ratings in order to better understand man at work. Such ratings are important complements to behavioral and physiological measurements of physical performance and work capacity. This is true for both theoretical analysis and application in medicine, human factors, and sports. Perceptual estimates, obtained by psychophysical ratio-scaling methods, are valid when describing general perceptual variation, but category methods are more useful in several applied situations when differences between individuals are described. A presentation is made of ratio-scaling methods, category methods, especially the Borg Scale for ratings of perceived exertion, and a new method that combines the category method with ratio properties. Some of the advantages and disadvantages of the different methods are discussed in both theoretical-psychophysical and psychophysiological frames of reference.