RACHEL WOODS
ST08002851
School of Sport:
UNIVERSITY OF WALES INSTITUTE CARDIFF
ANALYSIS OF TYPES OF TURNOVERS AND OUTCOME IN INTERNATIONAL
WOMEN’S BASKETBALL
TABLE OF CONTENTS
Page Numbers
List of tables
List of figures
Acknowledgements
i
Abstract
ii
Chapter one
1
Introduction
1.1 Background of study
1.2 Aim of the study
1.3 Summary of method
Chapter two
3
Literature Review
2.1 Performance Analysis linked coaches
2.2 Eurobasket level of competition analyses
2.3 Statistics within basketball
2.4 Turnovers
2.4 Basketball- turnover related articles
Chapter three:
Methodology
3.1 Team, games and equipment
3.2 Pilot study 1- Key terms
3.3 Pilot study 2
3.4 Pilot study 3
3.5 Final system
3.6 Reliability study 3.7 Data analysis
9
Chapter four:
16
Results
Chapter five:
24
Discussion
5.1 Future research
Chapter six:
Conclusion
Appendices
APPENDIX A: Participant sheet
APPENDIX B: Informed consent sheet
APPENDIX C: Pilot studies
APPENDIX D: Final System Key
APPENDIX E: Reliability
APPENDIX F: Spreadsheet calculations
32
List of Tables
Table
1. Mann Whitney U descriptive statistics
22
2. Statistics of the Mann Whitney U
23
List of Figures
Figure
1. Pie chart of all turnovers throughout the 8 games
16
2. Positive and negative outcomes of each performance indicator
17
3. The different types of negative outcomes of missed shots.
18
4. The different types of negative outcomes of the bad pass.
19
5. The different types of negative outcome from a fumble or steal.
20
6. The different types of negative outcomes from a blocked shot.
20
7. Diagram of basketball court sections defined in this study.
21
Acknowledgements
I would like to give a thank you my dissertation tutor Lucy Witt for supporting me
throughout this process.
Thank you to Damian Jennings and again to Lucy Witt for allowing me to use the
footage for the Great Britain Squad from summer 2010.
i
Abstract
The aim of the study was to find out if higher placed teams in the league compared
with lower placed teams in the league have an effect on turnovers, if there were
specific trends to these turnovers and where on court turnovers came from. There
were eight International games analysed, each focusing on the Great Britain team
during the summer of 2010. Four games against top placed teams in Division A and
four placed lower in the league. This was done through analysing DVD’s and a hand
notation system was used. Results found more turnovers came from bottom of the
league, missed shots main outcomes was field goals, bad passes and fumbles/steals
mainly lead to out of bounds and blocked shots did not find a trend. The main area of
the court that turnovers came from was the front area of the court on the left hand
side. In conclusion higher teams did not force more turnovers, showing higher
opposition was not a factor that influenced performance of turnovers. Factors that
made influence performance to be looked at in the future may be types of defence,
home court advantage or referees.
ii
CHAPTER ONE
INTRODUCTION
Introduction
1.1 Background of study
Basketball is currently one of the fastest growing sports in the world (Wissel, 2004).
It is a fast, pulsating, exciting and rewarding game at every level wherever it is
played but the game relies on solid fundamentals (Nemeth, 2002). Basketball is a
game played with two teams, which consists of either 10 or 12 players per team
(Nemeth, 2002) and each team has 5 players on the court (Wissel, 2004). The aim of
basketball is to score by putting the ball through the basket as frequently as possible
and to stop the opposing team from scoring (Wissel, 2004).
1.2 Aim of the study
This study is going to look at the possessions of a team that did not lead to a score
and the reasons for this. This can also be referred to as “turning the ball over” to the
opposition or the basketball term “turnover”. The purpose of this study is to
investigate the importance of turnovers. This study will determine if the quality of the
opposition is a factor that affects a team’s performance. This will be measured be
analysing one team and comparing their performance to teams placed at bottom and
top of their division. The team that will be the subject of this study is the Great Britain
Women’s Basketball team. The study will aim to determine if higher placed teams
who finish top of the division force a team such as Great Britain to have more
turnovers; this will be measured through the number of turnovers the team gains.
The information that is going to be shown throughout this study is where on court
that turnover came from, the type of outcome the turnover had and if the outcome of
this turnover is positive or negative. This information can then be useful to coaches
to use as feedback for their players. If Nemeth’s (2002) statement that 85% of
turnovers lead to a score is true, then this is an issue the coach will have to address.
The type of outcome, such as a score or foul, will also be linked to the type of
turnover and to show if there are specific trends for the different types of turnovers.
1
Barnes (1980) defines a turnover as an offensive player either losing the ball not
through a missed shot, committing an offense foul or through a violation. This study
is going to classify a turnover as ‘any possession of the ball that did not end in a
score’. The reason for adding missed shots to this study as a turnover is because
this study is looking at an elite level. The Great Britain team are in Division A of the
European League. Percentages of scores per team are higher in higher level
competitions. This is shown through the Division B statistics of field goal percentages
for the top five teams ranged between 50%- 56.5% (FIBA, 2010). Division A statistics
showed the top five teams had higher percentages; these were between 55.2 and
65.4 (FIBA, 2010).
This study has three hypotheses. Hypothesis one: teams placed higher in the league
will force more turnovers then those placed lower in the league and these will come
from missed shots. Hypothesis two: more turnovers will come from the front court.
Hypothesis three: games played against lower teams in the league will have a higher
percentage of positive outcomes.
1.3 Summary of method
The study is going to be undertaken through a hand notation system. It aims to
statistically analyse outcomes of the turnovers, measuring games against teams
placed top and bottom of the league with the aim of find differences between the two.
2
Chapter two
Literature Review
Literature Review
2.1 Performance Analysis linked coaches
Performance analysis of invasion games has received much attention in recent years
(Lago, 2009). In order to measure improvement of an athlete’s performance,
effective coaching and teaching methods depend heavily on analysis (Hughes and
Franks, 2004). Hughes and Bartlett (2002) also agreed with this statement and
believe notational analysts are concerned with the analysis and development of sport
performance. This data within basketball can be gathered for the whole team or for
players individually (Hughes and Franks, 2008). When notational analysis data is
gathered a coach can then assess strengths and weaknesses of a performance
through statistics of a game individually and as a whole team or opposition and then
make decisions on how to correct them (Hughes and Franks, 2008). Notational
analysis is commonly used within research and applied settings to investigate the
technical aspects of performance through recording behaviour incidence and
outcomes (Carling, Williams, & Reilly, 2005).
Hand notation is going to be used during this study to see patterns and where
mistakes in a game are made, after this analyse judgements are going to be made
on the key areas and this information could then be used to feed back to coaches in
order to limit turning the ball over during a game of basketball.
2.2 Eurobasket: level of competition analysed
FIBA is the official site of the International Basketball Federation (FIBA 2011) it gives
information on the current rankings and standing of everything going on of each
country involved in basketball. It gives news on basketball and also gives information
on things such as rules and regulations of basketball. Therefore it is shown that FIBA
is a well established website within the basketball world. Eurobasket is the European
Women’s Basketball Championships, which are where the Great Britain games that
are being analysed are played. The 16 teams from the competition are put into four
groups and the first two top teams go through to the knock out stages the following
year (FIBA, 2010). The knockout stage will begin this June (FIBA, 2011). The games
that are being analysed for this study are from the Eurobasket competition during
summer 2010.
3
2.3 Statistics within basketball
Statistics are used within basketball and are usually displayed through box scores.
Statistics are regularly used in performance analysis as this data can then be used to
give feedback to players and coaches (Hughes and Franks, 2004). Feedback was
used because it assesses performance they cannot see for themselves (Graham,
2001). Rose (2004) shows an example of a NCAA box score of basketball, the
variables of this are field goals, made goals, attempted goals, rebounds, personal
fouls, turnovers, assists, blocked shots and steals for each player, this can also be
known as performance indicators. “A performance indicator is a selection, or
combination, of action variables that aims to define some or all aspects of a
performance” (Hughes and Bartlett, 2002) they are used to asses a team or an
individual and should relate to getting a successful performance or outcome of this
team or individual (Hughes and Bartlett, 2002).
Rose (2004) states players quickly learn the importance of collecting statistics across
the board. The more rounded their game, the better their chance for collecting
numbers. When a player’s individual execution of these things improve, teams
become more productive. Components of the performance rating systems include
statistics, and for basketball each statistic is even a value of importance by the coach
and players. Performance ranking is used for both coaches and players, and is used
overall to get an environment that is fair, competitive and motivating.
Turnovers are on of the variables focused on when looking at box scores within
basketball. The higher a player’s turnover rate, the lower their on-court success
(Morse, Shapiro, McEvoy and Rascher 2008). This says not committing turnovers is
a vital part of basketball in order to be successful. Turnovers are a performance
indicator used in many basketball studies shown below. This shows their importance
when it comes to a team being successful or not and therefore this study is going to
focus purely on turnovers. This study is also looking at turnovers in more depth as
most studies do not go into detail as to what type of turnover their team commits.
4
2.4 Turnovers
A player that commits a large number of turnovers (violations or offensive foul)
needs to practice the basic skills of basketball (Barnes, 1980). The main definition of
a turnover is either a violation or loss of possession by the team in control of the ball
without it coming from a shot (Nemeth, 2002). This study is going to focus mainly on
losses of possession and the outcomes that result from this loss. It will include
defensive rebounds coming from shots, as this is still a turnover in possession to the
opposition without a successful result of scoring. Nemeth, (2002) identifies the
importance of turnovers. He states it is a ‘nightmare’ for coaches and can destroy a
team’s performance. 95% of turnovers come from a players bad pass and statistics
also show that 85% of turnovers lead to a score (Nemeth, 2002). Most turnovers
come from a point guard, this is because they handle the ball the most (Barnes,
1980). This study will be focusing on the team as a whole.
2.5 Basketball- turnover related articles
This study looks at the effect and trends of turnovers and the positive and negative
outcomes of each turnover. It is explained above by Nemeth how important
turnovers are within a game of basketball. Basketball studies have shown the
importance of turnovers from analysing them as a key variable, showing the
significance they have to a game of basketball. Oliver (2005) listed turnovers as the
second of four factors to analyse a team’s offensive performance at NBA level. He
showed turnovers have a very high relevance to success which indicates why they
are looked second. The first factor is shooting and the others factors are rebounding
and free throws.
A non-basketball article which is relevant to this study was undertaken by
O'Donoghue et al. (2008). This was a similar study focusing on interceptions within
British National Super League Netball. He used analysis to measure the different
types of interceptions in netball which is the equivalent to turnovers in a basketball
game. Again, like other studies he has taken into consideration the top half of the
teams in the league to be analysed against the bottom half.
5
Zarren (2010) reported on the well-known NBA Men’s basketball team the Boston
Celtics. He report focused on giving an insight into how players and the coach are
concerned with their turnovers. It looks at how different “points off a turnover” can be
misleading. This is through his view of the opponent usually gets an advantage of
scoring off a turnover, not from getting the ball calling a timeout and still scoring, as
this was not from the turnover directly because if time has stopped there is no longer
an advantage. This makes sense as if the clock is stopped then the defence have
time to get back and set up and they have the opportunity to find the player they
were marking. Therefore, the points are not a direct result of the turnover. So from
this positive and negative outcomes from a turnover will be looked at but only if it is
whilst the ball is still live leading up to the outcome.
One of the studies which focus on turnovers is Ibáñez, Sampaio, Sebastian, Gomez
and Ortega (2008). This study focused on teams positions in the league. It was
undertaken in the Spanish Basketball league comparing data from successful and
unsuccessful teams throughout the 2001/02 season and the 2005/06 season.
Turnovers were one of the variables researched. There was two different tables of
results, the first showed the difference between the teams that made the playoffs
and the teams that did not. The second table showed the importance of each aspect
with any value over 0.30 being significant, for example assists had a significant
difference between good and bad teams. Turnovers showed a negative value
meaning it has no correlation at all between being a good and bad team. Results for
individual types of turnover showed there was correlation for steals and blocked
shots between the best and worst teams. The study was very in depth with the data,
but only looked at male participants. Looking at this study it has therefore been
decided to look at different levels of playing as the opposition’s ability is a factor
which will affect the turnovers of a game, but has shown that opposition do not have
an effect on a game.
Although, this goes against the study of Sampaio, Lago,
Casais and Leite (2010) who looked at both the quality of opposition and the game
location being factors on performance within basketball. The performance indicators
of this study were shots scored and missed and these were recorded during 504
quarters of games in the Spanish Basketball Professional League, these games
were classified as balanced (score line being 8 points or under) and unbalanced
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(score line being 8 points or over). The influences of opposition found small effects
within the second and third quarters. The game location only showed an effect when
the whole game was being analysed rather than just the quarters. Sampaio, et al
(2010) did the study to see if the quality of opposition does have an effect on a
team’s performance and affected their box scores. This did not show any major
effect so the study that is about to be done will see if opposition does have an effect.
There have been other studies done on opposition effects such as Lago (2009) who
did a study on football and showed the strong effect that opposition had on
performance. From this study the opposition is a factor that is going to be taken into
consideration, so the different places (top, middle and bottom) in the league will be
compared.
A study that focused on the effects of the opposition not within basketball was
Taylor, Mellalieua, James and Sherer (2008). They looked at a study on the effects
of match location, quality of opposition, and match status on the technical aspects of
performance within a single professional British football team. Forty matches from
the 2002–2003 and 2003–2004. The study found that the odds of winning were lower
when playing against a stronger opposition, showing that the opposition did have an
effect of the score line of a football match.
Gomez et al (2009) did a study, which like every other basketball study has used
basketball statistics. Again turnovers were a performance indicator used. The study
researched the Women’s National Basketball Association League (WNBA) statistics
of those who started the game compared with to those who came off the bench and
it also looked at European teams. The problem with this study was the differences in
rules between the different countries. The study is different compared with others
because of the fact that it looked at women, however it only focused on individuals
rather than the whole team. It showed the mean turnovers from both starters and
non-starters against both the best and worst teams. Again this study looked at
quality of opposition, and does look at women’s basketball rather than the majority of
articles who look at men’s. A problem is no data from the UK, even though European
teams are used. This is another reason for using the Great Britain Basketball team.
7
A recent study on turnovers was done by Tiernan (2009), there were many statistics
measured during this study and one of the aspects focused on was turnovers. It
looked at 54 teams from 1985-2008 during the NCAA basketball tournament. It
looked at how the different performance indicators may affect if a team wins or loses,
one of these being turnovers. It found turnovers the second highest attribute that
affected why a team won or lost games. It was measured by whether the turnover
gap between both teams was more than 3. The teams that managed to force their
opposition to commit 3 or more turnovers than themselves managed to win on
average 16 more games above seed. This study had a lot of data collected over the
23 years it was conducted but does not take into consideration the ability of the
opposition.
The evidence from these studies shows the importance of turnovers and the affects
they have on winning and losing games. Only one of the studies looked at women’s
basketball, and there were no studies on basketball within the UK. Therefore this
study is going to focus on International Basketball, which will be the Great Britain
basketball team. The most recent games they played were over the summer of 2010,
so all the games that will be analysed for this study are going to be from this
tournament. Instead of looking at turnovers as one variable the whole study will be
focusing on turnovers. This will enable us to gain more of an insight and back up
Nemeth’s (2002) statement of turnovers being able to destroy a team. As this study
will only be looking at turnovers, the root that this study is going to go down is
comparing Great Britain’s performance to the teams at the top and bottom of the
league. The study will be comprised of four games for each team, resulting in there
being eight games to analyse overall.
8
Chapter three
Methodology
Methodology
3.1 Team, games and equipment
This study researched the Senior International Great Britain Women’s Basketball
team over 8 matches. The teams involved were: Great Britain, Netherlands,
Portugal, Bulgaria, Ukraine, Israel, Italy, Latvia and Belgium. The data for this
experiment was recorded through watching DVD’s of the basketball games which
could be rewound if necessary, and were analysed using hand notation throughout
each game. Before the final experiment was made pilot studies were conducted in
order to find a final effective system. Throughout all of the pilot studies DVD’s were
also watched as well as the data being gathered through hand notation. All the pilot
studies were analysed by either using International games or the Division 1 UWIC
Archers Women’s Basketball team, who won the play-offs during the 2009/2010
making them British basketball Champions. This means all of the data that was
analysed is on the elite stage within the UK or countries within Europe.
3.2 Pilot study 1- Key terms
The first pilot study was a simple task to find the types of turnovers and changes in
possession during a game of basketball. The game was UWIC Archers vs. Brixton
Ladies Topcats from a Division 1 National League game during the 2009/2010
season. The template of this study is shown in Appendix C named Pilot study 1.
After watching the game and identifying the types of turnover, each performance
indicator was defined for the study to make sure there was no misunderstanding for
the final study. These were defined specifically for this study or using coaching
books.
These are the types of turnovers and their definitions:
1. Timing regulations- (24 shot clock, 8 seconds, 5 seconds, 3 seconds)- a
team has 8 seconds once gaining possession to get it over into the front
court. From the time a team gains possession of the ball it has 24 seconds to
9
take a shot that hits the rim. A five second call is either to get the ball in
bounds which must touch somebody from the sideline or end line and a 3
second call is being in the key area for longer than 3 seconds on offense
(England basketball, 2002). The key is the trapezium shaped area where
each offence player can only be inside for 3 seconds (Nemeth 2002).
2. Bad pass (interception or out of bounds) - this is a pass was made and it
was not received with both hands by a player on the same team.
3. Defensive rebound from a missed shot. If the attacking team miss a shot
and the defensive team gain the rebound.
4. Travelling- taking more than two steps with the ball without dribbling.
5. Steal- to take the ball from an opponent (Nemeth, 2002).
6. Offensive Foul- a charge or setting an illegal screen.
7. Jump ball- when two people have hold of the ball for a period of time.
8. Double Dribble- dribbling, picking the ball up with both hands and dribbling
again.
9. Block- a defender hitting the ball away from the attacking player taking a
shot or layup without fouling.
10. Back court violation- being in the front court either dribbling with both feet
and ball in the front court, and changing back into the back court or the ball
getting passed to the front court and going back into the backcourt within the
same offence.
3.3 Pilot study 2
Leading on from this, a second pilot study was conducted (see appendix C) named
pilot study 2. This was done by watching the first quarter of an International
Women’s Basketball game between Hungary and Australia. The system that was
used for this study was:
1. Type of turnovers: a list of turnovers were set out in a table in column one
with T1 (Team one) and T2 (Team two) as the other columns. When T1
(Hungry) made a turnover a tally was made beside they type of turnover it
was and same for T2 (Australia).
T1= team 1’s turnovers, with team 2’s outcome from this turnover.
10
T2= team 2’s turnovers, with team 1’s outcome from this turnover.
2. Where on the court the turnover was caused: the court was split into four
sections in the front court and four in the back, the front court being the half in
which a teams attacking, the back court in the half where the teams defending
(Nemeth, 2002) and there are two different courts for Team 1 and Team 2 and
tallies were made on the diagrams for each team.
3. Where on the court the team got to: 1) Back court 2) Front court 3) Within
the 3 point line 4) Within the key. Again tallies were used.
4. Attempt at shot: from this turnover were the opposing team able to get a
shot off, tallies were then recorded in a table with either Yes or No boxes to
tally.
5. Outcome of shot: whether the shot was missed or made, again Yes and No
tallies were recorded in a table.
One of the problems with this study was another outcome that had not been picked
up on before was if the player was fouled. Therefore in the next study being fouled
was added into the outcome of shot section. The biggest problem with this study was
the turnovers did not all link up meaning the data was just random tallies; it did not
show the trends of each turnovers as a whole. Another setback with this study was if
the ball went out of bounds or a violation of the player was committed then the clock
would be stopped and this does not mean the outcome was directly from that
turnover. This was discussed in the study undertaken by Zarren (2010) in an NBA
report on the Boston Celtics turnovers shown in the Literature Review section. As a
result the data collection method will be changed. If the ball was dead resulting in
the clock being stopped then that would be the turnover outcome, not what follows
with the possession from the out of bounds ball.
3.4 Pilot study 3
Following on from this a last pilot study was carried out (see appendix C), named
pilot study 3. This study analysed a whole forty minute game of the UWIC Archers
Division 1 Women’s Basketball team during the 2009/2010 season again against
11
Brixton Ladies Topcats. The new system looked at trends to see how the turnovers
linked up as a whole.
In this last pilot study the structure was slightly different, this time the study only
focused on one team, the team chosen to look at was UWIC. The study showed the
turnovers UWIC committed, with positioning on court that they happened, which then
lead onto the outcome of Brixton’s offence after each turnover had occurred.
Firstly a key was made as a reference to refer back to. The hand notations were
done on a separate sheet. The plan/key had three sections. The first section was the
type of turnover again, each of the performance indicators were given a number at
the side. The second section was the position on court the ball was turned over. The
court was shown in a diagram and split into 8 equal parts. Each part of the front court
was labelled F1, F2, F3 and F4 and then the back quarter sections were labelled B1,
B2, B3 and B4. The last section of the three was again different outcomes of a
turnover; these were also numbered at the side of them.
Once this plan/key was set out the analysis of the game could now be undertaken.
As soon as a turnover was committed by UWIC, the type of turnover by the number it
has beside from the plan/key was recorded on the separate sheet. Next to this on
the same line, so that trends of the turnover could be seen, was the area on the
court the turnover was committed, e.g. F1, F2 etc, then finally the outcome. This was
done through a number again. The reason for using the number system was
because it became quicker to record the data, instead of having to pause the video.
This data was split into different quarters so it looked clearer and it would be easier
to be paused and come back to later, or if the DVD crashed the analysis would not
have to start from the beginning of the game again. There also might be trends
shown throughout each part of the game.
There were still problems with this study that needed to be changed for the final
experiment. These were:
12

When splitting up the court FR (Front right) would now be used to make it
easier. This change was made at half time.

Do UWIC gain control again?

Outcome: was the player fouled, were they shooting or not shooting.

Should a jump ball be classified as a turnover as possession depends on
which way the arrow is facing as UWIC may or may not get the ball back.
All of these things are to be taken into consideration when devising the final method
of the experiment. The main problem that seems to be occurring was the ability to
compare between games against top and bottom teams. This can be solved by
simply saying whether the outcome is positive or negative. This still shows the
outcomes too as this information will be helpful. Also, a few changes were made to
show the types of outcomes, for example being fouled.
3.5 Final system used
Therefore the final study (which is shown in the appendix D) looks at the Senior
Women’s Great Britain basketball team analysing the type of turnover, where this
turnover was committed on court, the outcome and if the outcome was positive or
negative. This information will then be compared to different teams in the division.
The comparisons will be made with top teams and bottom teams. This was found out
through the FIBA website. As they do not have current rankings due to last year
being a qualifying year, the top teams are those in Division A that finished first and
second in their group, unless there was 5 teams in the group instead of 4 and those
who finished third would also be in the top of the league teams. The bottom teams
were those who finished within the bottom two of their group. The top of the league
teams were Israel, Latvia, Bulgaria and Italy and the bottom of the league teams
were Portugal, Ukraine, Belgium and Holland.
The final method used for this study was similar to the last. There was a key/ plan to
refer back to again. These had the same sections:
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1. Type of turnover: 1. Missed shot (defensive rebound) 2. Interception of a pass
on court, 3. Block, 4. Violation- (anything which makes the clock stop e.g. time
regulation, double dribble, travel, back court, offensive foul, illegal screen).
2. Where on court the ball was turned over: Front right 1 (FR1), Front left 1
(FL1), Front Right 2 (FR2) Front left 2 (FR2) Back right 1 (BR1) Back left 1
(BL1) Back right 2 (BR2) Back left 2 (BL2). These were all shown on a key
with the sections the same as before split evenly, only now named differently,
a diagram of this is labelled and shown in appendix D.
3. Outcome of turnover: the same outcomes were written and numbers. These
were: scored shot, scored layup, attempted shot, attempted layup, missed
shot, fouled and shooting, fouled sideline ball, violation (when the clock
stops), out of bounds.
4. If the turnover was positive or negative: positive for Great Britain was if they
managed to get the ball back, causing the opposition to turn the ball over
through a steal or interception or forcing the opposition to travel etc an
violation. These were number 7 and 8 on the outcome list. The other way in
which a positive outcome for Great Britain occurred was if the shot or layup
were attempted but not successful and Great Britain gained the defence
rebound. Negatives were allowing a shot to be attempted and an offence
board and allowing another attempt, any score or fouling. Positives were
defined by a P and negative was defined by putting an N as shown in
appendix D.
3.6 Reliability study
Reliability measures the consistency or repeatability of test scores or data (Berg and
Latin, 2004), therefore this short study is going to repeat the same system twice and
see the differences. Once the final version of the hand notation system that was
created is used, the reliability of the study was tested. An intra operational study was
undertaken and percentage error of 5.7% was found. The test layout is shown in
appendix E and the data was input through tallies of watching the first game. The
range of accuracy is usually set by the researcher, which is usually less then 5%
error (Hughes and Frank, 2004), making the test not quite reliable.
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3.7 Data analysis
The last section that was undertaken throughout this experiment was the analysis of
the data. All the turnovers types with the different outcomes were input into Excel.
Games against top of the league and bottom of the league were kept in separate
columns. After this the data was grouped into the different types of turnovers that
lead to either positive or negative outcomes, again showing top and bottom columns.
All types of turnovers were then added together, and percentages of each were then
worked out.
As the test completed was ordinal data (could be ranked) the information needed to
be compared to find the differences. The applicable test for this study was the Mann
Whitney U. Numbers of all the top teams positive and negative for each of the four
turnovers plus violations were added to an excel sheet, and the same process was
used for bottom of the league. Once this was done, the data could now be
transferred in SPSS to perform the Mann Whitney U test. The test shows if the data
is significant or not (the p value) and the standard was set at 0.05.
15
Chapter four
Results
Results
Results were gathered through tallies of each turnover, recording teams placed at
top of the league and at bottom of the league tallies in separate columns. As the
study was about trends, instead of just tallying each turnover, the spreadsheet
showed the turnover and also its outcome. A Man Whitney U test on SPSS was also
performed to see if any of these had a significant difference between games against
the top of the league and bottom of the league in any of the four types of turnovers.
The data first analysed shows the type of turnovers committed in all 8 games. The
pie chart (figure 1) below shows the most frequent type of turnover committed was
missed shots with 150 instances. The second highest type turnover was through bad
passes which was 60. The next two were similar, these were violations with 48 and
fumbles/steals which was 44. Then there were 23 blocked shots during all the games
analysed.
48
Missed Shot
23
Bad pass
150
Fumble/steal
44
Blocked shot
Violation
60
Figure 1. Pie chart of all turnovers throughout the 8 games
Percentages of all the different types of turnovers were worked out through a simple
equation knowing throughout the 8 games there were a total of 325 turnovers. The
equation was: amount of turnovers / total amount of turnovers x 100. The end results
showed that 46% of all turnovers came from missed shots, 18% was through a bad
pass, 14% came from fumbles or steals of the opposition, 7% which was the least
16
amount were blocked shots, and lastly 15% were from violations (this is defined in
the Method section 3.5 Final System Used).
Figure 2 below shows the differences in all the type of turnovers from bottom of the
league and top of the league and if the outcome was positive or negative. The X axis
shows the type of turnover and whether it was positive or negative, the blue being
the top of the league and the red being the bottom. It shows from the 9 different
types of turnover categories 5 of the 9 in bottom of the league games had higher
turnover rates. These were: both positive and negative outcomes of missed shots
(meaning a lot more missed shots happened when Great Britain were playing
against the lower league teams), bad passes leading to a positive outcome, although
this was close between the teams, as there were very few fumbles or steals leading
to a negative outcome and blocked shots leading to a negative outcome. The data
showed that teams at the top of the league had higher turnovers rates in bad passes
leading to a negative outcome, fumbles and steals leading to a positive outcome,
blocked shots leading to a positive outcome and violations.
60
Frequency
50
40
30
20
Top
10
Bottom
0
Missed
Missed Bad pass
Bad
Fumbles/ Fumbles/ Blocks
Blocks Violations
shots
shots leading to passes
steals
steals leading to leading to
leading to leading to negative leading to leading to leading to negative positive
negatives positive outcome positive negative positive outcome outcome
outcomes
outcomes outcome outcomes
Figure 2. Positive and negative outcomes of each performance indicator
Calculations of each turnover are given in the excel spread sheet which can be
found in the appendix E overall there were more turnovers from games against
17
teams placed bottom of the league, this was 179 compared with games against
teams higher in the league which was 146. From these 146, 36 outcomes were
positive and 110 outcomes were negative and with the games against bottom of the
league, 129/179 were negative and the other 50 had positive outcomes.
In figure 3 below it is shown that the most frequent outcome from a missed shot is
related to field goals, this was in games against bottom of the league teams. It shows
that missed shots leading to fouls that were not shooting or an out of bounds ball
were similar for games against top of the league and bottom. Games against top of
the league led to more outcomes of fouls that were shooting fouls. The overall
positive outcomes from missed shots were 19 for games against top of the league
and 37 for teams against bottom of the league.
30
Frequency
25
20
Top
15
Bottom
10
5
0
Missed Shots Missed Shots Missed shots Missed Shots Missed shots
Leading to
Leading to leading to out Leading to
leading to
scored field fouls shooting of bounds fouls sidleline offensive
goals
or endline
rebounds
Figure 3. The different types of negative outcomes of missed shots.
Figure 4 shows the negative outcomes from bad passes. As shown below it is clear
the biggest trend of outcomes leading from a bad pass is to an out of bounds ball.
Overall there are more bad passes against top of the league teams than bottom of
the league teams. More fouls were given away in games against top of the league,
after the turnover of a bad pass. Positive outcomes of a bad pass from games
18
against top of the league were 7 and against bottom for the league 8. The results
were similar between the two.
14
12
Frequency
10
8
6
Top
4
Bottom
2
0
Bad passes Bad passes Bad passes Bad passes
Leading to Leading to leading to leading to
scored field
fouls
out of
fouls
goals
shooting
bounds sidleline or
endline
Bad passes
leading to
offensive
rebounds
Figure 4. The different types of negative outcomes of the bad pass.
Figure 5 underneath clearly demonstrates for the most common trend for negative
turnovers via a steal or fumble comes from games against bottom of the league, with
fumbles/steals ending in an out of bounds ball. As there is a spread between the
outcomes of the games against the top of the league teams there is no real trend
shown. Also, although there is an equal spread of outcomes across the board of
games against top of the league there are still more occurrences of fumbles/steals in
games against bottom of the league. There were 4 fumbles and steals that had
positive outcomes for games against top of the league and 3 for games against
bottom, again showing not much difference.
19
Frequency
16
14
12
10
8
6
4
2
0
Top
Bottom
Fumbles/ Fumbles/ Fumbles/ Fumbles/
steals
steals
steals
steals
Leading to Leading to leading to leading to
scored field
fouls
out of
fouls
goals
shooting
bounds sidleline or
endline
Fumbles/
steals
leading to
offensive
rebounds
Figure 5. The different types of negative outcome from a fumble or steal.
Figure 6 demonstrates the negative outcomes from blocked shots. There were a lot
less blocked shots throughout the games against top of the league teams. There
was not one most common result from a blocked shot as games against bottom of
the league had four outcomes which had the same amount of tallies. For blocked
shots that lead to positive outcomes there were 6 against top of the league and 2
against bottom of the league teams.
4
Frequency
3
2
Top
1
Bottom
0
Blocks
Blocks
Blocks
Blocks
Blocks
Leading to Leading to leading to leading to leading to
scored field
fouls
out of
fouls
offensive
goals
shooting
bounds sidleline or rebounds
endline
Figure 6. The different types of negative outcomes from a blocked shot.
20
The area of the court turnovers were committed was also recorded. It is shown
overall most turnovers came from front left 1, so underneath the oppositions basket
on the left hand side. There were few turnovers in the back court but there were
more against top of the league teams. This meant that the majority of turnovers were
committed in the front court. There was no big difference between top and bottom of
the league teams and the results showed turnovers occurred in similar places.
Throughout the 8 games there were 112 turnovers committed within the FR1 area,
39 turnovers within the FR2 area, 124 turnovers in the FL1 area, 29 turnovers in the
FL2 area and 18 turnovers in the back court. There was no significant trend as to
which position turnovers were committed in the back court as there were few. The
diagram of the court is shown below in Figure 7.
FL1
FR1
Attacking half
FL2
FR2
BL1
BR1
Defensive half
BL2
BR2
Figure 7. Diagram of basketball court sections defined in this study.
21
The data analysis done through SPSS analysed the types of turnover, except
violations as this will always be negative data, top and bottom of the league teams
and whether the outcome was positive or negative. Two types of turnover showed a
significant different and two didn’t. The two types of turnover done were shown as
significant were fumbles/steals and bad passes. Obviously making missed shots and
blocks as no significant differences.
As shown in the table below the maximum amount of turnovers came from missed
shots at 55, which were all the missed shots that lead to a negative value against
bottom of the league. The lowest value was 2, this was the amount of blocks that
happened against top of the league which negative outcomes and it was also the
value that had positive outcomes from games against teams placed bottom of the
league.
Table 1. Mann Whitney U descriptive statistics
Performance
N
Mean
Std. Deviation
Minimum
Maximum
Missed Shots
4
37.5000
14.73092
19.00
55.00
Bad Passes
4
15.0000
9.41630
7.00
27.00
Fumble/steal
4
11.0000
8.90693
3.00
21.00
Blocked Shot
4
5.7500
5.18813
2.00
13.00
League
4
1.5000
.57735
1.00
2.00
indicator
placing level
Table 2 shows the outcomes from the Mann Whitney U test, this will give the data a
statistical difference rather than just showing a difference like the figures above, still
comparing games against top and bottom. This shows Z (the significant difference)
the difference of bad passes and fumbles/steals between the two different levels of
teams. Bad passes the difference was with games against top teams having more
whereas games against bottom teams forced more fumbles/ steals. Missed shots
and blocked shots did not show a significant difference but as the cut off for this (the
p value) was 0.05 and the significant value for blocked shot was only 0.4 and missed
22
shots 0.8 they are not too far from the p value. As violations did not have a positive
of negative outcome there were not inputted to perform the Mann Whitney U test, as
all violations will mean turnover in possession and the clock stopped so the outcome
of the next possession is not directly linked in the possession.
Table 2. Statistics of the Mann Whitney U
Missed Shots
Bad Passes
Fumble/steal
Blocked Shot
Mann-Whitney U
1.000
2.000
2.000
1.500
Wilcoxon W
4.000
5.000
5.000
4.500
Z
-.775
.000
.000
-.408
1.000
1.000
.683
1.000a
1.000a
.667a
Asymp.
Sig.
(2- .439
tailed)
Exact Sig. [2*(1- .667a
tailed Sig.)]
23
Chapter five
Discussion
Discussion
It has been proven that performance analysis can improve sporting performance. By
recording and analysing a game it can be seen more clearly and looked back on to
see if anything was missed. The recording can be put into slow motion and looked at
in more detail in order to improve performance.
The main aim of this study was to determine if the quality of opposition had an effect
on turnovers and their outcomes. This was accomplished through producing results
which showed differences in each type of turnover in relation to the levels of
opposition. The study also aimed to show trends between turnovers and whether a
specific turnover led to a certain outcome. This was shown through figures in the
results section. It showed each type of turnover recorded and the resulting outcome,
allowing the study to show the opposition effects on a team’s performance.
The study had three hypothesises. The first was to determine if the quality of
opposition had an effect on a team’s turnover numbers. The second was to establish
which area on the court most turnovers came from. The third hypothesis aimed to
discover which games had more positive outcomes.
Hypothesis one was rejected. More turnovers overall came from teams placed lower
in the league and most of these were a result of missed shots. This was not
expected as it was thought teams would play worse against top of the league teams
as they of a higher quality. Most turnovers did come from missed shots with a total of
150 out of 325.
There were a lot more missed shots against lower level teams. This could be
explained by the fact they were open to take a lot more shots against teams placed
lower in the league. This could be proved by doing a further study and calculating the
percentages of missed and made shots. The strength of the defence may have been
a factor when looking at the missed shots. The aim of a good defence is to not let a
shot be taken unless it is uncontested (Wissel, 2004). This may mean that the
defence putting pressure on the shooter may be a reason for a lot more missed shot
attempts. Another possible reason for more turnovers coming from missed shots was
the types of defence the opposition played. Wooten (2003) explains how zone
24
defences are put in place to clog up they key and to not allow post moves, forcing
the shots to take more long distance attempts. When they opposition played a zone
it was seen there were a lot more turnovers committed. The new court markings also
may influence the missed shots. FIBA (2008) are making teams change their court
markings starting in October 2010. So therefore at this stage some teams have
changed and some have not. The Great Britain home games were not played with
the new court markings where as some of the games played away had the new
markings. This may affect missed shots as the 3 point line is further out and the
spacing on the court is different. This could result in players taking longer shots
without realising.
Another reason for having worse performances against lower quality opposition may
be the squad rotation of the coach. If the coach starts with their strongest team and
they give the team a good lead then the coach can afford to play their lower ability
players who may turn the ball over more. This relates to the study of Gomez (2009)
which is discussed in the literature review. The study compared individuals rather
than the whole team, looking at the performances of the starting players on the team
against those who come off the bench. This could be another factor when deciding
the cause of turnovers.
A further factor relating to a team playing worse against worse teams is researched
by Kostopoulos and Dimitrios (2010). The study was done on ninety male players of
eight teams, within two different basketball senior divisions. The study focused on
injury incidence between training and games and found in high level teams there
were higher incidence of injuries during games. Overall, 37% of the higher teams
were involved in injuries through the course of the season. Injury is a factor that
could have influenced the games. This could be a reason for performing worse
against lesser ability teams. The team could have had injured players who were key
to their performance. As Great Britain is of an elite level there may be an increase in
the likelihood of a player on the team being injured. This is especially possible given
with the amount of league and warm up games the team played throughout the
summer. The team also had a number of trials and training sessions. These are all
factors that could results in a higher chance of losing a player to injury.
25
Tucker (2009) wrote an article on the NBA team the Los Angeles Lakers overcoming
their struggle with losing or being involved in close games against lower ability
teams. The article explained in recent games that the team have had a lack of
defensive intensity, lack of commitment to playing at full potential, a frustrating
tendency to play down to their opponents' level and an inability (or unwillingness) to
put lesser teams in their place. He believed this was down to lack of focus of the
players. This could have been caused by the players assuming the team is going to
win before the game starts resulting in them being overly confident. This is an issue
for the coach to address. The coach needs understand what technique will keep his
players motivated before a game. A team being overly confident could be
researched further in a future study through sports psychology and questionnaires
before games that measure confidence levels.
All of these factors may or may not be relevant to Great Britain. The article is
relevant for Great Britain games as it shows possible reasons for performing at a
lower level against worse teams. The result of this could be lowering to their level of
the opposition rather than playing at your own.
All the factors that have been highlighted may have affected Great Britain’s
performance. A team may have started poorly and improved throughout or started
well and lost players due to injury. These are all things that can be taken into
consideration with more in depth research and looking at the other teams and their
own statistics and squad. This can be done through getting footage of other teams’
games and scouting their main players. Performance analysis can also be used to
analyse the oppositions’ performance rather than just you own team.
Hypothesis two expected that most turnovers would be committed in the front court.
This statement was accepted. The area of the court which had the most common
turnovers was the front left underneath the basket. There was a slight difference
between the left and right hand side of the court with more occurrences of turnovers
on the left hand side. This could be because predominately people are right handed
and the most turnovers came through missed shots. This could have been because
on the left hand side of the court is players were attempting layups or under the
basket shots with their weaker hand. As a result of this the shot is less likely to be
26
successful than on the right hand side of the court when a player is more likely to be
shooting with their dominant hand. If this study was to be repeated the sections of
left and right would still be used as they showed to be a factor and gave an area for
teams to improve upon. Also, to make the study more of effective the type of shot
could be added. This would show what type of shot for was taken and as an example
could be broken down into the groups lay up, 2pt jump shot and 3pt jump shot. This
will show the areas that most need to be improved upon in order to have a more
effective offense. It will also show which type of shot is most likely to lead to a
defensive rebound which is the type of turnover the team will be attempting to avoid.
Hypothesis three stated that the percentage of positive outcomes would be higher
against bottom of the league teams than in games against top of the league teams.
The results showed that against top of the league there were 36 positive outcomes
and 110 negative outcomes resulting in 25% positive outcomes and 75% negative
outcomes. The games against bottom of the league showed that there were 50
positive outcomes and 129 negative outcomes with results of 28% positive outcomes
and 72% negative outcomes. This proves the hypothesis true. There was a slight
difference in positive percentages showing 3% more in games against placed bottom
of the league.
An aim of the study stated in the introduction was to look at trends of the turnover.
This was to see if there was a specific outcome to a particular type of turnover. One
of the strengths of this study was the fact it looked at a direct outcome from the
turnover and once the clock was stopped it was seen as a new possession. This
allowed the study to discover specific trends.
The trends of missed shots showed that the main outcome was leading to a scored
basket by the opposition. Missed shots leading to field goals as the major outcome
could be done to lack of transition defence after a shot. Transition defence is when
changing from playing offence to defence and there must be communication from all
five players in order to protect the basket (Krause, 1991). One player must engage
the player with the ball to try and slow the ball down and the other players should
27
focus on protecting the basket. Although the study does show the direct outcome of
a score, it does not show whether an outcome was the result of a fast break and
having an advantageous situation or in a normal offence and scoring a basket from
it. To advance this study even more a factor such as if the shot was contested or
uncontested could be looked at. This will allow us to see if the defence of the team
gets back in time to force the offence to set up instead of an advantageous situation
of a fast break.
Bad passes and fumbles or steals main outcome was an out of bounds ball. There
were more bad passes from teams against bottom of the league, shown in figure 2.
As for fumbles or steals there was not much of a difference between top and bottom
placed teams. Fumbles or steals also mainly lead to the ball going out of bounds.
There were a lot of fumbles from not fully securing a rebound which lead to the ball
going out of bounds. Also, bad passes in general were thrown out of bounds. Timing
and accurate passes are needed to make a successful pass and also knowing when
and where to pass under pressure reduces interceptions (Wissel, 2004). Another
factor that influenced the passing was the type of defence. Full court zone presses
are put in place to trap and double team players to make the offensive player make a
decision (Krause et al., 1999). The aim of this it to make the offensive players fumble
the ball or made a bad pass hence why the ball may have been thrown out of
bounds. It was seen during the analysing the game that when there was full court
pressure from the defence longer passes were made and if you are throwing a pass
a longer distance it becomes less accurate. Fumbles and steals may also have been
caused by the defence. The main aspect that was picked out from the video as to
where they came from was whilst contesting rebounds. This may be because the
opposition are very good at making contact to not allow catches on offensive
rebounds. The height of the opposition when rebounding may also be a factor that
could have influenced the team to fumble the ball.
Blocks did not have on particular trend, this may have be because there were very
little blocked shots and the data may not have been a large enough sample to
determine if there was a trend in this area. To improve the data more games could
be looked at in order to see if a trend did occur. It was shown that against top of the
28
league teams the outcome did not lead to any type of foul. This shows a positive for
the team that after they got blocked they did not allow a foul.
From the literature review there was an expectation that turnovers had an influence
on performance. Turnovers were used as a performance indicator for other studies
but the turnovers were not looked at in as much detail as this study. This study
showed the type of turnovers committed and the outcomes from the specific types of
turnovers. Relating back to the literature review, Nemeth (2002) made the statement
that statistics show that 85% of turnovers lead to a score. This did not prove true in
this study as bad passes and fumbles or steals main outcome was to be an out of
bounds ball. In total there were 33 missed shots that lead to field goals, 13 bad
passes, 10 from fumbles and steals and only 4 from a blocked shot making a total of
60 turnovers that lead to field goals. This was only 18% of the turnovers overall.
Ibáñez, et al. (2008) believed that the quality of opposition did not make a difference
when looking at turnovers and found no correlation. Sampaio (2010) believed that in
some quarters it did make a different to the score line. The results of this study found
there was a difference between the league position of teams played against and
turnovers. Sampaio’s study found the two most significant factors to be steals and
blocks, where as this study found the two most significant factors to be bad passes
and fumbles or steals. This shows part of this study agrees with Sampio (2010) study
but not with Ibanez, et al. (2008). A possible reason for this is that this study did not
focus on the score line and maybe something that could be researched further in a
future study.
Tiernan (2009) found that turnovers were the biggest factor within a basketball game
when determining if a game is won or lost. The results of this study looked at top and
bottom teams but if the study was focused on wins and losses the outcomes may be
different. This is significant because it is possible Great Britain may have lost to
bottom of the league teams and won against top of the league teams. Possible
reasons underperforming against weaker teams have been discussed earlier. A
study which looks at won and lost games may better show a correlation between
turnovers and winning.
29
If this particular study was repeated next time all the points (scores) of a turnover
would be recorded to find the exact amount of points given away directly from
turnovers. This would be more accurate than just recording field goals and fouls
shooting and this would enable the coach to see how many points are being given
away through their teams players own mistakes. This would make the coach keen to
stress the importance of making good decisions and not committing errors. Another
improvement that could be made to this study would be to record if the foul shots
were missed or made. Again, this would show how many points come as a result of
the turnover.
A weakness of this study was the amount of data collected. As it only looked at a
specific year there was not a lot of games to choose from, therefore the study
decided to look at both friendly games and competitive league games. Practice
games are put in place to get players in a competitive environment in order to see
what they need to improve (Giannini, 2009). The games against lower teams tended
to be friendly games and this could have been an influencing factor on performance.
In friendly games teams may look at practicing more, running through set plays that
have not been executed properly yet and allowing new players to come together who
are not used to playing together and the styles of play. An example would be for post
players who like to play in different ways. Different players prefer to receive the ball
in different positions and in different ways.
5.1 Future research
As shown above a key factor when looking at reasons for turnovers occurring is
defence. The ball pressure of the opposition, the physical build and the type of
defence they play. With the court markings, home advantage may be a factor when it
comes to affecting a team’s performance within turnovers. A study which looks at
home court advantage is Sampaio, Ibanez, Gomez, Lorenzo and Ortega (2008).
They did a study that looked at the effects home court advantage has on players
who play different positions on a basketball court. Results showed that it did affect
some of the ways that players played compared with away games but this may have
been down to preparation for the game (Sampaio, et al. 2008). Preparation for a
game could be the disadvantage of having to travel to an away game etc. This
30
seems to be the main influence that has been looked at by researcher. Another
factor of home court advantage is the crowd but these factors are more prominent at
a higher level. It is probably more important at a high level because teams will have
further to travel and there are likely to be larger crowds. A possibility is a team will
have to take flights which could cause jet lag if they have not adjusted to their new
time zone or more likely general tiredness from being away from home. In higher
level competitions there will crowds for the games but this is more of a factor for
competitive games rather than the friendly warm up games.
There are many other factors which can affect performance such as referees and
officials. It was seen in some games that a lot more fouls were called, resulting in
teams getting in foul trouble early on. This could vary between referees and change
the outcomes of the turnover. Rodenberg and Chong (2009) looked at the impact of
referees on a game of basketball by analysing 654 NBA (National Basketball
Association) games. The study covered 77 different referees over a seven season
period. 574 of the games were regular season games and 80 were from play off
games. Through this study there were no obvious findings that one specific referee
had been biased towards the Dallas Mavericks as this is the team that was focused
on. The study wanted to know whether the referee influences a team performance
through being biased and if it was more likely a referee would be biased during
playoff games rather than the regular season. Results found that over the regular
season there were no officials that were seen as biased against the Dallas
Mavericks. However, in playoff games which were more meaningful one official was
seen to be biased against the Dallas Mavericks. This could mean referees may be
biased towards a certain team which may have an influence on the game.
31
Chapter six
Conclusion
In conclusion, most turnovers seemed to occur against bottom of the league teams,
showing half of hypothesis one to be true, and half rejected. The half that was
rejected was the statement teams that are higher placed in the league will allow
more turnovers than those placed lower in the league. The half that was proved true
was that most turnovers came from missed shots. The turnovers came mainly during
games against lower placed teams. As Tucker (2009) describes it has been known
teams play down to the level of their opposition, rather than competing at their own
level. There are other explanations shown in the discussion such as being overly
confident. As the study looked at the whole team and not individuals there may have
been more bench players on court in these games and also potential injuries to key
players within the Great Britain team or opposition.
The second hypothesis was accepted. Most of the turnovers came from within the
front court. Although there was not a big difference between the two front sections
(FR1 and FL1), the area that had the most turnovers committed in was the Front Left
1 sector underneath the basket. There were 12 less turnovers within the Front Right
1 sector. This is because the highest amount of turnovers are caused by a missed
shot and most missed shots are rebounded under the basket. This is an area the
Great Britain team to improve on.
The last hypothesis was that the percentage of positive outcomes would be higher
against lower placed teams in the league. This statement proved to be true. There
were 28% positive outcomes during games against the bottom of the league and
25% positive outcomes against the higher placed teams in the league.
During the eight games that were analysed there were 325 turnovers. The highest
amount of turnovers came as a result of a missed shot with almost half at 46%. The
lowest amount of turnovers came from blocked shots which was only 7%.
The trends that were shown in the study were that the main outcome a missed shot
was a field goal by the opposition. The main outcome from fumbles or steals and bad
passes was the ball going out of bounds. There was no real trend of outcome from a
turnover via a blocked shot.
32
It was seen the main area on the court which turnovers came from was the front
court but some came in the back court also. There was a significant difference
between the placing of teams in a league in bad passes and fumbles or steals. The
other two types of turnovers (missed shots and blocks) that were not shown as
having a significant difference between top and bottom of the league teams were not
very far away from the required p value showing they were not far away from being
significant too.
If a future study was to be undertaken it would change slightly. It would take the
score line into consideration instead of the level of the teams played against. This
would allow the study to compare the compare the amount of points resulting from
turnovers to the final score of the game. There are other factors that could be taken
into consideration on top of this which could include referees of each game, home
court advantage, individual statistics and injuries as these may have an effect on a
team’s performance.
33
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Appendix