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Unit 5 Research Project
Worthing College Sports Science
Liam Lee
2015
‘To investigate the affect of
premiership standard back 5
forward height and the amount of
lineouts won per game.’
P2: Carry out / P4: Produce
Abstract
The aim of the study was to investigate the relationship between the
height of the starting back five forwards in elite level male rugby and
their lineout success rate. The study had a sample size of around 80
male professional rugby players who were involved in the Aviva rugby
premiership season between 2014-2015. the data for the study was
collected using the Aviva rugby premiership website. The data
collected was shown using excel on a spearmint rank order correlation
and on a scatter graph. The results on the spearmint correlation
showed that there was very little correlation between the height and
lineout success rate. One thing to look into in the future would be the
hookers throwing technique and if it affects accuracy and another
would be to look at the height of the lifters in the lineout as they can
have a huge part on the height of the lift.
P2: Carry out / P4: Produce
Contents: General
Page 3 – Aim
Page 4 – Abstract
Page 5 – General contents
Page 6 – Contents appendices
Page 7 – Contents figures and tables
Page 8 – Acknowledgments
Page 9 – Introduction
Page 10 – Literature review and references
Page 11 – Project 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 19-26
Page 19 – Review 1/3
Page 20 – Review 2/3
Page 21 – Review 3/3
Page 22 – Future recommendations 1/5
Page 23 – Future recommendations 2/5
Page 24 – Future recommendations 3/5
Page 25 - Future recommendations 4/5
Page 26 - Future recommendations 5/5
P2: Carry out / P4: Produce
Contents: Appendices
Page 27 – Research project appendices
Page 28 - Appendix 1
Page 29 - Appendix 2
Page 30 - Appendix 3
Page 31 - Appendix 4
Page 32 - Appendix 5
P2: Carry out / P4: Produce
Contents: Figures and Tables
Page 33 - Research project figures and tables
Page 34 - Figures and tables 1/5
Page 35 - Figures and tables 2/5
Page 36 - Figures and tables 3/5
Page 37 - Figures and tables 4/5
Page 38 - Figures and tables 5/5
P2: Carry out / P4: Produce
Acknowledgements
• I would like to thank my peers who have given
me advice throughout my project.
• I would also like to thank my teachers Mark
Sambrook and Paul Cox for their advice and
guidance throughout my project.
P2: Carry out / P4: Produce
Introduction
My project is ‘To investigate the affect of
premiership standard back 5 forward height and
the amount of lineouts won per game.’ I chose
this aim because I wanted to see if the height of
the back five forwards affects lineout success
rates in elite level rugby. My timescale for this
project was one month.
P2: Carry out / P4: Produce
Literature Review and References
Here is a link to my literature review.
https://worthingsportscience.wordpress.com/20
15/02/26/unit-5-literacy-review-liam-lee/
P2: Carry out / P4: Produce
Project Hypothesis
1. At the end of my research project I expect to
find that teams with taller back five forwards
will have a better lineout success rate.
2. At the end of my research project I expect to
find that teams with the highest average
lineout success rate will have higher league
positions then those who have a low lineout
success rate.
P2: Carry out / P4: Produce
Method
1. First create an excel document with all the Aviva premiership teams names down the side.
2. Add the columns 4, 5, 6, 7, 8, total height, average height, lineouts had, lineouts won and finally lineouts won
percentage.
3. Add calculations that will work out the total height for the combined heights of 4, 5, 6, 7 and 8 and calculations
that will find the mean for their total combined heights.
4. Add calculations that will work out the lineout win percentage using the calculation: lineouts had divided by
lineouts won time 100 = the percentage of lineouts won. To see an example of the excel document see
(Appendix 1).
5. Copy this excel document four times saving them as round 1, round 7, round 15 and round 20.
6. Using Google, go to the Aviva premiership rugby fixtures and results webpage.
7. Go to round 1 and look at each game. Take the names of each teams starting back 5 forwards and research their
heights on the Aviva premiership rugby website and record them on your excel document (this is where excel
will need to calculate the total height for each team and the mean height for each team).
8. Then, on the same website, find each teams stats for the game showing lineouts had and lineouts won. Then
record these for each team on your excel document. (this is where excel will calculate each teams lineout
success percentage).
9. Do this for rounds 1, 7, 15 and 20 (putting each rounds results in the appropriate excel document).
10. Find the mean height and mean lineout win percentage for each team over the 4 rounds and make a scatter
graph and a spearman correlation graph (See figures and tables 1).
11. Write up a conclusion of what you found and your opinions.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
Data Collection
I carried out a desk based research project that
consisted of collecting secondary based
quantitative data from a reliable source (see
appendix 2). It consisted of looking at each teams
lineout stats for games 1,7,15 and 20 and recording
them in excel. It also consisted of looking at each
teams starting back 5 forwards and researching
their individual height using the teams official
webpage on the Aviva rugby site. The benefit of
using these sites to get my data is that they are a
reliable source whereas using a website such as
Wikipedia may not have accurate information.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
Data Analysis
I will analyse my secondary data using excel by
looking at each teams average starting back 5
forwards height and comparing it to their
lineout win percentage. I will then make a
scatter graph on excel which will allow me to see
if there is a correlation between height and
lineout win percentage. I will also use the
spearmint correlation measure which will allow
me to see if there is any correlation between
height and lineout win percentage.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
Results
My results show that there is a very low
correlation between the height of the back 5
starting forwards and the lineout win
percentage in the Aviva rugby premiership (see
figures and tables 2 and 3). I got my results by
entering my data into the a spearmint
correlation measure using excel and seeing if
there was a strong correlation. I also saw this on
my scatter graph which I made on excel and so
my results were accurate.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
Discussion
I found that the average height of Aviva premiership
rugby teams starting back 5 forwards has no
correlation to them having a better lineout success
rate. This finding was not what I expected as I
thought the opposite and so this result was quite a
surprise to me. The trend that I identified was that
the average height of the back 5 forwards rarely
changed and was quite consistent throughout my
project, this indicates to me that the height of the
team which is picked is not a tactical decision.
P2: Carry out / P4: Produce
Conclusion
‘To investigate the affect of premiership standard back 5
forward height and the amount of lineouts won per game.’
My key trends were that all the sources will support my
research project. Another is that all my sources are valid and
will help me during my project. Another key trend is that my
sources are all looking at elite level male athletes. And finally
that they are all related to the height and weight of athletes.
Overall, my results did not support my hypotheses and my
results were not what I expected as they showed that there
was no correlation between average height of the back 5
forwards and lineout win percentage
P2: Carry out / P4: Produce
Review (1/3)
My project conclusion did not meet my project aims
very well at all. My conclusion found no correlation
between what I was looking into (as shown on
figures and tables 2). My conclusion also did not
prove any of my hypotheses which was also a
disappointment. One thing my conclusion tell me is
that I should not continue research on this aim as
no correlation was found and so it would be a
waste of time.
P5: Describe / M3: Explain / D2: Justify
Review (2/3)
• One strength of my research project is the
reliability of my data because I used a very
accurate and reliable source (see appendix 2).
• Another strength is the organisation of my data
and how it has been presented on excel. This is a
strength as the data can easily been seen (See
figures and tables 1,2 and 3).
• Another strength of my research project is the
validity of my data. It is valid because it allows me
to clearly see whether height affects lineout win
percentage.
P5: Describe / M3: Explain / D2: Justify
Review (3/3)
My area to improve would be to learn more
about how to use excel and the spearmint
correlation measurement as I did not really
know about it. Also knowing how to do it would
have saved me time as I had to wait for help.
P5: Describe / M3: Explain / D2: Justify
Future Recommendations (1/5)
If I was to do this project again I would take into
account the hookers throw more. I would do this
as from my research in this project I have
learned that different hookers use different
techniques when throwing with one of the
techniques proving to be the more accurate. I
would choose this as I feel that the hookers
throw can have a real affect on how successful a
lineout is and by doing research on it I would be
able to justify that statement further.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Future Recommendations (2/5)
The benefit of taking the hookers throw into
account would be that you would be able to see
which is more effective in terms of the lineout,
the height of the back 5 forwards or the hookers
throw accuracy/technique. It will also help
support whether this research projects aim was
correct or whether it could be questioned with
evidence to back it up.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Future Recommendations (3/5)
Look into the hookers accuracy/technique when
throwing in more depth. As during my project I
learned that different throwing techniques
affect accuracy.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Future Recommendations (4/5)
Look at the height of the lifters in the lineout. I
think this would be a good thing to look into as
taller lifters can get more height in the lift which
could course a tactical advantage.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Future Recommendations (5/5)
I would recommend someone else who is more
experienced to redo my project in order to see
if they get the same results. I would advise them
to do this as height in the forwards can be a way
of using talent identification in young athletes
but if it doesn’t benefit the team then it
shouldn't be a way of identifying talent.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Research Project Appendices
Appendix 1
Here is a photo of my excel sheet used to show
data I collected.
Appendix 2
http://www.premiershiprugby.com/
Research Project Figures
and Tables
Figures and Tables 1
Here is a photo of my
excel sheet showing my
data
Figures and tables 3
Here is a photo of my spearmint correlation
Figures and Tables 2
Here is a photo of my scatter
graph.

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Unit 5, Liam Lee

  • 1. Unit 5 Research Project Worthing College Sports Science Liam Lee 2015
  • 2. ‘To investigate the affect of premiership standard back 5 forward height and the amount of lineouts won per game.’ P2: Carry out / P4: Produce
  • 3. Abstract The aim of the study was to investigate the relationship between the height of the starting back five forwards in elite level male rugby and their lineout success rate. The study had a sample size of around 80 male professional rugby players who were involved in the Aviva rugby premiership season between 2014-2015. the data for the study was collected using the Aviva rugby premiership website. The data collected was shown using excel on a spearmint rank order correlation and on a scatter graph. The results on the spearmint correlation showed that there was very little correlation between the height and lineout success rate. One thing to look into in the future would be the hookers throwing technique and if it affects accuracy and another would be to look at the height of the lifters in the lineout as they can have a huge part on the height of the lift. P2: Carry out / P4: Produce
  • 4. Contents: General Page 3 – Aim Page 4 – Abstract Page 5 – General contents Page 6 – Contents appendices Page 7 – Contents figures and tables Page 8 – Acknowledgments Page 9 – Introduction Page 10 – Literature review and references Page 11 – Project 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 19-26 Page 19 – Review 1/3 Page 20 – Review 2/3 Page 21 – Review 3/3 Page 22 – Future recommendations 1/5 Page 23 – Future recommendations 2/5 Page 24 – Future recommendations 3/5 Page 25 - Future recommendations 4/5 Page 26 - Future recommendations 5/5 P2: Carry out / P4: Produce
  • 5. Contents: Appendices Page 27 – Research project appendices Page 28 - Appendix 1 Page 29 - Appendix 2 Page 30 - Appendix 3 Page 31 - Appendix 4 Page 32 - Appendix 5 P2: Carry out / P4: Produce
  • 6. Contents: Figures and Tables Page 33 - Research project figures and tables Page 34 - Figures and tables 1/5 Page 35 - Figures and tables 2/5 Page 36 - Figures and tables 3/5 Page 37 - Figures and tables 4/5 Page 38 - Figures and tables 5/5 P2: Carry out / P4: Produce
  • 7. Acknowledgements • I would like to thank my peers who have given me advice throughout my project. • I would also like to thank my teachers Mark Sambrook and Paul Cox for their advice and guidance throughout my project. P2: Carry out / P4: Produce
  • 8. Introduction My project is ‘To investigate the affect of premiership standard back 5 forward height and the amount of lineouts won per game.’ I chose this aim because I wanted to see if the height of the back five forwards affects lineout success rates in elite level rugby. My timescale for this project was one month. P2: Carry out / P4: Produce
  • 9. Literature Review and References Here is a link to my literature review. https://worthingsportscience.wordpress.com/20 15/02/26/unit-5-literacy-review-liam-lee/ P2: Carry out / P4: Produce
  • 10. Project Hypothesis 1. At the end of my research project I expect to find that teams with taller back five forwards will have a better lineout success rate. 2. At the end of my research project I expect to find that teams with the highest average lineout success rate will have higher league positions then those who have a low lineout success rate. P2: Carry out / P4: Produce
  • 11. Method 1. First create an excel document with all the Aviva premiership teams names down the side. 2. Add the columns 4, 5, 6, 7, 8, total height, average height, lineouts had, lineouts won and finally lineouts won percentage. 3. Add calculations that will work out the total height for the combined heights of 4, 5, 6, 7 and 8 and calculations that will find the mean for their total combined heights. 4. Add calculations that will work out the lineout win percentage using the calculation: lineouts had divided by lineouts won time 100 = the percentage of lineouts won. To see an example of the excel document see (Appendix 1). 5. Copy this excel document four times saving them as round 1, round 7, round 15 and round 20. 6. Using Google, go to the Aviva premiership rugby fixtures and results webpage. 7. Go to round 1 and look at each game. Take the names of each teams starting back 5 forwards and research their heights on the Aviva premiership rugby website and record them on your excel document (this is where excel will need to calculate the total height for each team and the mean height for each team). 8. Then, on the same website, find each teams stats for the game showing lineouts had and lineouts won. Then record these for each team on your excel document. (this is where excel will calculate each teams lineout success percentage). 9. Do this for rounds 1, 7, 15 and 20 (putting each rounds results in the appropriate excel document). 10. Find the mean height and mean lineout win percentage for each team over the 4 rounds and make a scatter graph and a spearman correlation graph (See figures and tables 1). 11. Write up a conclusion of what you found and your opinions. P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
  • 12. Data Collection I carried out a desk based research project that consisted of collecting secondary based quantitative data from a reliable source (see appendix 2). It consisted of looking at each teams lineout stats for games 1,7,15 and 20 and recording them in excel. It also consisted of looking at each teams starting back 5 forwards and researching their individual height using the teams official webpage on the Aviva rugby site. The benefit of using these sites to get my data is that they are a reliable source whereas using a website such as Wikipedia may not have accurate information. P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
  • 13. Data Analysis I will analyse my secondary data using excel by looking at each teams average starting back 5 forwards height and comparing it to their lineout win percentage. I will then make a scatter graph on excel which will allow me to see if there is a correlation between height and lineout win percentage. I will also use the spearmint correlation measure which will allow me to see if there is any correlation between height and lineout win percentage. P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
  • 14. Results My results show that there is a very low correlation between the height of the back 5 starting forwards and the lineout win percentage in the Aviva rugby premiership (see figures and tables 2 and 3). I got my results by entering my data into the a spearmint correlation measure using excel and seeing if there was a strong correlation. I also saw this on my scatter graph which I made on excel and so my results were accurate. P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
  • 15. Discussion I found that the average height of Aviva premiership rugby teams starting back 5 forwards has no correlation to them having a better lineout success rate. This finding was not what I expected as I thought the opposite and so this result was quite a surprise to me. The trend that I identified was that the average height of the back 5 forwards rarely changed and was quite consistent throughout my project, this indicates to me that the height of the team which is picked is not a tactical decision. P2: Carry out / P4: Produce
  • 16. Conclusion ‘To investigate the affect of premiership standard back 5 forward height and the amount of lineouts won per game.’ My key trends were that all the sources will support my research project. Another is that all my sources are valid and will help me during my project. Another key trend is that my sources are all looking at elite level male athletes. And finally that they are all related to the height and weight of athletes. Overall, my results did not support my hypotheses and my results were not what I expected as they showed that there was no correlation between average height of the back 5 forwards and lineout win percentage P2: Carry out / P4: Produce
  • 17. Review (1/3) My project conclusion did not meet my project aims very well at all. My conclusion found no correlation between what I was looking into (as shown on figures and tables 2). My conclusion also did not prove any of my hypotheses which was also a disappointment. One thing my conclusion tell me is that I should not continue research on this aim as no correlation was found and so it would be a waste of time. P5: Describe / M3: Explain / D2: Justify
  • 18. Review (2/3) • One strength of my research project is the reliability of my data because I used a very accurate and reliable source (see appendix 2). • Another strength is the organisation of my data and how it has been presented on excel. This is a strength as the data can easily been seen (See figures and tables 1,2 and 3). • Another strength of my research project is the validity of my data. It is valid because it allows me to clearly see whether height affects lineout win percentage. P5: Describe / M3: Explain / D2: Justify
  • 19. Review (3/3) My area to improve would be to learn more about how to use excel and the spearmint correlation measurement as I did not really know about it. Also knowing how to do it would have saved me time as I had to wait for help. P5: Describe / M3: Explain / D2: Justify
  • 20. Future Recommendations (1/5) If I was to do this project again I would take into account the hookers throw more. I would do this as from my research in this project I have learned that different hookers use different techniques when throwing with one of the techniques proving to be the more accurate. I would choose this as I feel that the hookers throw can have a real affect on how successful a lineout is and by doing research on it I would be able to justify that statement further. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 21. Future Recommendations (2/5) The benefit of taking the hookers throw into account would be that you would be able to see which is more effective in terms of the lineout, the height of the back 5 forwards or the hookers throw accuracy/technique. It will also help support whether this research projects aim was correct or whether it could be questioned with evidence to back it up. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 22. Future Recommendations (3/5) Look into the hookers accuracy/technique when throwing in more depth. As during my project I learned that different throwing techniques affect accuracy. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 23. Future Recommendations (4/5) Look at the height of the lifters in the lineout. I think this would be a good thing to look into as taller lifters can get more height in the lift which could course a tactical advantage. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 24. Future Recommendations (5/5) I would recommend someone else who is more experienced to redo my project in order to see if they get the same results. I would advise them to do this as height in the forwards can be a way of using talent identification in young athletes but if it doesn’t benefit the team then it shouldn't be a way of identifying talent. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 26. Appendix 1 Here is a photo of my excel sheet used to show data I collected.
  • 29. Figures and Tables 1 Here is a photo of my excel sheet showing my data
  • 30. Figures and tables 3 Here is a photo of my spearmint correlation
  • 31. Figures and Tables 2 Here is a photo of my scatter graph.