There are a number of factors that can influence an athlete's
performance during a game other than the athlete's skill. Athletes
must perform in front of crowds in every game, and crowds express their
feelings about athletes' performances by, for instance, cheering
(supporting them) or jeering (discouraging them). The presence of such
an audience may affect team and individual athlete performance.
Social facilitation has been characterized as the effect of
observers on individual performance (Butler & Baumeister, 1998;
Zajonc, 1965). In general, research shows the presence of one or more
spectators can enhance performance if the skill is easy or well learned,
but performance may decrease if the task is difficult or unfamiliar
(Cottrell, Wack, Sekerak, & Rittle, 1968; Forgas, Brennan, Howe,
Kane, & Sweet, 1980; Strauss, 2002a; Zajonc, 1965). For example, in
one of the earliest studies on social facilitation, Travis (1925) found
that participants engaged in a pursuit-rotor task performed
significantly better (made fewer tracking errors) when they were
observed by an audience of four to eight people compared to when they
performed alone. Michaels, Blommel, Brocato, Linkous, and Rowe (1982)
showed that better pool players improved their performance when they had
a small group of spectators, but mediocre players had a decrease in
performance when being watched. Taken at face value, then, given that
the skills athletes perform during their sport are familiar,
well-practiced ones, one might expect positive effects of social
facilitation to exist for athletes during sporting games (cf., Carron,
Burke, & Prapavessis, 2004).
But of course, audiences for sporting events are not merely
present; they do not merely observe the performance of athletes during a
game. Rather, they engage in a variety of behaviors that interact with
the players for each team in games (Cox, 1985). They may applaud when a
receiver catches the football and heads for the end zone. They may
heckle the batter on deck for the opposing team. They may offer silence
for the player shooting from the foul line if she or he is on their
preferred team, or they may rumble loudly trying to distract the shooter
if she or he is on the non-preferred team. In simple terms, audiences
cheer and jeer. Audience effects, then, may be very different than mere
spectator effects. Studies have shown clearly that audiences can impact
physiological variables of athletes (e.g., arousal, cardiac
performance), as well as cognitive variables such as self-concept and
perceptions of performance (e.g., see Jones, Bray, & Lavallee,
2007). However, less is known about how particular audience behaviors,
like cheering or jeering, influence athletes' actual performance.
The notion that what audiences do interacts with and has an effect
on the performance of athletes ostensibly is substantiated in the
home-field advantage literature. Home-field advantage refers to the
established finding across several sports that, given a balanced home
and away schedule, teams typically win more home games than away games
(Courneya & Carron, 1992; McCutcheon, 1984; Nevill & Holder,
1999). Many aspects of the sports situation, such as facility
familiarity, relative fatigue, referee bias, and territorial defense
effects have been proffered as influential factors in home-field
advantage (Moore & Brylinsky, 1993; Salminen, 1993; Schwartz &
Barsky, 1977). But researchers, athletes, and fans repeatedly assert
that the crowd is a key element. More specifically, it is widely
believed that "crowd support," "supportive
audience," "home crowd," "home team fans" is
one of the aspects that gives the home team the edge (Courneya &
Carron, 1992; Schwartz & Barsky, 1977; Tauer, Guenther, & Rozek,
Presumably, having a supportive and encouraging audience motivates
the athletes to perform better. Some studies have investigated whether
having an audience present enhances performance, and have found rather
surprising results. For example, taking advantage of quarantine due to a
measles outbreak that resulted in some season basketball games being
played with an audience and others without, Moore and Brylinsky (1993)
found measures of team performance did not differ depending on audience
presence, by one analysis. However, by a second analysis examining
effect sizes, they concluded that team performance was actually better
when there was no audience. In one of the few experimental studies in
the area, Forgas, et al. (1980) systematically varied the composition of
the audience for squash players, with no audience, female audience, and
male audience, and found overall, the presence of an audience decreased
performance. But importantly, these audiences were spectator-only; the
observers did not interact with the players in any way.
Other studies have tried to consider the mood or reactions of the
audience as a predictive variable for team performance. For instance,
Salminen (1993) studied Finnish soccer, hockey, and basketball matches,
with a focus on the relationship between audience reactions and goals
and penalties, based on 5-minute game intervals. Results suggested
neither enhancing effects of a supportive audience nor inhibiting
effects of an unsupportive audience. Focusing more exclusively on
moments of negative or unsupportive audience action, Greer (1983) found
the five minutes following particularly noticeable audience protesting
behaviors (e.g., collective booing) were associated with basketball home
teams gaining advantage (more scoring, fewer violations/turnovers)
simultaneous with visiting teams suffering decline (fewer successful
shots, more violations/turnovers). They suggested the primary
contributor to home-team advantage may be the visiting team performance
being actively hurt by unsupportive audience behavior (rather than, say,
that the audience behavior generated a bias in refereeing). Thirer and
Rampey (1979) discovered interesting relationships between extreme
negative audience behavior and team performance in basketball. Normal
audience conditions were associated with fewer fouls and turnovers for
the home team compared to visiting teams. Yet, in 5-minute periods
following extreme negative audience tactics (i.e., behavior beyond
normal 'booing', such as throwing objects, fighting, chanting
obscenities), the home team tended to have more infractions than
visitors. That is, extreme anti-social behaviors of the audience were
predictive of performance decrements for the home team; this audience
behavior was not related to changes in performance of visiting teams.
Ultimately, years of research have revealed contradictory results
about both the reality of the home-field advantage and the specific role
of audiences (e.g., Baumeister, Hamilton, & Tice, 1985; Baumeister
& Steinhilber, 1984; Schlenker, Phillips, Boniecki, & Schlenker,
1995; Smith, 2005; Strauss, 2002b; Tauer, et al., 2009; Wright, Voyer,
Wright, & Roney, 1995). Yet despite these equivocal findings,
perception and belief in enhancing effects of the home crowd remain
strong in fans and athletes alike, as well as researchers and the media
(e.g., Bray & Widmeyer, 2000; Schlenker, et al., 1995; Smith, 2005;
Wallace, Baumeister, & Vohs, 2005; Wang, 2006; Wolfson, Wakelin,
& Lewis, 2005). Moreover, it is worth noting that most of the
studies that consider audience factors and sports performance have been
archival, observational, or quasi-experimental; there has been no
systematic control over the behavior of the audience, for example. In
addition, most studies have looked at whole game situations and overall
team performance (e.g., number of points, wins/losses, RBIs, etc.). Of
course, these are important, as indeed the performances of interest do
occur in real games, with uncontrolled audiences and whole teams (Greer,
1983; Moore & Brylinsky, 1993; Tauer, et al., 2009). But there seem
to be two largely untested issues embedded in conclusions about the role
of interactive audiences in home advantage: (1) that team outcomes
reflect performance across individual athletes and various skills; and
(2) that specific audience behaviors are at least partially responsible
for individual athletic performance leading to team outcomes. That is to
say, it is commonly presumed that the crowd's cheering and jeering
offers social support to their team and that such behavior actually
affects specific skills of individual athletes in ways that produce
differential outcomes for the teams (cf., Greer, 1983; Nevill &
Holder, 1999; Tauer, et al., 2009).
The assumption is not without merit. After all, we know that
supportive behavior from coaches reinforces specific team and individual
skills, at least during practices. Operant techniques have been used
widely to develop and improve motor behaviors, many related specifically
to performance in sports. For example, contingent access to music
increased the productive practice behaviors and decreased the
nonproductive behaviors of teenaged competitive swimmers (Hume &
Crossman, 1992). Also working with swimmers, McKenzie and Rushall (1974)
found that social reinforcement from peers and praise from coaches
increased practice attendance as well as the number of laps individuals
swam each day. Allison and Ayllon (1980) showed that specific
consequences delivered by coaches affected the blocking skills of
teenage football players. Given encouraging responses (e.g.,
"good," "that's better") from the coach for
correct blocks and unsupportive responses (e.g., "you lack
courage," "horrible") plus having to run laps after
incorrect blocks, the young players' good blocks increased and
their errors decreased compared to baseline performance. Similar
behavioral coaching resulted in improvements for three gymnastics skills
and three tennis strokes as well (Allison & Ayllon, 1980). Such
behavioral coaching (i.e., praise, corrective feedback, tracking
data/performance charts) also has been shown effective for increasing
correct tags of inline roller speed skaters (Anderson & Kirkpatrick,
2002) and for improving punching and kicking techniques of martial
artists (Harding, Wacker, Berg, Rick, & Lee, 2004). These studies
primarily consider the effects of coaches' behaviors on
athletes' performance, but it seems a plausible extension, and
certainly congruent with popular opinion, that cheering (praise) from
fans also could be a reinforcing consequence of individual athletic
skills and jeering could be a punishing consequence. Yet, there is
little direct experimental evidence to support this contention.
The present experiment investigated the effects of differential
audience behavior (cheers, jeers, silence) on individual golf, baseball,
and basketball players' performance of a particular sport-specific
skill. Given that in golf, silence is encouraged in the audience, it was
hypothesized that athletic performance in golfers would be best when the
audience was silent as opposed to cheering or jeering. However, it was
hypothesized that athletic performance for baseball and basketball would
increase when the audience cheered over being silent and that
performance would be lowest with the jeering audience.
This study used a 3 x 3 mixed factor design. The independent
variables were type of audience feedback (cheers, jeers, or silent), a
within subjects manipulation, and type of sport played (golf, baseball,
and basketball), a between subjects variable. The dependent variable was
accuracy for the sport-specific tasks. These tasks were operationally
defined as the distance from the flag where the golf ball stopped,
number of strikes pitched by baseball players, and number of successful
free throws by basketball players.
Athletes. Thirty-two college athletes at a small Division III
all-male college volunteered as participants in this study: 8 golfers,
10 baseball players, and 14 basketball players. All participants were
undergraduate students who played their respective sports regularly as
members of the college teams.
Audience. The audience consisted of undergraduate students from the
same college who volunteered from introductory psychology classes and a
campus fraternity. Audience size was always 10 students. In order to
control extraneous variables during each feedback condition, each
audience member was randomly assigned a specific "cheer"
(e.g., "Yeah! Great job!"; "You are the man!") and
"jeer" (e.g., "Miss it!"; "You suck!") to
use in the good (cheer) and bad (jeer) feedback conditions. Audience
members were told to speak from the script only, and they shouted their
various cheers or jeers through each of 10 trials in each condition. In
the silent condition, the audience was present but not interactive for
10 trials (i.e., spectator only).
Testing for baseball took place on the college baseball field.
Materials used included a regulation baseball, a regulation height
pitching mound, and a net with a target 30 inches high and 17 inches
wide (i.e. strike zone). Testing for the basketball task took place in
the college basketball gymnasium. Materials used included a regulation
basketball, a regulation basketball goal (10 feet high), and a
regulation free throw line (15 feet from the goal). Testing for golf was
examined on the college campus driving range. The materials for this
sport included 30 regulation golf balls, a 9-iron golf club, and a flag
100 yards from the hitting point. A 100 ft measuring tape measured the
distance, in yards, each ball stopped from the target.
Testing took place in different sessions according to the sport. As
participants arrived, they signed an informed consent form. All athletes
were allowed to warm up for 10 minutes before the test trials began.
Athletes were told they would perform their sport skill 30 times in
front of an audience comprised of fellow students at the college. Given
the small size of the college, athletes may have known some of the
audience members. The audience was then put into the stands around the
test area. Athletes were brought in one at a time, and each completed 10
sport specific task performances in the good, bad, and silent conditions
for a total of 30 trials (golfers hit the balls from 100 yards away from
the target; baseball pitchers pitched from the pitching mound;
basketball players shot from the free throw line). The order of the
audience conditions was randomized across participants in each sport.
Each audience member was assigned a feedback statement for the session
to make sure that each feedback statement was used equally. During the
cheering condition, the audience was asked to clap and shout positive
remarks to the athlete such as, "Way to go!" or "You can
do it!" During the jeering condition, the audience was asked to boo
and shout negative comments such as, "Choke!" or "You
suck!" During the silent condition, the audience was asked to be
completely silent while the participant completed his 10 hits, pitches,
or shots. In golf, the cheers and jeers began as the golfer set up for
his swing, continued through the swing and stopped after the ball had
been hit. In baseball, the cheers and jeers began as the athlete set up
before the pitch, continued through the pitch and stopped after the ball
had been thrown. Similarly in basketball, the cheers and jeers began as
the athlete set up to shoot a free-throw, continued through the throw
and stopped after the ball was shot. All participants were debriefed at
the end of the performances and asked not to talk about the experiment
with other athletes that may also be in the study.
The design was a 3 x 3 mixed factor design with audience condition
as a within subject factor and sport as a between subject factor, and
accuracy of performance as the dependent variable. Accuracy for baseball
was measured by number of strikes out of 10 pitches. Similarly,
basketball accuracy was the number of baskets made out of 10 free
throws. In contrast, the distance from the target in yards represented
golfers' hitting accuracy. Table 1 provides the means and standard
deviations for each audience condition for each sport separately (i.e.,
number of successes for baseball and basketball and distance in yards
for golf). Given dependent measures of different metrics, audience
condition and sport could not be considered together. Thus, for each
sport, collapsed across audience condition, data were transformed to
z-scores so that all the data could be analyzed together. A 3 x 3
repeated measures ANOVA analyzed the transformed data. Because the data
were transformed within each sport, giving each sport a mean z-score of
0, the analysis for a main effect of sport is virtually meaningless,
F(2, 29) = 0.00, p = 1.00. There was no main effect of audience
condition on performance, F(2, 58) = .838, p = .438. However, there was
a significant interaction between sport and audience condition on
performance, F(4, 58) = 5.077, p = .001, [[eta].sub.p.sup.2] = .259,
indicating that the effect of audience condition differed depending on
the specific sport.
Simple main effects revealed that audience condition did not affect
the success of basketball free throws, F(2, 58) = 0.00, p > .05.
Indeed, a glance at the means for basketball in Table 1 reveals that on
average basketball players missed very few of their free throws and the
means of the three conditions were essentially identical (to the 16th
decimal); basketball players shot with 80% success on average. Simple
main effects on the data from baseball players showed audience condition
did significantly affect pitching performance, F(2, 58) = 8.527, p <
.01, [[eta].sub.p.sup.2] = .512. Post-hoc LSD tests indicated that jeers
resulted in worse performance compared to both cheers (p = .002) and
silence (p = .001), but pitching did not differ significantly between
the cheers and silent audience conditions (p = .521). Audience condition
also significantly influenced the hitting performance of golfers, F(2,
58) = 5.084, p < .05, [[eta].sub.p.sup.2] = .359. Specifically,
golfers' accuracy decreased in both the jeers and cheers conditions
compared to the silent audience condition (both p's < .05), but
performance was not different between cheers and jeers (p = .459).
The purpose of this experiment was to examine the effects of
differential crowd behavior (cheers, jeers, and silence) on individual
golfer, baseball, and basketball players' performance. The effect
of audience condition differed depending on the sport. Pitchers threw
significantly fewer strikes given an unsupportive audience than they did
given supportive or silent audiences. Golfers performed best when the
audience was silent and performed worse given both jeering and cheering
audiences. Yet audience condition did not affect the success of
basketball free throws at all. These findings suggest a number of
considerations for understanding audience effects, the home advantage,
and future research.
The present study is one of few experimental studies in the area,
and possibly the only study involving systematic manipulation of
audience behavior and its effects on performance of specific sport
skills by athletes. In general, the nature of the audience did matter,
at least for the athletic skills tested in baseball and golf. Thus, the
present findings provide additional support, at the individual athlete
level, for archival and quasi-experimental studies concluding that
differential crowd behavior creates changes in performance. Furthermore,
congruent with studies like Greer (1983) and Thirer and Rampey (1979),
the present results especially highlight the role of negative audience
behavior like jeering. As such, this study and its findings serve as a
call for more attention to changes in performance of individual
athletes, as well as on specific skills as individually contributing
factors to home advantage. It may be that it is the susceptibility of
certain athlete behaviors to differential crowd behavior that
contributes to home advantage. For instance, maybe pitching is
particularly important in baseball, or possibly a combination of
pitching and changes in reaction times for outfielder plays. Perhaps in
basketball, it is not free throws that are the issue, but changes in
rebounds or 3-pointers. Simply put, there may be value in dissecting
both what the audience is doing and which sport skills are affected.
It is not clear why the nature of the audience would affect the
three sport skills differently, but one possibility is that the specific
skills chosen may not have been of equal complexity. For example,
basketball players made 80% on average across conditions, suggesting
that the free throw is perhaps an excessively easy task for the
athletes. To this end, as a simple task, it is possible that the
basketball results reflect a general social facilitation effect, wherein
the mere exposure of an audience (regardless of specific behavior)
boosted performance (cf. Platania & Moran, 2001). But because this
study was focused on the influence of differential audience behavior,
there was no "no audience" condition; thus, whether the
basketball players would have had similar or lower success in free throw
shooting compared to having an audience cannot be confirmed.
Nevertheless, the fact that baseball pitchers and golfers showed changes
in performance as a function of changes in audience behavior rules out a
simple social facilitation effect (cf. Guerin, 1986).
Golf performance here could be interpreted to suggest that
self-presentation played a role such that positive audience support may
have increased the chances of the golfers "choking" (cf.,
Baumeister and Steinhilber, 1984; Wright, Jackson, Christie, McGuire,
& Wright, 1991). Golfers did perform worse when a supportive
audience cheered (compared to silence); of course, they performed
equally poorly with the unsupportive audience. This was also not a
particularly high-pressure situation (cf. Baumeister & Steinhilber,
1984). Furthermore, the same self-presentation concerns were possible
for baseball and basketball players as well, yet the cheering audience
did not lead to worse performance for those athletes. Thus it is
unlikely that self-presentation concerns were a primary contributing
factor in this study. Much more likely is the fact that accepted
audience behavior is quite different for golfing than for baseball and
basketball games. It is common for golf audiences to be silent, thus
cheering and jeering might be equally distracting, leading to similar
performance decrements compared to the silent condition. Indications are
that the days of pure silence are over in golf (Hawkins, 2002; Verdi,
2001), though, so it may become increasingly interesting to study
audience behavior effects on skills within golf. For example, there
could be a golf skill that actually improves under cheering conditions
or one that is differentially hindered by jeering. Considering which
skills may be most affected by audience behavior may shed light on some
of the inconsistent or contradictory findings in the traditional home
Nevertheless, fans commonly believe that their cheering matters
(e.g., Bray & Widmeyer, 2000), and research has shown that
supportive feedback, at least in coaching, can effectively improve
athletic performance (e.g., Allison & Ayllon, 1980). In contrast,
the present results showed that having a supportive audience, compared
to a silent audience, did not improve performance for baseball,
basketball, or golf, and in fact, actually harmed performance of
golfers. On the other hand, the unsupportive audience (jeers) did result
in lower accuracy for both baseball pitchers and golfers. Under these
conditions, then, cheers did not function as a reinforcer for any of the
tested behaviors, but jeers functioned as a punisher for throwing
strikes and accurate golf hits. These results may suggest the real value
of fan behavior during a sporting event is in their antagonism of the
opposing team (though the authors are not advocating encouraging this
among fans). Interestingly, this also has implications for our
understanding of the so-called homefield advantage.
Like other studies (e.g., Salminen, 1993; Strauss, 2002b), the
present study found no evidence for an enhancing effect of supportive
audience behavior (cheering). Nor did the present study find a
detrimental effect of cheering, as has been suggested by other studies
(e.g., Baumeister & Steinhilber, 1984; Wright, et al., 1991). Jones,
et al. (2007) noted the difficulty in resolving the seeming
contradiction between general findings that supportive audiences do not
seem to improve athletic performance and the fact that home teams still
win more often. The beginnings of a resolution may be in a
reinterpretation of the home advantage. Specifically, the home advantage
may be better conceptualized as a visitor disadvantage due to effects of
unsupportive audience behavior. That is, "bad" (the jeers) may
simply be more powerful than "good" (cf., Baumeister,
Bratslavsky, Finkenauer, & Vohs, 2001). In this study, cheers did
not lead to better performance for the baseball players, but jeers hurt
performance. In a typical home game, the larger (and louder) portion of
the audience tends to be the home-team fans. Although the visiting
team's fans surely jeer the home team, the home crowd's cheers
may drown out those jeers. Thus, perhaps cheers are not improving
performance, but rather providing a shield against the negative effects
of jeers. On the other hand, the visiting team's fans may cheer,
but they cannot overcome the louder jeers from the comparatively larger
home team fans. Consequently, performance of the visiting team is
disadvantaged because there is no insulation against the negative
effects of jeers. Of course, this is a possibility only suggested by the
baseball data in the present study, and warrants further investigation.
Conclusions from this study are limited by a few considerations.
First, the sample sizes for each sport were fairly small. Yet, it should
be noted that despite such small samples, effects were still found.
Certainly, the ability to detect an effect was strengthened by the
within-subject manipulation, which again also points to the potential
value of more research attention on changes in individual athletic
performance across audience conditions. As a small-scale study, the
present study offers a cautious starting point with interesting effects
that provide some fodder for future investigations.
Second, there were no audience effects on basketball free throw
accuracy. Initially, this result is odd given that evidence of a home
advantage and arguments for crowd support as a major player in home
advantage have often been among the strongest in basketball (Courneya
& Carron, 1992; Nevill & Holder, 1999; Schwartz & Barsky,
1977; Tauer, et al., 2009). Recall, though, that there is some contrary
evidence of the importance of crowds in basketball performance (e.g.,
Moore & Brylinsky, 1993). Furthermore, in the present study, only
free throws were considered. It may be that the skill chosen here is
simply too easy under these conditions, not a skill affected by crowd
behavior, and/or not one that contributes to scoring changes that
produce part of the home advantage (cf., Greer, 1983). A future study
might involve a more challenging task for basketball players such as
shooting from the three-point-line.
Third, participants were college athletes who engaged in these
sport skills in front of audiences regularly, but the empirical
situation was nonetheless contrived. That is, the athletes were not
playing in a real game and could not win or lose as they can in a real
game. Such an environment may not induce the same pressure of performing
well or desire to win; the player was essentially competing against
himself. Moreover, the audiences in the present study were comprised of
10 people, certainly smaller than in a typical game situation. This may
have been a factor, but research has shown audience size does not
predict crowd effects or home advantage results well (though audience
density may play some role; for an overview, see Jones, et al., 2007).
Finally, athletes performed a single sport-specific task as individuals
rather than as part of a team. Research has shown a positive
relationship between team cohesion and individual performance suggesting
that individuals might perform better on a team than by themselves
(Carron, et al., 2004). Prapavessis and Carron (1996) suggested that
this relationship might exist in part due to the increased efforts of
group members, which may lead individual athletes to believe that they
have more responsibility to perform well for the group.
In any case, it is not known if performing in a team situation or
more authentic game environment would alter the differential effects of
audience behavior on individual athletic skill performance found here.
One might argue that the current study offered a deconstructed home-team
situation, wherein the focus was on individual performances (which make
up team performance) and one isolated sport-specific skill (which is a
regular and necessary skill of a game), in front of a small group of
fans (i.e., as fellow students at the college, the audience members
could reasonably be assumed to be fans), who engaged in behaviors
typical of audience members (cheering and jeering). How all of the
aspects of game situations may contribute individually or together
remain empirical questions. Nevertheless, the somewhat surprising
results of the present study indicate that future research in this area
should continue to consider not just an audience, but the behavior of
that audience as well. There are numerous avenues to pursue in this
regard. For example, studies might test for similar effects with
additional isolated skills in baseball, such as hitting, catching, or
throwing for distance and accuracy. Others might add elements
systematically to approximate real-game situations, such as having other
players, who contribute to the cheering typically, on the field with the
pitcher. Still another avenue might include testing the notion that the
home crowd behavior is blocking the effects of jeers by having two
audiences present during individual athlete performance, manipulating
the behavior and volume of each audience. Ultimately, it may be the case
that such deconstructions of the elements will allow experimental
analyses of the relevant variables, which can then be systematically
recombined in efforts for synthesis and a more complete understanding of
role of the audience in sports.
Author Note: The authors would like to thank Brian Rolander, who
designed the procedure and oversaw the data collection for the golf
portion of the study, and two reviewers for comments on a previous
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L. Kimberly Epting and Kristen N. Riggs
Joseph D. Knowles and John J. Hanky
Author info: Correspondence should be sent to: Dr. L. Kimberly
Epting at email@example.com or Department of Psychology, Campus Box 2337,
Elon University, Elon, NC 27244.
TABLE 1 Performance Accuracy in Each Audience Condition
Silent Cheers Jeers
Sport M SD M SD M SD
Baseball 5.200 0.789 4.700 2.363 2.800 1.229
Basketball 8.214 1.477 8.214 1.762 8.214 1.578
Golf 10.391 1.857 11.889 2.492 12.713 3.471
Note. Accuracy is in terms of number of successes (of 10 attempts)
for baseball and basketball but distance (yards) to the flag for