A New Method for Ranking Total Driving Performance on the PGA Tour

Abstract

The Professional Golf Association Tour (PGA Tour) currently ranks its
players according to their overall Total Driving performance by adding
together individual ranks for their average driving distance and for their
driving accuracy percentage. However, this widely used and reported measure
is inappropriate because it is based upon the addition of two ordinal-scaled
measures in which the underlying differences between successive ranks
are not equal. In this paper, we propose a new method for ranking golfers
in terms of their overall driving performance. The method eliminates the
drawbacks of previously reported measures, including the one used by the
PGA Tour. Using the new methodology, we re-rank all PGA Tour golfers for
the 2005 season and compare these ranks to the “official” ranks reported
by the PGA Tour. In some cases, large differences in players’ rankings
existed. The reasons for these differences are then discussed.

Introduction

In recent years, numerous statistical analyses have been conducted in
an attempt to assess the relative importance of various shot-making skills
on overall performance on the PGA Tour and among amateur golfers (Shmanske,
2000; Dorsel and Rotunda, 2001; Engelhardt, 1997 and 2002; Callan and
Thomas, 2004 and 2006; and Wiseman and Chatterjee, 2006). While most of
the measures that have been used in these analyses have been well-defined
and widely accepted, there is one performance statistic, “Total Driving,”
that has not been well-defined. This particular statistic, which combines
a golfer’s (i) average driving distance and his/her (ii) driving accuracy
percentage, has been operationally defined in numerous ways, but no methodologically
sound measure has emerged to date. This includes the measure now being
used by the PGA Tour.

In this paper, the authors propose a new statistical measure based upon
standardized z-scores for ranking golfers according to Total Driving performance.
This new measure eliminates the methodological drawbacks of previously
developed measures by re-ranking PGA Tour golfers on their Total Driving
performance during the 2005 season and comparing these rankings to the
“official” PGA Tour rankings for that season.

The evolving nature of the relationship that has existed between driving
distance and driving accuracy on the PGA Tour over the last sixteen years
(1990-2005) was examined. Then, alternative ranking methods that have
been proposed and the necessity of and the rationale for a new composite
measure of Total Driving performance were discussed. Following this, the
new measure can be applied to the 2005 PGA Tour season. These new rankings
dramatically alter the previous ranking of many golfers on the tour. The
reasons for the differences in rankings will be explored.

Distance and Accuracy on the PGA Tour: 1990-2005

The average driving distances and the driving accuracy percentages have
changed significantly since 1990, with the largest changes taking place
in recent years. This is shown in Table 1. The average driving distances
have increased every year since 1993 and these increases have been relatively
steady on a year-by-year basis, except in 2001 and 2003, when the increases
were significantly higher. We surmise that technological improvements
in golf balls and equipment are likely to have played a part in these
two years.

A similar trend did not exist for the driving accuracy percentage. Here,
the accuracy percentage steadily increased from 1990 to 1995, and then
remained relatively stable over the next six-year period, only to decline
dramatically in the last few years. This dramatic decline occurred at
the same time that the average driving distance substantially increased.
In fact, during the 2005 PGA Tour season, the average driving distance
was at its sixteen year high of 288.6 yards and the driving accuracy percentage
was at its sixteen year low at 62.8%.

The negative relationship between a golfer’s average driving distance
and driving accuracy percentage increased in strength over this sixteen
year period. As indicated in Table 1, the strength of the relationship
has grown in recent years and it reached its highest level in 2005, when
the correlation between the two measures was -.679.

Current Measures of Total Driving Performance

Ranking golfers on each of the two driving measures presents no problems.
Driving distance is simply defined as the average number of yards per
measured drive. For each golfer, these drives are measured on two holes
per round. Driving accuracy is the percentage of all drives that come
to rest in the fairway. However, the PGA Tour and others (for example,
Engelhardt, 1997) have indicated the need for a single measure that takes
into account both the driving accuracy percentage and the average driving
distance. Numerous researchers have attempted to obtain such a measure;
unfortunately all of the measures that have been proposed have had methodological
flaws associated with them.

The most widely used measure is the one used by the PGA Tour. It is obtained
by adding together the individual ranks of a golfer on each of the two
measures and then obtaining a final overall ranking based upon the total
score. That is, for example, a golfer who was ranked 32nd in driving distance
and 42nd in driving accuracy percentage would have a total score of 32+42=74.
The PGA Tour would rank such a golfer higher than another golfer who ranked,
for example, 25th in average driving distance and 60th in driving accuracy
percentage, since the former summated score of 74 is lower than the latter
summated score of 85.

Such an approach is flawed despite its widespread use and acceptance.
The major flaw is that the level of measurement of each of these two rankings
(driving distance and driving accuracy) is at the ordinal level and, as
such, it does not take into account the underlying differences in distances
or in driving accuracy percentages. Stated differently, while the differences
in successive ranks remain the same, the corresponding differences in
distance and accuracy are not equal. Thus, it is not possible to add the
distance and accuracy ranks directly, without loss or distortion of the
underlying information.

Davidson and Templin (1986) suggested a somewhat different approach.
They proposed a measure which first divided all PGA Tour players into
three groups based upon their average driving distance. They then made
a similar classification based upon the driving accuracy percentage. The
three groups were coded as 1 (top one-third), 2 (middle one-third), and
3 (bottom one-third). To arrive at a measure of Total Driving performance,
the researchers multiplied the individual coded scores of each golfer.
The larger the score, which ranged from 1 to 9, the better the performance.
The authors used this new measure in a multiple regression analysis in
an attempt to isolate the effects of driving on overall scoring performance.

This measure was questioned by Belkin et al. (1994) because no evidence
was provided to support the construct validity of the measure and because
of the multiplication of the individual codes at the ordinal level of
measurement.

More recently, Wiseman and Chatterjee (2006) proposed a multiplicative
measure of Total Driving which ranked golfers according to the product
of their average driving distances and their driving accuracy percentages.
Essentially, this measure reduced golfers’ average driving distances by
the proportion of times their drives did not land on the fairway. Thus,
a golfer who had an average driving distance of 300 yards and an accuracy
percentage of 60% would be ranked lower than another golfer who had an
average driving distance of 280 yards and an accuracy percentage of 70%,
since 300(.60) =180 < 280(.70)=196. This measure was found to be highly
correlated with the PGA Tour measure, but subsequent analyses revealed
that it was also flawed because it gave far greater weight to driving
accuracy than it did to driving distance. However, unlike the two previously
discussed measures, it was operationally sound in that it was appropriate
to multiply the two quantities together.

In summary, different measures for Total Driving performance that have
been used are all flawed, and it is difficult to justify any of them as
an appropriate measure. In the next section of this paper, a new method
for ranking golfers that have none of the drawbacks of the previously
discussed measures will be explained.

A New Measure for Ranking Total Driving Performance

Both average driving distance and the driving accuracy percentage are
ratio-scaled data. To combine these two measures into a single overall
measure of Total Driving performance, the measure we propose is based
upon two statistically independent standardized z-scores, one for driving
distance, and the other for driving accuracy given driving distance.

In proposing such a measure, if the distance and accuracy measures are
statistically independent and they are viewed as being of equal importance
in driving performance, then it would be reasonable to compute the standardized
z-score of each measure, and then to add these z-scores to arrive at an
overall score. However, this approach does not seem reasonable in the
present situation because (i) there is a strong negative correlation between
driving distance and driving accuracy, and (ii) driving distance is the
primary factor in determining accuracy, rather than the other way around
(driving distance is primarily a function of a player’s physical strength
and athletic ability). With this reasoning, we propose the following as
a composite score of Total Driving:

Zsum = ZDD + ZDA|DD

where:

ZDD = Standardized z-score of
driving distance, and

ZDA|DD = Standardized z-score
of driving accuracy given driving distance.

To compute ZDD for a player, we subtract the average driving
distance for all players, µDD, from the given player’s
average driving distance, DD, and divide the result by the standard deviation
of average driving distances, σDD. This is expressed
as:

ZDD= DD-µDD
σDA|DD

Computation of ZDA|DD is a somewhat more involved procedure.
We need to determine the mean or expected accuracy percentage of all golfers
who drove the ball a specified average distance, DD, as well as the standard
deviation of the driving accuracy percentages given the specified average
distance, DD. The formulas for these are:

µDA|DD = ρσDA((DD-µDD)/σDD),
and σDA|DD = √((1-ρ2DA2

where ρ is the correlation coefficient between distance and accuracy.
The conditional standardized z-score of driving accuracy given driving
distance is then computed using the following formula:

ZDA|DD = (DA – µDA|DD) / √((1-ρ2DA2.

Statistical theory about bivariate normal distributions tells us that
z-scores for distance and accuracy, ZDD and ZDA|DD,
both have a mean of 0.0 and a standard deviation of 1.0. Further, the
conditional z-score for accuracy given distance, ZDA|DD, is
statistically independent of the z-score for driving distance, ZDD.

Because the two standardized z-score measures are statistically independent,
and because ZDA|DD is an indicator of accuracy after taking
distance into account, they can be added together to obtain an overall
summated z-score for overall driving performance. The higher the overall
value of Zsum = ZDD + ZDA|DD, the better
the overall performance.

The authors will discuss in greater detail the application of this approach
for ranking golfers based upon their Total Driving performance in the
2005 PGA Tour season.

Application to the 2005 PGA Tour Season

In 2005, there were 202 golfers on the PGA Tour. Detailed statistical
data for these players can be found on the PGA Tour’s website (www.pgatour.com).
Anderson Darling’s (AD) test was used to determine if driving distance
has a normal distribution. With this test, we reject the null hypothesis
that the data came from a normal distribution if the AD statistic is very
large, or equivalently, if the p-value is smaller than a chosen level
of significance (usually 0.05 or 5% level of significance). Our data show
that the AD statistic was 0.367, which is small, and the p-value is 0.429,
which is larger than the 5% level of significance. Therefore, we do not
reject the hypothesis that the data came from a normal distribution.

Similarly, we used the AD statistic to test whether the driving accuracy
percentage variable was Normally distributed. The AD test produced a test
statistic of 0.350 with a p-value of 0.471. As a result, we do not reject
the hypothesis that the driving accuracy percentages are Normally distributed.
Given these results, we concluded that the joint distribution of driving
accuracy and driving distance can be represented by a bivariate Normal
distribution, with a correlation coefficient of ρ = -.679 between
the two variables.

Next, the authors computed the values of Zsum as the Total
Driving scores, and ranked these values in descending order. The scores
for the top forty players in the resulting ordering, together with the
corresponding PGA Tour ranks, are shown in Table 2.

As it is seen in Table 2, Tiger Woods was the number one ranked golfer
in terms of Total Driving under the proposed method, which stands in sharp
contrast to his rank of 83rd in the PGA Tour rankings. In terms
of average driving distance, Woods was ranked 2nd in 2005 among
202 Tour players with an average driving distance of DD = 316.1 yards.
The top ranked player was Scott Hend, who had an average driving distance
of 318.9 yards. Woods’ average driving accuracy percentage of DA = 54.6%
gave him a PGA Tour ranking of 188th on this measure. The top
ranked player was Jeff Hart with a driving accuracy percentage of 76.0%.
Woods’ two ranks of 2nd and 188th led to his overall
ranking of 83rd for Total Driving based upon the PGA Tour method.

To illustrate the computation of ZDD , ZDA|DD ,
and Zsum for Tiger Woods, in 2005, the average driving distance
among all players was 288.6 yards with a standard deviation of 9.32 yards.
The average for the driving accuracy percentage was 62.8% with a standard
deviation of 5.32%. As noted previously, the correlation between driving
accuracy and driving distance was -.679. Then, the standardized driving
distance z-score for Tiger Woods is:

ZDD = (316.1 – 288.6) / 9.32 = 2.95.

The conditional mean driving accuracy percentage given the average driving
distance of 316.1 yards is:

µDA|DD = 62.8% + (-.679)(5.32%)(2.95)
= 52.1%.

That is, Tiger Woods or any golfer who has an average driving distance
of 316.1 yards would be expected to have a driving accuracy percentage
of 52.1%. Since Woods’ actual driving accuracy percentage for 2005 was
54.6%, his conditional z-score would be equal to:

ZDA|DD = (54.6 – 52.1) / √((1-(-.679)2)(5.32)2)
= .63

By adding the two z-scores for Tiger Woods, an overall Zsum
score of 3.58 is obtained, which is the highest of any of the PGA Tour
players in 2005.

The rationale for Woods’ jump in the rankings can be seen by a closer
examination of the z-scores. His average driving distance of 316.2 yards
far outdistanced all other golfers (except one). His z-score value of
2.95 reflects this large differentiation, whereas previously his ranking
of 2nd did not because it assumed that the distances between
ranks were equal when they were not. Further, his conditional z-score
for driving accuracy is now positive where before it was negative. The
reason for this is because his relatively low driving accuracy percentage
of 54.6% did not reflect at all how far Woods drove the ball. Actually,
for those who drive the ball this far, a driving accuracy percentage approximately
two percentage points lower could be expected. These two factors taken
together accounted for his top ranking.

The Spearman rank correlation between the PGA Tour rankings and the new
rankings was computed to be rs = .90 (p < .001). This
shows that there was a large degree of similarity between the two rankings.
On the other hand, and as illustrated by the case of Tiger Woods, there
were also dramatic differences in some cases. To get a better feel for
the differences, consider the scatterplot of the rankings under the two
methods, which is shown in Figure 1. It is seen that the rankings under
the two methods are generally similar, particularly in the middle range
of rankings, but discernibly less so near the top or the bottom ranges.
Divergence of the rankings at the extremes in this way emphasizes the
effect of the ranking method on the results, which in turn brings the
virtues and flaws of the ranking methods into focus.

Golfers whose rank improved included V. J. Singh, from 38th
to 13th, Davis Love III, from 59th to 11th,
and Brett Wetterich, from 73rd to 4th. Those going
in the opposite direction included Marc Calcavecchia, from 21st
to 45th, Jonathan Kaye, from 23rd to 44th,
and Justin Rose, from 13th to 33rd. Typically, the
reason for a golfer improving rank is because one of the measures was
quite good and the standardized z-scores now reflect this, while the previous
ranking system did not. For those golfers falling in rank, their old ranks
tended to be clustered around many other golfers and their actual differences
in rank did not reflect this closeness. For example, Justin Rose had a
driving accuracy percentage of 63.7%, which gave him a ranking of 81st
among all golfers on this measure. However, fellow competitor Marc Hensby
had a driving accuracy percentage of 62.7%, just one percentage point
less, yet Hensby’s rank of 102nd was 21 ranks below that of
the rank given to Justin Rose.

Summary

The proposed method for ranking golfers according to their Total Driving
skill takes into account the magnitude of the differences that exist between
players on each of the two driving dimensions. The current PGA Tour method
does not. The proposed method also takes into account the strong negative
relationship that exists between driving accuracy and driving distance.
This negative relationship is reflected in the new conditional standardized
z-score. As a result, this new method gives a better overall reflection
of the true Total Driving performance of PGA Tour golfers than does the
current ranking system. Computationally, the proposed method is slightly
more involved than other existing methods, but this is not a significant
factor today.

It should be noted that this methodology can be applied in other areas
in which an overall ranking is desired based on two correlated factors,
which have different units of measurement and thus need to be combined
in some way to provide an overall ranking.

References

Belkin, D.S., Gansneder, B., Pickens, M., Rotella, R. J., & Striegel,
D. (1994) “Predictability and stability of Professional Golf Association
tour statistics.” Perceptual and Motor Skills, 78, 1275-1280.

Callan, S. J. & Thomas, J. M. (2004) “Determinants of success among amateur
golfers: An examination of NCAA Division I male golfers.” The Sports Journal
7, 3 at http://www.thesportjournal.org/2004Journal/Vol7-No3/CallanThomas.asp.

Callan, S. J. & Thomas, J. M. (2006) “Gender, skill and performance in
amateur golf: An examination of NCAA Division I golfers.” The Sports Journal
8, 2 at http://www.thesportjournal.org/2006Journal/Vol9-No3/Callan.asp.

Dorsel, T.N., & Rotunda, R. J. (2001) “Low scores, Top 10 finishes and
big money: An analysis of Professional Golf Association Tour statistics
and how these relate to overall performance.” Perceptual and Motor Skills,
92, 575-585.

Engelhardt, G. M. (1997) “Differences in shot-making skills among high
and low money winners on the PGA Tour.” Perceptual and Motor Skills, 84,
1314.

Engelhardt, G. M. (2002) “Driving distance and driving accuracy equals
total driving:Reply to Dorsel and Rotunda.” Perceptual and Motor Skills
95, 423-424.

Shmanske, S. (2000) “Gender, skill and earnings in Professional Golf.”
Journal of Sports Economics 1(4), 385-400.

Wiseman, F. and Chatterjee, S. (2006) “A comprehensive analysis of golf
performance on the PGA Tour: 1990-2004.” Perceptual and Motor Skills,
102, 109-117.

 

TABLE 1
Driving Distance and Driving Accuracy: 1990-2005

Year Average Driving
distance (yds.)
Driving accuracy
percentage
Correlation between
distance and accuracy
1990 262.7 65.3% -.359
1991 261.4 67.1% -.306
1992 260.4 68.6% -.416
1993 260.2 68.8% -.417
1994 261.9 69.2% -.346
1995 263.4 69.5% -.457
1996 266.4 68.3% -.469
1997 267.6 68.6% -.448
1998 270.5 69.5% -.469
1999 272.5 68.4% -.471
2000 273.2 68.3% -.379
2001 279.4 68.4% -.346
2002 279.8 67.7% -.474
2003 286.6 66.1% -.612
2004 287.2 64.1% -.606
2005 288.6 62.8% -.679

 

Table 2
Revised 2005 PGA Tour Rankings for Total Driving (Top 40 players)

Player Driving
Distance
(yards)
Driving
Accuracy
(%)
Expected
Driving
Accuracy (%)
ZDD ZDA|DD ZSUM Rank PGA
Rank
Woods 316.1 54.6 52.1 2.95 0.63 3.58 1 83
Perry 304.7 63.4 56.6 1.73 1.75 3.48 2 2
Gutschewski 310.5 57.9 54.3 2.35 0.92 3.27 3 54
Wetterich 311.7 56.6 53.8 2.48 0.70 3.18 4 73
Hearn 295.2 68.5 60.2 0.71 2.11 2.82 5 1
Gronberg 301.4 63.2 57.8 1.37 1.37 2.74 6 6
Frazar 301.0 63.5 58.0 1.33 1.41 2.74 7 3
Warren 299.2 64.2 58.7 1.14 1.41 2.55 8 3
Glover 302.2 60.7 57.5 1.46 0.81 2.27 9 26
MacKenzie 300.2 62.1 58.3 1.24 0.97 2.22 10 11
Love III 305.4 57.9 56.3 1.80 0.41 2.21 11 59
Garcia 303.5 59.4 57.0 1.60 0.61 2.21 12 38
Durant 289.2 70.9 62.6 0.06 2.13 2.20 13 5
O’Hair 300.1 61.4 58.3 1.23 0.78 2.02 14 26
Singh 301.1 60.2 58.0 1.34 0.57 1.92 15 38
Long 298.3 62.4 59.0 1.04 0.86 1.90 16 13
Smith 300.8 60.2 58.1 1.31 0.54 1.85 17 44
Hend 318.9 45.4 51.1 3.25 -1.45 1.890 18 107
Hughes 291.3 67.5 61.8 0.29 1.47 1.76 19 7
Stadler 300.1 60.4 58.3 1.23 0.53 1.76 20 50
Allenby 297.7 62.3 59.3 0.98 0.77 1.75 21 20
Mayfair 288.2 69.8 63.0 -0.04 1.75 1.71 22 9
Appleby 300.6 59.3 58.1 1.29 0.29 1.58 23 61
Snyder III 291.8 66.3 61.6 0.34 1.21 1.56 24 8
Purdy 295.2 63.4 60.2 0.71 0.81 1.52 25 15
Brigman 295.5 63.1 60.1 0.74 0.76 1.50 26 18
Bryant 283.2 73.0 64.9 -0.58 2.07 1.49 27 30
Rollins 294.4 63.7 60.6 0.62 0.81 1.43 28 10
Jobe 302.3 57.3 57.5 1.47 -0.05 1.42 29 82
Brehaut 286.6 69.9 63.6 -0.21 1.62 1.40 30 17
Ogilvy 298.0 60.7 59.2 1.01 0.39 1.40 31 54
Henry 297.6 61.0 59.3 0.97 0.43 1.40 32 44
Rose 294.1 63.7 60.7 0.59 0.78 1.37 33 13
Westwood 296.8 61.5 59.6 0.88 0.48 1.36 34 43
Johnson 290.0 66.9 62.3 0.15 1.19 1.34 35 15
Senden 291.0 66.0 61.9 0.26 1.06 1.31 36 11
Mickelson 300.0 58.7 58.4 1.22 0.08 1.30 37 77
Watney 298.9 59.4 58.8 1.11 0.15 1.26 38 68
Trahan 295.8 61.8 60.0 0.77 0.46 1.23 39 33
Pappas 309.4 50.6 54.7 2.23 -1.06 1.17 40 109

Figure 1.
Scatterplot of Revised Rankings Versus PGA Tour Rankings

Are There a Higher than Expected Number of Early Life Critical Part Failures in NASCAR Vehicles? A Reliability Studywhat

Abstract

This paper investigates whether or not the DNF’s (those who ‘did
not finish the race’) due to early life critical part failures are
higher than would be expected in NASCAR vehicles. The hypothesis is that
early life critical part failures are, in fact, higher than would be expected
in NASCAR vehicles. This hypothesis is based on the fact that NASCAR teams
have sizeable budgets and use only highly specialized components. In addition,
the extensive mileage typically associated with commercial vehicles is
not required of these parts. This paper develops a reliability model to
test whether the average time of failure for these critical components
is higher than what would be expected of high performance critical components.

Introduction

The origins of NASCAR reach back to the days of Prohibition, when cars
used by
moon shiners needed speed to make delivery runs and avoid the authorities
in pursuit. More horsepower was needed but the greater loads put on factory
designed engines had the adverse effect of increasing engine failures.
So began the quest to modify cars with horsepower and reliability. Simultaneously,
the sport of auto racing began. The inaugural auto race at Daytona Beach
took place March 8, 1936 (Felden, 2005).

These early races, however, were not officially organized, so races were
haphazard and drivers tended to show up randomly. Fans were few and driving
stock cars remained a hobby since it didn’t generate enough income
to qualify as a job. Over the next ten years, fan interest increased considerably
and stock car racing evolved from an occasional, hastily organized race
on sand and dirt tracks, to the frequent races in stadiums and paved tracks
we know today. In December of 1947, Bill France, Sr., a driver and race
promoter, developed the idea of NASCAR as organized stock car racing subject
to specific rules. On February 15, 1948 NASCAR ran its first race at the
Daytona Beach road course. The Daytona 500 remains the premier NASCAR
race.

NASCAR vehicles have evolved to become highly sophisticated pieces of
equipment. Parts are designed individually to maximize horsepower and
reliability. However, maximizing horsepower often compromises reliability
and vice versa. This paper has two objectives. First, NASCAR has received
scant attention in sport economics literature and the data available lend
themselves to the development of a body of academic literature on engineering
and economic issues specific to NASCAR. This paper seeks to add to that
literature. Second, this paper examines the question of whether or not
critical part failures are higher than would otherwise be expected in
NASCAR vehicles. The basis for the model presented here is standard in
the reliability engineering literature.

The paper proceeds in five parts. Part II discusses some of the literature
on NASCAR and reliability issues. Part III explains the data used in this
paper. Part IV develops a reliability model and tests it against the empirical
data. Part V presents the results and conclusions of the analysis.

Current Research

Scholarly research on NASCAR as a sport in any form is in its infancy.
This is particularly true where quantitative studies on NASCAR vehicle
performance and reliability are concerned. Majety, Dawande, and Rajgopal
(1999) show that in general, the typical reliability allocation problem
maximizes system reliability subject to a budget constraint. They note
that cost is an increasing function of reliability, hence the tradeoff
between dollars spent and system reliability. The latter point is certainly
true but the nature of the budget constraint specific to NASCAR is a crucial
aspect of the question pertaining to maximizing system reliability. By
many anecdotal accounts, NASCAR owners are willing to spend virtually
unlimited amounts of money to earn a spot in Victory Lane (New York
Times
, 2/13/06; CBS News, 10/6/05; Pfitzner, January, 2006).
However, Wachtel (2006) suggests that a budget constraint does exist,
although budgets in NASCAR racing are far more substantial than those
common to commercially produced vehicles.

Pfitzner and Rishel (2005) developed a model predicting order of finish
in NASCAR races based on variables such as car speed, driver characteristics,
and the like. This research is significant because it takes a predictive
and quantitative approach rather than an informal and subjective approach
to predicting NASCAR race outcomes. Such academic research may eventually
become a common source of information for NASCAR teams in their pursuit
of victory. Williamson (1997) views teamwork as the key to reliability
in NASCAR component performance, hence the key to winning. Williamson’s
analysis, however, is limited to a basic management approach and largely
excludes quantitative analysis.

The Data

The data used in this paper were obtained from the NASCAR website. Results
were taken from the thirty-six races in each season from 2002-2005. Each
race includes forty-three cars. The data include length of race in hours,
average speed over duration of race, order of finish, laps completed,
and completion condition. Completion condition indicates one of three
outcomes for each car. The vehicle was running when it completed the race,
the vehicle did not finish the race (DNF) due to an accident, or the vehicle
did not complete the race due to critical part failure. The order of finish
statistic for the DNF’s ranks them according to laps completed at
the time of an accident or failure of a non-repairable and therefore,
as this paper defines it, a critical part.

Using 144 races over four seasons, the average time per race was calculated
to be 3.2 hours. The average percentage DNF failure rate due to critical
part failure over the four seasons was calculated to be 9.7%. For purposes
of this paper, those are the two key empirical data points needed.

The Model

During a NASCAR race, a certain percentage of cars do not finish the
race. Some of these DNF’s are due to crashes, which are not relevant
to the question here. This paper examines the DNF’s due to critical
part failures. Stock cars, as the term is used in NASCAR, are not “stock”
as the term is used for automobiles purchased by consumers. In the latter
sense, stock simply means that the vehicle comes equipped with factory
made parts common to other vehicles with minor variations based on make
and model. NASCAR uses the term stock in name only. As was discussed earlier,
original NASCAR vehicles were stock in the traditional sense of the word,
although amateur expert mechanics were employed to enhance the vehicular
performance. Since 1947, when NASCAR became official, NASCAR vehicles
have been stock in name only and highly trained engineers and mechanics
are allowed to modify the cars for maximum performance within a set of
rules. Sponsorship money has created budgets to build teams that can create
the winning car.

It is reasonable to assume that NASCAR teams operate with a budget constraint,
but one that is different than is the case for commercially produced vehicles.
Specifically, dollars per part spent on NASCAR vehicles are substantially
higher than dollars per part spent on commercially produced vehicles (Wachtel,
2006). This is because a NASCAR vehicle is essentially custom built, while
a typical passenger car is factory built in mass quantities. The larger
budgets afforded NASCAR teams would suggest that critical part failure
during races should be low. How low? Consider a 500 mile race. We would
expect a regularly maintained commercial vehicle with mid-level mileage
to make a 500 mile trip without a critical part failure. Yet with NASCAR
vehicles, a percentage of DNF’s over the course of a 500 mile race
occur due to critical part failure despite the higher dollar per part
expenditure and the well above average maintenance that goes into these
vehicles. Furthermore, these vehicles are virtually brand new at the start
of every race. For this reason, the model we use here assumes reliability
for critical parts in NASCAR vehicles given average race time to be .99.
This is, in other words, what we would expect from a commercially produced
vehicle.

This paper utilizes the reliability function

R(T) = e-λ T

where T = average race time over the season and λ = the failure
rate (Evans and Lindsay, 1993). The function R(T) then represents the
probability that a part will not fail within T units of time. At this
point, the question we have to pose as theoretical concerns the expected
number of early life critical part failures in NASCAR vehicles. Based
on the theoretical assumptions of the model, we expect this failure rate
to be .01.

Letting T = 3 for average race time in hours and setting R(T) = .99,
we can calculate λ.

(1)

R(T) = .99 = e-λ3

ln .99 = -3λ

λ = (ln .99)/3 = -.003

or λ = 1/3%

This means that if, as is documented, the average NASCAR race lasts three
hours and if we assume, according to our theory, an expected critical
part reliability rate of 99% for critical parts, then the DNF rate per
race due to critical part failure should be 1/3%. This means that 99.7%
of the cars should either finish the race or DNF due to reasons other
than critical part failures. Note that the average race time over the
four season period was slightly higher than three hours, but did not change
the value of λ to an extent that warranted rounding down to three
hours.

Using the NASCAR data described in Section III, we find that the average
critical part failure rate over the four seasons 2002-2005 was, in fact,
9.7%. We can recalculate equation (1) and solve for the time in hours
this generates for first failure. We re- write equation (1) as

(2) R(T) = .99 = e-.097T

and calculate for T. Following the same procedure, we find that T = .1036.
In other words, the average time to the first critical part failure is
1/10th of an hour or six minutes in a NASCAR race. For example, this is
consistent with the data from the 2005 Daytona 500 finishes where the
first car to drop out due to critical part failure was at fourteen laps.
This, at an average speed of 135 mph on the 2.5 mile oval, amounts to
about six minutes.

The graphical depiction of this reliability function, or the failure
rate curve, further illustrates our results.

In general, the failure rate curve shows the expected life of some manufactured
part. The negatively sloped portion depicts early part failure, the flat
portion depicts the useful life of a part, and ordinarily the function
would show a positive slope depicting the wear-out phase of the part.
The above function is a graphical representation of our mathematical equations
where 3.0 shows that we expect 1/3% of commercially manufactured auto
parts in a passenger vehicle to show early life failure, which means,
in this case, not beyond three hours. However, based on empirical data,
NASCAR vehicles show close to a 10% early life critical part failure suggesting
that, other things equal, a driver has a 10% chance of not finishing the
race to a critical part failure.

It should be noted, however, that this analysis assumes a constant failure
rate, which means that different test lengths during a given period of
time should show the same results. This is highly desirable where passenger
cars are concerned and when time is such a crucial element of reliability.
While one would assume this to be desirable for NASCAR vehicles, it is much more likely that the failure
rate will vary from race to race and year to year. In fact, the empirical
data bear that out.

Results and Conclusion

This paper hypothesized a reliability rate of 99% for a conventionally
manufactured vehicle over a three-hour time span. We used this as a reasonable
expectation for NASCAR vehicles because of the higher dollar per part
spent on NASCAR as compared to commercially manufactured vehicles, in
addition to the number of highly trained mechanics and engineers devoted
to essentially custom building a new car for each race. However, for thirty-six
races for each of four NASCAR seasons between 2002 and 2005, our results
showed a 9.7% critical part failure rate. The question then becomes, what
accounts for this?

The 9.7% critical part failure rate may be attributable to two factors.
First, under normal driving circumstances, NASCAR vehicles would demonstrate
the same reliability of 1/3% critical part failure rate over a three hour
time period as commercially produced vehicles do, were it not for the
fact that in an effort to increase horsepower and speed, critical parts
in NASCAR vehicles are pushed to their tolerance limits throughout the
race and can be expected to fail at higher rates. Second, NASCAR rules
place restrictions on the critical part reliability improvements that
NASCAR teams can make. For examples, compression ratios must be 12:1,
engine size cannot exceed 358 cubic inches, and the materials composition
of the vehicles and its parts cannot include titanium. These are a few
of the rules designed to prevent certain team specific technological improvements
that would make each race predictable in terms of outcome and thus potentially
reduce competitiveness and fan interest in NASCAR.

Areas for further research in NASCAR and the economics of sports are numerous.
One such application of this particular paper might be an examination
of the specific rules NASCAR places on the use of technology, which may
be useful in re-formulating the reliability function. Another application
might be the inclusion of a specific budget constraint to re-formulate
the problem as one of optimization subject to constraint.

References

Evans, James and William Lindsay. The Management and Control of Quality,
3rd ed., 1996, West Publishing Company.

Felden, Greg. NASCAR: A Fast History, 2005, Publications International
Ltd.

Lorincz, Jim. “CNC machining improves NASCAR Cars,” Manufacturing
Engineering
, vol. 136, no.1, January, 2006.

Majety, Subba Rao, Millind Dawande, Jayant Rajgopal. “Optimal reliability
allocation with discrete cost-reliability data for components,”
Operations Research, vol. 47, no.6, Nov-Dec., 1999.

Martin, Mark. NASCAR for Dummies, 2005, Wiley Publishing.

“Weather man made to order for NASCAR’s engine tests,”
New York Times, February 13, 2006.

Pfitzner, Barry, Tracy Rishel. “Do reliable predictors exist for
the outcomes of NASCAR races?” The Sport Journal, vol.
8, no.2, Spring 2005.

Wachtel, Gene. Mechanical Engineer, Hendrick Motor Sports, Personal Interview,
February 10, 2006.

Williamson, Robert. “NASCAR racing teamwork leads to reliable equipment,”
AFE Facilities Engineering, July-August, 1997.

The Effect of Modern Marketing on Martial Arts and Traditional Martial Arts Culture

Abstract

This paper examines the effect of modern marketing strategies upon martial
arts activity in the United States. The concentration of the inquiry is
twofold. How has marketing effected the economic activity of the martial
arts business industry? How has marketing effect the martial arts culture?
This paper begins with a historical analysis of the evolution of martial
arts as a business practice involving the use of marketing to gain customers.
Martial arts marketing practices have proven most effective when they
are personal due to the geographic location of specific schools or the
instructor-client relationship. Internet marketing is a synthesis of personal
and mass marketing, providing readily available information in a client’s
home while offering to the martial school the potential audience of a
large mass marketing campaign. Marketing has generated sufficient commercial
interest in the field, transforming martial arts into a thriving business.

Section I: Introduction

As a professional martial artist and instructor, I have a sincere interest
in understanding how modern marketing initiatives have affected both the
martial arts culture and the business industry. In order to appropriately
evaluate modern marketing practice’s effect upon the martial arts
field, this paper begins with an examination of the historical development
of martial arts in the United States, as well as the application of marketing
in popularizing the field. This paper seeks to answer the following questions:

  • How has modern marketing affected the perception of martial artists
    among non-practitioners?
  • Has marketing redefined the term “martial arts”?
  • Has marketing raised or lowered the standard of quality among practitioners
    and schools?
  • What effect does commercialized marketing have on traditional martial
    arts culture?

This information is useful for a variety of reasons. First, for those
practitioners interested in developing their own martial arts business,
this paper contains valuable information on what works to attract and
retain customers. Secondly, this information is important to those seeking
to gain a greater knowledge and appreciation of the practice of martial
arts. Finally, and perhaps most importantly, the information is useful
for scholars ascertaining the effect that commercializing a traditional
recreational activity has on the culture, practice, and development of
the field.

Section II: Literature Review

Overview of the Available Literature

This review includes literature from a variety of sources, including
scholarly journal articles, books, and Internet websites. Little has been
written concerning the specific involvement and effect of marketing practices
upon the field of martial arts. However, extensive literature is available
concerning marketing general sporting events, including the ways that
business enterprises effect the culture of entertainment and recreational
activities. In addition, extensive online sources document the involvement
and history of martial arts in American culture. The combination of these
two primary source categories offers insightful data concerning the evolution
of martial arts marketing in the United States in the past century.
Definition of a Martial Art

The term “martial art” is difficult to define because of
the cultural significance of the term. Understood in its traditional form,
martial arts are the practices and methods of the military (Musashi and
Wilson, 2002, p. 39). However, this is hardly the definition used by most
of today’s practitioners (Zhang, 2006). The specific practices of
a particular martial art will vary according to centuries of tradition
and the country of origin.

Modern definitions of martial arts have attempted to distinguish contemporary
practices from those practiced in previous systems of combat. Some critics
contend that modern practices are merely a trickled down version of their
predecessors. This criticism has reached a new level of furor over the
past few years with “Modern Wushu,”1 a combination
of dance, martial arts, and gymnastics set to replace Taekwondo at the
2008 Olympic Games (Niu, 2006). In the U.S., most modern martial arts
schools focus upon cognition and recreation, as opposed to self-discipline.
Donohue (1994) noted that modern martial arts systems such as judo and
karate tend to associate “nominally physical techniques with well
defined philosophical and spiritual ideas” (p. 36). The sport and
entertainment focus of today’s martial arts education is also one
clearly distinguishing characteristic from the more traditional definition
(Draeger, 1990).

History of Martial Arts

The recitation of folk history has played a major role in the perpetuation
of the world’s martial arts (Green and Svinth, 2003). Students learn
the methods, traditions, and stories associated with their particular
discipline from their masters or teachers. While these histories are not
always accurate, they succeed in transmitting the culture and value to
successive generations (Shengli and Yun, 2006). In many early societies,
martial arts developed within a period of centuries as an integral component
of culture. In China, for example, schools were not generally commercial
ventures but family endeavors in which successive generations preserved
the knowledge of their ancestors (Kennedy and Guo, 2005, p. 15).

The earliest recorded instances of Asian martial arts interest in the
United States can be traced back to the turn of the Twentieth Century.
This history begins with President Grant’s 1879 observation of a
judo evaluation during a trip to Japan (“Complete Martial Arts.com,”
2006, p. 1). President Theodore Roosevelt was also a known enthusiast.
During the 1920’s, the Japanese art of judo was introduced to the
U.S. by young Japanese immigrants (Rosenberg, 1995, p. 19).

Martial arts popularity surged following World War II (Friman, 1998).
During the late 1940’s, martial arts became a popular recreational
activity among members of the military stationed in Asia. Within a decade,
prominent U.S. military officers, including General Thomas E. Power of
the Strategic Air command, were “encouraging the training of their
personnel by inviting Japanese instructors to conduct classes at military
bases in Japan and the United States” (Friman, 1998, p. 19).

During the 1960’s, these formally trained ex-military joined traditional
foreign instructors in bolstering interest and activity in martial arts
in the U.S. Interest was not limited to Japanese martial arts. American
contact with Vietnam and Korea spurred interest in these nation’s
martial arts forms (“Complete Martial Arts.com,” 2006). In
the 1970’s, interest intensified with the star power of Bruce Lee
and a movie industry capitalizing upon public interest by offering a variety
of martial arts inspired movies.

Justifications for Practicing Martial Arts

When understood as military practices, martial arts are justified by
conquest and military victory (Musashi and Wilson, 2002). Soldiers are
trained in combat techniques that will assure them of victory in battle.
However, martial arts have traditionally included more than physical prowess.
The basis of many martial arts specialties have been upon training the
whole individual, so that they are mentally, physically, and spiritually
prepared to meet the challenges of everyday life (Musashi and Wilson,
2002; Tsunetomo and Wilson, 2002).

For example, during the Golden Age of Korean history, a select number
of Korean noblemen were indoctrinated into the military order known as
the Hwarang (“Flowering Knights”) (Haines, 1995, p. 106).
These martial arts practitioners subscribed to a particular code of conduct
based upon five fundamental tenets.

  1. Loyalty to the king
  2. Faithfulness to one’s friends
  3. Devotion to one’s parents
  4. Bravery and absolute obedience on the battlefield
  5. A prohibition against wanton killing of any form of life (Haines,
    1995, p. 106).

This focus on the whole individual is also present in many Japanese and
Chinese martial arts. In the 1950’s, Morihei Ueshiba, the founder
of the popular Japanese martial art “Aikido,” stated:

The martial arts must be a path that brings our hearts into oneness with
the spirit of heaven and earth… Aikido is not the art of fighting
using brute strength or deadly weapons, or the use of physical power or
deadly weapons to destroy one’s enemies, but a way of harmonizing
the world and unifying [all people] (Sunadomari, 2004, p. 1, 29).

Marketing of Martial Arts

Basic marketing focuses upon the four “P”s: Product, Price,
Place, and Promotion (Kim, 2002, p. 217). For a martial arts school, the
important products include the offered classes and the associated items
sold through business, such as videos, books, gear, uniforms, and clothing
(Peterson, 2002).

Marketing strategies can be divided into two basic categories. Direct
marketing, which includes one on one contact with potential customers,
may also include paid and unpaid advertisement ventures. Mass marketing
is the more familiar form of advertising, such as commercials on television
and radio. Martial arts schools have succeeded largely through the use
of direct marketing.

For martial arts schools, direct marketing works better than mass marketing
for two reasons: First, teaching martial arts is a personal business.
You win students and keep students by letting them know you can meet their
personal needs. You win and keep students by being the kind of person
they want to study with. Second, people typically choose fitness facilities
close to their home or work. Mass marketing can rarely target that specifically.
Direct advertising can (Peterson and Vactor, 2002, p. 103).

Zhang Sheng Yi, the founder of the Beiyu Wushu Association in Beijing,
China, agreed with this point. In his interview he stated, “I do
not use commercials or signs. I think I should meet people face-to-face.
When they see my “gongfu2” they will want to learn
it” (Zhang, 2006).

It is also important to understand that marketing has rarely been the
focus of traditional martial arts instructors. In the past, martial arts
schools were supported by the military or the state; teachers had little
reason to worry about financial necessities (Kennedy and Guo, 2005). However,
some business-minded individuals have demonstrated the effectiveness of
careful marketing in the accumulation of personal wealth. For example,
in the 1970s, Rorion Gracie emigrated from Brazil to teach the art of
Gracie Jiu-Jitsu (Green and Svinth, 2003, p. 69). He believed that the
timing was right to introduce the Brazilian wrestling technique to the
United States, due to the success of martial arts film stars. He met with
initial failure because the patient and slow discipline did not match
the public’s enthusiasm for acrobatics. However, he implemented
an aggressive marketing campaign that included prominently advertised
matches and frequent media exposure. “That marketing, as distinct
from martial art, was foremost in his mind is demonstrated by his copyrighting
both the Gracie Jiu-Jitsu name and logo” (Green and Svinth, 2003,
p. 70). Rorion Gracie was pivotal in influencing the treatment of modern
martial arts in America. He would help develop the model used in the Ultimate
Fighting Championships (Green and Svinth, 2003).

Martial Arts Role in Society

How has marketing changed the role of martial arts in society? Historical
evidence demonstrates that martial arts were primarily practiced in Asia
for self-defense purposes (Friman, 1998). However, the modern world views
martial arts differently. Individuals typically practice martial arts
for one of three reasons. First, they engage in martial arts for personal
enjoyment. Second, martial arts practice is an excellent form of exercise
that can contribute to a healthful lifestyle. Third, many individuals
decide to engage in martial arts for competitive reasons. The rise of
interest in martial arts has coincided with a greater visibility of athletic
competitions. Each of these three factors has contributed to national
interest in martial arts (“Complete Martial Arts.com,” 2006).

Martial Arts for Fun

Much of the post World War II interest in martial arts resulted from
communication and technological advances that revolutionized the entertainment
business (Friman, 1996). Radio, television, and most notably movies began
to feature characters engaging in martial arts to settle disputes. Many
movie stars became associated with martial arts, such as Bruce Lee and
Chuck Norris. Popular teen-oriented films such as The Karate Kid
focused upon the accessibility of martial arts: anyone who trained hard
enough could attain near superhero-like capability through martial arts
prowess (Green and Svinth, 2003).

The potential for violence and injury through martial arts involvement
has been largely ignored by regulators in the United States (Friman, 1998,
p. 21). “The martial arts in the United States have a long tradition
of being backed and promoted by state authorities” (Friman, 1998,
p. 21).

Martial Arts for Health

One dramatic effect upon the image of martial arts in the American conscious
is the wave of interest in martial arts as a means of physical fitness.
The women’s movement has been especially active in incorporating
martial arts into their own agenda for health. “Women are empowering
themselves by appropriating male symbols of physical capital and shifting
gender relations of power” (Green and Svinth, 2003, p. 219). Popularity
in karate and boxing inspired fitness regimes has been broadened by marketing
campaigns involving famous actress-turned advocates, such as Cindy Crawford,
Jodie Foster, and Claudia Schiffer (Green and Svinth, 2003, p. 219). Linda
Hamilton’s physique in Terminator II made “the muscular
and aggressive female image… an international phenomenon”
(Green and Svinth, 2003, p. 219).

Competitive Martial Arts Sports

Competitions such as the Ultimate Fighting Championships have further
solidified martial arts practices within modern pop culture. Now, even
non-participants may thrill to the victory and defeat of their favorite
fighters. Such sports competitions have been the premise of many popular
films.

The Effects of Marketing on “Traditional Martial Arts Culture”

How have martial arts culture changed? The examination of historical
texts written for practitioners of martial arts uncovers a wealth of knowledge
about the foundations of martial art practices. For example, in the authoritative
samurai text Hagakure, the author explains the role of the enlightened
samurai warrior as one who is obedient to his master and academically
trained. The authority of the master was unquestioned and second to none.

Every morning one should first do reverence to his master and parents
and then to his patron deities and guardian buddhas. If he will only
make his master first in importance, his parents will rejoice and the
gods and the Buddhas will give their assent. For a warrior there is
nothing other than thinking of his master (Tsunetonomo and Wilson, 2002,
p. 23).

Marketing has redefined the role of the martial arts instructor. Martial
arts instructors do not have a familial or cultural basis of training
in the United States. This is a very different business environment from
the ancient practices of generational instructors. As a result, marketing
has sought to establish the expertise of potential instructors in the
minds of students.

Before you can establish yourself as an expert, you have to have the
knowledge, experience, and credentials to back up your reputation. This
may not be possible or even desirable for every instructor. The best
plan of attack is to concentrate on the conventional media first and
use the non-conventional media as reinforcement (Kim, 2002, p. 171).

This radically changes the teacher-student dynamic. Earlier, students
were expected to display complete obedience to their masters. Now, it
is the masters who must seek student approval or risk losing business.

But understand that not many people can relate to a teacher like that.
People in our consumer culture are used to comparison shopping. They
select products and services that suit them. If their doctor, dentist,
hairdresser, or church isn’t listening to them, isn’t meeting
their needs, they will find another. In the eyes of the average American
consumer, you can be replaced. But if you continue to listen and meet
your students needs, you will remain an important part of their lives”
(Peterson and Vactor, 2002, p. 178).

This statement is also supported by the words of Taijiquan Master Niu
Sheng Xian. While Master Niu lives and teaches in Beijing, China, he also
believes that students come and go based on boredom and value.

I do not need to advertise. I have never made a commercial. I teach
my students well and thus they bring more students. Many students leave
because they get too tired or too bored. Some do not want to work. I
don’t worry about that. I just worry about making the students
that I have as good as possible. If I treat them well and show them
how to improve, other people will want to learn and more students will
come (Niu, 2006).

In the United States, involvement in martial arts is primarily seen as
a recreational activity. It is expected to be fun and this assumption
is supported by most teaching practitioners. Kim (2002) cautions against
monotony in drills, explaining that “boredom – your students’
boredom and your own – is your biggest enemy as a martial arts instructor.
Teaching classes every day, year after year, quickly become monotonous”
(p. 11). As a result, the authority of a martial arts master in the modern
day is open to constant questioning from students who may seek another
master with relative ease.

This ability of audience members to witness such frequent fighting spectacles
is a unique component of modern culture (Green and Svinth, 2003). Previously,
non-practitioners were barred from witnessing practices and competitions
were few and private. This publication of martial arts events through
marketing is one of the most profound effects of commercialization upon
martial arts practices.

Past generations of masters refrained from teaching their skills to
the public at large because of a widely shared belief that such knowledge
could be dangerous if given to ill-intentioned or irresponsible people.
In such cases, it was fear that high-level martial arts skills might
be used for destructive purposes. So, martial arts knowledge was carefully
guarded and taught only to those deemed worthy of using it for beneficial
purposes… The resulting risk that skills might be lost was considered
preferable to the risk that a malevolent person might learn martial
arts skills and use them for evil intent (Shengli and Yun, 2006, p.
xxiii).

Martial arts instructors no longer fear that their fighting techniques
will be used against them; instead, many educators view themselves as
business actors first. They gain financially by teaching their own brand
of martial art to the largest audience possible. This, in turn, leads
to greater publicity through practice, which may lead to more circles
in a cycle that perpetuates the physical practice of the martial arts
discipline, but largely sacrifices many of the philosophical foundations
of the martial arts practice.

The Future of Martial Arts Marketing

Advocates of education argue against too much marketing. Public relations,
publicity, and word of mouth are all important to the success of an educational
establishment (Firman, 1996). After all, a school’s reputation should
precede its advertising budget. Kim (2002) notes that this is no different
for a martial arts school:

An active, targeted and ongoing publicity campaign is essential to
the survival of a professional martial arts school… Ongoing publicity
makes your school name a household word… Make your school name
so familiar that people in your community automatically think of you
when they think “martial arts” (p. 167).

Such a marketing strategy has the additional bonus of saving money. A
successful publicity campaign can reduce the need for a formal marketing
budget (Kim, 2002).

The growth of the Internet has also had a direct effect of the marketing
of martial arts. “The internet is a fast growing medium that provides
easy access public relations” (Kim, 2002, p. 171). A martial arts
instructor can use the Internet in a variety of ways. “There are
two primary ways to use the internet to benefit your school: Promotion
and Communication. A well designed website is the cornerstone in any internet
strategy” (Kim, 2002, p. 197).

Many newsgroups, chat rooms, and public forums are available for the
general discussion of martial arts. A business may also generate name
recognition and respect by hosting a specially designed website. ”When
the internet first gained popularity, many businesses saw it as a selling
tool. Martial arts schools quickly put up websites and registered with
search engines only to be disappointed when no one signed up for lessons
online” (Kim, 2002, p. 197). As a result of this failure to attract
new students, websites evolved as primarily tools for reference.

Many Internet enthusiasts develop sites aimed at creating more interest
in martial arts, not necessarily registering new students. These enthusiasts
often choose to report book excerpts or publications featuring the history
or evolution of martial arts. For example, the website Complete Martial
Arts.com markets itself as a “complete and comprehensive up to date
information on all aspects of Martial Arts” (“Complete Martial
Arts.com,” 2006, p. 1). This website lives up to its claim by offering
one of the most thorough discussions of the history of martial arts in
the United States currently available on the Internet. The site’s
history is a reprint of The Original Martial Arts Encyclopedia
by John Corcoran and Emil Farkas.

Martial arts instructors can also use the Internet as a tool for communication.
Instructors post schedules, class information, and registration information
online. These are all tools of convenience that aid in retention of current
students. Professional associations created by martial arts business leaders
offer support and provide advice to potential martial arts entrepreneurs.
The Martial Arts Teachers Association presents a website that offers free
advice on low cost marketing strategies for martial arts schools.

Section III: Summary and Conclusion

How has marketing effected the practice of martial arts in the United
States? First, marketing has effected the number of people practicing.
What began as the interest of a select group of culturally inclined or
militarily trained individuals has evolved into a field that has attracted
hundreds of thousands of practitioners.

Marketing has also effected the quality of martial arts and martial arts
instruction. Martial arts have evolved from recreational activities with
many volunteer coaches to a lucrative industry where interested parties
may forge careers regarding the training of clients.

A more difficult consideration is marketing’s effect on the culture
of martial arts. Because marketing is a business practice, the involvement
of marketing is one aspect of a wider commercialization of the activity.
Potential students are prone to “shopping around” to see what
style of instructor and discipline best fit their needs. The most obvious
effect that marketing has had is on the role of instructor. While previous
martial arts teachers might have enjoyed total obedience in a military-like
training setting, the entertainment nature of martial arts in the United
States, as well as the business aims of individual schools, force instructors
to accommodate student desires. For example, the choice to only teach
children may not generate sufficient financial interest in some areas.
Teachers that fail to be flexible or to assess the needs of their local
population risk business failure. Such a commercial concern is very different
from traditional training or military settings.

Martial arts marketing tends to focus upon the physical aspects of the
practice, reflecting society’s sensationalization of violence. As
a result, the philosophical components of early martial arts disciplines
have been largely forgotten. As Zhang put it, “Everybody wants to
learn to fight. Nobody wants to learn real gongfu3.”
(2006). This is especially true of the multitude of martial arts sites
which focus upon drawing in as many students as possible to sustain a
strong business model.

Very little is written in academic journals specific to the marketing
of martial arts; the bulk of the academic literature involves either using
sports figures to market particular products or concentration of marketing
upon more popular recreational activity. As martial arts gains more supporters
in the U.S., this is likely to change. There are many potential areas
of study and research for the future. For example, researchers might seek
to evaluate specific forms and combinations of different marketing strategies
to demonstrate the most effective means of marketing in the martial arts
field. As gender and racial stereotypes are a concern in both martial
arts and in marketing, a researcher may explore the prevalence of stereotypes
within particular marketing campaigns. The economic effect of marketing
upon a specific school or area of the country may also be pursued.

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Rosenberg, D. (1995). Paradox and dilemma: The martial arts and American
violence. Journal of Asian Martial Arts 4(2), 10-33.

Shengli, L., and Yun, Z. (2006). Combat Techniques of Taiji, Xingyi,
and Baqua: Principles and Practices of Internal Martial arts
. Berkeley,
CA: Blue Snake Books.

Slack, T. (1998). Studying the commercialization of sport: the need for
critical analysis. Sociology of Sport Online Journal, 1. Accessed
online 11/25/2006 at http://physed.otago.ac.nz/sosol/v1i1/v1i1a6.htm.

Sunadomari, K. (2004). Enlightenment Through Aikido (Dennis Clark Trans.).
Berkeley, CA: North Atlantic Books.

Tsunetomo, Y. and Wilson, S. (2002). Hagakure: The Book of the Samurai.
Tokyo: Kondansha International Ltd.

Zhang Sheng Yi (November, 2006). Personal Interview. Conducted and translated
by Joseph D. McNamara. Beijing, China.

Appendix: Notes

1Translator’s Note: “Wushu,” is the classic
Chinese term for martial arts. However, because of the recent morphing
of traditional martial art forms into more aesthetically appealing gymnastic
style performances, Chinese practitioners have separated “modern
wushu” from traditional wushu. Modern wushu is now an accepted category
of performance art that will be presented in the 2008 Olympic Games. However,
it is hotly debated in China as to whether or not it should be considered
a “martial art”.

2Translator’s Note: “Gongfu” is the Romanization
of the Chinese characters These
characters are more commonly known in the west as “kung fu.”
However this is a misrepresentation of the original Chinese meaning. Gongfu,
in the sense meant here, represents hard-work, diligence, and mastery
of a skill. In Chinese, to say a person has real “gongfu”
is a high compliment of the person’s skill, whether it is in martial
arts or any other vocation.

3See footnote 2 above for an explanation of “gongfu”.

Use of the Athletic Coping Skills Inventory for Prediction of Performance in Collegiate Baseball

Abstract

The Athletic Coping Skill Inventory (ACSI-28) was completed by twenty-six
collegiate baseball players. Performance statistics were collected, including
batting average (BA), number of errors committed (ERR), and earned run
average (ERA) for pitchers. Regression analysis was carried out using
the seven areas of the ACSI-28 (peaking under pressure, freedom from worry,
coping with adversity, concentration, goal setting and mental preparation,
confidence and achievement motivation, and ‘coachability’)
as the independent variables, and the current season’s performance
statistics as the dependent variables. Correlation coefficients revealed
significance between concentration, confidence, and ERA, while there were
no significant relationships with BA or ERR and any of the psychological
variables. Many of the psychological variables were highly related. While
sequential linear regression did not reveal statistically significant
relationships between the performance statistics and the psychological
variables, large effect sizes indicated a strong degree of practical significance.
Specifically, peaking under pressure and ‘coachability’ appeared
to be strong predictor variables for ERA, concentration for ERR, and ‘coachability’
for BA.

Introduction

Athletes and theorists in human performance agree on the influence of
psychological factors in the performance of motor skills, particularly
at a high level of competition. As a result, an abundance of research
has been dedicated to finding out not only how to prepare athletes mentally
for high-pressure situations, but also what psychological factors are
specifically determinants of performance. The link between research and
application is of great importance because the business of sports is at
an all-time peak and athletes from early childhood to advanced age are
seeking ways to improve their game not only physically but mentally.

The use of self-reporting instruments that indicate specific psychological
skills is widespread, especially in collegiate and professional athletics.
Because of the comparable levels of physical abilities among top-tier
athletes, coaches seek to understand which psychological factors separate
the elite from the non-elite. In sports where “choking” may
cost a player or team a championship ring or millions of dollars, it is
understandable that non-invasive, simple indicators of psychological skill
measures have become popular.

The baseball skills of pitching, hitting, and fielding are arguably as
mental as they are physical. Pressure can affect a pitcher at any point
in the game; managers and pitching coaches make it their business to “know”
which pitchers will crumble under pressure and which will rise to the
occasion. Certainly, if a method for predicting correctly the mental toughness
(coping, if you will) of an athlete was shown to be valid and reliable,
it would be of great benefit to coaches, managers, and athletes alike.

The Athletic Coping Skills Inventory (ACSI-28), created in 1988, contains
seven sport specific subscales: coping with adversity (COPE), peaking
under pressure (PEAK), goal setting/mental preparation (GOAL), concentration
(CONC), freedom from worry (FREE), confidence and achievement motivation
(CONF), and ‘coachability’ (COACH) (Smith, Schutz, Smoll,
& Ptacek, 1995). Smith and Christensen (1995) defined the subscales
as follows as they apply to the sport of baseball:

Peaking under Pressure: is challenged rather than threatened by pressure
situations and performs well under pressure; a clutch performer

Freedom from Worry: does not put pressure on self by worrying about
performing poorly or making mistakes; does not worry about what others
will think if he/she performs poorly

Coping with Adversity: remains positive and enthusiastic even when
things are going badly; remains calm and controlled; can quickly bounce
back from mistakes and setbacks

Concentration: not easily distracted; able to focus on the task at
hand in both practice and game situations, even when adverse or unexpected
situations occur

Goal Setting and Mental Preparation: sets and works toward specific
performance goals; plans and mentally prepares self for games and clearly
has a “game plan” for pitching, hitting, playing hitters,
base running, and so on

Confidence and Achievement Motivation: is confident and positively
motivated; consistently gives 100% during practice and games and works
hard to improve skills

‘Coachability’: open to and learns from instruction; accepts
constructive criticism without taking it personally or becoming upset
(p. 402).

Smith and Christensen (1995) studied the usefulness of the ACSI as a
performance prediction tool in an elite athlete population, namely professional
baseball players. The participants were 104 minor league baseball players
(forty-seven pitchers and fifty-seven position players) of the Houston
Astros organization. Participants completed the ACSI during spring training;
batting averages (BA) for the position players and earned run averages
(ERA) for the pitchers were used as performance indicators. For position
players, only CONF was a significant predictor of BA, while ERA for pitchers
correlated significantly with CONF and PEAK scores. High CONF and PEAK
scores were related to lower ERA’s. Interestingly, ACSI results
were predictive of survival in professional baseball two and three years
after the testing was conducted and ACSI predicted ERA better than coaches’
ratings of physical skill.

Guarnieri, Bourgeois, and LeUnes (1998) used the ACSI with aspiring baseball
umpires at three professional umpire training schools in Florida. They
found that the more experienced umpires used athletic coping skills more
effectively than did those in training. Little research has been done
with the ACSI recently, other than the development of a Greek version
in 1998 (Goudas, Theodorakis, and Karamousalidis), and its usefulness
as a predictive tool for success in sport may remain to be seen.

The purpose of the current study was to examine the usefulness of the
ACSI in predicting BA, ERA, and errors (ERR) for collegiate baseball players.
The seven skills identified by the ACSI at surface level appear to be
related not only to each other, but also to success in discrete motor
skills in baseball that are always performed in the context of pressure:
batting, pitching, and fielding.

Method

Participants

Participants were twenty-six collegiate baseball players from the same
team that were active players during the 2005 season (twelve pitchers,
thirteen position players, and one pitcher/position player). The players
signed a consent form that assured them that their responses would only
be used for research purposes and would not be seen by any member of the
organization or any other individual other than the investigators. None
of the athletes had played baseball professionally.

Procedure

The ACSI (see Appendix) was distributed to the players at a regular meeting
of the team and instructions were read by the investigator. After the
participants signed and returned an informed consent form, they completed
the ACSI-28. Participants were instructed to consider each item and answer
without consulting any other individuals. The procedure took about ten
minutes, and all participants completed the instrument as instructed.
Each participant also indicated on the instrument his/her position, year
of eligibility, and scholarship status (full, partial, or none). Statistics
from the 2005 baseball season were collected; batting average (BA), number
of errors committed (ERR), and earned run average (ERA) for pitchers were
computed.

Statistical Analysis

The statistical analyses were carried out in three stages using SPSS
version 13.0 for windows (SPSS, 2004). First, data screening and descriptive
statistics were completed to examine participant characteristics. Regression
analysis was carried out using the seven areas of the ACSI (COPE, PEAK,
GOAL, CONC, FREE, CONF, and COACH), as the independent variables, and
the current season’s earned run average (ERA05), and batting average
(BA05) as the dependent variables. The primary outcome measures were analyzed
using three separate regression analyses. Differences (p values)
of less than .05 were considered statistically significant.

Results

After data collection, all variables were entered for analysis and screened
to determine if statistical assumptions were met. This screening included
examinations for distribution linearity and outliers. All statistical
assumptions were met for the variables.

In the current study, baseball players were broken down by position, scholarship,
and class level. Of this group, 54% were pitchers (n = 14), 23% were infielders
(n = 6), and 23% were outfielders (n = 6). Only one athlete did not receive
a scholarship; 85% percent of the athletes were on partial scholarships
(n = 22), and 11% were on full scholarships (n=3). Lastly, 27% were freshman
(n = 7), 19% were sophomores (n = 5), 19% were juniors (n = 5), and 35%
were seniors (n = 9). When examining the relationships between variables,
Pearson Product moment correlation coefficients revealed significance
between CONC, CONF, and ERA05, while there were no significant relationships
with BA05, ERR05, and any of the independent variables (Table 1). For
the psychological skills variables, COPE was significantly related to
PEAK, GOAL, and CONC. PEAK was significantly related to CONC and FREE.
Lastly, CONF, COACH, GOAL, and CONC were significantly related. These
correlations were moderately correlated, and ranged from r = 0.444 – 0.541
(see Table 1).

Table 1. Descriptive statistics and correlation coefficients between
ACSI variables and performance statistics.

Variable M SD AVG04 AVE05 ERA05 ERR05 COPE PEAK GOAL CONC FREE CONF COACH
BA05 0.30 0.13 0.50 —-
ERA05 6.98 2.70 0.32 NA —-
ERR05 4.00 3.99 NA 0.34 NA —-
COPE 2.04 0.48 -0.34 -0.13 -0.16 0.03 —-
PEAK 2.41 0.57 -0.34 -0.19 -0.23 -0.03 .521* —-
GOAL 1.74 0.71 -0.19 -0.30 0.11 -0.17 .541* 0.32 —-
CONC 2.41 0.41 -0.19 -0.17 -0.08 -0.41 .444* .606* .485* —-
FREE 1.74 0.73 0.08 -0.01 -0.12 -0.10 0.22 .447* 0.02 0.33 —-
CONF 2.63 0.39 -0.24 -0.02 0.22 0.14 -0.07 0.31 0.01 0.13 .408* —-
COACH 2.52 0.48 0.25 0.31 0.37 0.23 -0.13 0.17 -0.10 0.05 0.31 .408* —-

*p<.05

Sequential linear regression was used to determine significant psychological
predictors of ERA05 , ERR05, and BA05. There was not a statistically significant
relationship among the predictors and ERA05, F(7,6) = .507, p
= .802. A large effect size was evident, R2 = .37, indicative
of a strong degree of practical significance. Peaking and coaching appear
to be stronger predictor variables, each uniquely accounting for 5% of
the variance in the model (see Table 2).

Table 2
Results of Multiple Regression Analysis

Variable B SE B ß sr2
Regression for ERA
coping with adversity 0.53 3.06 0.13 0.00
peaking under pressure -2.24 3.04 -0.54 0.05
goal setting/motivation 0.39 2.28 0.10 0.00
concentration -0.26 2.50 -0.06 0.00
freedom from worry -0.41 1.80 -0.12 0.01
confidence 1.86 3.67 0.45 0.03
‘coachability’ 2.02 2.84 0.47 0.05
Regression for Errors
coping with adversity 4.77 4.22 0.74 0.07
peaking under pressure 3.25 3.08 0.67 0.06
goal setting/motivation -0.98 2.44 -0.18 0.01
concentration -11.45 3.95 -1.87 0.49
freedom from worry -0.25 2.58 -0.05 0.00
confidence 0.82 2.76 0.16 0.01
‘coachability’ 3.77 2.58 0.72 0.12
Regression for Batting Average
coping with adversity 0.19 0.18 0.84 0.10
peaking under pressure -0.09 0.13 -0.51 0.04
goal setting/motivation -0.08 0.10 -0.39 0.05
concentration -0.01 0.17 -0.03 0.00
freedom from worry 0.03 0.11 0.16 0.01
confidence -0.09 0.12 -0.48 0.05
‘coachability’ 0.14 0.11 0.79 0.15

There was not a statistically significant relationship among the predictors
and ERR05, F(7,7) = 1.46, p = .315. A large effect size
was evident, R2= .59, indicative of a strong degree of practical significance.
CONC was the strongest predictor, uniquely accounting for 49% of the variance
to the model. COACH was also a strong predictor, uniquely accounting for
12% of the variance to the model. COPE uniquely accounted for 7% of the
variance to the model. PEAK uniquely accounted for 6% of the variance
to the model.

There was not a statistically significant relationship among the predictors
and BA05, F(7,7) = .60, p = .745. A large effect size
was evident, R2 = .37, indicative of a strong degree of practical
significance. COACH was the strongest predictor, uniquely accounting for
approximately 15% of the variance to the model. COPE uniquely accounted
for 9% of the variance to the model. GOAL and CONF each uniquely accounted
for 5% of the variance to the model.

Discussion

The results of this exploratory study indicate that the usefulness of
the ACSI in predicting performance outcomes in collegiate baseball may
be of benefit. Due to the small sample size of this study, coupled with
the large number of predictor variables, no statistical significance was
found in any of the relationships. However, the large effect sizes for
all three criterion variables were indicative of a strong degree of practical
significance. Specifically, concentration appears to be strongly related
to errors, and ‘coachability’ to batting average. To even
a casual observer of baseball, this observation may seem to be simply
common sense. The usefulness of the ACSI-28 may be designed for managers
of relatively young teams where batting order, starting positions, and
pitching strategies have not yet been determined. If a coach knows (with
some certainty) which players are can be coached and which can maintain
high levels of concentration, the coach’s decisions can be based
more on fact than feeling. Please note that the use of the ACSI does not
guarantee success of the athletes who complete it or coaches who make
decisions based on it. However, I strongly suggest that managers take
advantage of these findings and add the ACSI-28 to their arsenal for strategic
decision-making.

Future research in this area should focus on obtaining larger sample
sizes. An increase in statistical power would likely identify statistically
significant relationships, given the meaningfulness of the predictor variables
in this study.

References

Goudas, M., Theodorakis, Y., and Karamousalidis, G. (1998). Psychological
skills in
basketball: Preliminary study for development of a Greek form of the Athletic
Coping Skills Inventory-28. Perceptual and Motor Skills, 86(1),
59-65.

Guarnieri, A., Bourgeois, T., and LeUnes, A. (1998). A psychometric
comparison of
inexperienced and minor league umpires
. Paper presented at the meeting
of the Association for the Advancement of Applied Sport Psychology, Hyannis,
MA.

Smith, R. E., and Christensen, D. S. (1995). Psychological skills as
predictors of
performance and survival in professional baseball. Journal of Sport
and Exercise Psychology
, 17, 399-415.

Smith, R. E., Schutz, R. W., Smoll, F. L, and Ptacek, J. T. (1995). Development
and
validation of a multidimensional measure of sport-specific psychological
skills: the Athletic Coping Skills Inventory-28. Journal of Sport
and Exercise Psychology
, 17, 379-398.

SPSS Version 13.0 [Computer Software]. (2004). Chicago, IL: SPSS.

Appendix

ACSI SURVEY
NAME:
POSITION: OF INF P C
YR: F SO JR SR
SCHOLARSHIP: NONE PARTIAL FULL

0 = ALMOST NEVER, 1 = SOMETIMES, 2 = OFTEN, 3 = ALMOST ALWAYS

  1. On a daily or weekly basis, I set very specific goals for myself that
    guide what I do. 0 1 2 3
  2. I get the most out of my talent and skills. 0 1 2 3
  3. When a coach or manager tells me how to correct a mistake I’ve
    made, I tend to take it personally and feel upset. 0 1 2 3
  4. When I am playing sports, I can focus my attention and block out distractions.
    0 1 2 3
  5. I remain positive and enthusiastic during competition, no matter how
    badly things are going. 0 1 2 3
  6. I tend to play better under pressure because I think more clearly.
    0 1 2 3
  7. I worry quite a bit about what others think about my performance. 0
    1 2 3
  8. I tend to do lots of planning about how to reach my goals. 0 1 2 3
  9. I feel confident that I will play well. 0 1 2 3
  10. When a coach or manager criticizes me, I become upset rather than
    helped. 0 1 2 3
  11. It is easy for me to keep distracting thoughts from interfering with
    something I am watching or listening to. 0 1 2 3
  12. I put a lot of pressure on myself by worrying how I will perform.
    0 1 2 3
  13. I set my own performance goals for each practice. 0 1 2 3
  14. I don’t have to be pushed to practice or play hard; I give 100%.
    0 1 2 3
  15. If a coach criticizes or yells at me, I correct the mistake without
    getting upset about it. 0 1 2 3
  16. I handle unexpected situations in my sport very well. 0 1 2 3
  17. When things are going badly, I tell myself to keep calm, and this
    works for me. 0 1 2 3
  18. The more pressure there is during a game, the more I enjoy it. 0 1
    2 3
  19. While competing, I worry about making mistakes or failing to come
    through. 0 1 2 3
  20. I have my own game plan worked out in my head long before the game
    begins. 0 1 2 3
  21. When I feel myself getting too tense, I can quickly relax my body
    and calm myself. 0 1 2 3
  22. To me, pressure situations are challenges that I welcome. 0 1 2 3
  23. I think about and imagine what will happen if I fail or screw up.
    0 1 2 3
  24. I maintain emotional control no matter how things are going for me.
    0 1 2 3
  25. It is easy for me to direct my attention and focus on a single object
    or person. 0 1 2 3
  26. When I fail to reach my goals, it makes me try even harder. 0 1 2
    3
  27. I improve my skills by listening carefully to advice and instruction
    from coaches and managers. 0 1 2 3
  28. I make fewer mistakes when the pressure’s on because I concentrate
    better. 0 1 2 3

‘Sponsorship in the Trenches’: Case Study Evidence of Its Legitimate Place in the Promotional Mix

Abstract

An important theme in sponsorship literature involves its definition and its place in marketing theory. With regards to the latter, differing opinion exists as to whether sponsorship is a subset of advertising or whether it is a distinct member of the promotional mix. This research adopts a case study approach to argue that sponsorship should be viewed – both in marketing theory and in business practice – as a distinct and legitimate member of the promotional mix. The subject of the case is KMAC, a sports marketing agency specializing in sponsorship. Results support sponsorship’s inclusion in the promotional mix and outline future research.

Introduction

Sponsorship is a promotional practice that has evolved from its roots as a tool for corporate donations (Wilkinson, 1993) to a highly-developed course of action by which both the sponsor (investor) and the sponsee (property) benefit in a marketing relationship (Polonsky & Speed, 2001). Its rapid adoption into practice by organizations is reflected by the huge growth of worldwide sponsorship investments, which went from US $500,000 in 1984 to what was expected to reach US $28 billion in 2004 (IEG, 2003). This impressive growth in practice, however, has not been matched by theory development. Although a difficult concept to define, the majority of the definitions in related literature are relatively similar (Olkkonen, 2001) but sponsorship’s role in relation to other resource and promotional generating strategies (i.e. philanthropy, advertising, cause-related marketing) remains unclear (e.g. Polansky & Speed, 2001). In particular, sponsorship’s position in marketing’s traditional promotional mix ranges from no inclusion at all (e.g. the vast majority of marketing and marketing communications texts) to recognition that it is an integral part of the communications mix – alongside publicity, public relations, sales promotions, personal selling, and advertising (Crimmins & Horn, 1996; Meenaghan, 2001; Tripodi, 2001; Crompton, 2004). This is supported by a number of studies suggesting that sponsorship plays an important role in supporting an organization’s attainment of its communications objectives (e.g. awareness, reach target markets).

The purpose of this research is to provide evidence to previous academic work (e.g. Meenaghan, 1991; Tripodi, 2001) arguing for sponsorship’s inclusion as a legitimate member of the promotional mix by presenting the case of a successful Canadian sport marketing firm.

Sponsorship and the Promotional Mix

Sponsorship growth is credited, in part, to the increased amount of clutter found in traditional media towards the end of 1970’s (Otker, 1988; Meenaghan, 1991; Sandler & Shani, 1993; Wilkinson, 1993). The increase in the number of television and radio networks available created added clutter in the marketplace and the competition between advertisers to attract consumers’ attention was fierce. As a result, the effectiveness of the ability of advertising to reach consumers was questioned (Howard & Crompton, 1993). For many, sponsorship became an effective and less costly alternative to break through the clutter in order to reach specific targets (Mullin, Hardy & Sutton, 2000). In this regard, a number of studies supporting sponsorship’s distinction from advertising have emerged in the literature emphasizing that it (i) functions differently, (ii) is perceived by audiences differently, and (iii) includes the ‘association’ element that advertising does not (see Javalgi, Traylor, Gross, & Lampman, 1994; Hoek, Gendall, Jeffcoat & Orsman, 1997; Bloxom, 1998).

Nevertheless, as companies’ investments in sport sponsorship increased, so did the need to justify its “Return-On-Investment” (ROI). Thus, the establishment of clear and measurable objectives was identified as important to sponsorship programmes. Irwin and Asimakopoulos (1992) suggest that corporations attempt to achieve objectives that are corporate in nature or specific product/brand related. Similarly, Sandler and Shani (1993) identify three groups of sponsorship objectives: broad corporate objectives (image related), marketing objectives (brand promotions, sales promotions), and media objectives (reach target markets, cost efficiency). Overall, much of the research on sponsorship objectives tends to be dominated by corporate image and/or public goodwill categories (Otker, 1988; Witcher, Craigen, Culligan, & Harvey, 1991; Kuzma, Shanklin, & McCally, 1993).

Berrett (1993) suggests that sponsorship is often used by corporations to achieve multiple objectives. While others, such as Irwin and Sutton (1994) and Crompton (2004), agree, Crompton (2004) proposes that enhancing profitability by generating additional sales remains the ultimate goal of a total communications strategy. Thus, it could be argued that sponsorship plays a strategic role in communicating an organization’s objectives.

The remarkable increase in the number of sport properties available and the number of sponsors investing in sport properties suggest that sponsorship is able to assist a company to achieve its corporate and marketing objectives. This, in turn, would lend support to Tripodi’s argument (2001) that sponsorship (as a promotional tool) has become one of the top promotional considerations for marketers. A well-planned and coordinated approach to communications appears essential if sponsorship is to be effectively integrated into other marketing activities. Keller (2003) suggests that event sponsorship provides an interesting communication option for a company, as the brand becomes engaged during a “special and relevant moment in consumers’ lives” (p.315). In this way, how is sponsorship different from advertising?

As noted by Brooks (1994), a key challenge for sponsorship is to provide evidence that it is more effective than advertising or sales promotion. According to Meenaghan (2001), advertising seeks to “exploit” emotion, while sponsorship strives to “connect” with the emotion inherent in the property (e.g. sport). The association between the two parties (sponsor and sponsee) is often felt to be the key differentiator from advertising as it enhances the relationship beyond a basic cash purchase of promotional value (e.g. McCarville & Copeland, 1994). For Crimmins and Horn (1996), sponsorship is a way to persuade consumers indirectly through an association with a property. If used strategically, it is suggested that a sponsorship programme can be developed into a distinctive competence, thus creating competitive advantage (Amis, Slack & Berrett, 1999).

Gaining a competitive advantage is becoming more of a challenge within a cluttered market place in which there are increased incidences of ambush marketing (Sandler and Shani, 1998; Hoek and Gendell, 2001; Crompton, 2004; Seguin, Teed & O’Reilly, 2005). This has led corporations to explore new ways to activate (leverage) their investments and maximize sponsorship return. Tripodi (2001) suggests that firms should employ an integrated approach and use sponsorship with other elements of the communications mix (publicity, advertising, sales promotion, personal sales). A synergetic effect will not only maximize communications effectiveness, but also contribute to building brand equity (Tripodi, 2001; Keller, 2003). The literature provides evidence that sponsorship’s membership in the promotional mix should be legitimate, however, uncertainty remains. The current research involves a case study designed to further support this literature.

Case Methodology

The case study presented in this paper was selected from a number of in-depth interviews conducted by the authors as part of a major research project currently underway in Canada. More than thirty-five sport properties, corporate sponsors, and sport marketing firms took part in this research, which examined a number of questions related to sponsorship acquisition, sponsorship objectives, sponsorship leveraging, and sponsorship evaluation. The case presented herein comes from a successful Canadian marketing firm called K.Mac & Associates (K.Mac) that specializes in sport sponsorship. The analysis of this case will shed some light on sponsorship’s true strategic position with respect to the promotional mix.

The data was collected through an in-depth semi-structured interview over two hours with Keith McIntyre, the founder and CEO of K.Mac & Associates, on January 26th, 2005. Scripted questions and open discussion took place, with the entirety of the conversation being recorded, transcribed, and analyzed. In addition, secondary data was obtained in the form of case studies, marketing strategies, and websites.

The Company: K.Mac & Associates

K.Mac & Associates (K.Mac) was founded in 1992, at a time when sponsorship in Canada experienced significant growth. For the first few years, K.Mac worked closely with a number of professional hockey players with the main objective of maximizing potential revenues from promotional activities. The firm quickly expended its services and has since worked with hundreds of Olympic and professional athletes, properties, sponsors, and events, including Major League Baseball, hockey superstar Mark Messier, Procter & Gamble (for eleven years), the National Football League, Pfizer (for five years), UPS, the Canadian Olympic Committee, General Mills (for seven years), and the National Hockey League. The founder attributes much of K.Mac’s success to being a “marketing resource company with sport as the playing field, and not a sport marketing firm” (McIntyre, personal communication, Jan. 26, 2005). Sponsorship “leveraging” comprises a significant portion of its business, driven by the firm’s focus on ‘superior execution’ and ‘measurable outcomes linked to objectives’ which K.Mac can perform at a level of detail and execution that a large agency cannot.

Specific to sponsorship, K.Mac follows a detailed, focused four-step process of ‘relevance, differentiation, integration, and activation’ in which the client’s objectives and motivations (either sponsor or sponsee) are researched in detail and followed through on each step. In implementing its process, K.Mac has assembled a tool box of key leveraging tactics that it customizes based on the situation. Further, it has developed its own evaluation methodology based on incremental sales: “we are tracked on incremental units…I can tell you the incremental sales we’ve provided to our clients” (McIntyre, personal communication, Jan 26th, 2005). Being able to track sales has been identified as a key factor by K.Mac, if sponsorship is to be taken as a serious component of the promotional mix. Shank (2005) noted that the eventual objective for nearly all organizations involved in sponsorship programmes is an increase in sales. This seems to be supporting Crompton’s (2004) argument, which suggested that enhancing profitability by generating additional sales remains the ultimate goal of sponsorship. However, measuring increases in sales that are directly linked to a sponsorship remains a challenge.

Results: ‘Sponsorship in the Trenches’

Given that the initial investment only buys the rights to an association, it has been suggested that sponsors “leverage” their sponsorship by spending resources into additional communications/promotional activities (Meenaghan, 1991, 1998, 2001; Sandler & Shani, 1993, 1998; Amis et al.; 1999; Tripodi, 2001; Crompton, 2004; and Seguin et al., 2005). This can be achieved by using a variety of marketing communications elements (Ludwig & Karabetsos, 1999; Meenaghan, 2001). By supporting sponsorship with other marketing components such as advertising, sales promotion, point-of-purchase, on-pack signage, and production of merchandise, a corporation may be in a better position to claim its space in an increasingly cluttered sponsorship environment (Séguin, 2003). It has been suggested that the sums required for successful leveraging may be up to three to five times the initial expenditure (Abratt & Grobler, 1989, Witcher et al., 1991; Shanklin & Kuzma, 1992). Such an approach to sponsorship was found to be embraced in practice by K.Mac: “sponsorship is not a money grab…it is about business, selling product. I work in the trenches and that is where it is” (McIntyre, personal communication, Jan. 26, 2005).

Given sponsorship’s varied roots in philanthropy and advertising, it is interesting to note that, according to K.Mac, sponsorship is still misunderstood within corporate Canada, especially within the advertising industry. For many, sponsorship is no different than advertising and, in fact, is treated as advertising:

I’ve got clients that disagree, one says ‘if I want foot-steps in my store I’ll put my most popular product on sale’…this is not helpful except for awareness building. We are interested in effecting consumer behaviour. What is the incremental [sales] volume? That is what we want…to drive business” (McIntyre, personal communication, Jan. 26, 2005).

While more research is needed to identify the reasons for this lack of differentiation between sponsorship and advertising, it is suggested that large advertising agencies understand advertising and public relations, but not necessarily the role of sponsorship. As a result, “they may fail to see that sponsorship meets the needs of sponsor and sponsee driven by the passion of both the property and the consumer, as opposed to an advertising deal which is one directional” (McIntyre, personal communication, Jan. 26, 2005). Accordingly, it is suggested that a number of marketing executives working for sport properties also have advertising backgrounds.

To further support this argument, K.Mac. provides an example of how sponsorship has been used to ‘ambush’ an advertising campaign from a competitor. While in the past, ambush marketing research has primarily examined the effects of ‘ambushers’ (eg. corporations not having official rights) over official sponsors, it is suggested that ambush may be examined from a different perspective. For example, a company that acquires the rights to sponsor a National Olympic Committee (General Mills in Canada), begins negotiation with the official broadcaster (CBC) to buy all advertising inventory within the specific product category. As the bidding with a competitor (Kellogg) intensifies, the company (General Mills) pulls out just prior to the deadline. While the competitor may have won the television advertising rights for Olympic coverage, the official sponsor has the opportunity to ‘ambush’ the advertiser by focusing its efforts at the retail: “let them [competitor] buy advertising and let sponsorship with its direct, authentic association ambush [the advertising]” (McIntyre, personal communication, Jan. 26, 2005). In this context, sponsorship is the only way to have “authentic” association and sponsors must be strategic in providing promotional programs that take advantage of this ‘authenticity’. This strategy was used by General Mills during the 2000 and 2002 Olympic Games. A Canadian Olympic Committee sponsor, General Mills leveraged its sponsorship by sponsoring “Team Cheerios” which consisted of a group of selected Olympians featured on cereal boxes (Cheerios). This included pictures, bios, and personal stories of the athletes. This was an excellent way for consumers to discover the athletes and ‘connect’ with them on a personal level. While competitor Kellogg’s cereal brand “Victor” secured television advertising rights for both Olympics, General Mills’ strategy was focused at the retail. “We worked closely at developing relationships with key accounts at the retail, making sure they understood that we held the authentic association with the Olympic rings, the Games and the athletes, we owned the space!” (McIntyre, personal communications, Jan.26, 2005). General Mills’ approach to Olympic sponsorship was fully integrated into the marketing and promotional mix. This included product packaging (integrating rings and athlete profiles on boxes), pricing (special pricing leading up to and during Olympics), distribution (working with key retail accounts, developing in-store positioning) and promotional mix (developing sales promotion campaigns, athletes’ appearances, personal selling programs, advertising, publicity). The promotional campaign provided something “meaningful” to consumers and received tremendous publicity. This approach to sponsorship enables associations linked to emotions and passion, as opposed to signage or rink boards. Meenaghan’s (2001) work on sponsorship effects on consumers supports the importance of the emotional connection in sponsorship. When asked to summarize his view on sponsorship in the promotional mix, K.Mac clarified:

I look at sponsorship as part of the promotional mix – and as one of the four or five components of how you build a communications program. Signage [advertising] used to be a big deal but that is now just wallpaper. Sponsorship now is about defining your consumer (demographics plus psychographics, what makes them tick). Then you know what they want and can identify a sponsorship that meets those criteria. Then, you build that link by telling them why it is important to them [consumer]. You also need to tell them [consumer] on their own terms. Get them excited and meet their needs and wants. It has to get really deep these days to really actually make it work (McIntyre, personal communication, Jan. 26, 2005).

Clearly, such an approach makes sponsorship, like advertising, as valid a promotional tool as any member of the promotional mix. In fact, the evidenced above is supporting that in some cases, it may be a superior communications choice when the objective is to drive sales. In this regard, K.Mac points out: “our Litmus test is [to ask] what will sponsorship do to effect consumer behaviour? What will it do to meet the client’s pillars [objectives] of evaluation?” (McIntyre, personal communication, Jan. 26, 2005).

The case of K.Mac provides additional support for sponsorship as a legitimate member of the promotional mix. First, as suggested in the literature, a key benefit associated with sponsorship is the ability to target specific markets (Sandler & Shani, 1993; Irwin & Sutton, 1994; Mullin et al., 2000; Shank, 2005). This is supported in this case, as K.Mac suggests “Sponsorship is very target driven…corporations want to communicate with their core targets” (McIntyre, personal communication, Jan. 26, 2005).

Second, sponsorship’s ability to focus on the exact objectives of the sponsor was highlighted. “Companies do not care about what is going on behind the scenes. They are very sophisticated. Signage…is not enough. Brand managers’ careers are on the line, they do not take big risks and throw up signs; they want return (McIntyre, personal communication, Jan. 26, 2005). A number of authors (e.g. Arthur, Scott, Woods, & Booker, 1998; Amis, Slack & Berrett, 1999; Fahy, Farrelly, & Quester, 2004) identify sponsorship’s ability to achieve specific objectives as an efficient way by which to differentiate a sponsor from competitors.

Third, the ability to build a promotional campaign around a sponsorship was highlighted and the need to leverage a sponsorship was strategically stressed by McIntyre: “a major threat to my business is when a sponsor occupies a category but does not leverage [that sponsorship]” (McIntyre, personal communication, Jan. 26, 2005). Further, he added that “my rule of thumb is that you must leverage at least 2:1. Tylenol [sponsor of Rowing Canada and Canadian Olympic Committee] leveraged 6:1 as a minimum, maybe even 8:1 with TV” (McIntyre, personal communication, Jan. 26, 2005). Leveraging is a topic that has been touched on by numerous authors in the literature. It provides ways to communicate with the consumers and has also been identified as an effective way to combat ambush marketing (Sandler & Shani, 1993; Meenaghan, 1998; Shani & Sandler, 1998; Crompton, 2004; Seguin et al., 2005).

Fourth, the need to evaluate sponsorship in a more sophisticated fashion than eyeballs reached was emphasized. “For the evaluation of my sponsorships, renewal is one thing but ‘up-ing’ [the value of the] sponsorship is another. [For the sponsor], evaluation is tracked on volume from incremental sales volume” (McIntyre, personal communication, Jan. 26, 2005). The evaluation of sponsorship has been a contentious point in the literature. In fact, Slack and Berrett (1995) suggest that evaluation is controversial and a challenging component of sponsorship. As companies seek different objectives from sponsorship, different types of measures and designs should be required for each objective (Crompton, 2004). Despite such planning, the plurality of objectives pursued by corporations and the use of other promotional tools for leveraging purposes makes sponsorship evaluation a complicated task (Meenaghan, 1983; Berrett, 1993, Crompton, 2004). This case suggests that perhaps the industry has found ways to measure sponsorship return that have yet to be tested or reported from academics (see Hoek & Gendell, 2001).

Finally, the case study provides that future trends may increase sponsorship’s effectiveness as compared to advertising:

…think about the playing field for a minute. TV is powerful, 700 channels. Mass advertising moves awareness of new products but it does not do the trick for sales. People can easily avoid commercials…so unless there is an inherent interest or association [in the product that] people have, it [the promotion] doesn’t work (McIntyre, personal communication, Jan. 26, 2005).

Table 1 below summarizes these six supporting points.

Table 1: Additional Support Points for Sponsorship in Promotional Mix

Point Support Related Literature
1 ability to target specific markets Shank, 2005; Mullin et al., 2000; Irwin & Sutton, 1994; Sandler & Shani, 1993
2 ability to specifically address sponsors objectives Arthur, 1998; Fahy, Farrelly, & Quester, 2004; Amis, Slack & Berrett, 1999
3 ability to use sponsorship as the basis for a complete promotional campaign Crompton, 2004; Seguin et al., 2005; Sandler & Shani, 1998, 1993; Meenaghan, 1998
4 the fact that sponsorship requires more sophisticated evaluation than advertising Hoek & Gendell, 2001; Meenaghan, 1983; Berrett, 1993, Crompton, 2004
5 future business trends enabling sponsorship effectiveness Suggested by Séguin & O’Reilly, 2005

Conclusion

The significance of the K.Mac case to the sport industry is its demonstration that, in practice, sponsorship is used as part of the promotional mix of sponsors. In general, results strongly support that authors of journal articles and textbooks need to consider what is happening in practice in their future writings. This would, in turn, provide students and practitioners with the knowledge of the strategic potential that sponsorship possesses, “sponsorship will play an increased marketing role in the future. It gives you the platform of a unique association that allows you to get your message out to a targeted passionate and emotional group” (McIntyre, personal communication, Jan 26th, 2005). Industry trends and sponsorship spending trends support this continued growth of sponsorship in the future, further supporting the need to formalize its strategic place in marketing strategy classifications.

Although limited to a single case, current research provides an impetus for continued work in establishing sponsorship as a legitimate member of the promotional mix alongside advertising, public relations, publicity, sales promotion, and personal selling. In this regard, quantitative research on large samples of promotional activity is required to demonstrate sponsorship’s distinction from advertising and its important role in collaboration with the other established members of the promotional mix.

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