20of the Session RPE Method for Quantifying Training in Australian Football,A Comparison of the CR10 and CR100 Scales

Journal of Strength and Conditioning Research Publish Ahead of PrintDOI: 10.1519/JSC.0b013e3182541d2e

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Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.

Manuscript title: Validity and reliability of the session RPE method for quantifying training

in Australian Football: A comparison of the CR10 and CR100 scales

Running head: Monitoring training loads in Australian Football

Authors: Tannath J. Scotta, Cameron Blackc, John Quinnc and Aaron J. Couttsab

Laboratory:

aHuman Performance Laboratory, University of Technology, Sydney, AUSTRALIA

bCentre for Health Technologies, University of Technology, Sydney, AUSTRALIA

cGreater Wester Sydney Giants, Blacktown, AUSTRALIA

Corresponding author: Associate Professor Aaron Coutts

Email: [email protected]

Phone: +61 2 95145188

Financial support: No external financial support was received for this study

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ABSTACT

The purpose of this study was to examine and compare the criterion validity and test-retest

reliability of the CR10 and CR100 rating of perceived exertion (RPE) scales for team sport

athletes that undertake high intensity, intermittent exercise. Twenty one male Australian

football (AF) players (age: 19.0 ± 1.8 years, body mass: 83.92 ± 7.88 kg) participated the first

part (Part A) of this study which examined the construct validity of the session-RPE (sRPE)

method for quantifying training load in AF. Ten male athletes (age: 16.1 ± 0.5 years)

participated in the second part of the study (Part B), which compared the test-retest reliability

of the CR10 and CR100 RPE scales. In Part A, the validity of the sRPE method was assessed

by examining the relationships between sRPE, and objective measures of internal (i.e. heart

rate) and external training load (i.e. distance travelled), collected from AF training sessions.

Part B of the study assessed the reliability of sRPE through examining the test-retest

reliability of sRPE during three different intensities of controlled intermittent running (10

km⋅hr-1, 11.5 km⋅hr-1 and 13 km⋅hr-1). Results from Part A demonstrated strong correlations

for CR10- and CR100-derived sRPE with measures of internal training load (Banisters

TRIMP and Edwards TRIMP) (CR10: r = 0.83 and 0.83, and CR100: r = 0.80 and 0.81,

p<0.05). Correlations between sRPE and external training load (Distance, higher speed

running and player load) for both the CR10 (r = 0.81, 0.71 and 0.83) and CR100 (r = 0.78,

0.69 and 0.80) were significant (p<0.05). Results from Part B demonstrated poor reliability

for both the CR10 (31.9% CV) and CR100 (38.6% CV) RPE scales following short bouts of

intermittent running. Collectively, these results suggest both CR10 and CR100 derived sRPE

methods have good construct validity for assessing training load in AF. The poor levels of

reliability revealed under field testing indicate that the sRPE method may not be sensible to

detecting small changes in exercise intensity during brief intermittent running bouts. Despite

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this limitation, the sRPE remains a valid method to quantify training loads in high intensity,

intermittent team sport.

Key Words: session-RPE; Australian Football; training quantification; monitoring training

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INTRODUCTION

Due to the highly stochastic nature of the training activities in team sports it is difficult to

accurately quantify the training loads experienced by athletes. Moreover, many team sports

such as Australian Rules Football (AF), Rugby Union and Rugby League require collisions

and eccentric muscle actions which contribute to the overall load endured by these athletes.

In the field setting, there are presently a number of methods that are used quantify the

training loads undertaken by these athletes (5). These methods can be described as a measure

of either the external training load (a measure of training load independent of individual

internal characteristics, e.g. distance covered, training duration), or a measure of internal

training load (the physiological stress imposed on the athletes by the external load) (14).

Theory suggests that internal training loads may be most appropriate for monitoring training

(i.e. the load endured by athletes), whilst the external load is generally considered to be

important for the prescription and planning of training. Indeed, in a review of aerobic

training within soccer players (13), it was suggest that although the individual’s physiological

response to a training stimulus (internal load) may be a more acute marker of training load, it

is the combination of both the external load (quality, quantity and organization of the training

stimulus) and the individuals characteristics that make up the complete training process (14).

Therefore it might be that these two constructs of training provide different information to

coaches that can be used to influence decisions about the training process (i.e. external

training loads confirm if planned training outcomes are achieved; while internal training load

measures can be used to determine how players are responding / coping with training).

Currently, the relationships between internal and external training loads have not been

appropriately examined. It is important to understand these relationships so that coaches and

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sport scientists can make informed decisions about choosing appropriate methods for

quantifying training.

At present, the common methods for quantifying training load in team sports are heart rate

and micro-technology, including global positioning system (GPS) and accelerometers (5).

The GPS devices are often used to provide feedback on distance travelled, running speeds

and repeated-sprint efforts of players while accelerometers provide further information on the

impacts endured by the athletes, giving feedback on the overall body load these impacts

generate. It has recently been demonstrated that accelerometers have acceptable level of

technical reliability both within- and between-devices for measuring physical activity in AF,

providing increased practical application within team sports (6). Unfortunately however, all

these methods have a strong reliance on technology and technical expertise. As such, these

methods can be quite expensive and difficult to implement with large groups of athletes.

Moreover, the risk of data loss is high with these technologies (1, 7, 13). For example,

Wallace et al (22) reported that ~36% of HR measures taken during swimming sessions were

lost when monitoring training intensity over a season. Therefore, alternative methods that are

low cost and easy to implement with large groups may be more effective and appropriate for

team sports.

The session-RPE (sRPE) method has been proposed as an alternative, practical and non-

invasive method for evaluating internal training load in athletes (11). Based on

psychophysical principles, this simple method calculates internal training load by multiplying

the individuals rating of perceived exertion (RPE) (using Borg’s category ratio 10 point

(CR10) scale) by the duration of the session (in minutes). The sRPE method has been

previously shown to be valid across numerous exercise intensities and activities, comparing

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favourably with more complicated methods of quantifying training load. Indeed, previous

studies have shown strong relationships between sRPE and other measurements of internal

training load amongst team sport (1, 13), endurance (10) and resistance trained athletes (8).

Recently, Borg proposed a new category ratio scale that attempts to delimit the sensitivity

limitations detected in the CR10 scale (3). The CR100 scale is a refined version of the Borg

CR10 scale and contains a 1−100 range, giving the individual a greater numerical range to

express their perceived exertion. Although it has been shown previously that the CR100 is a

valid and reliable method in the perception of effort (3), these results were found using a five

stage bicycle ergometer protocol conducted in laboratory testing, and therefore may not apply

to prolonged, high intensity exercise such as team sports. Moreover, it has yet to be

determined if the CR100 provides a more sensitive measure of training load than the CR10

scale. Furthermore, although previous research has suggested the sRPE method to be valid

across numerous exercise modes (1, 8, 10), no study has examined the reliability levels of the

recent CR100 or previous CR10 RPE scales.

At present no study has examined the validity of the sRPE method in AF, particularly using

the CR100 as a measure of intensity. Moreover, the relationships between internal and

external load with the CR10 and CR100 measures of intensity are not known. Therefore, the

first purpose of this study was to examine the validity of the sRPE method within AF using

both the CR10 and CR100 scales as markers of intensity. Additionally, this study will

investigate the relationships between various measurements of both intensity and training

load. It is hypothesized that both the CR10 and CR100 scale derived sRPE methods would be

valid measures of TL within AF. Furthermore, it is hypothesized that strong relationships

between sRPE and measures of internal and external TL will be shown.

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Currently, to the author’s best knowledge, no study has examined the reliability of either the

CR10 or CR100 RPE scales. Therefore, the second purpose of this study was to examine and

compare the criterion validity and test-retest reliability of the CR10 and CR100 RPE scales. It

was hypothesized that the CR100 would be a more reliable scale due to the increased

sensitivity previously shown (3).

METHODS

It is common practice for professional AF clubs to monitor training loads using sRPE.

However, the common CR10 RPE scale has been criticised for its lack of sensitivity to small

changes in effort and its validity in AF has not yet been assessed. Therefore, this study was

conducted in two parts: 1) to assess the construct validity (Part A); and, 2) to assess the

reliability of the CR10 and CR100 RPE scales when used to quantify training load using

Fosters’ sRPE approach.

PART A

Experimental Approach to the Problem

Part A of this study was conducted to assess the validity of the sRPE method within AF using

both the CR10 and CR100 RPE scales. This study compared the CR10 and CR100 as

methods for quantifying exercise intensity and training load during prolonged high-intensity

intermittent exercise. Additionally, the relationships between CR10 and CR100 sRPE

methods with internal and external training loads were determined. Individual RPE, heart

rate and GPS measurements were recorded during skill-based training sessions over a 13

week period. Training loads were calculated daily using the session-RPE method (10).

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Subjects

Twenty one male Australian football players (age: 19.0 ± 1.8 years, body mass: 83.92 ± 7.88

kg, height: 187.5 ± 6.3 cm, sum of 7 skinfolds: 48.8 ± 6.1 mm) representing the Greater

Western Sydney Football Club volunteered to participate in this study. The club competed in

the Northern Eastern Australian Football League (NEAFL). All players were given a verbal

and written description of the procedures, possible risks and potential benefits prior to

participation and written consent was obtained from each subject. In the week preceding the

study period, each player was familiarized with the exact protocols employed in the study.

Players were familiarised with both CR10 and CR100 RPE scales and were clearly explained

the use and protocol of these scales (4). Test procedures were approved by the University

Human Research Ethics Committee.

Procedures

Criterion Measures of Internal Load

Session-RPE

The training load for each session was calculated using the sRPE method (10) for each player

during the study period. This method involved multiplying the training duration in minutes by

the mean training intensity. The training intensity was measured using the CR10 (4) and

CR100 (3) RPE scales. Players were asked ‘How intense was your session?’, and were

requested to make certain that their RPE referred to the intensity of the whole session rather

than the most recent exercise intensity. Players were randomly assigned which RPE scale

they were first to answer (i.e. CR10 or CR100) and then responded to the alternative scale 5

minutes later.

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Heart Rate

Heart rate was recorded over the course of each training session at one second intervals using

Polar® Team2 System (Polar® Electro Oy, Finland) HR monitors. Heart rate was downloaded

from transmitters using Polar® Team2 software (Polar® Electro Oy, Finland) and was

analysed at the completion of each training session.

Two HR-based methods for quantifying internal training load were used as criterion measures

of training load. The TRIMP method proposed by Banister et al. (2) was used as the first

criterion measure of internal training load and was determined using the following formula:

Training load = D(∆HR ratio)eb(∆HR ratio)

where: D = duration of training session, and b = 1.67 for females and 1.92 for males (19).

The HR-based method proposed by Edwards (9) was also used as a criterion measure of

internal training load in the present study. This method involves integrating the total volume

with the total intensity of each physical training session relative to five intensity phases. A

score for an exercise bout was calculated by multiplying the accumulated duration (minutes)

of time spent in these HR phases (50-60%, 60-70%, 70-80%, 80-90 and 90-100%) by the

weighing factor allocated to each zone (1= 50-60%, 2= 60-70%, 3= 70-80%, 4= 80-90 and 5=

90-100%) and then summating the results.

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Criterion Measures of External Load

Global Positioning Systems

During each training session 10 players wore a non-differential, commercially available GPS

receiver with a sampling rate of 10 Hz (MinimaxX, Team 2.5, Catapult Innovations,

Scoresby, Australia). The GPS unit was placed in a backpack harness and positioned between

the subject’s shoulder blades in accordance with manufacture’s specifications. For the

purpose of validity and reliability, GPS participants were fitted with the same GPS unit each

session (15). Distance, m/min and individual player load (the vector magnitude formulated

from accumulated data of all three axis measured by the MinimaxX accelerometer) were

recorded by GPS devices and downloaded following the completion of each training session

using Logan Plus 4.7.0 software (Catapult Innovations, Scoresby, Australia) before being

exported for analysis. All training was completed on a grassed AF field, clear of large

building to allow clear satellite reception. The mean (±SD) number of satellites during data

collection was 12.5 ± 0.6.

Statistical Analyses

Within individual correlations between CR10, CR100 and measures of internal (HR) and

external (GPS-based measures) training load and intensity were analysed using the Pearson’s

product moment correlation. Ratio measures for 95% limits of agreement were calculated.

SPSS statistical software package version 19 (SPSS Inc., Chicago, USA) was used for all

statistical calculations. The level of statistical significance was set at p<0.05. All data are

mean ± standard deviation (SD) unless otherwise stated.

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PART B

Experimental Approach to the Problem

To date, no studies have examined the reliability of either the CR10 or CR100 RPE scales.

Reliability is important to coaches and sports scientists as it indicates the reproducibility of a

measurement. Indeed, in this case, poor reliability reduces your ability to track changes in

measurements of an individual’s training load. Therefore, the purpose of Part B of the present

investigation was to examine and compare the criterion validity and test-retest reliability of

the CR10 and CR100 RPE scales. To achieve this, RPE measures were taken following 8

minutes of controlled intermittent running of three different intensities. The players

completed each running speed twice so that the test-retest reliability could be calculated. This

study was conducted using a randomised group design in order to ensure speeds were kept

anonymous from participants.

Procedures

The study was completed over a 3 week period; during which each athlete was required to

complete the testing protocol twice a week. Testing was conducted at the same time on the

two same weekdays over the three weeks in order to determine the test-retest reliability.

Athletes were familiarised with both CR10 and CR100 RPE scales and were clearly

explained the use and protocol of these scales (4), as well as protocols used throughout the

study. Individual training programs and periodisation strategies were kept identical during the

study period. In the 24 h prior to testing each athlete avoided any moderate to heavy training

and to standardise their food and fluid intake to increase the reliability of perception of effort

responses.

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Subjects

Ten young male team sport athletes (age: 16.1 ± 0.5 years, body mass: 83.1 ± 8.4 kg, height:

183.2 ± 7.6 cm) volunteered to participate in part B of the study. All athletes were given a

verbal and written description of the procedures, possible risks and potential benefits prior to

participation. Written consent was obtained by each athlete and their guardian and ethical

approval was granted by the University Human Research Ethics Committee for all

experimental procedures.

Standardized Intermittent Running Test

This present study used three different speeds of the Yo-YoIR1 (Yo-Yosubmax) speed

protocols in order to control the external training load of each athlete and assess the

sensitivity of the CR10 and CR100 RPE scales. These Yo-Yosubmax protocols were undertaken

for 8 minutes at speeds of 10 km⋅hr-1 (Level 1), 11.5 km⋅hr-1(Level 2) and 13 km⋅hr-1(Level

3). Athletes were asked to run intermittently back and forth a 20 m marked course to

standardised audio signals following similar methods previously described for the Yo-YoIR1

(16). All trials were completed outdoors on a grass playing field. The three testing protocols

were allocated to both groups in a randomized order while the speed profiles of each test

were kept anonymous from athletes.

Physiological Measures

Heart rate and RPE-based measures were recorded with the equipment and protocol methods

similar to Part A.

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Statistical Analyses

Typical error as a coefficient of variation (CV) and interclass correlation coefficients (ICC)

were calculated to establish the reliability of the CR10 and CR100 scales as well as Edwards

TRIMP and %HRpeak. Ratio measures for 95% limits of agreement were calculated. SPSS

statistical software package version 19 (SPSS Inc., Chicago, USA) was used for all statistical

calculations. The level of statistical significance was set at p<0.05. All data are mean ±

standard deviation (SD) unless otherwise stated.

RESULTS

Part A

A total of 38 training sessions with a mean duration of 63 ± 23 minutes were observed during

a 13 week period. Twenty-one subjects completed an average of 23 ± 4 sessions. Session-

RPE and HR-based measures were collected from all players for each session completed. Due

to limitations with the number of GPS devices available, data from 10 subjects over 18 ± 3

training sessions was recorded. Training load measures were recorded for sessions completed

by all players (n=21) (CR100-training load: 3740 ± 2470 AU, CR10-training load: 382 ± 246

AU, Edwards’ TRIMP: 157 ± 79, Banister’s TRIMP: 129 ± 67).

The within-individual correlation (r) of CR100-training load and CR10-training load, two

HR-based training load methods and various measurements of external training load are

shown in Figure 1. All correlations were statistically significant (P <0.05) There were also

significant correlations between the sRPE and all external training load measures (Distance,

High speed running and player load).

INSERT FIGURE 1 ABOUT HERE

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The within-individual correlations of CR100 and CR10, %HRpeak and various external

measures of intensity are outlined in Figure 2. Moderate correlations were observed between

both RPE scales and %HRpeak (P<0.05). Poor to moderate correlations were observed

between RPE and external measures of intensity (P<0.05).

INSERT FIGURE 2 ABOUT HERE

Part B

The %CV and %ICC from both trials, each of the RPE scales showed a poor level of

reliability over all speed categories (CR10 [31.9% CV, 0.66 ICC] and CR100 [38.6% CV,

0.70 ICC]). A poor level of reliability was shown for both scales at the slowest speed protocol

(CR10-Level 1 [34.8% CV, 0.55 ICC] and CR100-Level 1[(52.4% CV, 0.55 ICC]). These

reliability levels were improved for faster Yo-Yosubmax protocols ([CR10-Level 3 (21.2% CV,

0.66 ICC] and CR100-Level 3 [25.5% CV, 0.79 ICC]).

DISCUSSION

The first purpose of this study was to examine the validity of the CR10 and CR100 sRPE

methods in quantifying training load in AF. Additionally, this study compared the efficacy of

the CR10 and CR100 as methods for assessing exercise intensity and training load in

intermittent running. The main findings of this study support previous research (1, 13),

indicating that the CR10 and CR100 sRPE method is valid for monitoring training load in

team sports. However both the CR10 and CR100 sRPE measures show poor levels of

reliability for assessing internal training load.

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The present results are the first to show that sRPE is a valid method for assessing training

load in AF. These findings are in agreement with previous studies in team sports such as

soccer (1, 13) and basketball (10) that have shown strong relationships between HR-based

and RPE-based methods for quantifying training load. For example, Impellizzeri et al (13)

assessed 19 young soccer players and reported correlation coefficients between Banister’s

TRIMP (range: 0.50−0.77) and Edwards’ TRIMP (range: 0.54−0.78) and sRPE training load.

A possible explanation for the higher correlation coefficients in the present study compared

to this previous study could be due to the nature of the AF training sessions monitored in this

study. For example, whilst the training drills used in this study typically required the players

to complete high-intensity, intermittent running, the time periods between the drills was kept

to a minimum so that there was relatively little rest time. It has previously been reported that

there is a poorer relationship between HR and RPE during interval type training sessions that

required long periods of rest between exercise efforts in both soccer training (1) and

resistance training (8, 21). Specifically, Alexiou and Coutts (1) showed higher correlation

coefficients between sRPE training load and Banisters TRIMP and Edwards’ TRIMP during

conditioning sessions compared to matches. It was suggested, that these sessions require a

greater proportion of time active with minimal rest periods. It is likely that both the

differences in the nature of the sport-specific requirements and differences in the ratio of

work to rest, between the present and previous studies also explain the differences in the

measured correlations. Collectively the present results show that sRPE relates well to HR-

based measures of training load in AF, especially in skills-based training with a relatively low

proportion of time spent resting. However, further work is still required to determine the most

appropriate method for determining ‘session duration’ when using the sRPE method for

quantifying training load.

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A new finding of the present study was the strong correlation between measures of external

training load (distance, higher speed running and player load) and sRPE. These observations

confirm the training theory (14) that suggests internal load is a product of an individual’s

external load, and provides further evidence for the construct validity of sRPE as a tool for

assessing training load. Additionally, these findings provide evidence for accelerometer-

derived player load as a valid method for assessing training load in team sports, particularly

in AF. Notably however, these results are in contrast with previous research (12) which

reported no relationship between sRPE and accelerometer-derived player load during soccer

small–sided games in professional players. Whilst it is difficult to accurately compare these

studies due to the different nature of the sports and the different RPE scales (6-20 vs. CR10

and CR100 scales) used in the experimental protocols, it is possible that the lack of

differences in the previous study may be attributed to the use of pooled correlations, rather

than within individual correlations used in the current study. Further differences may be due

to both the different accelerometer devices used to assess player load and the software

algorithms for calculation. These findings suggest further research is required to examine the

validity of player load data in team sports that require high-intensity intermittent exercise,

frequent collisions and sports specific skills.

In this study, we observed stronger relationships between HR-based methods and sRPE when

compared to external load measures (i.e. distance, player load) and sRPE for both exercise

intensity and training load. This observation is not surprising as HR is a measure of internal

training load (similar to sRPE), while other measures report the external load which examines

a different construct of training load. Taken collectively, these results suggest that the

external load is only one, albeit important, contributor to the overall internal load experienced

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by the individual. Other factors such as training status, fatigue state, previous training and

genetics may also influence an athlete’s response to training (14). These results also highlight

that different information provided by external and internal training load measures.

Accordingly, we suggest that external training load measures be used by coaches and sport

scientists to prescribe training stimulus and evaluate whether the load being undertaken by

players is intended, whilst internal training load be used to monitor how players are

responding to with the applied training load. It is also possible that the relationship between

internal and external training load may be a valuable marker of how athletes are coping with

training, especially during standard training sessions.

A further aim of this study was to compare the CR10 and CR100 as methods for assessing

exercise intensity and training load during AF training. To the author’s best knowledge, no

study has assessed the validity of the CR100 in team sport activities nor compared the

information provided by each of these scales. The CR100 scale is a refined version of the

Borg CR10 scale and has been suggested to overcome the sensitivity limitations detected in

the CR10 scale increasing the validity and reliability of this method (3). However, in contrast

to these suggestions, we observed similar levels of validity for all measures of intensity and

training load. Interestingly, whilst there were no significant differences between the scales,

the CR10 had a slightly larger correlation coefficient with every measure of intensity and

training load. Overall however, these methods provide similar information on the athlete’s

perceptions of training intensity and training load during AF training, and the CR100 does

not improve the reported limitations of the CR10 scale when applied in the manner used in

this study.

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In summary, our findings provide further evidence to show sRPE is a valuable tool for

assessing training load and training intensity and is the first to demonstrate these relationships

in AF. Moreover, the strong relationships between sRPE and external training load measures

(distance, higher speed running and player load) suggest that an athlete’s internal load is

related to the external load applied during training (13). It also seems that the CR10 and

CR100 scales provide similar information regarding exercise intensity. Finally, since other

methods of monitoring training intensity and load can be expensive, require technical

expertise, may result in data loss and be time consuming, we suggest that sRPE provides a

practical and valid alternative for monitoring training in AF.

In Part B of this study the reliability of both the CR10 and CR100 scales for quantifying

training intensity in intermittent activity were examined. The results showed relatively poor

levels of reliability for each of the RPE methods (CR10 [31.9% CV] and CR100 [38.6%

CV]) for quantifying internal training intensity. These results are similar to those previously

reported (20) and indicate that the use of RPE may be limited by its reliability in brief bouts

of intermittent activity, which is common in team sports. However, it is important to

acknowledge that the determining the coefficient of variation may be a poor method for

determining the reliability of ordinal scales such as the CR10 and CR100 scales. Still, to our

knowledge, there is no method available to appropriately measure the reliability of these

scales or allow comparisons with ratio scales (e.g. HR, RPE 6-20 scales). Furthermore,

previous authors have also suggested an increased difficulty in determining the reliability of

the CR10 scale due to the multifactorial nature of the scale, which is mediated by both

physiological and psychological factors (4, 18). Nonetheless, we suggest sRPE data should be

interpreted in the context of its %CV and that future studies should assess the %CV in a more

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ecologically valid environment, using longer exercise bouts that the 8 minute efforts used in

the current study and also a wider range of exercise intensities

Interestingly, both perception of effort scales showed an increased reliability with higher

exercise intensity. Therefore, it would appear that perception of effort becomes more reliable

as a marker of exercise intensity as it increases. These observations are supported by the

findings of Lamberts et al. (17), who showed that HR has improved lower levels of reliability

during increase speeds of interval shuttle running. Collectively, this present study showed

that the CR10 and CR100 both had similarly poor levels of reliability. This may be related to

the short exercise bout (8 min) efforts used in the present study. Indeed, it is suggested that

future studies examine the reliability of sRPE over a wider range of intensities and for longer

exercise durations. It is therefore important that these levels of reliability should be taken into

account when interpreting data using the CR100 and CR100 as a sRPE measure; whilst care

should be taken when applying these observations to sRPE measures taken during longer

training sessions.

PRACTICAL APPLICATIONS

There are a variety of methods available to coaches for determining the individual stress

placed on an athlete from an exercise bout. The current results show that sRPE is a valid

indicator of global internal training load in AF. Indeed, these findings indicate that both the

CR10 and CR100 sRPE are valid methods of quantifying training load in team sports.

However, it is important that coaches take care when assessing and comparing training loads

between athletes and different training load methodologies. We suggest that these measures

(internal and external) be used to provide a greater depiction of the overall load undertaken

by the athlete and not be used interchangeably to compare exercise intensity or training load.

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Findings from this study revealed poor reliability levels for both the CR10 and CR100 RPE

scales. These levels of reliability should be taken into account by coaches and sport scientists

when interpreting data using the CR100 and CR100 as a sRPE measure during short bouts of

intermittent exercise. However, due to the strong validity of this measure across numerous

exercise intensities coupled with the simplistic and non-invasive nature of this method, it is

still suggested that the sRPE remains a valid method to quantify training loads in high

intensity, intermittent team sport.

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REFERENCES

1. Alexiou, H., and A.J. Coutts. The validity of the session-RPE method for monitoring training load in elite female soccer players. Int. J. Sports Physiol. Perf. 3:320–330, 2008. 2. Banister, E.W. Modeling elite athletic performance. In: Physiological Testing of Elite Athletes. H.J. Green, J.D. McDougal and H.A. Wenger (Eds.) Champaign, Illinois: Human Kinetics, 1991, pp. 403-424. 3. Borg, E. On Percieved Exertion and its Measurement. Stockholm University, Dapartment of Pschology, Stockholm, 2007. 4. Borg, G., P. Hassmén, and M. Lagerstrom. Perceived exertion related to heart rate and blood lactate during arm and leg exercise. Eur J Appl Physiol Occup Physiol. 56:679-685, 1987. 5. Borresen, J., and M.I. Lambert. The quantification of training load, the training response and the effect on performance. Sports Med. 39:779-795, 2009. 6. Boyd, L.J., K. Ball, and R.J. Aughey. The reliability of MinimaxX accelerometers for measuring physical activity in Australian football. Int. J. Sports Physiol. Perf. 6:311-321, 2011. 7. Coutts, A., A.C. Sirotic, C. Catterick, and H. Knowles. Monitoring Training Loads in Professional Rugby League. In: Science and football VI: the proceedings of the Sixth World Congress on Science and FootballNew York: Routledge, 2008, pp. 272-277. 8. Day, M., M.R. McGuigan, G. Brice, and C. Foster. Monitoring exercise intensity during resistance training using the session-RPE scale. J. Strength Cond. Res. 18:353-358, 2004. 9. Edwards, S. High performance training and racing. In: The Heart Rate Monitor Book. S. Edwards (Ed.) Sacramento, CA: Feet Fleet Press, 1993, pp. 113-123. 10. Foster, C., J.A. Florhaug, J. Franklin, L. Gottschall, L.A. Hrovatin, S. Parker, P. Doleshal, and C. Dodge. A new approach to monitoring exercise training. J. Strength Cond. Res. 15:109-115, 2001. 11. Foster, C., L.L. Hector, R. Welsh, M. Schrager, M.A. Green, and A.C. Snyder. Effects of specific versus cross-training on running performance. Eur. J. Appl. Physiol. 70:367-372, 1995. 12. Gomez-Piriz, P.T., P. Jimenez-Reyes, and C. Ruiz-Ruiz. Relation between total body load and session rating of perceived exertion in professional soccer players. J. Strength Cond. Res. 25:2100-2103, 2011. 13. Impellizzeri, F.M., E. Rampinini, A.J. Coutts, A. Sassi, and S.M. Marcora. Use of RPE-based training load in soccer. Med. Sci. Sports Exerc. 36:1042-1047, 2004. 14. Impellizzeri, F.M., E. Rampinini, and S.M. Marcora. Physiological assessment of aerobic training in soccer J. Sports Sci. 23:583-592, 2005. 15. Jennings, D., S. Cormack, A.J. Coutts, L. Boyd, and R.J. Aughey. The validity and reliability of GPS units in team sport specific running patterns. Int. J. Sports Physiol. Perf. 5:328-341, 2010. 16. Krustrup, P., M. Mohr, T. Amstrup, T. Rysgaard, J. Johansen, A. Steensberg, P.K. Pedersen, and J. Bangsbo. The Yo-Yo Intermittent Recovery Test: Physiological response, reliability, and validity. Med. Sci. Sports Exerc. 35:697-705, 2003. 17. Lamberts, R.P., K.A. Lemmink, J.J. Durandt, and M.I. Lambert. Variation in heart rate during submaximal exercise: implications for monitoring training. J Strength Cond Res. 18:641-645, 2004. 18. Morgan, W.P. Psychological components of effort sense. Med. Sci. Sports Exerc. 26:1071-1077, 1994.

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19. Morton, R.H., J.R. Fitz-Clarke, and E.W. Banister. Modeling human performance in running. J. Appl. Physiol. 69:1171-1177, 1990. 20. Rampinini, E., F.M. Impellizzeri, C. Castagna, G. Abt, K. Chamari, A. Sassi, and S.M. Marcora. Factors influencing physiological responses to small-sided soccer games. J. Sports Sci. 25:659-666, 2007. 21. Sweet, T.W., C. Foster, M.R. McGuigan, and G. Brice. Quantitation of resistance training using the session rating of perceived exertion method. J. Strength Cond. Res. 18:796-802, 2004. 22. Wallace, L.K., K.M. Slattery, and A.J. Coutts. The ecological validity and application of the session-RPE method for quantifying training loads in swimming. J. Strength Cond. Res. 24:33-38, 2009.

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Figure Legends

Figure 1: The mean (± 95% CI) within individual correlations between CR100-training load

and CR10-training load and various measurements of training load (mean ±95%

CI) (HSR- High speed running, PL- Player Load) (n =21).

Figure 2: The mean (± 95% CI) within individual correlations between CR100 and CR10

with various markers of intensity (n= 21).

ACCEPTED


Figure 1: The mean (± 95% CI) within individual correlations between CR100-training load

and CR10-training load and various measurements of training load (mean ±95%

CI) (HSR- High speed running, PL- Player Load).

ACCEPTED


Figure 2: The mean (± 95% CI) within individual correlations between CR100 and CR10

with various markers of intensity.

Documents

20of the Session RPE Method for Quantifying Training in Australian Football,A Comparison of the CR10 and CR100 Scales