Sports Coaching – Page 36 – The Sport Journal

An Exploration of State and Trait Anger, Anger Expression and Perfectionism in Collegiate Springboard Divers

Submitted by: Jacob Sinclair, Daniel R. Czech, A. Barry Joyner & Barry A. Munkasy

Abstract

The purpose of this study was to examine the relationships between the
dimensions of perfectionism and various aspects of anger, such as state,
trait, and the expression of anger, for collegiate springboard divers.
The role of gender was also investigated. Forty women and 19 men were
administered the State-Trait Anger Expression Inventory-2 (STAXI-2; Spielberger,
1999) and the Frost Multidimensional Perfectionism Scale (F-MPS; Frost,
Marten, Lahart, & Rosenblate, 1990). Data analysis showed no significant
differences between genders for any scales or subscales of anger or perfectionism.
State anger and its subscales were not significantly correlated with any
subscales of perfectionism. Anger expression scales were not found to
be significantly correlated with the subscales of perfectionism. Only
trait anger, and the subscale trait anger/ angry reaction, were found
to have significant relationships with the concern over mistakes dimension
of perfectionism. The perfectionism personal standards subscale was also
correlated with trait anger/ angry reaction.

Introduction

Many athletes strive to reach the highest levels of competition possible.
Competitors dream of the perfect game, performance, or skill execution
required of sport. Much time is invested into practice, conditioning,
and competition to provide athletes the best opportunity for a quality
experience. With such emphasis placed on attaining so difficult a goal,
resulting failures are to some extent inevitable. Individuals who exhibit
qualities characteristic of the construct “perfectionism”
may be significantly affected by these failures. How people experience
and react to failure is directly associated with the level and type of
perfectionism possessed. Those who demonstrate more adaptive perfectionistic
reactions to failures are more likely to express positive, or success
oriented, thoughts about sport. Those whose reactions align with maladaptive
perfectionism likely will exhibit negative, or failure oriented, behaviors
following failure in sport (Frost & Henderson, 1991; Hamachek, 1978).

The most common components present in the various definitions of perfectionism
are the engagement of actions and behaviors that lead to the setting of
exceptionally high standards for the purpose of being the best in a chosen
endeavor. These actions are often accompanied by highly self-critical
evaluations by the perfectionist (Burns, 1980; Frost, Marten, Lahart,
& Rosenblate, 1990; Hill, Zrull, & Turlington, 1997; Lombardi,
Florentino, & Lombardi, 1998).

Hamachek (1978) has characterized perfectionism as either normal (adaptive)
or neurotic (maladaptive). According to him, adaptive perfectionists are
those who set extremely high personal standards, are highly motivated
to do their best on every task attempted, experience pleasure while working
hard, and are able to recognize weaknesses which enable the individuals
to perceive themselves as successful, even when those high standards are
not met. In contrast, maladaptive perfectionists are characterized as
those who set unrealistic and inflexible goals, are driven by an intense
fear of failure, are extremely self-critical, and are unable to experience
satisfaction from accomplishments.

To measure perfectionism, a number of scales have been constructed (Anshel
& Eom, 2002; Burns, 1980; Garner, Olmstead, & Polivy, 1983; Randolph
& Dykman, 1998), two of which have been used the most consistently:
The Hewitt and Flett Multidimensional Perfectionism Scale (HF-MPS; Hewitt
& Flett, 1991) and the Frost Multidimensional Perfectionism Scale
(F-MPS; Frost, Marten, Lahart, & Rosenblate, 1990). The HF-MPS measures
three dimensions of perfectionism: Self-oriented perfectionism, other-oriented
perfectionism, and socially prescribed perfectionism. The F-MPS examines
an overall perfectionism score, and six independent dimensions of perfectionism:
Concern over mistakes, personal standards, doubts about actions, parental
expectations, parental criticism, and organization.

Perfectionists, maladaptive and adaptive, require that certain standards
for themselves, others, and situations be met. When results are not perceived
to be adequate by the perfectionist, an emotional response may be elicited.
One such emotion is anger (Saboonchi & Lundh, 2003). Anger can be
described as a state emotion, or as a trait personality characteristic.
Spielberger, Jacobs, Russell, and Crane (1983) have conceptualized state
anger as the experience of negative feelings similar to being annoyed
or irritated, or to a greater extent, filled with rage. During this experience,
the autonomic nervous system can become aroused to different degrees depending
on the situation. Spielberger et al. describe trait anger as how frequently
state anger is experienced.

An exploration of perfectionism and anger by Hewitt and Flett (1991)
was one of the first to examine how these constructs may be related. Using
data from 91 university students, the study concluded that self-oriented
and socially prescribed perfectionism were correlated with anger, with
socially prescribed perfectionism being more strongly related. These results
were inconsistent with Saboonchi and Lundh (2003) who found that in a
randomly selected sample of adult men and women with a mean age of 37
years, self-oriented perfectionism had a weak correlation with anger,
but other-oriented and socially prescribed perfectionism had no significant
relationship. This study concluded that anger in perfectionists was manifested
more so because of high goals not being achieved, than by any perception
regarding treatment by others. The age difference in the samples may have
confounded these results, as evidenced by another study (Hewitt et al.,
2002) using children which resulted in dissimilar conclusions. Unlike
earlier research, this study found no correlation between self-oriented
perfectionism and anger, but did indicate a relationship between socially
prescribed perfectionism and aspects of anger. This type of perfectionism
was shown to be positively correlated with outward expressions of anger
and negatively correlated with actions indicative of anger suppression.
This lack of a relationship between self-oriented perfectionism and anger
may be explained by children not holding themselves as accountable for
their actions as an adult might, and instead, lashing out at others who
are perceived to be placing unfair perfectionistic demands upon them.

The results of these studies, albeit somewhat inconclusive, do provide
evidence that socially prescribed perfectionism may have a slightly stronger
relationship with anger than with other dimensions of perfectionism. This
interesting association has seemingly been unexplored within the realm
of sport, despite consistent findings of perfectionism in athletes (Owens
& Slade, 1987) and an association between poor performances precluded
by high goal setting and anger (Fazackerley, Lane, & Mahoney, 2004).

Recently researchers began to examine perfectionism, anger, and sport
collectively. Valance and Dunn (2002a), using their newly developed sport-specific
version of the Frost Multidimensional Perfectionism Scale (Frost, Marten,
Lahart, & Rosenblate, 1990), found that with adolescent ice hockey
players, trait anger was highly correlated with the subscales concern
over mistakes and perceived coach pressure. Perceived coach pressure,
a subscale of the sport oriented version of the F-MPS, is similar to the
parental expectations subscale of the F-MPS. The results of this study
demonstrated a significant relationship between maladaptive perfectionism
and trait anger. A follow up study examining state anger and perfectionism
implemented a situation criticality variable. Youth ice hockey players
were measured for perfectionism and state anger in two scenarios which
had different degrees of criticality to the outcome of the competition.
The results indicated that maladaptive perfectionists had higher state
anger and experienced greater levels of anger following mistakes than
adaptive perfectionists during competition, particularly during a critical
time period. The study also concluded that situation criticality, or the
extent to which a situation within a competition is perceived as critical
to the outcome, was positively correlated with emotional responses during
competition (Vallance & Dunn, 2002b).

An aesthetic sport such as springboard diving has innate characteristics
that focus on attaining perfectly executed performances. As a subjectively
scored athletic event, there is a set “perfect” score, for
which divers aim. It is plausible to believe that this standard may draw
competitors in this sport towards perfectionistic thoughts and behaviors,
which in turn may lead to situations conducive to experiencing greater
levels of anger and anger expression. If an athlete who experiences anger
consistently while engaged in sport can become more aware of how that
anger may be stemming from maladaptive perfectionism, a greater understanding
regarding the ensuing dysfunctional beliefs and actions may be attained.
This may lead to a greater control over anger, more appropriate expressions
of anger, and potentially, performances that are less affected by experiences
of anger.

Statement of Purpose

The primary purpose of this study was to examine the relationships between
the concern over mistakes and personal standards dimensions of perfectionism
with the various scales and subscales of anger, as measured by the State-Trait
Anger Expression Inventory-2 (STAXI-2; Spielberger, 1999). Secondary purposes
were to: a) examine how the parental criticism and parental expectations
subscales of perfectionism relate to state anger, trait anger, and anger
expression, and b) to explore how gender relates to the perfectionism-anger
relationships.

Methodology

Participants

Fifty-nine springboard divers, 19 men and 40 women, from varsity collegiate
teams throughout the United States participated in this study. The divers’
ages ranged from 18-26 years, had competed the previous two years, and
had a minimum of two years competitive experience. Competitive experience
was operationally defined as a minimum of six United States Diving sanctioned
meets or six NCAA Collegiate meets per year.

Instrumentations

The Frost Multidimensional Perfectionism Scale (Frost, Marten, Lahart,
& Rosenblate, 1990) was used to assess the dimensions of perfectionism.
This scale consists of 35 items that use a five-point Likert scale ranging
from 1 (Strongly disagree) to 5 (Strongly agree). The scale measures overall
perfectionism and six independent dimensions of perfectionism. The subscales
are concern over mistakes (CM), personal standards (PS), parental expectations
(PE), parental criticism (PC), doubts about actions (DA), and organization
(ORG). The CM subscale measures the extent to which an individual reacts
negatively to one’s own mistakes. PS measures the extent to which
a person sets high standards. The PE subscales indicates the strength
of an individual’s perceptions regarding his or her parents’
setting of high standards for the individual. PC is a measure of how a
person perceives criticism from his or her parents regarding their performances.
The subscales DA and ORG measure how satisfied or dissatisfied an individual
is with a performance or project, and how important order and neatness
is to an individual, respectively. For greater interpretation of the scores,
a directional scale was added by the primary investigator of this study.
This seven-point Likert scale measures how an individual feels perfectionism
affects his or her performance. Overall internal reliability for F-MPS
has been reported at .90 (Parker & Adkins, 1995) and has been concurrently
validated by Frost et al. with the HF-MPS (Hewitt & Flett, 1991) and
the Burns Perfectionism Scale (Burns, 1980). Frost et al. also demonstrated
a Cronbach’s alpha of .91 for this scale.

The State Trait Anger Expression Inventory-2 (Spielberger, 1999) was
used to measure trait anger, state anger, and anger expression. The STAXI-2
is a 57-item scale which uses four-point Likert scales. The first part
of the STAXI-2 is the state anger (SANG) scale. It consists of fifteen
items measuring how intensely an individual experiences anger during either
the testing period, or a time or situation specified by the test administrator.
For this study, the individuals were directed to indicate how he or she
generally feels during a competition or practice. The Likert scale for
the state anger scale ranges from 1 (Not at all) to 4 (Very much so).
The state anger scale consists of three subscales: state anger / feeling
angry (SANGF), state anger / feel like expressing anger verbally (SANGV),
and state anger / feel like expressing anger physically (SANGP). The second
part of the STAXI-2 is the trait anger (TANG) scale. This scale consists
of ten items measuring an individual’s proneness to experience angry
feelings. The Likert scale for this measure ranges from 1 (Almost never)
to 4 (Almost always). Two subscales are used to comprise the TANG scale:
Trait anger / angry temperament (TANGT) and trait anger / angry reaction
(TANGR). The final part of this inventory measures the ways in which an
individual expresses and controls anger. These scales consist of 32 items
using the same Likert scale as the TANG scale. The following scales make
up this final part of the STAXI-2: The anger expression-out (AX-O) scale,
the anger expression-in (AX-I) scale, the anger control-out (AC-O) scale,
the anger control-in (AC-I) scale, and the anger expression index (AX).
Like the F-MPS, and additional seven-point Likert directional scale was
added to measure how an individual feels anger positively or negatively
affects performance. The three primary components of the STAXI-2 have
been concurrently validated by Spielberger with various subscales of the
Buss-Durkee Hostility Inventory (Buss & Durkee, 1957), Minnesota Multiphasic
Personality Inventory (Hathaway & McKinley, 1967), Spielberger’s
(1979) State-Trait Personality Inventory (as cited in Spielberger, 1999)
and the Eysenck Personality Questionnaire (Eysenck & Eysenck, 1975).

Procedures

A packet containing a cover letter, the Frost Multidimensional Perfectionism
Scale, the State-Trait Anger Expression Inventory-2, informed consent
forms, directions for the administration of the surveys, and a self-addressed
stamped envelope, was sent to university teams. The letter included a
rationale for the study and the possible benefits to springboard diving,
in addition to information on the length of time necessary to complete
the scales. A requested return date was also noted in the cover letter.
The informed consent form addressed issues regarding an assurance of confidentiality
and anonymity. The information in the packet was to be read by those administering
the scales.

The diving programs were contacted by either phone or email prior to
receiving the surveys. The scales were administered primarily in the practice
facilities for each team. Data were also collected at a diving competition
from those individuals who met the prerequisites. In this case, the packets
were distributed at a pre-competition meeting and were to be returned
as soon as possible. Most were returned by mail several weeks later.

A reminder email was sent two weeks prior to the return date. Packets
were mailed a second time to those programs who had requested an additional
packet. Collection ceased soon after the deadline had passed.

Results

Multiple Pearson’s Correlation analyses were conducted to examine
the relationships between: a) the F-MPS subscales CM and PS with all scales
and subscales of the STAXI-2, and b) the F-MPS subscales PE, PE, DA, and
ORG with the STAXI-2 scales SANG, TANG, and the AX Index. Because there
were 35 correlations examined and 10 independent t-tests analyzed, the
alpha level was adjusted to p < .01.

The subscale CM resulted in two significant correlations. TANG showed
a weak, positive relationship (r = .374, r2 = .140, p < .01), while
TANGR (r = .490, r2 = .240, p < .01) demonstrated a moderate, positive
relationship. No other scales or subscales of the STAXI-2 were found to
be significantly correlated with CM, and only one other scale approached
significance; AX-I (r = .310, r2 = .096, p = .019). Results for all correlations
for CM are shown in Tables 1, 2, and 3.

For the F-MPS subscale PS and the STAXI-2 scales and subscales, only
one significant correlation surfaced. TANGR was found to have a weak,
positive relationship with PS (r = .408, r2 = .166, p < .01). Two other
STAXI-2 scales approached significance: TANG (r = .307, r2 = .094, p =
.019) and AC-I (r = .310, r2 = .096, p = .018). The correlations for PS
are shown in Tables 1, 2, and 3.

For all other correlations examined, only one was found to be significant
at the alpha level of p < .01. PE was found to have a weak, positive
relationship with TANG (r = .397, r2 = .158, p < .01) as shown in Table
4.

To examine the differences between genders for the F-MPS subscales CM,
PS, PE and PC, four two-tailed independent t-tests were utilized. These
independent t-tests, along with all others used in this study, had an
alpha level adjusted to p < .01. Results show no significant differences
between men and women for the above constructs. See Table 5.

Three one-tailed independent t-tests revealed no significant differences
between genders on SANG, AX-I, and AX-O. See Table 6.

For the STAXI-2 scale TANG, a two-tailed independent t-test again resulted
in no significant differences between genders. See Table 7.

The directional scales added to the F-MPS and the STAXI-2 surveys also
resulted in no significant differences between genders. See Table 8.

To examine the differences between the correlations specified in the
hypotheses, a Fisher’s zr transformation was utilized. However,
only a single transformation contained at least one significant correlation,
thus essentially nullifying any significant results for all others, of
which there were none. The one Fisher’s zr transformation that did
contain a significant relationship, CM and PS for TANG, also resulted
in a non-significant difference between correlations.

Discussion

The data analysis on the relationship between the perfectionism subscales
and SANG resulted in unexpected outcomes. Individuals who score highly
on the CM subscale have an increased focus on errors (Frost, Marten, Lahart,
& Rosenblate, 1990) and have a greater desire to self-present positively
to others (Hamachek, 1978). Because athletes fitting this criterion are
less able to remove negative athletic related images from his or her mind
(Frost & Henderson, 1991) it was hypothesized that SANG would be positively
correlated with CM. Additionally, Hewitt and Flett (1991) found a correlation
between socially prescribed perfectionism and a measure of anger, which
although not specified, appeared to be more closely related to state anger.
Socially prescribed perfectionism has been found to be significantly correlated
with CM (Frost, Heimberg, Holt, Mattia, & Neubauer, 1993) but unexpectedly,
CM was not found to have a significant relationship with SANG for the
current study despite its correlation with AX-I approaching significance
(r = .310, r2 = .094, p = .019). This may lead to the conclusion that
those who score highly on CM may experience angry feelings, but perhaps
not during diving practice or competition, as only the SANG scale of the
STAXI-2 (Speilberger, 1999) inquires about emotions coinciding with the
diving experience.

Examining the subscales of SANG, and the relationships present with the
CM and PS subscales of perfectionism, resulted in additional counter-intuitive
findings. Vallance and Dunn (2002b) found that maladaptive perfectionists,
or those who’s CM score was high, had significant correlations with
SANGF and SANGV. The current study’s hypothesis proved to be incorrect,
in that CM did not have a significantly stronger correlation with these
subscales than did PS. In fact, PS had a stronger correlation with SANGF,
although none of these correlations were significant at p < .01.

The final SANG subscale, SANGP, also resulted in relationships with PS
and CM that were not significant. It was presumed that participating in
a sport in which the participant is under water and out of view immediately
following a performance, in addition to having the opportunity to leave
the immediate vicinity of the competitive venue during a competition or
practice, would increase the incidence of a diver’s desire to express
anger in a physical manner. Examples of these expressions might be hitting
walls under water, clenching fists or other muscles, or slamming lockers.
However, this proved not to be the case, and may be due to the fact that
two of the five items of the STAXI-2 (Spielberger, 1999) which measure
SANGP describe acting violent toward “somebody.” The participants
of this study may have interpreted “somebody” as someone else
in the practice or competition setting. In springboard diving, this is
not socially acceptable, as it may be in a few other sports, and would
potentially result in greater negative consequences.

TANG, and its subscale TANGR, were found to have the greatest number
of significant correlations. TANGR was significantly correlated with both
CM and PS, with CM having a stronger relationship. These results were
not unexpected as it follows logic that those who are most concerned with
how they appear to others naturally might experience greater levels of
anger in frustrating situations, or following a negative evaluation. However,
it was unexpected that CM had a significant relationship with TANG, but
PS did not. Hewitt and Flett’s (1991) self-oriented dimension of
perfectionism, which is significantly correlated with PS, has been found
to be positively correlated with TANG, but socially prescribed perfectionism,
which correlates with CM, was not (Saboonchi & Lundh, 2003). Because
of these previous findings, it was believed that PS would have a stronger
relationship with TANG than CM. However, results of this study showed
the opposite. These findings demonstrate some support the premise that
springboard divers who are more concerned about mistakes and how a performance
is evaluated may experience a greater frequency of angry emotions than
those who are more concerned with eclipsing self-imposed standards.

The perfectionism subscales examining perceptions of parents also resulted
in interesting findings. TANG was found to be significantly correlated
with PE, however PC was not. It appears that within the springboard diving
community, anger may be experienced in greater frequency by those who
perceive parents as having extremely high standards imposed on him or
her, than by those who perceive parents as overly critical for not meeting
certain standards. Perhaps this is due to other emotions being elicited
by those with overly critical parents, such as sadness, apathy, or resignation.
More research is needed in this area for a greater understanding of this
dynamic.

Examining gender in the context of perfectionism, anger, and springboard
diving also brought about interesting findings. Based on previous literature
(Anshel, & Eom, 2002; Flett, Hewitt, Endler, & Tassone, 1995;
Frost, Heimberg, Holt, Mattia, & Neubauer, 1993; Gotwals, Dunn, &
Wayment, 2003; Saboonchi, & Lundh, 2003) it was believed that perfectionism
would not be significantly different between genders. The results of this
study supported conclusions drawn in earlier research regarding the similarities
between how men and women experience perfectionism. What was surprising
were the differences between genders for the various scales and subscales
of anger.

Results for TANG and gender were consistent with the findings of Spielberger’s
(1999) investigation. There were no significant differences between gender
and the two subscales of TANG. This was also true for SANG and its subscales,
despite Spielberger’s findings demonstrating significantly higher
scores for men than women on each construct. In addition to Spielberger
(1999), Forgays, Forgays, and Spielberger (1997) revealed results supporting
the belief that men and women experience anger differently.

One possible explanation for the incongruence of SANG scores between
the current study and those cited above is that for Spielberger’s
(1999) study, survey items were to address the participant’s state
at the time of the test administration in a controlled setting. The participants
used in this study were asked to recall and indicate how he or she generally
felt during a competition or practice. It is possible that while diving,
similar state anger emotions may be elicited between genders, regardless
of how state anger is experienced in a more controlled setting.

With regard to anger expression, it was hypothesized that women would
score significantly higher on the AX-I scale, and men would score significantly
higher on the AX-O scale. Results showed neither to be supported, with
women actually scoring slightly higher on AX-O. It is less surprising
that AX-I scores were not significantly different, as Spielberger (1999)
had similar results. However, the assumption in this case was based on
previous findings that women experience shame with greater frequency,
and that shame is positively correlated with AX-I (Lutwak, Panish, Ferrari,
& Razzino, 2001). It was thought that being an elite athlete on display
in an individual sport such as diving, may have lead to increased instances
of shame if the athlete were to perform poorly. If this were the case,
women may experience shame with greater frequency than men, thus leading
to a greater propensity for experiencing and suppressing anger, as measured
by the AX-I scale. It appears, though, that participating in springboard
diving is not sufficient enough to alter the extent to which men and women
typically experience and suppress angry feelings.

Interestingly, women did score higher on AX-O, although not significantly.
These results refute the findings of Spielberger (1999) that men scored
significantly higher than women on this scale, and are even more noteworthy
when juxtaposed with Forgays, Forgays, and Spielberger’s (1997)
conclusion that the outward expression of anger is a more distinctive
and significant event for women than men. It is possible that the lack
of significant differences within this sample may be due to the disparity
in the number of men and women participants, but greater research is needed
regarding the uniqueness of the similarities between genders for these
typically asymmetric constructs.

Overall, findings in this study produced unexpected results. The similarities
between genders prompts the need for future research on how springboard
divers differ with samples derived from other sport populations. The relatively
small number of participants and the difference in the number of men and
women who participated may have affected these findings. Having only 59
participants may have decreased the power for the correlations and independent
t-tests to such an extent, that few correlations and independent t-tests
resulted in significance. Despite this possibility, it may be that there
is an aspect of springboard diving that either draws in a certain type
of individual to participate, or fosters similar personality characteristics
through participation.

The lack of variability in this sample decreases the ability of the results
of study to be generalizable to individuals who participate in other sports.
Because of this, differences between team and individual sports should
be examined in future studies. There appears to be a very small amount
of research examining perfectionism and anger in an athletic setting and
comparisons between team and individual sport participants has not been
a focus. With social evaluation and individualized standards, cornerstones
of the dimensions of perfectionism, varying greatly between team and individual
sports, anger and perfectionism may prove to be experienced very differently
through participation in diverse settings. More research of this kind
may lead to a greater understanding of how the perfectionism-anger dynamic
is uniquely experienced in springboard diving.

Although not specifically scrutinized in the current study, there did
appear to be differences in scores between the normal population and springboard
divers. Greater research is needed comparing the relationships of anger
and perfectionism between these groups. Understanding how these populations
differ on these constructs may shed light on the presence of conditions
that lead to the formation of relationships between the various dimensions
observed in this study.

Finally, research that has a deeper focus on the trait anger-perfectionism
dynamic is needed. This study found the strongest and greatest number
of correlations between these dimensions, and understanding why this is
the case could prove to be useful. Perfectionism is also a trait characteristic
and examining the development of these qualities, and the ties between
them, could lead to greater insight into how they may be fostered or discouraged.

Table 1
Correlations for the F-MPS subscales Concern Over Mistake (CM) and Personal
Standards (PS) and the STAXI-2 scale State Anger (SANG) and subscales
State Anger / Feeling Angry (SANGF), State Anger / Feel Like Expressing
Anger Verbally (SANGV), and State Anger / Feel Like Expressing Anger Physically
(SANGP)

	SANG	SANGF	SANGV	SANGP
CM	.189	.139	.217	.120
PS	.209	.202	.160	.210

Table 2
Correlations for the F-MPS subscales Concern Over Mistake (CM) and Personal
Standards (PS) and the STAXI-2 scale Trait Anger (TANG) and subscales
Trait Anger / Angry Temperament (TANGT) and Trait Anger / Angry Reaction
(TANGR)

	TANG	TANGT	TANGR
CM	.374**	.187	.490**
PS	.307*	.123	.408**

**Correlation is significant at the .01 level (two-tailed)
*Correlation is significant at the .05 level (two-tailed)

Table 3
Correlations for the F-MPS subscales Concern Over Mistakes (CM) and Personal
Standards (PS) and the STAXI-2 scales Anger Control-In (AC-I), Anger Control-Out
(AC-O), Anger Expression-In (AX-I), and Anger Expression-Out (AX-O)

	AC-I	AC-O	AX-I	AX-O
CM	-.092	-.177	.310*	.135
PS	.310*	.113	.234	.136

*Correlation is significant at the .05 level (two-tailed)

Table 4
Correlations for the F-MPS subscales Parental Criticism (PC), Parental
Expectations (PE), Doubts About Actions (DA), and Organization (ORG) and
the STAXI-2 scales State Anger (SANG), Trait Anger (TANG), and the Anger
Expression Index (AX)

	PC	PE	DA	ORG
SANG	.178	.159	.035	-.078
TANG	.274*	.397**	.165	.031
AX	.179	.176	.030	-.054

**Correlation is significant at the .01 level (two-tailed)
*Correlation is significant at the .05 level (two-tailed)

Table 5
Results for independent t-tests for gender on the F-MPS subscales Concern
Over Mistakes (CM), Personal Standards (PS), Parental Expectations (PE),
and Parental Criticism (PC)

Subscale	Gender (Number)	Mean	Standard Deviation	Sig.(2-tailed)
CM	Men (19)Women (40)	24.7923.33	9.076.57	.483
PS	Men (19)Women (40)	26.6825.03	5.575.07	.260
PE	Men (19)Women (40)	13.7914.65	4.383.98	.455
PC	Men (19)Women (40)	6.958.20	3.923.09	.188

Table 6
Results for independent t-tests for gender on the STAXI-2 scales State
Anger (SANG), Anger Expression-In (AX-I), and Anger Expression-Out (AX-O)

Scale	Gender (Number)	Mean	Standard Deviation	Sig. (1-tailed)
SANG	Men (19)Women (40)	26.8924.40	8.778.10	.286
AX-I	Men (19)Women (40)	17.8917.26	4.563.44	.554
AX-O	Men (19)Women (40)	14.4214.56	3.664.22	.900

Table 7
Results for independent t-test for gender on the STAXI-2 scale Trait Anger
(TANG)

Scale	Gender (Number)	Mean	Standard Deviation	Sig. (2-tailed)
TANG	Men (18)Women (40)	17.2817.25	4.744.67	.983

Table 8
Results for independent t-tests for gender on the directional scales added
to the F-MPS (PERDIRECT) and the STAXI-2 (ANGDIRECT)

Scale	Gender (Number)	Mean	Standard Deviation	Sig. (2-tailed)
PERDIRECT	Men (18)Women (38)	1.33.76	1.331.73	.223
ANGDIRECT	Men (18)Women (39)	-.28-.62	1.021.31	.339

References

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U.S. Sports Academy2015-03-27T11:32:30-05:00March 4th, 2006|Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off

Are Physical Education and Sports Teachers in Turkey Trained Appropriately? : A Study of Basic Education Institutions

Submitted by: Hakan Sunay, Ph.D. and Surhat Muniroglu, Ph.D.

Abstract

Teaching physical education and sports activities are among the indispensable
occupations of our time. Sports, apart from being an occupation of entertainment
and free time, have also a function that develop health and contributes
joy and happiness to the participants’ daily lives. Physical education
and sports activities have become signs of contemporariness. In Turkey,
the average beginning age for children’s participation in many or
team or individual sport activities is between ages 8 and 12. This is
also the average age level that most children start to participate in
school Physical Education and Sport courses. Physical Education is not
an elective course. It therefore is a core course and Turkey has a national
physical education teaching program. Despite the fact physical education
teachers are educated in various public and private physical education
programs, the core of the curriculums are very similar. All of the Physical
Education Teacher Education programs for the eight-year mandatory elementary
schools are monitored and constituted through the ministry of education.
While entire P.E. curriculums for education teachers are administrated
centrally and monitored by the ministry of education, there are few special
programs that training and preparing quality physical education and sports
teachers to teach high level physical education and sports courses at
8-year compulsory basic education institutions. The effectiveness of the
current programs that applied at most of compulsory basic education institutions
of eight years is a significant concern of this study. The purpose of
this research is to determine to what extent the physical education teacher
training programs that are currently used by those universities are effectively
and successfully training preparing physical education teachers to teach
at compulsory eight-year elementary schools.

Introduction

Education can be described as a planned and programmed process which
is applied in order to attain the desired changes in a person’s
behavior. Two basic and indispensable elements of education are the student
and the teacher. Unlike the traditional perspectives, in addition to lecturing,
the role of a teacher should be geared mostly towards guiding and advising.
This is also true for teaching physical education and sports. Physical
education teachers should guide students according to their interest and
skills. In order to attain the desired mental, social, psychological and
psychomotor developments, teachers should be creative and develop important
student specific tasks to improve individual creativity of various age
groups. The significant importance should be given to the programs that
deal with children who are at the beginning level(s). This situation brings
into the agenda a modernization of the programs to improve both the ability
of teachers to teach effective physical education courses and the program
tools that are going to be used in this process. It is a common belief
that currently most physical education teachers are ill prepared to successfully
teach physical education courses at the eight year compulsory schools.

Historically successful physical education programs have one thing in
common: they all use history as a learning process. For instance, those
who prepared and developed the modern physical education programs in the
United States America have benefited from teaching philosophies of Europe
(Lumpkin, 1990). The first modern efforts in order to train contemporary
physical education teachers began in the 18 th Century in Europe and in
the USA (Friedman, 1983). In the Ottoman Empire, these courses entered
the Curriculum in 1846 under the name of Gymnastics which was brought
about by the Tanzimat decree declared in 1839 during the reign of Sultan
Abdulmecit (Kasap, 1992). Selim Sirri Tarcan attended the Heyet-I Ilmiye
which assembled in 1923 and succeeded in integrating one-year-long the
‘physical education teachers’ school” into the government
program (Terbiye-i Bedeniye DarUlmuallimini).

The efforts for training sports instructors continued by the assistance
of three instructors (one woman, two men; Inge Nerman, Ranger Jonson and
Sven Alezanderson) who were called from Sweden between 1926-1929 and with
the 3,5-9 months – lasting courses of physical education teachers
during the years 1929-1930. In the scholar years of 1932-1933 a –
three- year- long physical education department was started at the Gazi
Education Institution in Turkey in order to train teachers for secondary
and high school levels. This was the only institution until 1966-1967.
Since then several other institutions have been developed and have been
offering physical education teachers education programs such as Istanbul
Institute of Physical Education, and various other universities in Bursa,
Izmir and Diyarbakir. In 1992 most of these schools were transformed into
physical education and sports higher schools. In Turkey, youth and sports
academies contributed to the process for training physical education teachers
as well as education institutes. Youth and sports academies were founded
under the youth and Sports ministry and were put into service in three
cities. The basic objective of the youth and sports academies is “to
train coaches, youth leaders, managers, experts as provided for in the
Body Training law numbered 3530.” Although the primary goal of youth
and Sports Academies was not to train physical education teachers as demands
raised for more physical education teachers the Sports Academies started
to certify their graduates to also be physical educators without pedagogic
training. At the end the Youth and Sports Academies lasted for only 10
years and they were closed forever.

Methodology

In Turkey, there are 48 universities that offer teaching physical education
programs and a total of 411 instructors are teaching physical education
courses. 171 instructors from Gazi University, Hacettepe University, Middle
East Technical University (METU), Ege University, Akdeniz University,
Celall Bayar University, Marmara University and Ankara University were
surveyed. A survey questionnaire consisting of 57 questions was developed.
The reliability coefficient of the survey is r = .96. By taking this course
of method, the research was formulated and determined by those who participated
in the research, taking into consideration the order of importance of
the branches determined by the Higher Education Board (HEB). These values
were interpreted according to the arithmetic averages of the participating
instructors’ (subjects) views. In conclusion, some significant statistical
differences were observed among various programs in terms of application
of teachers education programs both at the administrative and academic
levels. The research was carried out in July, August and September 2000.

The data we got in order to fulfill the purposes of the research were
provided by the surveys created by the researchers. The survey form was
prepared by means of the programs of the 48 physical education and sports
teaching departments of universities. Within this context, firstly the
programs which are aimed at training physical education and sports teachers
were scanned and the related courses were determined for the physical
education and sports teachers who will be on duty at primary and secondary
schools. The determined courses were grouped and submitted to a group
of instructors for their opinions and as a last stage, they were revised.
Thus a survey of 57 courses was created which would be submitted to the
instructors for their views. The reliability coefficient of the survey
is a + 96. The proposal concerning 57 courses, which formed the basis
of the research, were subdivided and evaluated according to the branches
determined by HEB. These branches are:

1 – Coach and Movement Sciences

2 – Sports Management Sciences

3 – Sports Health Sciences

4 – Psycho Social Fields in Sports

5 – Sports Training

6 – General Culture

7 – Applied Sports Field

8 – Information on the Teaching profession.

The subjects were determined under 8 dimensions. The proposals for courses
forming the bases of the research were developed taking into consideration
the order of importance of these courses the fields of which have been
determined by HEB.

Statistical processes were realized according to the arithmetic averages
of the participating instructions views about the related courses. The
courses determined in the program Draft proposal were put into order according
to their importance. The arithmetic averages of each group of courses
involving their own fields were taken as basis. The courses, which were
found above the arithmetic averages of the 57 courses submitted, were
proposed as elective courses. Lastly, a program was created which was
based on these findings.

Findings and Discussion

The purpose of the research is to determine the appropriateness of the
programs at the schools that are aimed at training physical education
and sports teachers who will work at 8 – year – long compulsory
basic education institutions. Within this context the programs applied
in Turkey were investigated and an evaluation was made for each of the
common courses.

The need for training staff in the academic and professional fields of
the sports sciences that were brought about by the constant change and
development in sports has become evident. This change and development
continued with the transformation of some of these schools into higher
schools and with the acceptance of eight fields by HEB within the framework
of related domains (Acikada, 1991). Moreover, the distribution of the
eight fields within the curriculum was determined as followed:

1 – Applied Sports Field; this field entails the
definition of the applied sports branches and teaching techniques.

2 – Field of Information on the Teaching profession; this section
includes the courses which are compulsory for teaching profession according
to ministry of national Education and HEB. In our country as in other
parts of the world, it is not possible to be a teacher without having
the necessary information on the teaching profession.

3 – General Cultures; this is the information necessary for a
qualified teacher. These include some courses that are not compulsory
for teaching but which are about current issues.

4 – The Field of Movement and Exercise Sciences; it is to evaluate
sports within the fact of movement and to shape it according to exercise
dimension.

5 – Field of Sport Health Sciences; involves the health dimensions
of sports and the relation between sports and health.

6 – The Field of Sports management and Sciences; involves the
dimension of sports related to management sciences.

7 – Sports Education; emphasized the manner of teaching sports
and involves the introduction of sports field.

8 – Psycho-Social Fields in Sports; involves the psychological
and sociological dimension of sports.

The determined groups of courses were divided into the above-mentioned
fields and evaluated within this framework.

Related to this, the proposed courses are presented in the table of
Annex 1 according to their order of importance for training physical education
and sports teachers who will be on duty at the basic education institutions.

As understood from the table, the group arithmetic average of the courses
included in the applied group has been found as X = 3.02. In this respect,
the basic and team sports such as gymnastics, athletics, rhythmic gymnastics,
volleyball and handball have been found on the highest level, whereas
the sports branches such as bodybuilding, marksmanship, and weight lifting
have been found at the lowest values. When we investigate the education
programs of Wales and England, we could see that team sports such as football,
volleyball, basketball, handball, gymnastics and rhythmic gymnastics were
at the highest level in term of the values attributed to them (Anonymous,
1995).

The research of Acikada (1991), which was carried out of 22 physical
education teachers with the purpose of development of physical education
and sports curriculum, produced similar results. The arithmetic average
for the courses which were under the information on teaching profession
has been found as X = 4.16. Although the arithmetic averages of the views
of the instructors for courses such Education Psychology, Education Sociology,
Program Development, Introduction to Education Sciences and Education
management has remained under the group average, these courses are compulsory
for the teaching profession.

The arithmetic average of the courses under the group of general culture
has been found as X = 3.41. in this respect, Foreign Language and already
compulsory Revolution History of the Turkish Republic and Computer courses
have been attributed and it has been noted that the Courses of Physics,
Chemistry, mathematics and Statistics were not important according to
the instructors for the physical education and sports teachers who will
be on duty at primary secondary schools. The research of Acikada (1991
gives similar results (Acikada, 1991).

The group arithmetic average of the courses under the movement and Exercise
Sciences has been found as X = 3.83. in this respect, the courses of motor
Development and Exercise Information were at the highest level, while
the course of Biomechanics has remained under the group arithmetic average
(X = 3.52).

The group arithmetic average of the courses under the Sports health Sciences
has been found as X = 3.95. In this respect the courses of First Aid and
sports physiology were at the highest level, whereas the Anatomy course
has been found under the group arithmetic average (X = 3.67).

Two courses were determined under the Sports Management Sciences. The
group arithmetic average of the courses under this group has been found
over the group average (X = 4.11). We think this is significant.

The group arithmetic average of the courses under the Sports Training
Field has been found as X = 4.18. In this respect, the courses of Skill
Acquiring and Special Teaching methods have been found at the highest
level, while the course of Comparative Sports Education was at the lowest
level.

There were two courses under the Psycho-Social Field in Sports and their
group arithmetic averages has been found as X =3.73. The course of Sports
Psychology was over the group arithmetic average (X = 4.11), while the
course of Sports history has been found at the lowest level in terms of
importance attributed to it, not only in its own group, but also in comparison
with all of the proposed courses (X = 3.34). These results show similarities
with those of the study carried out by Ursprung and his colleagues. Ursprung
and his colleagues have grouped courses offered at the physical education
and sports departments as Personal and Teams Sports pedagogy, Movement
and Health Sciences, Social Sciences and Scientific method (Ursprung and
his colleagues, 1995). Moreover, the groups of courses that should be
offered are parallel to the courses determined by Harrison,
Blakemore (1992) and Nicholas (1990), (Harrison and Blakemore, 1992),
(Nicholas, 1990).

Results and Suggestions

According to the results of the research, the participating instructors proposed to include gymnastics (aerobics and rhythmic gymnastics), athletics, swimming and team sports such as basketball, volleyball, handball, football, and racket sports such as badminton in the curriculum of the eight-year-long compulsory basic education institutions, especially during the periods covering 1-5 (ages 6-11). On the other hand, courses such as First Aid and Sports Physiology under the Sports Health Sciences, Motor Development and Exercise Information under the movement and Exercise Sciences, Recreation under the Sports Management Sciences, Skills Acquiring and Special Teaching method under the Sports Training Fields, Sports Psychology under the psycho-Social Fields in Sports were also proposed by the instructors. Within this context, the compulsory and elective courses that were determined in the draft program with the purpose of training physical education and sports teachers are as follows:

1. Semester	T	P	CH
Gymnastics	1	4	3
Athletics I	1	2	2
Foreign Language I	2	0	2
Rev. History I	2	0	2
Intr. To Teaching Prof.	3	0	2
2. Semester
Foreign Language II	2	0	2
Rev. History II	2	0	2
Turkish II	2	0	2
Basketball I	1	4	3
Handball I	1	4	3
Athletics II	1	2	2
Rhytm T. and R. Gym	1	4	3
First Aid	1	2	2
3. Semester
Foreign Language III	2	0	2
Gymnastics II	1	4	3
Athletics III	1	2	2
Volleyball I	1	4	3
Gen. Teaching Meth.	3	0	2
Motor Development	2	0	2
Football I	1	4	3
Program Dev. (Elective)	3	0	2
Edu. Sociology (Elective)	3	0	2
4. Semester
Foreign Lang. IV	2	0	2
Table Tennis	1	2	2
Aerobic Gym.	1	2	2
Swimming I	1	2	2
Scouting	1	2	2
Learning Skills	3	0	3
Basketball II	1	4	3
Edu. Psychology (Elective)	3	0	3
Edu. Management (Elective)	3	0	3
5. Semester
Foreign Language V	2	0	2
Exercise Information	3	0	3
Sports Psychology	2	0	2
Handball II	1	4	3
Football II	1	4	3
Psych. Counseling	3	0	3
Sports Management (Elective)	2	0	2
Sports history (Elective)	2	0	2
6. Semester
Foreign Language VI	2	0	2
Volleyball II	1	4	3
Swimming II	1	2	2
Test. Evaluation	3	0	3
Badminton	1	2	2
Anatomy (Elective)	3	0	3
Biomechanics (Elective)	3	0	3
Anthropometry (Elective)	3	0	3
7. Semester
Foreign Language VII	2	0	2
Recreation	2	0	2
Teaching Application	2	4	4
Natural Sports	1	2	2
Research Techniques (Elective)	2	0	2
Campa. Sports Teaching (Elective)	2	0	2
8. Semester
Foreign Language VIII	2	0	2
Sports Physiology	3	2	4
Optional Specialization	2	4	4
Teaching Application	2	4	4
Sports Sociology (Elective)	3	0	3
Sports Health (Elective)	3	0	3


Total Credit Hours: 145

T = Theoretical Courses

P = Practical Courses

CH = Number of Credit Hour Values

Table 1: The distribution of the courses that are proposed to be included in the main program, which trains physical education and sports for eight-year-long basic education institutions (according to the field and order of importance).

Fields	Courses	N	Median	SD	Order of
		Subjects	Median	Standard	Importance
				Deviation
Applied Sports Field	Gymnastics	171	4.6056	0.64	1
	Athletics	171	4.5352	0.88	2
	Rhythm Training	171	4.2113	0.97	3
	Volleyball	171	3.9014	0.93	4
	Handball	170	3.9	0.98	5
	Basketball	171	3.8592	0.96	6
	Swimming	171	3.662	1.29	7
	Scouting	171	3.662	1.08	7
	Football	171	3.5775	1.13	8
	Table Tennis	170	3.4	1.1	9
	Natural Sports	170	3.1857	1.15	10
	Aerobics	171	3.1127	1.29	11
	Badminton	170	3.0571	1.14	12
	Tennis	169	2.9275	1.12	13
	Wrestling	171	2.7324	1.3	14
	Cycling	170	2.7286	1.18	15
	Skating	171	2.5352	1.21	16
	Fencing	170	2.1714	1.06	17
	Archery	171	2.1408	1.06	18
	Rowing	171	2.0704	1.11	19
	Underwater Sports	169	2.0435	1.04	20
	Far Eastern Sports	170	1.9714	1.09	21
	Weightlifting	170	1.9571	1.12	22
	Marksmanship	171	1.9155	1.04	23
	Bodybuilding	170	1.8286	1.15	24
Info. On Teaching	Teaching Application	170	4.6286	0.76	1
	Gen. Teaching Methods	171	4.4225	0.8	2
	Psychological Counseling	169	4.2609	0.92	3
	Testing Evaluation	171	4.2113	0.92	4
	Educational Psychology	171	4.1408	0.97	5
	Educational Sociology	171	4.1127	1.02	6
	Program Development	171	4.0428	1.06	7
	Intro. To Educ. Science	171	3.9296	1.11	8
	Education Management	171	3.7465	1.04	9
General Culture	Foreign Language	171	4.0141	1.13	1
	History of Turkey	171	3.6479	1.32	2
	Computer	170	3.5286	1.15	3
	Research Techniques	171	3.4085	1.3	4
	Statistics	170	3.0143	1.2	5
	Basic Services	170	2.8714	1.14	6
Movement/Exercise	Motor Development	170	4.4714	0.96	1
	Exercise Info.	170	4.0857	1.13	2
	Antropometry	170	3.5286	1.16	3
	Biomechanics	170	3.2676	1.23	4
Sports Health	First Aid	169	4.2609	0.83	1
	Sports Physiology	170	3.9571	1.26	2
	Sportive Health	117	3.8286	1.08	3
	Anatomy	171	3.7606	1.2	4
Sports Management	Recreation	170	4.1143	1.08	1
	Sports management	170	3.4714	1.14	2
Sports Education	Learning Skills	169	4.4348	0.78	1
	Special Teaching Methods	169	4.3913	0.93	2
	Intro to PE and Sports	170	4.0714	1.13	3
	Comparative Sports Education	170	3.5857	1.2	4
Psycho- social field	Sports Psychology	170	4.1143	1.15	1
	Sports History	169	3.3478	1.23	2

U.S. Sports Academy2016-04-01T09:59:08-05:00January 5th, 2006|Contemporary Sports Issues, Sports Coaching, Sports Management|Comments Off

Playing with the Percentages When Trailing by Two Touchdowns

Submitted by: J. Denbigh Starkey

Abstract

It is relatively common for football teams to find themselves down by two touchdowns late in the game. If they score a first touchdown then coaching folklore says that the team should go for the extra point at that time. In this paper I will show that this strategy, which appears to be universally used in both the NFL and the NCAA, is incorrect, and that going for the two-point conversion after the first touchdown is nearly always significantly better. I will also show that going for the extra point after the first touchdown is only correct if either the coaches believe that they have about a two thirds chance of winning in overtime (which seems rash after a tied game when the result of the coin toss is still obviously not known) or if they believe that their chances of making a two-point conversion are far below national averages.

Introduction

On September 10 th, 2005, the University of Michigan football team was trailing by 14 points when they scored a touchdown with 3:47 left in their game against Notre Dame. Their coach decided to kick an extra point to get within seven points. Even though this strategy is followed in the NCAA and the NFL almost without exception, it is, in general, incorrect. In this paper I will show that the correct strategy in this situation is to immediately attempt the two-point conversion.

When their team is down by 14 points late in the game, NCAA and NFL coaches must base their strategy on the assumption that they will score two touchdowns while holding their opponents scoreless. When they score the touchdowns they have three choices of strategy that they can use:

Go for two first: Under this strategy the team attempts a two-point conversion when they score the first touchdown. If it succeeds then they go for the extra point after the second touchdown in an attempt to win the game. If the first one fails, which happens on average about 57% of the time, then they attempt another two-point conversion after the second field goal in an attempt to go into overtime. Although this strategy is apparently never used in professional or college games, and isn’t intuitively very good, I will show that it is clearly the best approach to take, based on well known probabilities for extra point and two-point conversion success rates.

Go for one both times: The commonly used strategy is to attempt the extra point after both of the touchdowns, playing to go into overtime. If the first extra point misses, which happens on average about 6% of the time, then the backup plan is to go for the two-point conversion after the second touchdown. Although this strategy is almost uniformly used, I will show that it is very inferior to the “go for two first” strategy.

Go for one then two: Under this strategy the team attempts the extra point after the first touchdown and then a two-point conversion after the second. This strategy is sometimes used when the coaching staff believes that their team is unlikely to win in the overtime and so they should go for the win now. As an example of this (Mallory & Nehlan, 2004) discuss, without criticism, a game where Bowling Green used this strategy to beat Northwestern in 2001. However I will show that it can never be as good as the “go for two first” strategy, and so it should never be used.

A fourth possible strategy, “go for two both times,” makes no sense logically or mathematically, unless the team’s extra point special team is so terrible that its chance for success is less than the chance for making a two-point conversion, and so I will ignore it here.

In summary, I will show that the “go for two first” strategy is considerably better than the commonly used “go for one both times” strategy, and that the “go for one then two” strategy should never be used.

Assumptions

The NCAA and the NFL have similar statistics for the success rate of two-point conversions and extra points. In the NFL the figures are 43% for the two-point conversion and 94% for the extra point, while in the NCAA the figures are 43.5% and 93.8% (Mallory & Nehlan, 2004). I’ll use the 43% and 94% figures for most examples in this paper, and will also develop the general formulas to show when the “go for two first” strategy is best. I’ll assume initially that the two sides have equal chances of winning the overtime, and will then extend the analysis to consider the more general case of what to do if, for example, the coaching staff believes that they have a higher or lower chance of winning in the overtime.

Mathematical Justification for the “Go for Two First” Strategy

I’ll assume a minimal level of probability knowledge for the rest of this paper. In particular I will assume that if there are two independent events like attempting a two-point conversion after one touchdown and then an extra point after another touchdown then the probability of both succeeding is the product of their probabilities. E.g., if the two-point conversion has a 43% chance of succeeding, and the extra point has 94%, then these will be assigned probabilities of 0.43 and 0.94, respectively, and the probability of both succeeding is 0.43 × 0.94, which is 0.4042, which using percentages is 40.42%.

The Average Case

Initially I’ll just look at the average case where the percentages for the two-point conversion and the extra point are 43% and 94%, respectively, (and so the percentages for failing on the two-point conversion and missing the extra point are 57% and 6%, respectively), and where the teams are equally likely to win if the game goes into overtime. Then I’ll generalize the mathematics to other percentages.

Under the “go for two first” strategy the team will score three additional points (i.e. in addition to the twelve points for the two touchdowns) if they get the two-point conversion and the subsequent extra point, two additional points when either they miss the first two-point attempt and hit the second or when they make the two-point attempt but miss the extra point, or no additional points if they miss both two point attempts. One additional point cannot occur under this strategy. The probability of three additional points, which will win the game, is 0.43 × 0.94 (making the two-point and then the conversion), which is 0.4042. The probability of two additional points (making the two-point and missing the extra point or missing the first two-point but getting the second) is 0.43 × 0.06 + 0.57 × 0.43, which is 0.0258 + 0.2451, which is 0.2709, which will send the game into overtime. The probability of zero additional points, which will lead to a loss, comes from missing both two-point attempts, which is 0.57 X 0.57, which is 0.3249. So there is a 0.4042 chance of winning outright plus a 50% chance of winning the overtime, which adds half of .2709, for a total winning percentage of 0.540.

The “go for one both times” strategy requires hitting both extra points, which has a probability of 0.94 × 0.94, which is 0.8836, or missing the first one and then attempting the two-point conversion which has a probability of 0.06 × 0.43 for an additional 0.0258, and then assuming a 50% chance of winning the overtime gives this strategy a winning probability of half of 0.9094, for a winning percentage of 0.455.

The “go for one then two” strategy is the worst. It succeeds and wins the game when both succeed with probability 0.43 × 0.94, which is 0.4042, and ties and goes into overtime if the extra point is missed but the two-point conversion succeeds, which will add half of 0.06 × 0.43, for another 0.0129 and for a total winning probability of 0.417.

In summary, the chances of winning under the three strategies, assuming an even chance in an overtime, 43% for two-point conversions, and 94% for extra points (the NFL average statistics), and assuming that you get two touchdowns without the opponents scoring, are shown in the table below:

Strategy	Percentage of winningin average case
Go for two first	54.0%
Go for one both times	45.5%
Go for one then two	41.7%

Clearly the proposed strategy, even though it is not commonly used, is by far the best strategy to take in this average case.

The General Case

Let’s assume that for your team you estimate that you have a probability x of making a two-point conversion, y of making an extra point, and in this game you believe that you have a probability of z of winning if the game goes into overtime. In the average case example above x = 0.43, y = 0.94, and z = 0.5. The probabilities now become

Strategy	Probability of winning
Go for two first	xy + x(1-y)z + (1-x)xz
Go for one both times	yyz + (1-y)xz
Go for one then two	yx + (1-y)xz

Interpreting these equations, the “go for two first” strategy wins if either the two-point conversion and subsequent extra point both succeed (probability xy), or the two-point conversion succeeds and the extra point fails but you win in overtime (x(1-y)z), or the first two-point conversion fails, the second one succeeds, and you win the overtime

((1-x)xz). The “go for one both times” strategy wins if either both extra points succeed and you win the overtime (yyz) or the first one misses but the backup two-point conversion succeeds, and again you win in overtime ((1-y)xz). Finally the “go for one then two” strategy wins if the extra point and the subsequent two-point conversion both succeed (yx) or the extra point fails and the subsequent two-point conversion succeeds and you win in overtime ((1-y)xz).

At this point we can completely reject any further consideration of the “go for one then two” strategy because the “go for two first” strategy always has (1-x)xz better probability and this quantity can’t be negative. (In most practical cases it will be about a 0.12 higher probability, or a 12% higher percentage.) The problem with the “go for one then two” strategy is that if the two-point conversion fails then the game is lost, while with the “go for two first” strategy if the two-point conversion fails then the team can attempt a second two-point conversion, going for the tie, after the second touchdown.

Assuming 50% Overtimes

In most games the probability of winning in overtime is dominated by the coin flip and luck, and so it is very close to 50% when evaluated in advance of that flip. Even if a fairer system were developed that took away the 60% advantage of the coin flip, like the pizza splitting system (Smith, n.d.), the success rate in overtime is likely to be very close to 50% for most teams over a reasonable number of overtimes. Given the assumption that z = 0.5, the probability table for the two reasonable strategies becomes:

Strategy	Probability of winning
Go for two first	xy + ½x(1-y) + ½(1-x)x
Go for one both times	½yy + ½(1-y)x

Given a particular value for y, your probability that you’ll make an extra point, we can compare these two formulas to determine how confident you need to be in your two-point conversion before you decide to use the “go for two first” strategy. As we’ll see, if you believe that you will make at least 38.2% of your two-point conversions (which is significantly below the national average) then you should always use the “go for two first” strategy, even if you know that you’ll never miss an extra point. As you reduce your confidence in your extra point special team, your required confidence in your two-point conversion team can drop even further and still mandate the use of the “go for two first” strategy. So, for example, if you have a poor kicking team and only expect to make 90% of your extra point kicks then you should use the “go for two first” strategy if you expect to make at least 32.8% of your two-point conversions.

To justify these numbers I just need to ensure that xy + ½x(1-y) + ½(1-x)x is greater than ½y 2 + ½(1-y)x, cancel out the common term, and solve the equation for x. This gives

xy + ½(1-x)x > ½y 2 which is –x 2 + x(2y+1) – y 2 > 0, which can be solved with the standard quadratic equation formula to get the equation that one should use the “go for two first” strategy whenever:

This looks complicated, but it is easy to apply. E.g., if y = 1.0, and so you believe that your team will never miss an extra point, then substitution shows that if your team can make at least 38.2% of their two-point attempts then the “go for two first strategy” is best. Break points for different expected field goal percentages are shown below:

Extra point percentage	Required two-point percentageto select “go for two first” when 50% chance in overtime
100%	38.2%
94% (NFL)	34.9%
93.8% (NCAA)	34.8%
90%	32.8%
80%	27.5%
70%	22.5%

So, for example, if your kicking team only succeeds 90% of the time with extra points, then if you estimate that you will make a two-point conversion at least one third of the time then you should adopt the “go for two first” strategy. A normal kicking team in either the NCAA or NFL should use the “go for two now” strategy if they can expect to make at least 35% of their two-point conversion attempts.

Assuming Other Overtime Percentages

While most teams will, when they are being honest with themselves, decide that their chances of winning if the game goes into overtime are close to 50%, there might be times when they are more or less confident than that. For example most analysts believe that a team with a much stronger field goal team has an advantage in overtime under either NFL or NCAA rules. In this section I’ll look at how this changes the odds. For any particular expectation of winning or losing in the overtime one can substitute the value in for z in the general equations and solve them using the quadratic equation as I did for the z = 0.5 situation, above. In general this gives the break point on whether or not to use the “go for two first” at

I’ll rebuild the table that I had above for two situations; when the coaching staff aren’t very confident going into overtime, and estimate their chances at 45%, and when they are confident and estimate their chances at 55%.

Extra point percentage	Required two-point percentageto select “go for two first” when 45% chance in overtime
100%	34.8%
94% (NFL)	31.9%
93.8% (NCAA)	31.8%
90%	30.0%
80%	25.4%
70%	20.9%

Extra point percentage	Required two-point percentageto select “go for two first” when 55% chance in overtime
100%	41.6%
94% (NFL)	37.9%
93.8% (NCAA)	37.8%
90%	35.5%
80%	29.7%
70%	24.1%

These figures show that even if you are fairly confident that you will win in overtime (55% confident) then you should still use the “go for two first” strategy unless you think that your chances of making a two-point conversion are way below the 43% average, and that if you believe that your chances are not good in an overtime (45%) then you should use the “go for two first” strategy unless your two-point conversion team is really awful.

They also give rise to one final question: How confident do you need to be in your ability to win in overtime before you reject the “go for two first” strategy and use the “go for one both times” strategy? Some math will provide that information. We know that we should use the “go for one both times” strategy when:

This surprisingly simple condition says that you should only use the “go for one both times” strategy whenever . Assuming the standard NFL values for x and y, 0.43 and 0.96, respectively, then this is , which is 0.633 or 63.3%. So the traditional “go for one both times” strategy should only be used if you believe that your team is nearly twice as likely to win as the opponents in overtime, which seems a wildly optimistic assumption after tying in regular time.

Discussion

I have shown that under nearly all circumstances the “go for two first” strategy is significantly better than the “go for one both times” strategy when trailing by two touchdowns late in the game, and than also the “go for one then two” strategy should never be used.

The only times when the “go for one both times” strategy should be used is when either the coaches believe that they are nearly twice as likely to win as the opponents are (which seems overly optimistic after a tied game unless there are external factors like late injuries to some of the opponent’s important players) or when they believe that their team is far below average at making two-point conversions.

Since the correct strategy never appears to be used, an interesting question is why coaches have always got it so wrong. They have probably been led astray by the expected value of going for two point conversions vs. extra points. The expected value is the expected long term return from taking a particular action. In the case of a two-point conversion it is, for a typical team, (2 points)x0.43, which is 0.86 points each time that you try it. For an extra point it is (1 point)x0.94, which is 0.94 points. So for most of the game kicking extra points after touchdowns is slightly better than going for two-point conversions. When trailing at the end of the game the expected value of the points is no longer relevant, since all that matters is whether you are more or less likely to win. Looking at it differently, if the coaches use the “go for two first” strategy then, as we saw earlier, there is a 0.4042 of winning outright, a 0.3249 of losing outright, and the rest of the time (0.2709) you’ll go into overtime. So you are more likely to win than lose. Using the “go for one both times” strategy there is no chance of an outright win, a 0.9094 of going into overtime, and the rest of the time (0.0906) you will lose outright. So with this strategy you are more likely to lose than win. One reason expected values don’t help here is that if you lose outright with the “go for two first” strategy it will be by two points, but with the “go for one both times” strategy it will sometimes be by only one point, but a loss is a loss, so this isn’t relevant.

In this paper I haven’t discussed how to handle other situations like trailing by seven points (attempt the extra point) or by 21 points (go for two first). I also haven’t discussed high school football because two-point conversion attempt and extra point percentages vary so spectacularly across high school teams. However once high school coaches have some estimates for their team’s percentages in these two areas they can use the formulas in this paper to determine their best approach. It appears that for all practical cases the “go for two first” strategy will also be best for them.

References

Mallory, W. & Nehlan, D. (eds.) (2004). Complete Guide to Special Teams, American Football Coaches Association, ISBN 0736052917.
Smith, M. (n.d.) Splitting the Overtime Pizza, Football Outsiders Web Page, Retrieved September 19, 2005, from http://www.footballoutsiders.com/ramblings_print.php?p=87&cat=1.

U.S. Sports Academy2018-10-25T10:22:13-05:00September 6th, 2005|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off

Intercollegiate Athletic Corporate Sponsorships and the First Amendment

Submitted by: Eric Bentley

Intercollegiate Athletic Corporate Sponsorships and the First Amendment:

In response to the recent escalation of head coaches’ salaries in intercollegiate athletics, and the constant pressure for athletic directors to adhere to shrinking budgets, many athletic directors are turning to corporate sponsorships to increase revenue. Athletic departments can raise money from corporate sponsors in a variety of methods ranging from selling advertising on the outfield fence of the baseball stadium to allowing corporate sponsors to set up an information booth and distribute advertisements on the concourse in the basketball arena. While an athletic director may be eager to welcome with open arms corporate sponsors with open checkbooks, an athletic director may at times be placed in a situation where he or she does not want to allow a corporate sponsorship to a company or organization that could portray a negative image on the athletic department or the university. For example, an athletic director may decide to decline an offer from Hooters, or a local “gentlemen’s club” to become a corporate sponsor for fear that it will negatively impact the family atmosphere and image the athletic department would like to portray. However, an Athletic Director at a state institution must be aware that providing sponsorship opportunities to certain companies while refusing sponsorship opportunities to others could implicate the right to free speech under the First Amendment. This article will attempt to provide an Athletic Director with information regarding lawful distinctions between corporate sponsors in order to avoid infringing on the First Amendment rights of the members of a corporation who are seeking to become a corporate sponsor for a state institution’s athletic department.

From the outset, it must be noted that this article only applies to state institutions because the First Amendment is not implicated with regard to private institutions. Thus, if a private religious university such as Brigham Young University refuses to allow Budweiser or Coors to become corporate sponsors (since alcohol consumption is contrary to the religious beliefs supported by B.Y.U.), it can lawfully decline such a corporate sponsor without any possible First Amendment implications.

The first step in analyzing a freedom of speech problem such as whether the athletics department can constitutionally deny a corporate sponsor an opportunity to engage in athletic department promotions is to determine the type of forum in which the intended speech is to take place. See Cornelius v. NAACP Legal Defense & Educ. Fund, 473 U.S. 788, 800 (1985). The 9 th Circuit in Diloreto noted that “where the government acts in a proprietary capacity to raise money or to facilitate the conduct of its internal business, the Supreme Court generally has found a nonpublic forum, subject only to the requirements of reasonableness and viewpoint neutrality.” Diloreto v. Downey Unified School Dist. Bd. of Educ , 196 F.3d 958 (9 th Circuit, 1999), citing Lehman v. City of Shaker Heights, 418 U.S. 298, 303-304 (1974). The Diloreto court held that where a high school offered advertising opportunities to businesses allowing the business to post an advertisement on a sign at the high school baseball field, and where the intent of the school in opening the baseball field to advertising was to raise funds, not to create a forum for unlimited public expression, the forum was a nonpublic forum open for a limited purpose. Id. at 966.

When an athletic department offers corporate sponsorships, it is clearly doing so to raise funds for the athletics department, not to create a forum for unlimited public expression. Thus, when an athletic department solicits and receives a corporate sponsorship such as for the signage at the athletic field or arena, the forum that has been created will likely be found to be a nonpublic forum open for a limited purpose.
In a nonpublic forum open for a limited purpose, restrictions on access “can be based on subject matter…so long as the distinctions drawn are reasonable in light of the purpose served by the forum” and as long as the restrictions discriminate on the basis of content rather than viewpoint. See Id.; Rosenberger, 515 U.S. at 829 (1995); Lamb’s Chapel, 508 U.S. at 392-93 (1993); Cornelius at 806. Thus, before denying an opportunity to a corporate sponsor, an athletic director must ensure that the he or she is making a reasonable distinction based on the purpose of the sponsorship opportunities it is offering, as well as ensuring that he or she is not making a distinction between two corporate sponsors on the basis of a corporation’s viewpoint.

Making a Reasonable Distinction

In Lehman, the U.S. Supreme Court addressed the issue of whether it was reasonable for a city transit system to decide which type of advertising may be displayed in its buses; an issue that arose when a political candidate was not allowed to advertise on the city buses. Lehman at 298. The Lehman court held that the city’s decision to exclude political advertising from bus signs was reasonable given the city’s desire to generate revenue and the potential for “ lurking doubts about favoritism, and sticky administrative problems [that] might arise in parceling out limited space to eager politicians.” Id. at 304.
An athletic director’s reason to decline offers from corporate sponsors such as Hooters or a local “gentlemen’s club” may be to keep a family oriented atmosphere at its games, and maintain an environment that is suitable for children. It is likely that making a distinction between a corporate sponsor such as Hooters and a corporate sponsor such as Ford or Coke based on the atmosphere that the corporate sponsor may create would be seen as a reasonable distinction.

Viewpoint Versus Content Discrimination

However, even assuming that an athletics department’s reason to deny a sponsorship opportunity to a certain corporation is reasonable, it may still violate the First Amendment if doing so discriminates on the basis of viewpoint, rather than content. Diloreto at 969, citing Cornelius at 811.

The U.S. Supreme Court noted that the distinction between viewpoint discrimination and content discrimination is not a precise one. Rosenberger at 831. The Diloreto court attempted to explain the distinction when it stated, “ Permissible content-based restrictions exclude speech based on topic, such as politics or religion, regardless of the particular stand the speaker takes on the topic.” Diloreto at 969, citing Children of the Rosary, 154 F.3d at 981. The Diloreto court further stated, “In contrast, impermissible viewpoint discrimination is a form of content discrimination in which the government targets not subject matter, but particular views taken by speakers on a subject.” Id. citingRosenberger at 829.
In Diloreto, a businessman was not allowed to buy advertising space at the high school baseball field because his proposed sign listed the text of the Ten Commandments, which was against the school’s policy of not allowing religious advertising. Id. at 962. The school district refused to post the sign “based on (1) concern about running afoul of the Establishment Clause; and (2) disruption, controversy and expensive litigation that might arise from community members seeking to remove the sign or from religious or political statements that others might wish to post.” Id. at 963. The Diloreto court stated, “We conclude that the District’s decision not to post Mr. DiLoreto’s sign was pursuant to a permissible, content-based limitation on the forum, and not viewpoint discrimination.”
If an athletic director allows corporate sponsors that promote a family environment to engage in sponsorships, while he or she refuses to allow corporate sponsors that promote an adult oriented environment to engage in the same sponsorships, the athletic director would likely be seen to be engaging in permissible content discrimination rather than viewpoint discrimination. By way of example, the athletics department would not be allowed to refuse to allow Hooters to be a corporate sponsor, while at the same time allow another adult oriented business such as a local “gentlemen’s club” to be a corporate sponsor because doing so would be deciphering between two different businesses that are adult oriented, which would likely be seen as viewpoint discrimination because the decision to exclude Hooters instead of the local “gentlemen’s club” would appear to be based on the particular views or specific stance Hooters takes. Similarly, an athletic director could not allow certain religious organizations such as the local Baptist Church to become a corporate sponsor while refusing to allow other organizations such as an atheist group to become a corporate sponsor because doing so would likely be seen as impermissible viewpoint discrimination.

However, the Diloreto case offers support for an athletic director to refuse to allow a religious organization or an adult oriented business to become corporate sponsors so long as the athletic director refuses to allow all religious organizations and adult oriented businesses to become corporate sponsors because doing so would likely be viewed as permissible content discrimination rather than impermissible viewpoint discrimination.

Conclusion

Therefore, since an athletic department, through its corporate sponsorships has likely created a nonpublic forum open for a limited purpose, if the distinction the athletic director is making between different corporations is a reasonable distinction that does not amount to viewpoint discrimination, it is likely that the athletic director’s actions of refusing to allow such a corporation to be one of its corporate sponsors would be found to be constitutional.

U.S. Sports Academy2015-03-24T10:33:18-05:00September 4th, 2005|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off

The Effects of the Speed Function on Some Technical Elements in Soccer

Submitted by: Surhat Muniroglu

Abstract

The purpose of this study was to examine the effects of the speed function on some technical elements (dribbling, slalom and agility) in soccer, and to determine the effect ratio of these elements on one another. Some information regarding the purpose of this research is given by means of literature review. The subjects of the study, 177 soccer players selected from the 1st, 2nd, and 3rd League, amateur and two youth teams in Ankara, Turkey, has undergone a performance test including one each of a sprint 0-15-30 m, slalom 0-15-30 m, and dribbling 0-15-30 m, and an agility test. Sprint, slalom and dribbling tests were applied twice, with the players resting between each trial. Finally, the agility test was performed. The reliabilities of the tests (Sprint = .74; Slalom = .61; Dribbling = .76; Agility = .81) were determined for the players (n=40). The performance values of the subjects examined showed that while speed function does affect the agility competency, it had no effect on slalom and dribbling competency. The other findings showed that slalom and dribbling competencies affect each other positively.

Introduction

In soccer, in addition to mental, psychological, physiological and coordinational features, the improvement of conditional features is important as well. Peak conditional features in soccer players provide an advantage. Much of what affects the results of a match occurs during or after the high intensity sprint. Analysis of the specific movements and activities performed by football players during games can provide much relevant information on which suitable training programs can be designed (Dawson, 2003).

Success in soccer is dependent upon a variety of factors including the physical characteristics and physiological capacities of the players, their level of skill, their degree of motivation, and tactics employed by them against the opposition. Some of these factors are not easily measured objectively, but others can be tested using standardized methods and can provide useful information for coaches (Mosher, 1985).

In soccer, speed plays an important role; the accelerated pace of the game calls for rapid execution of typical movements by every member in a team. In many instances, successful implementation of certain technical or tactical maneuvers by different team members is directly related with the degree of velocity deployed (Kollath & Quade, 1991).

According to the Dawson study (2003), the large majority of sprints performed in soccer take six seconds or less to complete, over distances of only 10-30 meters, and many of the sprints involve at least one change of direction.

As running speed increases, longer strides are taken. In this instance, the swing phase involves greater knee flexion and hip extension, and greater hip flexion in the latter part of the phase (Howe, 1996).

During soccer games, many actions affect the result of games. These actions are characterized by intermittent and multi-directional movements, as well as the movements of changing intensity and time.

Reilly and Ball (1984) stated that each game typically involves about 1000 changes of activity by each individual in the course of play, and each change requires abrupt acceleration or deceleration of the body or an alteration in the direction of motion.

Specific physical and physiological characteristics of soccer players can be used by coaches to modify training programs and to help players prepare for the game strategy. The modern soccer relies on the ability of all players to attack and defend whenever necessary. Therefore, it is important that all players achieve a high level of performance in the basic skills of kicking, passing, trapping, dribbling, tackling and heading. Analysis of the physical and physiological characteristics of the players and determination of the specific requirements for optimal performance are thus a necessity (Tiryaki et al., 1996).

Technique refers to the relationship and harmony a player demonstrates with the ball and describes the performance of a solitary action in isolation from the game, e.g. pass or dribbling (Bate, 1996).

Dribbling a ball was chosen in this study as this represents one of the most exciting aspects of the game for spectators, and a great deal of time is devoted in training to its practice (Reilly & Thomas, 1979).

When running with a ball, much shorter strides are taken as the player must be ready to change direction and speed. At the toe-off phase, the leg may not be as extended heel stride may not be as pronounced, rather the foot may land in a more neutral position or be plantarflexed (Howe, 1996).

It is known that players with sprint skills have advantage over other players. However, the degree of effect has not been determined. In this study, we wanted to determine the degree of effect of sprint on technical elements. In other words, the purpose of this study was to examine the effects of the speed function on some technical elements in soccer, and to determine the effect ratio of these elements on one another. Thus, soccer-training programs could specify and propose the degree, frequency, intensity and volume of sprint and technical elements.

Methodology

Participants

This investigation was performed during the 1999-2000 season and included players from different league group teams competing in Ankara, Turkey (177 soccer players selected from 1st, 2nd, 3rd League, amateur and two youth teams). All subjects were informed about the purpose of the study and of its voluntary nature, and all provided their consent to participate. The study involved analyses of performance of these players. We examined the literature for related investigations.

Apparatus and Task

To establish reliability, the tests were applied to 40 players in ‘on season’ and ‘off season’. Paired sample t – test statistical tests were used. The reliability values were determined as follows:

According to match analysis, in match situation maximum sprint distance is approximately 20 – 30 m. However, the soccer players run about 100 sprints in the match (Kelly et al., 1982).

The subjects ran 30 m to measure their sprint performance. Crossing values (15 m and 30 m) were recorded by photocell (sprint 0 – 15; = .67 ; sprint 0 – 30; =.74).

The subjects ran between nine slalom sticks located 1.5 m apart. With photocell, 15 m and 30 m crossing values were recorded. Slalom – dribbling tests established by Kunts were applied (1991). Van Rossum practiced the test over 15 m, and reliability was determined as approximately .51. In this investigation, we determined reliability for slalom 0 -15 m as = .53; and for slalom 0 -30 m as = .61. The subjects dribbled the ball between the nine slalom sticks located 1.5 apart. With photocell, 15 m and 30 m crossing values were recorded, and reliability for dribbling 0 -15 m was determined as = .68; and for dribbling 0 -30 m, = .76.

“Agility refers to the capability to change the direction of the body abruptly. The ability to turn quickly, dodge and sidestep calls for good motor coordination and is reflected in a standardized agility run test.” (Reilly, 1996). Agility tests comprise different directional movements with changes between 35 m and 142 m in area (Haywood, 1986). Wilmore (1992) has defined agility as the ability to change movement direction, and it constitutes conjunction of sprint, strength, stability and coordination factors.

The agility test used was that developed by Lindquist and Bangsbo (1994), and its formation and dimension included the football penalty area. The reliability was found as .81 (n=20). We conformed to the elements of this agility test, in which the athletes ran as fast as possible through the tests with this sequence: sprint (40 m), back sprint (8.25 m), sprint (8.25 m), sprint (8 m), slalom (70 m), sprint (8 m), side sprint (8.25 m), side sprint – opposite direction (8.25 m).

Testing Procedure

The tests included one each sprint 0-15-30 m, slalom 0-15-30 m, and dribbling 0-15-30 m, followed by the agility test. Sprint, slalom and dribbling tests were applied twice, with the players resting between trials. Finally, the agility test was performed. Descriptive statistics of the subjects are presented in Table 1.

Data Analysis

The acquired data was transferred to the computer and evaluated with SPSS (Statistical Package for Social Sciences). The descriptive statistics (f, %) and Pearson Moments Multiple Correlation and Paired sample t-test statistical tests were used. Significance level was determined at .05.

Results

All participants completed the test procedure. Results attained from the subjects were classified according to the mean, standard deviation, minimum, maximum and range, and are presented in Table 2.

Correlations between sprint, slalom, and dribbling were tested with bi-variate Pearson Moments Multiple Correlation, and results are given in Table 3. As can be seen, statistically significant positive (p.05) correlation was determined between the following: agility and sprint 15; agility and sprint 30; dribbling 15 and dribbling 30; slalom 15 and slalom 30; sprint 15 and sprint 30; dribbling 15 and slalom 15; dribbling 30 and slalom 15; dribbling 30 and slalom 30; and dribbling 15 and slalom 30.

Apart from the above, other relation among the variables was statistically insignificant. No statistically significant relation was determined between sprint and dribbling and slalom values, but there was a positive correlation between slalom and dribbling.

Discussion

We determined participants’ mean age as 23.72 3.4 years, mean height 179 6.5 cm, mean weight 72.4 6.7 kg, and mean training years as 8.5 3.4 years. In this study 0-15 m sprint value was approximately 2.25 sec, 15-30 m 1.85 sec and 0-30 m 4.14 sec. Winkler (1991) reported 0-15 m sprint value as approximately 2.43 sec, 15-30 m as 1.71 sec, and 0-30 m as 4.14 sec. These findings support our study.

In subjects with good sprint values, agility values were significantly more meaningful (r = .49) (P < .05). Although according to Balsom (1994), soccer players who have good sprint ability cannot also be skilled in agility. In this study, players having good sprint values also had significantly more meaningful agility values. Similar results were also found in the study done by Herm (1993). He found that there was a correlation between 30 m sprint value and agility (r =.65), and this data support our findings.

According to the Little & Williams study (2003), there is a significant correlation between maximum speed and agility ( r = 0.34 p< 0.05). There is a notion that maximum speed and agility are distinctly specific attributes. The specificity may be attributable to differences in the musculature utilized strength qualities required and complexity or of motor control, between the different speed components.

To find the relationships between dribbling and slalom, one study was conducted by Van Rossum and Wijbenga (1991). According to the statistical analysis, correlation value was found (r=.59). In this investigation, a statistically meaningful relationship (r=.55) was determined between dribbling and slalom. High perception skills are needed in slalom and dribbling skills; however, perception does not affect sprint and agility skills. The participants who did well in the slalom test also performed well in dribbling tests. This high correlation between slalom and dribbling can be explained by the similarity among step frequencies, movement and dynamic changes, and specific and compulsive concentration.

No significantly meaningful relation was found between sprint and dribbling and slalom values. According to the definitions of sprint and dribbling elements (Howe, 1996), it is seen that while the anatomical movements resemble each other, angle and velocity of the extremities differ. We assume this is why speed had no affect on dribbling.

According to the study, it is seen that performance of acyclic speed and dribbling are affected by performance of cyclic speed run. In soccer, the importance of cyclic running has decelerated because of changes in the structure of play. Because action is limited to a narrow field, acyclic speed and dribbling can be more important in taking opponents out of play and gaining an advantage. It is suggested that speed drills should be formatted with both acyclic and different dribbling, which more directly supports the necessary qualities of modern soccer.

References

Balsom, P. (1994). Sprint performance in soccer. Science and Football, III, (pp. 16-19). London: E & FN Spon.
Bate, D. (1996). Soccer skills practice. In T. Reilly (Ed.), Science and Soccer (p. 228). London: E & FN Spon.
Dawson, B. (2003). Speed, agility and quickness in football. World Congress on Science and Football-5: Book of abstracts. Lisbon: Faculty of Human Kinetics, Technical University of Lisbon.
Haywood, K. M. (1986). Life span, motor development. Illinois: Human Kinetics Publishers.
Herm, K. P. (1993). The evidence of sport anthropology in training of young soccer players. In T. Reilly, J. Clarrys, & A. Stibbe (Eds.), Science and football II. London: E & FN Spon.
Howe, T. (1996). Functional anatomy. In T. Reilly (Ed.), Science and soccer (p. 20). London: E & FN Spon
Kelly, L., Mariric, Z., Wasilewski, S., & Withers, R. T. (1982). Match analysis of Australian professional soccer players. Journal of Human Movement Studies, 8, 159-176.
Kolath, E., & Quade, K. (1993). Measurement of sprinting speed of professional and amateur soccer players. In T. Reilly, J. Clarrys, & A. Stibbe (Eds.), Science and football II (pp. 1-36). London: E & FN Spon.
Kunts, R., & Van Rossum, J.H.A. (1991). The usage of skills tests by trainers of youth teams: Tests of physical fitness and technique. In T. Reilly, J. Clarrys, & A. Stibbe (Eds.), Science and football II (pp. 319-323). London: E & FN Spon.
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Winkler, W. (1991). Computer-controlled assessment and video – Technology for the diagnosis of a player’s performance in soccer training. In T. Reilly, J. Clarrys, & A. Stibbe (Eds.), Science and football II (pp. 73-80). London: E & FN Spon

Appendices

Table 1. Height, Weight and Training Years of the Football Players

Variable ( n = 177 )Height (cm)Weight (kg)Training (year)

Mean (sec.)1.7972.48.55

SD (sec.).066.753.40

Min. (sec.)1.6560.01.0

Max. (sec.)1.9892.020.0

Range (sec.).3332.019.0

Table 2. Agility, Sprint, Slalom and Dribbling Results,

Variables ( n = 177 )AgilitySprint 0-15Sprint 15-30

Sprint 0-30

Slalom 0-15

Slalom 15-30

Slalom 0-30

Dribbling 0-15

Dribbling 15-30

Dribbling 0-30

Mean (sec.)41.902.251.85

4.14

4.48

4.92

8.88

7.59

7.72

15.31

SD (sec.)2.93.12.09

.17

.56

.89

1.31

.78

.72

1.17

Min. (sec.)35.871.981.67

3.72

3.13

3.51

7.06

6.07

6.15

13.04

Max. (sec.)51.862.502.11

4.94

6.28

6.76

12.92

9.69

9.90

17.98

Range (sec.)15.99.52.44

1.22

3.15

3.25

5.86

3.62

3.75

4.94

Table 3. Correlation Results

	Agility	Dribbling15	Dribbling30	Slalom15	Slalom30	Sprint15	Sprint30
Agility	———–	.33p.117	.35p.107	.36p.105	.35p.107	.45*p.019	.49p.011
Dribbling15	.33p,117	———–	.67*p.000	.53*p.000	.45*p.019	.31p.119	.29p.201
Dribbling30	.35p.107	.67*p.000	———–	.51*p.001	.55*p.000	.26p.227	.35p.107
Slalom15	.36p,105	.53*p.000	.51*p.001	———-	.84*p.000	.33p.117	.26p.227
Slalom30	.35p.107	.45*p.019	.55*p.000	.84*p.000	———–	.29p.201	.34p.112
Sprint15	.45*p.019	.31p.119	.26p.227	.33p.117	.29p.201	———–	.74*p.000
Sprint30	.49*p.011	.29p.201	.35p.107	.26p.227	.34p.112	.74*p.000	———-

*(P< .05)

U.S. Sports Academy2016-04-01T09:49:40-05:00June 8th, 2005|Contemporary Sports Issues, Sports Coaching, Sports Exercise Science, Sports Studies and Sports Psychology|Comments Off