Research project

Unit 5 Research Project
Worthing College Sports Science
Brooke Marshall
2015

Assessment Criteria
Pages 3-17 & 27-38
• P2: carry out sport science or exercise science-
based research
• P3: collect and record data from the research
project conducted
• M2: correctly analyse collected data, describing
techniques used
• D1: correctly analyse data, explaining techniques
used
• P4: produce a full research report using a
standard scientific structure

P2: Carry out / P4: Produce
To investigate whether there
is a relationship between
optimum levels of vigour and
16-25 year old female
footballers passing success
rate at participation level.

Abstract
The aim of this investigation was to assess the effect of level of vigour
on passing success rate of female footballers aged 16-25. This will
show whether a technical skill can be influenced by psychological
thought processes. A sample of 10 participation level female
footballers completed a Profile of Moods State (POMS) Questionnaire
in 10 minutes just before their game after being read a set of
standardized instructions. An observation was then carried out in
order to create a tally chart which includes the number of total passes
and number of unsuccessful passes in order to work out each athletes
overall passing success rate. Results, as hypothesized, showed that the
higher the level of vigour the higher the athletes passing success rate.
There was a significant relationship between passing success rate and
level of vigour with these participants as the scatter-graph showed a
strong positive correlation between these two factors. These results
indicate that level of vigour and therefore an athlete’s mood state can
influence their ability to effectively perform a technical skill required in
their game. Therefore the implications for further research are that
women's football is a priority area for research and level of vigour
should be tested on further technical skills.

Contents: GeneralPage 3 – Aim
Page 4 – Abstract
Page 5 – Contents - general
Page 6 – Contents - appendices
Page 7 – Contents – figures and tables
Page 8 – Acknowledgements
Page 9 – Introduction
Page 10 – Literature review and references
Page 11 – Hypothesis
Page 12 – Method
Page 13 – Data collection
Page 14 – Data analysis
Page 15 – Results
Page 16 – Discussion
Page 17 – Conclusion
Page 18 – Assessment criteria
Page 19 – Review 1/5
Page 22 – Future Recommendations 1/5
Page 23 – Future Recommendations 2/5
Page 24 - Future Recommendations 3/5

Contents: Appendices
Page 27 – Appendices introduction
Page 28 – Appendix 1 – standardised
instructions
Page 29 – Appendix 2 – Profile of Mood
States (POMS) test
Page 30 – Appendix 3 – tally chart

Contents: Figures and Tables
Page 31 – Figures and tables introduction
Page 32 – Figures & tables 1 – passing
success rate tally chart
Page 33 – Figures & tables 2 – level of
vigour results
Page 34 – Figures & tables 3 – graph 1
Page 35 – Figures & tables 4 – graph 2

Acknowledgements
I would firstly like to thank my participants,
without their level of commitment I
wouldn’t have been able to obtain the
results I did. I would also like to thank
Georgia Short for assisting me with my
data collection.

Introduction
My aim is to investigate whether there is a relationship
between optimum levels of vigour and 16-25 year old female
footballers passing success rate at participation level.
I chose this aim because I want to become a Sports
Psychologist and any insight into this area will strengthen my
knowledge and aid me in the future. I also chose to study this
aim as I am a footballer and am intrigued to see whether a
technical skill can be influenced by psychological thought
processes.
This project lasted from the 23rd Jan – 27th March. By the 1st
Feb I collected each participants level of vigour. I completed
the literature review by the 27th Feb. By the 8th March I had
also collected their passing success rates. After this I would’ve
completed the testing phase. This left me the rest of my time
to complete my data analysis phase and the write up.

Literature Review and References
My literature review can be found here

Project Hypothesis
1) At the end of my research project I expect to
see a positive relationship between the level
of vigour and passing success rate of each
participant.
2) At the end of my research project I expect to
see a positive relationship between the level
of vigour and the total number of passes.

Method
I used opportunity sampling to find my 10 participants for my research; these
participants all take part in participation level footballer, are female and between 16-
25.
Firstly I read out a set of standardized instructions (See Appendix 1) to the
participants and provided them with a glossary of some of the moods to ensure they
all understood.
I then gave out the POMS questionnaire (See Appendix 2) found on the Brian Mac
website which contains normative data.
I allowed them 10 minutes to complete the questionnaire before the game so they all
had the same amount of time; I then collected the questionnaires off them; this
provided me with quantitative data. This will be completed by the 1st Feb.
Either myself of Georgia then carried out non-participant observation on the game,
using a tally chart (See Appendix 3) to see the number of passes and the number of
those which are unsuccessful in order to create a percentage, I will also video the
games to ensure my accuracy. This will be completed by the 8th March.
I then carried out data analysis on my results and completed my write up by the 27th
March.
My research is field-based research as I am observing the participants in their natural
sporting environment. As I am conducting field-based research which gives me
primary data. My research design is experimental.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques

Data Collection
The data I’m collecting is nominal and ordinal. It is nominal as it’s
categorised through level of vigour. Within these categories I can rank
my data by passing success rate therefore making it ordinal. To collect
the level of vigour of each participant, they will be completing a POMS
questionnaire that was previously printed for them from the Brian Mac
website. I used this questionnaire as its from a reliable sports website
and contains a normative data table which I can use to compare my
participants to.
The collection of participants passing was field-based; either myself or
Georgia carried out non-participant observation of the game; this
involved filling out a tally chart throughout the game. I also videoed
the game so I could go back and verify my findings which improved the
accuracy of my data collection method.
Both of these method of collection will give me quantitative data that I
can analyse further later on.

Data Analysis
Firstly I looked at the tally charts and created a passing success rate as a
percentage for each participant based on their number of passes and number
of successful passes (See Figures and Tables 1). Using passing success rate as
a percentage of overall passes allows me to easily compare each participant
to one and other.
I then compared each participants level of vigour (See Figures and Tables 2) to
the average level of vigour for an athlete of their age and gender to see if they
were above or below the average. The average level was found on the Brian
Mac website.
I also compared each participants passing success rate to their level of vigour
by creating a scatter gram which includes a line of best fit (See Figures and
Tables 3). I will also create a second scatter gram with a line of best fit to
show the relationship between level of vigour and number of passes (See
Figures and Tables 4). I will use ICT based techniques to analyse the data as I
will be creating the scatter gram on Edexcel. Doing this allows me to see if
their was a trend or relationship between these two factors to see if my
hypotheses are correct. My data is simple frequency distribution as it is an
amount in each category.
Creating this graph also allows me to identify any outliers within my group
which may affect my results.

Results
My results show a clear correlation between level of vigour and passing
success rate (See figures and tables 3). I found a 0.96 correlation between my
two variables using Spearman’s rank order correlation. This shows there is a
very strong positive relationship between my two variables. Subject D had the
highest level of vigour; at 26 and her passing success rate was 87.2% which
was the highest out of all my subjects. Whereas subject B’s level of vigour was
only 9 and her passing success rate was 57.4%; the lowest out of everyone
tested. This strong link shows that my initial hypothesis is correct as there is a
positive correlation. There is a low standard deviation of 5.17 from the line of
best fit which shows all the results are close together and not widely spread
out.
I also found that there is not a definite link between level of vigour and
number of passes (See figures and tables 4). Using Spearman’s rank order
correlation I got a correlation of 0.19 thus supporting my statement of there
being no correlation between level of vigour and number of passes. Subject
C’s level of vigour was 12 and she made only 17 passes. Whereas subject A
made 58 passes and her level of vigour was 14. This shows my second
hypothesis isn’t supported as there is no correlation between these two
factors.

Discussion
There was a clear trend in my data showing a positive correlation
between level of vigour and passing success rate. There were no
outliers in this section of my study. I expected to get this finding as I
hypothesised having a higher level of vigour would result in a higher
passing success rate. This result shows my first hypothesis has been
supported by my findings.
There was no relationship between level of vigour and number of
passes made. This result surprised me as I was expecting a positive
correlation between these two factors. In this Subject C’s level of
vigour was 12 and she made only 17 passes. Whereas subject A made
58 passes and her level of vigour was 14. There is only a small
difference between these two participants level of vigour but a
significant difference between the number of passes made thus
showing other factors must be taken into account when looking into
the number of passes made. This shows that my second hypothesis
hasn’t been supported by my results and a further research study
would have to look into this area to get more conclusive evidence of a
link between level of vigour and passing success rate.

Conclusion
To investigate whether there is a relationship between optimum levels of vigour and
16-25 year old female footballers passing success rate at participation level. Looking at
my literacy review aided me to make my hypotheses because the previous research
found many links between level of vigour and enhanced performance.
My first hypotheses has been supported by my results as you can see a clear positive
correlation between level of vigour and passing success rate. Having higher levels of
vigour enables participants to put maximum effort and concentration into the task
making them more likely to succeed therefore it makes sense that this hypotheses is
supported through my findings.
My second hypotheses is not supported by my results as I found no correlation
between the number of passes made and level of vigour. There maybe other factors
that affect the number of passes made; these factors can be internal such as
motivation, fatigue and other moods or could be related to external factors such as
the game itself. For example when playing a game against a tough opposition strikers
will have fewer opportunities to pass the ball and when playing an easy opponent
defenders may suffer the same problem. These factors may be a key reason as to why I
found no correlation between level of vigour and number of passes.

Assessment Criteria Pages 19-26
• P5: carry out a review of the research project
conducted, describing strengths, areas for
improvement and future recommendations.
• M3: carry out a review of the research project,
explaining strengths, areas for improvement
and future recommendations.
• D2: carry out a review of the research project,
justifying future recommendations for further
research.

Review (1/3)
Although there is no clear link between level of vigour and
number of passes made my conclusion met my project aim
well because it confirmed there is a correlation between the
level of vigour and passing success rate of female footballers
at participation level between the ages of 16-25. As stated in
my conclusion my results showed a clear correlation between
level of vigour and passing success rate as there is a positive
correlation on my scatter graph (See figures and tables 3) and
I used Spearman’s rank order correlation to ensure my
correlation was significant. I believe this finding is due to the
fact having high levels of vigour will improve the players levels
of concentration and effort therefore increasing the players
passing accuracy. My results are reliable as passing success
rate was measured by an observer and checked from video
analysis.
P5: Describe / M3: Explain / D2: Justify

Review (2/3)
One main strength of my research project was the fact I
handed out standardised instructions before my participants
did their POMS questionnaire. This was a strength because
doing this meant each participant had the same information
which therefore improves the reliability of POMS test scores.
Another strength is that I videoed the game to improve the
accuracy of recording passing success rate; this was a strength
because it meant that I was able to check that I had recorded
the correct scores for each of my participants making the
scores more accurate.
Improving both the accuracy and reliability of my data
collection techniques is a massive strength as it means my
results are consistent and reliable. Doing this also means if I
was to carry out the research again I should find similar results
as there is a high level of reliability.

Review (3/3)
One weakness of my research project is that I only measured their passing
in one game. I should measure passing during different games as the
opponent may affect the number of passes; as playing against a tough
opponent will reduce the number of passes a striker does. This was a
weakness because only measuring it in one game will reduce the
reliability of my results.
Another weakness of my project is that I only measured it once
throughout the season. This is also a weakness because Lovell et al.
(2010) found level of vigour changes throughout a season and therefore I
would get more accurate and reliable results if they completed the POMS
test and I measured their passing success rate 3 time a season.
The final weakness of my project is that because I observed games with
Georgia and there maybe issues concerning inter-rater reliability as there
was no discussion of what counts as a pass or unsuccessful pass. This
means one of us may have counted something as a pass and the other
wouldn’t. This is a weakness as this reduces the reliability and accuracy of
the passing success rate scores.

Future Recommendations (1/5)
If I was to complete this research project again I would change
number of games watched from 1 to 3 to create an average of
passing success rate; there are many benefits of this including the
fact it would eliminate the influence of the opponents ability and
increase the reliability of the results.
I would also make this project longitudinal so it lasted throughout
the entire season. This allows me to measure level of vigour at least
3 times because Lovell et al. (2010) found that timing within the
season affects level of vigour in Sunday league soccer players.
The final thing I would change if I was to undergo this project again
would be the observers. I would improve the inter-rater reliability
by ensuring both observers have a discussion before the game to
make sure they are counting the same things as a pass or not; again
I would video the games to results here can be verified.
P4: Produce / P5: Describe / M3: Explain / D2: Justify

The first benefit would be I could create an average passing success
rate and number of passes to remove the influence of external factors
such as the opponent’s ability on their score. I would also be able to
remove any outliers; for example if one participant did 56, 53, 22
passes during the 3 games I would be able to remove the final one in
order to create a reliable and accurate average; this will further
improve the reliability and accuracy of my results.
I would also be able to create an average level of vigour as I would
measure it 3 times during the seasons. Lovell et al. (2010) found that
the time during season affects a players level of vigour so measuring it
3 times will have many benefits including it would remove the effect of
seasonal timing and improve the reliability of these results.
The final benefit of these changes are that ensuring observers have a
discussion before will improve the reliability between observers and
therefore ensures the passing success rate is correct for each player
improving overall reliability and accuracy of the results.

In future research I would recommend the same study is
carried out on men of the same population to see if there is a
similar correlation between the level of vigour and passing
success rate. Doing the same study would allow me to see if
there was a gender difference; this would show me whether
level of vigour affects the response between different genders
in different ways. This will also show me whether the same
psychological thought processes affects the ability of the
other gender to perform a technical skill; it allows us to see
whether different genders respond differently to these
thought processes. This could be done on a local football team
looking at all the players; looking at more than 10 people will
make the results more reliable. To remove the effect of other
variables I will have to ensure the players are chosen by the
same scope and the same project is carried out exactly.

In future research I would recommend the same study is carried
out on other sports looking at the same population to see if
there is a similar correlation between the level of vigour and
passing success rate within their sport. This could be done in
rugby, netball, basketball and hockey. Doing this study will allow
me to see if level of vigour affects a technical factor in different
sports or whether different athletes who have gone through
different training respond in a different way to the psychological
thought processes. It will theoretically show me which sport
requires higher levels of vigour for them to perform at their
optimum. This will also give me broader results which will
therefore make them more reliable as I have tested more people
from a variety of activities. Again to remove the effect of other
variables I will have to ensure the players are chosen by the
same scope and the same project is carried out exactly.

In future research I would recommend the same study is carried
out on a variety of sports and genders looking at the same
population to see if there is a similar correlation between the
other mood states in the POMS test and passing success rate
within their sport. There are 6 moods, vigour, tension, confusion,
fatigue, anger, and depression. I would want to see if any of the
other mood states have an influence and which one has the
biggest influence over the technical factor. This will tell me
whether level of vigour is the mood that has the biggest
influence over passing success rate. After finding out which
mood has the biggest influence the findings can be used to help
athletes control a specific emotion that will then optimise their
performance. Again to remove the effect of other variables I will
have to ensure the players are chosen by the same scope and
the same project is carried out exactly.

Appendix 1
Standardised instructions –
I have handed you a questionnaire and a glossary of
words; when I say you can begin please choose the
most appropriate response to each 65 moods; you
should be relating these moods to how you feel
within a game of football. Consult the glossary
whenever you don’t understand the definition of
the emotion. You have 10 minutes to complete the
questionnaire. Please begin

Appendix 2
http://www.brianmac.co.uk/poms.htm

Appendix 3
Tally chart – (example, not actual data)
Number of passes IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII
Number of unsuccessful
passes
IIIIII

Research Project Figures
and Tables

Figures and Tables 1
Tally chart – (number of successful passes/number of
passes) X100

0
10
20
30
40
50
60
70
80
90
100
0 5 10 15 20 25 30
Level of vigour
A graph to show the relationship between level of vigour and passing success rate of
participation level female footballers aged 16-25
Passingsuccessrate(%)

0
10
20
30
40
50
60
70
0 5 10 15 20 25 30
Level of vigour
Numberofpasses A graph to show the relationship between level of vigour and number of passes
of participation level female footballers aged 16-25

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