Quantifying the Physiological Positional Demands of Elite Netball

during a 5-day International Tournament

A dissertation submitted in partial fulfilment of the requirements for the award

BSc (Hons) Sport and Exercise Science

James McCabe

B00580498

Research Project SLS506 (64860)

University of Ulster, Jordanstown

Supervisor: Dr. Conor McClean

Submission Date: 06/05/2014

Word Count: 3,581

Journal of Sports Science

Acknowledgements

The author would like to thank and extend my appreciation to Dr. Conor McClean for

his help and guidance throughout this research.

The author would also like to thank the Sports Institute of Northern Ireland,

specifically Damian Martin for the continuous support as he provided both the

opportunity and facilities to undertake this study whilst constantly providing a source

of information and guidance throughout.

Abstract

Objective: The purpose of this study is to assess the physiological demands in elite

netball using an accelerometer (Catapult Minimax V4) in an attempt of define the

variability between positions in the elite netball. The completion of this objective

should provide adequate data, which may be utilised by high performance netball

coaches in an attempt to generate both, training programmes and individualised

recovery protocols in an attempt to optimise performance.

Methods: 12 Northern Irish netballers, mean (±SD) age, height and mass of 25.58 ±

3.99 years old, 175.00 ± 5.76 cm and 72.3 ± 10.93 kg respectively, competed in a 5

day international tournament. During which they wore a Catapult MiniMax V4 by

which Accelerometer Load (LoadTM·min-1) was recorded. Daily Creatine Kinase,

hydration and body mass was also collected, whilst additional subjective variables

were recorded as part of a daily diary.

Results: The appropriate application of these methods produced the required results

necessary for the fulfilment of the objective outlined at the beginning of this research.

The major finding of this research is that Load TM.min -1 (au) measured using tri-axial

accelerometers sampling at 100Hz, provided specific and useful results that

highlighted the differences across the various positions in netball. It is evident from

the results that the Centre Court player has the greatest Load TM.min -1 (au) on

average over the five-day tournament (185.58). Furthermore player load was

quantified for each position providing data that will be useful to coaches when aiming

to optimize performance. On average over a 5-day tournament, the player load for a;

Goal Keeper (103.35 Load TM.min -1), Goal Defence (139.38 Load TM.min -1), Wing

Defence (147.25 Load TM.min -1), Wing Attack (133.19 Load TM.min -1), Goal Attack

(122.38 Load TM.min -1) and Goal Shooter (75.50 Load TM.min -1).

The Pearson’s Correlation Co-efficient found no significant relationship when

examining the individual variables with peak creatine kinase levels (Decelerations

and Peak CK – r = 0.17), (Accelerations and Peak CK – r = 0.22) and (Total Jumps

and Peak CK – r = 0.2).

Conclusion: The purpose of the study was to assess the physiological demands in

elite netball using an accelerometer (Catapult Minimax V4) in order to provide data

that will be utilized by high-performance coaches. The findings of this research show

the centre court player to induce the greatest player load throughout each game of a

tournament. This research should allow specific training programs and individualised

recovery programmes to be generated.

Furthermore, we found no significant relationship between peak creatine kinase

levels and the assessed variables. It can therefore be concluded that, both the

integration of these variables and the continuous nature of netball tournaments may

induce the high creatine kinase levels.

Keywords; netball, elite, accelerometer, catapult minimax, player load

(Load TM.min -1), physiological demands

Introduction

Netball is predominantly a female team court sport, which is played by approximately

20 million people worldwide according to the International Netball Federation (INF).

Each team consists of seven players, and competition comprises of 4 X 15 minute

quarters conducted on a 15.25 X 30.5 court that is divided into thirds; outlining the

areas in which particular positions are allowed to move. Whilst there are strict rules

and regulations regarding contact, the most prominent distinctive aspect of the game

is that players are not permitted to move whilst in possession (Cormack et al, 2013).

Netball has been described as a dynamic and physically demanding game that

requires various movement patterns (Williams & O’Donoghue, 2005).

Nowadays, the value of success has increased dramatically, providing a need for an

industry of specialists capable of harnessing maximum potential. Each sport has its

own specific physiological demands and characteristics. These demands are

resultant of the rules and structure imposed, as well as the skill and tactical ability of

all players involved. An understanding of these requirements will aid in the

development of athletes with a view to optimising performance.

At present research related specifically to netball is scarce (Cormack et al, 2013).

This may be due to the lack of structure during match play (Allison, 1978). Much of

the research into netball has used time-motion analysis and/or individual

physiological fitness testing protocols. Intervention style research during competition

is minimal for netball; yet vast for other intermittent sports e.g. soccer (Mohr et al,

2003; Rampini et al, 2007b). The relatively small amount of netball physiology

research suggests that the game does have similarities to other intermittent sports.

However there are some well-defined differences specifically in the movement

patterns performed during a netball game. This discrete set of specific movements

makes the use of research using time-motion analysis and/or physiological data from

other sports implausible when investigating netball. The use of an up-to-date, state of

the art accelerometer and/or GPS may improve both reliability and specificity when

quantifying the physiological profile of netball players. The current paucity of research

has provided the rationale for this study.

Numerous researchers have assessed the quantification of physiological load in

netball; Steele and Chad (1991), Otago (1983), have utilised different methods of

analysing netball competition and practice. The methods used during these studies

however have incurred scrutiny as Hughes (2008a) claims them to be subjective and

qualitative in nature, as they are characterized by the observational techniques and

coaches evaluations as a measure. However recent enhancements in technology

has allowed for the quantification of physiological load during competition using a

non-invasive method. Petersen, Pyne, Portus and Dawson (2009) indicate that the

minimax V4 performs extremely well during short sprints and changes of direction.

This conclusion emphasizes the possibility of this accelerometer’s use when

quantifying the load in a netball tournament. Furthermore Cormack et al (2013)

claims the minimax v4 to provide an innovative and useful tool for the assessment of

the activity profiles in both lower and higher standards of netball.

It was hypothesised prior to data collection, based on previous literature, that player

load would be greatest in a centre due to the court restrictions in netball (Davison &

Trewartha, 2008). The centre has the greatest distance to cover; therefore this

should correlate with the load placed on that individual. It was also hypothesised that

the total number of decelerations throughout the tournament will have a significant

relationship with peak creatine kinase levels for each player. To put this hypothesis

into context, it is established based on the understanding that damage caused to the

sarcoplasmic reticulum as a result of exercise causes a leakage of CK, thus allowing

CK to be utilized as a marker for the amount of muscle damage. The eccentric nature

of decelerations, which is a variable recorded by the Catapult Minimax V4, therefore

generated an interest into this possible relationship. Also, if proved correct, numerous

sports including netball, can improve their training by increasing the amount of

eccentric contractions done during gym session, therefore training the muscle to deal

with the physiological stress it incurs during performance, minimising the amount of

muscle damage and possibly injury (Lindstedt, LaStayo & Reich, 2001).

The aim of this study was to highlight the variability between positions in netball

providing coaches with adequate data to produce individual training programmes,

and recovery protocols.

Methods

Participants

Twelve netballers with a mean (±SD) age, height and mass of 25.58 ± 3.99 years old,

175.00 ± 5.76 cm and 72.3 ± 10.93 kg respectively, that were selected for the

Northern Irish Netball team were recruited to participate in the study. The squad

participated in a 5-day international tournament in the Antrim Forum Leisure Centre

from the 30th October – 3rd November. Approval from the University Research Ethics

Committee, informed consent and each participant’s health history was gathered

from prior to commencement with the data collection.

Design

Data was collected from each individual involved in the study during the four

matches. During each match, accelerometer load TM min -1 (au) was collected for each

individual player. The position each player was allocated was recorded allowing

comparison during data analysis.

Study Period

Data Collection took place at the Antrim Forum Leisure Centre from the 31st October

until the 3rd October 2013. Prior to the tournament, the athletes completed a YoYo

Intermittent Test to establish baseline fitness parameters e.g. max heart rate. This

fitness testing was carried out on the 23rd October 2013.

Methodology

Participants match activity profile (mean 3 ± 1.4 samples per player) was recorded by

an accelerometer sampling at 100 Hz, contained inside a motion detection unit

(MinimaxX, Team 2.5, Catapult Innovations, Scoresby, Australia). Units were housed

in a custom made harness that prevented unwanted movement and held the units in

place in the middle of the upper back. Therefore limiting any potential hindrance on

performance. Accelerometer data (Load TM.min -1 (au) from individual X-medio-lateral,

Y- anterior/posterior, and Z-vertical vectors) was downloaded post match using

manufacturer specific software (Logan Plus v. 4.46.0) and divided by playing time to

calculate Load TM.min -1 (au). Load TM.min -1

(au) has demonstrated high levels of

validity and reliability in team sport specific movements (CV = 1.9 %).

Further subjective and objective measures were collected throughout the tournament

to compliment the research examining the differences across positions regarding the

physiological demands associated with that specific role. Objectively, each

participants Creatine Kinase (CK) levels were recorded the morning after competition

in an attempt to gauge muscle damage. This was gathered using a Reflotron Plus

system. Another objective measure was hydration; this was gathered using

osmocheck and recorded in the individual’s daily diary. Individuals body mass was

also recorded pre and post match in an attempt to quantify the amount of water lost

during competition.

Subjectively, each participant kept a daily dairy that consisted of a specific template

which would be completed both pre and post match-play (Figure 1). This diary

incorporated numerous factors that were divided, as they had to be completed at

different times. The pre exercise factors included; muscle condition, quality of sleep,

appetite, perceived mental & physical fatigue, mood states and any injuries or illness.

Post exercise consisted of similar questions with the addition of any recovery

protocols used post match e.g. Ice bath, foam roller, contrast showers etc. and the

perceived rate of exertion of the game (Borg’s scale).

Statistical Analysis

Load TM.min -1 (au) values from each individual was analyzed to assess the different

demands placed on each playing position. The data was recorded and processed

using Microsoft Excel (2010). Load TM.min -1 (au) values are presented as mean ±SD

and graphed to highlight the evident differences across positions.

SPSS statistical tests were not utilized as throughout the tournament the players in

each position varied, also substitutions provided a hindrance. A Pearsons Correlation

Co-Efficient was used however to examine the relationship between variables (total

jumps, total accelerations and total decelerations) with the individuals peak CK

levels.

Results

The average player load (Load TM.min -1

(au)) for each position throughout the

tournament is highlighted in Figure 1. The mean ±SD Load TM.min -1 (au) throughout

this competition was 129.52 ± 34.69. It is evident that the Centre position is

associated with the highest demand as the average player load was 185.58, which is

38.33 greater than Wing Defence that has the second greatest player load.

Table 1 shows the average between the positions across the numerous variables

assessed. This therefore allows an association between player load and specific

movements, by identifying the different demands associated with each position. The

Centre position does have the greatest number of decelerations (18.72) and also the

highest overall amount of changes in direction (64.88). Surprisingly the Goal Attack

position incorporated the greatest number of jumps (4.36) and the Goal Defence had

the greatest number of accelerations (15.56) and yet the overall player load for each

position is similar to the average (129.52) with each measuring 139.38 and 122.38

respectively. The Pearson’s Correlation Co-efficient (see figures 3,4 & 5) found no

significant relationship when examining the individual variables with the peak creatine

kinase of the participants (Decelerations and Peak CK – r = 0.17), (Accelerations and

Peak CK – r = 0.22) and (Total Jumps and Peak CK – r = 0.2).

Goal K

eepe

r

Goal D

efenc

e

Wing

Defe

nce

Centre

Wing

Atta

ck

Goal A

ttack

Goal S

hoote

r0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

200.00

Position

Pla

yer L

oad

(Loa

dTM

·min

-1 )

Figure 1; Average player load for each position during the tournament

Table 1; Average for each recorded variable per position

Average Jumps

Average Accel

Average Decel

Average Heart Rate

COD (Left)

COD (Right)

Goal Keeper

3.53 12.71 8 152.35 22.12 21.41

Goal Defence

3.33 15.56 16.38 164.56 20.92 21.52

Wing Defence

1.81 14 16.1 176.56 23.23 25.4

Centre 1.94 10.11 18.72 173.16 30.66 34.22

Wing Attack

2.58 10.44 16.63 171.3 27.94 24.58

Goal Attack

4.36 12.16 13.47 178.91 32.02 26.08

Goal Shooter

2.97 6.91 11.02 167.07 16.27 24

Figure 3; Relationship between peak Creatine Kinase Levels and the total number of

decelerations

Figure 4; Relationship between peak Creatine Kinase Levels and the total number of

accelerations.

Figure 5; Relationship between peak Creatine Kinase Levels and the total number of

jumps.

20 40 60 80 100 120 1400

100

200

300

400

500

600

700

800

900

R² = 0.169017842297917

Total Number of Decelerations

Pea

k C

reat

ine

Kin

ase

Leve

ls(IU

/L)

0 10 20 30 40 50 60 70 80 900

100

200

300

400

500

600

700

800

900

R² = 0.219586052116548

Total Number of Accelerations

Pea

k C

reat

ine

Kin

ase

Leve

l (IU

/L)

Participant Peak CK Levels (IU/L)

1 328

2 774

3 117

4 320

5 383

6 489

7 201

8 316

9 N/a

10 293

11 428

12 325

Table 2; Peak Creatine Kinase Levels throughout the competition for each participant

DiscussionWhile games analysis studies of netball have been regularly undertaken over the

past 30 years (Davidson & Trewartha, 2008; Loughran & O’Donoghue, 1999; Otago,

0 10 20 30 40 50 60 70 80 90 1000

100

200

300

400

500

600

700

800

900

R² = 0.200622114445092

Total Number of Jumps

Pea

k C

reat

ine

Kin

ase

Leve

ls (I

U/L

)

1983; Steele (1990), Steele & Chad (1991) only two studies have examined these at

the elite level in this time period (Otago, 1983; Fox et al, 2013). Therefore, the aim of

this study was to examine the current activity of elite level netball during competition

in order to provide coaches with up to date quantitative knowledge of the associated

demands of specific positions as a basis for the design of sport specific training

programmes and adequate recovery protocols.

The major finding of this research is that Load TM.min -1 (au) measured using tri-axial

accelerometers sampling at 100Hz demonstrated consistent, practically meaningful

differences across the different positions in netball. It is evident from the results that

the Centre Court player has the greatest player load on average over the five-day

tournament (Figure 1). The quantification of Load TM.min -1

(au) during netball

competition may be affected by numerous factors, such as; court restrictions, game

difficulty, tactics employed and the individual’s style of play/attitude. Each of these

influencing factors will be discussed in an attempt to provide a justification of the

results.

Court Restrictions

Due to the relatively small court and the rules of the games that restrict player

movement during netball, it could be said that each of the seven positions has its

own set of physiological demands (Woolford & Angove, 1991). The Centre court

players, who have less rule-imposed limitations on their court movement in

comparison with the other positions, corresponds with the high player load inflicted

on them as seen in Figure 1. In conjunction with the aforementioned, those positions

with the greatest court restrictions (GK & GS) player load had the least on average

over the four matches. (Wright, Slattery and Howell; Cormack et al, 2013).

Previous work has suggested that distance covered and Load TM.min -1 (au) had a

very strong relationship in research examining Australian Football Players (Aughey,

2011). This may provide reasoning as to how the Centre Court player’s Load TM.min -1

(au) was greater than that of the six other positions. This is perhaps evident in the

results seen in Table 1 as both, accelerations and jumps were higher in other

positions, yet the player load still remained highest in the Centre Court position.

Results from research by Davidson and Trewartha (2008) found that Centre players

in Britain cover 8km during a 60minunte match, which is significantly further than

both the GK and GS for example who both travelled on average 4.2km. However,

this study’s data collection procedures may not provide a true objective quantification

of the total distance covered. Therefore, to truly gauge the validity of this relationship,

a study using an indoor GPS system may provide a more reliable result for this

speculation.

Game Difficultly and Tactics Utilized

A study by Cormak et al (2013) examined the differences in Load TM.min -1 (au) across

two different playing standards finding that during higher standard games in

comparison with that of a lower standard, Load TM.min -1 (au) is considerably higher.

The possibility of this factor influencing this data set is minimal, as the data is

collected over four games in a competitive setting. Also the teams participating in the

competition included, Barbados, St Lucia and Botswana that are ranked 9th, 15th and

19th respectively in the world rankings, with the Northern Irish squad ranked at 11 th

worldwide, this should highlight the competitiveness of the assessed tournament.

The difficulty of the game, and/or standard of the opponent may however, affect

results of this nature, as how the coach tactically approaches the game may alter

according to these variables. It is essential therefore to assess the demands of

netball across numerous games and various playing styles.

Player Attitudes and Style of Play

It is evident across numerous sports, that each individual player has their own

particular playing style; this is also the case in netball at all levels. This therefore may

prevent this data set being useful to other countries in the development of specific

training programmes for performance enhancement, as the high play load associated

with the Northern Irish Centre Court may not correspond with that of other

international teams.

If this possible mechanism is true, the protocol utilized during this research and the

rich data set reaped from this work, should provide a basic blueprint for other

countries. The specificity of the results gathered using the Catapult Minimax V4

highlights both its practicality due to its lack of interference with the players and

effectiveness in assessing player activity (See Table 1).

Measured Variables vs. Peak Creatine Kinase

It was hypothesized prior to data collection that the total number of decelerations

throughout the tournament will have a significant relationship with peak Creatine

Kinase levels for each player. As aforementioned, a Pearsons Correlation Co-

efficient test was carried out to assess this relationship and found no relationship

between these two variables.

This hypothesis was based on the understanding that damage caused to the

sarcoplasmic reticulum as a result of exercise causes a leakage of CK, thus allowing

CK to be utilized as a marker for the amount of muscle damage induced (Tiidus,

Tupling & Houston, 2012). A study by Newham, Jones and Edwards (2004) found

that eccentric contractions are responsible for the large efflux of the enzyme creatine

kinase. Due to the eccentric nature of decelerations it was hypothesised that there

would be a significant relationship between CK and the number of decelerations.

Upon completion of this analysis, with the test producing no significant relationship (r

= 0.17), the other variables gathered by the accelerometer were tested in an attempt

to try and gain an understanding into whether any individual movement caused the

high CK levels (See Table 2). However, of the variables assessed; total jumps (r =

0.20) and accelerations (r = 0.22) neither proved to have a significant relationship

with peak CK levels.

It can therefore be assumed that a combination of these variables; total jumps, total

number of accelerations and total number of decelerations may all play their own

particular role in the damage caused to the working muscles during a netball match.

These variables, as well as distance covered and the consecutive nature of this

tournament will all constitute towards the high CK levels recorded in the results.

Conclusion and Future Directions

In conclusion we can accept our first hypothesis, which is in agreement with previous

literature in this area that the Centre Court play does in fact incur the greatest

amount of load during both a one-off match and therefore throughout the tournament.

This conclusion provides coaches of teams with a greater understanding into the

physiological stresses the human body is placed under during an international

tournament. This understanding will allow coaches to plan their training to suit the

individual requirements of each player with a view to optimizing the teams overall

performance.

Due to the nature of netball competition at an international level, an understanding of

this nature is of huge benefit to the coaches and the other backroom staff associated

with the squad. An understanding of the demands placed on these athletes will allow

the production of individualised recovery programmes to ensure that injury risk is

minimised and a high level of performance is maintained throughout the tournament.

However we must reject our secondary hypothesis that there was a significant

relationship between the total number of decelerations completed during the

tournament and the peak creatine kinase level.

This research should be of value to the entire netball community, as the information

collected from the Catapult Minimax V4 has provided a respected analysis for the

Northern Irish netball squad. The usefulness of this data may cause a need for

coaches of other squads to utilize this protocol in an attempt to optimise their team’s

performance.

With regards to future directions for this research, the above-mentioned variables

may have affected the results gathered. Not least, the tactics employed by the

particular coach and the individual players attitude/style of play. Therefore, to gain a

greater insight into the sport of netball meanwhile furthering this research, it is

essential that this protocol is utilized on other international squads.

This data provides an understanding into how netball is played in Northern Ireland at

elite level and therefore it would be thoughtless to assume that netball worldwide will

provide the same results. Future research may also compare this data set with other

factors such as fitness levels, strength and power qualities of the athletes.

Limitations

Prior to the commencement of this investigation it was recognised that the possibility

of injury is high due to the participant’s high volume of training and participation in

sport in general. During data collection, it is essential to note that an injury to the

upper body area (ribs) occurred to one of the participants preventing them from

wearing the Catapult (Accelerometer). However, data was collected from this

participant during a few of the quarters in which she participated allowing player load

to be recorded for that position.

Another limitation of this study is the lack of statistical analysis, as the ever-changing

team scenario e.g. substitutions and changes in position provided a interference

when trying to use SPSS. This interference arose as our subject number would have

varied for each position or the assessment would have examined the physiological

demand placed on the individual regardless of position, which would not have

coincided with the aims of the research.

Acknowledgements

The author would like to thank and extend my appreciation to Dr. Conor McClean for

his help and guidance throughout this research.

The author would also like to thank the Sports Institute of Northern Ireland,

specifically Damian Martin for the continuous support as he provided both the

opportunity and facilities to undertake this study whilst constantly providing a source

of information and guidance throughout.

References

Aughey, R. (2011) Increased high intensity activity in elite Australian football finals

matches. International Journal of Sports Physiology and Performance 6, 367-379

Allison, B. (1978). A practical application of specificity in netball training. Sports

Coaching. 2 (2), 9-13.

Cormack, S.J., Smith, R.L., Mooney, M.M., Young, W.B., O'Brien, B.J. (2013).

Accelerometer Load as a Measure of Activity Profile in Different Standards of Netball

Match Play. International Journal of Sports Physiology and Performance. 1 (1).

Davidson, A., Trewartha, G. (2008). Understanding the Physiological Demands of

Netball: A Time- Motion Investigation. International Journal of Sports Physiology and

Performance. 8 (1), 1-17.

Fox, A., Spittle, M., Otago, L, and Saunders, N. (2013). Activity profiles of the

Australian female netball team players during international competition: implications

for training practice. Journal of Sport Science. 31 (14), 1588-95.

Hughes, M. (2008a). Examples of notation systems. In M. Hughes and I.M. Franks

(Eds.), The Essentials of Performance Analysis An Introduction (pp. 111-149).

London: Routledge.

International Netball Federation. (2014). Netball for Life. Available:

http://www.netball.org/sustainable-global-development/netball-for-life. Last accessed

17th March 2014.

Lindstedt, S.L., LaStayo, P.C., Reich, T.E. (2001). When Active Muscles Lengthen:

Properties and Consequences of Eccentric Contractions. American Physiological

Society. 16 (1), 256-61.

Loughran, B.J. and O’Donoghue, P.G. (1999). Time-motion analysis of work- rate in

club netball. Journal of Human Movement Studies, 36, 37-50.

Mohr, M., Krustrup, P., and Bangsbo, J. (2003). Match performance of high-standard

soccer players with special reference to development of fatigue. Journal of Sports

Sciences, 21, 519-528.

Newham, J., Jones, D.A., Edwards, R.H.T. (1986). Plasma creatine kinase changes

after eccentric and concentric contractions. Muscle & Nerve. 9 (1), 59-63.

Otago, L. (1983). A game analysis of the activity patterns of netball players. Sports

Coach, 7 (1), 24-28.

Petersen, C., Pyne, D., Portus, M. and Dawson, B. (2009) Validity and reliability of

GPS units to monitor cricket-specific movement patterns. International Journal of

Sports Physiology and Per- formance 4, 381-393.

Rampini, E., Coutts, A.J., Castagna, C., Sassi, R., and Impellizzeri, F.M. (2007b).

Variation in top level soccer match performance. International Journal of Sports

Medicine, 28, 1018-1024.

Steele, J.R. (1990). Biomechanical factors affecting performance in netball:

Implications for improving performance and injury reduction. Journal of Sports

Medicine . 10 (1), 88-102.

Steele, J.R., and Chad, K.E. (1991). Relationship between movement patterns

performed in match play and in training by skilled netball players. Journal of Human

Movement Studies, 20, 249-278.

Tiidus, P.M. (2012). Energy Systems and Bioenergetics. In: Tupling, A.R. and

Houston, M.E. Biochemistry Primer for Exercise Science. 4th ed. Champaign, IL:

Human Kinetics. 234-321.

Williams, R. and O’Donoghue, P. (2005). Lower limb injury risk in netball: a time-

motion analysis investigation. Journal of Human Movement Studies, 49, 315-331.

Woolford, S, and Angrove, M. (1991). A comparison of training techniques and game

intensities for national level netball player. Sports Coaching. 14 (1), 18-21.

Wright, R., Slattery, K. and Howell, J. Using Session-RPE to Monitor Training Load in

Netballers. Available: http://old.netball.asn.au/_uploads/res/1_248473.pdf. Last

accessed 29th April.

Appendix 1

Competition Diary

Netball Tornament, Antrim Forum Oct - Nov 13

Date 30 31 1 2 3

1 - 10 Borg Rating of Percieved Exertion

Day Wed Thu Fr

iSat

Sun

Morning Pre-exercise

Muscle condition Fan

(F) OK (OK) Poor (P)

1 Rest

Mood state 2

Quality of sleep

3

Appetite 4 Sort of Hard

Fatigue (physical)

0 = None 5 = Extremely

5 Hard

Fatigue (mental)

6

Illness Yes / No Explain

7 Really Hard

Injury 8

Body Mass (kg) 9 Really, Really hard

Hydration(mOsm/L)

10

Max - Hardest ever game

Evening / Post-exerciseRecovery

Muscle condition

Fan / OK / PoorMood state A Pool

Fatigue (physical)

0 = None 5 = Extremely

B Ice Bath

Fatigue (mental)

C Contrast Shower

Illness Yes / No Explain

D Massage

Injury E Foam Roller

Game RPE 1-10 FCompression Garments

Body Mass (kg) GGym (Cycle, Cross Trainer)

Recovery A - H H Other

Notes

Appendix 1; Daily Dairy template that was completed by each individual player

throughout the tournament.

Appendix Two

Appendix Two; An Individual’s Daily Diary processed using Microsoft Excel.