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Decision Making Fatigue in Athletes
Decision Making Fatigue in Collegiate
Ultimate Frisbee Players
Sam Gordon-Koven
Lewis & Clark College
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Decision Making Fatigue in Athletes
Abstract
Decision making fatigue is based on this idea that the more
choices you make throughout the day, the harder each one becomes
for your brain, and eventually it looks for shortcuts. The main
shortcut you will end up using is impulsivity. An example of this in
everyday life can been seen in shoppers. When you go to the
supermarket for example, you end up making many decisions
regarding which brand you want, which price is better, whether or not
to spend the extra money on buying organic, etc. This leads to you
becoming tired and having less willpower. Coincidently, you end up
buying some sort of sugary treat that they sell at the cash register. In
other words, the process of making many decisions while shopping
fatigued you, making your later decision to buy some unhealthy treat
one based on impulsivity and low willpower to make smart decisions.
My paper however looks at the decision making fatigue in athletes. I
used 10 (4 female, 6 male) collegiate Ultimate Frisbee players as
participants. Each participant ran through a battery of decision
making tests based around Ultimate Frisbee. I analyzed each
individual’s reaction time (RT) for the first, tenth, and last trial, and
then averaged all of the participants’ scores together. My hypothesis
was that as the trials went on, the RT for the participants would
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Decision Making Fatigue in Athletes
decrease, illustrating the effects of decision making fatigue.
However, the results only showed correlation and not causation.
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Decision Making Fatigue in Athletes
We all know that we make many decisions every single day. But
did you know that the more decisions you make in a period of time,
the worse your decisions will be in the later period of that time? This
is the overarching theme to this paper. This phenomenon is otherwise
known as decision making fatigue. A common example of decision
making fatigue can bee seen in judges. The following is a real life
example of decision making fatigue as seen in judges given in John
Tierney’s 2011 New York Times Magazine article “Do You Suffer From
Decision Fatigue?”: “Three men doing time in Israeli prisons recently
appeared before a parole board consisting of a judge, a criminologist
and a social worker. The three prisoners had completed at least two-
thirds of their sentences, but the parole board granted freedom to
only one of them. Guess which one: Case 1 (heard at 8:50 a.m.): An
Arab Israeli serving a 30-month sentence for fraud. Case 2 (heard at
3:10 p.m.): A Jewish Israeli serving a 16-month sentence for assault.
Case 3 (heard at 4:25 p.m.): An Arab Israeli serving a 30-month
sentence for fraud” (Tierney, 2011). As it turns out, “prisoners who
appeared early in the morning received parole about 70 percent of the
time, while those who appeared late in the day were paroled less than
10 percent of the time” (Tierney, 2011). Based on the aforementioned
statistic, it is clear to see why the first parolee was the only one to be
granted freedom. Obviously these judges were demonstrating the
effects of decision making fatigue based on their interesting decision
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Decision Making Fatigue in Athletes
to grant freedom to one parolee who had the same case details as
another parolee.
One of the psychologists to be at the forefront of decision
making fatigue is Roy Baumeister. Baumeister has gone to say, “Even
the wisest people won’t make good choices when they’re not rested
and their glucose is low. And if a decision must be made late in the
day, they know not to do it on an empty stomach.” He furthers his
point by saying, “The best decision makers are the ones who know
when not to trust themselves.”
Some of these “best decision makers” can be seen in athletes,
and not just in judges and in shoppers. To understand how an athlete
can become fatigued by decisions, it is imperative to look into the
cognitive characteristics that go into an athlete when making
decisions. An article that gets into this point is “The Relationship
Between Cognitive Characteristics and Decision Making” by Gershon
Tenenbaum, Raya Yuval, Gabi Elbaz, Michael Bar-Eli, and Robert
Weinberg. Tenenbaum et al. explain that there are many “dynamic
movements” and “restricted rules” that athletes are exposed to. The
success of an athlete lies in their ability to choose from many cues and
pick out the essential ones. It is through this process in which an
athlete can determine the best possible decision. However, this task
is very difficult as the environment in which an athlete lives in is
overloaded with these cues. If an athlete has to go through each of
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Decision Making Fatigue in Athletes
these many cues to decipher which ones are essential, the athlete
ends up making many different decisions over the course of a game.
Tenenbaum et al. refer to two different sets of skills that an athlete
has: closed and open skills. Closed skills are centered on physical
characteristics. Open skills, “in which a variant sequence of events
occurs consistently, require the athlete to continually alter his
perceptual style (i.e., flexibility of cognitive style)” (Tenenbaum et al.,
1993). Thusly, it is the open skills in which an athlete relies on to help
make these decisions. It can then be inferred that by the end of the
game, after using their open skills to decipher the environmental
cues, choose the essential cues, and make a decision on how to adjust
based on those cues, an athlete’s ability to make quality decisions has
been effected negatively and is fatigued.
Another important aspect to examine is the cognitive process of
how we get fatigued from making so many decisions. One article that
gets at this point is “Making Choices Impairs Subsequent Self-
Control: A Limited-Resource Account of Decision Making, Self-
Regulation, and Active Initiative” by Kathleen Vohs, Roy Baumesiter,
Brandon Schmeichel, Jean Twenge, Noelle Nelson, and Dianne Tice.
According to Vohs et al., there is one central cognitive piece that
makes decisions, maintains action, and regulates the self. This agent
is the self’s executive function. Vohs et al. define self-regulation as
“the self exerting control to override a prepotent response, with the
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Decision Making Fatigue in Athletes
assumption that replacing one response with another is done to attain
goals and conform to standards” (Vohs et al., 2008). It is assumed
that based on the fact that self-regulation “consumes resources” to
complete the process of inhibition and then finding the correct action,
it is draining to self-regulate. Moreover, as this source of energy is
drained by continuous self-regulation, there is less and less energy to
maintain quality self-regulation. Vohs et al. conducted many studies
to discover the relationship between decision making and its possible
interference with future self-regulation. One of their studies looked at
shoppers at an outdoor mall. These shoppers reported how much
decision making they had done while shopping that day. After
recording the data, the researchers asked the shoppers to solve
arithmetic problems. The researchers were able to measure self-
regulation based on the performance on the arithmetic problems done
by the shoppers. According to the researchers’ results, “the more
choices the shoppers had made, the worse their computations on
simple arithmetic problems were” (Vohs et al., 2008). This leads to
the conclusion that there was a fatigue from the shoppers’ decision
making over the course of the day. Moreover, this fatigue negatively
affected the shoppers’ ability to self-regulate later.
Another interesting study that was done to see the effects of
decision fatigue is “Investigating the effects of ego depletion on
physical exercise routines of athletes” by Derrick Dorris, David Power,
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Decision Making Fatigue in Athletes
and Emily Kenefick. Dorris et al. looked into the effects of completing
difficult cognitive tasks on an athlete’s willpower. They specifically
tested an athlete’s ability to squeeze a handgrip. There were two
groups, both of which had to watch a distressing video clip before
completing the task of squeezing the handgrip. The first group was
told to regulate their emotions while watching the video, while the
other group was told to not regulate their emotions. As the results
showed, the first group was not able to squeeze the handgrip as long
as the second group. These results would suggest that because the
athletes that had to deplete their self-regulation source of energy,
they were unable to control their willpower during the physical
exercise. Furthermore, the results also show that when the athletes
did not use their self-regulation source of energy, they were able to
use more of that energy and control their willpower better during the
physical exercise.
Another interesting study that doesn’t come out and say
“decision making fatigue”, but does give supporting data on the
matter is “Criticality of game situations and decision making in
basketball: an application of performance crisis perspective” by
Michael Bar-Eli and Noam Tractinsky. In Bar-Eli and Tractinsky’s
study, they had experts analyze basketball games. These experts
managed to say that each game comprised of different phases.
Moreover, they said that the end of the game was otherwise known as
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Decision Making Fatigue in Athletes
the final phase. In particular, the experts were able to indicate that
final phase was characterized as “comprising twice as many highly
critical possessions than low-criticality possessions.” The experts
then were able to say that these highly critical possessions increased
dramatically towards the end of this final phase. Then the experts
said, “highly critical possessions were characterized by a lower
quality of decision making compared to low criticality possessions”
(Bar-Eli et al., 2000). In other words, these experts were explaining
that at the end of the game, athletes were making low quality
decisions. Now while this particular article does not outright say this
is the effect of decision making fatigue, based on the information
given by the previous studies mentioned in this paper, the results do
illustrate that athletes are affected by decision making fatigue.
Methods
Participants
The participants for my study were 10 collegiate Ultimate
Frisbee players (4 female, 6 male) from Lewis & Clark College. I
wanted to use only participants that were well versed in Ultimate
Frisbee for a few reasons. First, the questions are filled with Frisbee
lingo that non-Frisbee people would not understand. This would
inhibit me from seeing accurate results because the RT for the
questions would have been taken up with me explaining to the
participants what the questions meant. Another reason is because
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Decision Making Fatigue in Athletes
non-Frisbee people would not be able to analyze the pictures. This
would also inhibit me from seeing accurate results because the RT for
the pictures would be taken up with me explaining how to analyze the
picture. Furthermore, this would take away from the point of the
study: I am not trying to spoon feed answers to participants, I am
seeing how participants can analyze on their own and measure how
well they proceeded through the test.
Procedure
I compiled 50 freeze frame pictures from elite level Ultimate
Frisbee game footage, 200 questions (four questions for each picture),
and answers for each of the 200 questions individually into Superlab.
I compiled them so that the participant would see the picture for as
long as they wanted—only moving forward by pressing any key when
ready—then the four questions would appear in the same order every
time one at a time—only moving on to the next question once they
answered by either
pressing the “y” key
to signal yes, or the
“n” key to signal no.
[Figure 1.1]
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Decision Making Fatigue in Athletes
Figure 1.1 is one of the pictures the participants had to analyze.
Just like in this picture, there were markings that I made to act as
cues for the participants in order to answer the questions. The
vertical red circle is indicating who has the disc. The red arrow is
showing which direction is downfield. The writing inside the
horizontal red circle is indicating what the stall count is. The four
questions for each picture were as follows in this exact order for each
picture; “Is there a flick force?”; “Is there a poach on the field?”; “Is
there a man open?”; “Knowing what the stall count is, should the
thrower have looked to his dump by now?”. When the participants
were done answering the last question for the last picture, the test
ended. Afterwards, I asked the participants to partake in a little
reflective moment: I asked them if they started to feel impulsive with
their answers as the test went on—a characteristic of decision making
fatigue.
Results
The results were computed by taking the RT from the 1st, the
10th, and the 50th (last) trials from each individual. These RTs were
specifically from the picture stimulus and the proceeding four
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Decision Making Fatigue in Athletes
questions. After having the individual scores for the participants, I
averaged all of the scores together to get the group average for the
1st, the 10th, and the 50th trials. The reason I took the 1st and last trials
was to see if there was a general trajectory of the data, and not to be
confused by all of the in between data. The reason I used the 10th was
to avoid the warm-up effect. As you can see from the chart, there was
a period where the participants were in a “warm-up” stage. After the
warm-up period, participants’ RTs were still decreasing, but not as
dramatic of a drop as the warm-up period. Figure 1.2 below
illustrates the data from my experiment.
[Figure 1.2]
0 10 20 30 40 50 605000
100001500020000250003000035000
Average RT for all Partic-ipants
Trial number
RT
in m
ilis
econ
ds
Discussion
As you can see from Figure 1.2 above, there was a warm-up
effect, but despite that there was still an overall decrease in RT from
the beginning and the end of the test for all participants.
Unfortunately the results only show correlation and not causation.
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Decision Making Fatigue in Athletes
My hypothesis was that as the trials went on, the RT for the
participants would decrease, illustrating the effects of decision
making fatigue. However, due to the limitations of my study, I was
unable to prove that decision making fatigue is what caused the
results. However, based on the post-test interviews, participants
were suggesting that they were starting to rely on impulsivity—a
result of the draining of the self-regulation energy source (i.e.
decision fatigue)—as the test went on. Based on my hypothesis, this
would have been the reason for the decreased RT for the participants.
Nonetheless, this is not enough still to prove causation.
There were several limitations in my study. First, it would have
been better to do a field study on top of a lab study if I wanted to find
a better answer. Normally when measuring decision fatigue, you can
do relatively simple tasks on a computer. However, because I was
testing athletes it would have made most sense to look into an
athlete’s natural habitat, the game. If I had done this, I could have
accounted for variables I was not able to account for in the lab. I
could also have seen decision fatigue in a more natural and realistic
setting for athletes. If I could have looked at decision fatigue in this
natural and realistic habitat, I could have better gaged the effects of
decision-making fatigue for athletes. However, I was limited to lab
research.
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Decision Making Fatigue in Athletes
Beyond the limitations of my study, there are a few aspects of
my study that I would have done differently if I could re-conduct this
study. First, I would have added more pictures and questions, but not
more questions for each picture, just the same four questions.
Instead of 50 I would have liked to do maybe 100. However, I did not
have the time, nor would it have been easy to get participants to join
my study. I did not have the time for 100 pictures because I am not a
full time psychologist, and I do have several other time commitments.
Second, I would have changed up the questions every so often.
Maybe this way, when the questions are less predictable, the
participants would have not gotten into as much of a groove. Third, I
probably could have avoided the warm-up effect by having the
participants go through a practice stage. This would have also added
to the fatigue.
In conclusion, this project was thrilling to work on. Decision
making fatigue can bee seen in many different areas of life, but
because being an athlete is such a major aspect of my life, I wanted to
see how an athlete can be fatigued and its effects besides physical
fatigue. I have a better understanding of decision making fatigue and
how it can affect a person’s capabilities, and in particular, in the
context of athletics.
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Decision Making Fatigue in Athletes
References
Bar-Eli, M., & Tractinsky, N. (2000). Criticality of game situations and decision
making in basketball: An application of performance crisis perspective. Psychology of Sport and Exercise, 27-39.
Dorris, D., Power, D., & Kenefick, E. (2011). Investigating the effects of ego
depletion on physical exercise routines of athletes. Psychology of Sport and Exercise, 118-125.
Tenenbaum, G., Yuval, R., Elbaz, G., Bar-Eli, M., & Weinberg, R. (1993). The
Relationship Between Cognitive Characteristics and Decision Making. Canadian Journal of Applied Physiology, 48-62.
Tierney, J. (2011, August 17). Do You Suffer From Decision Fatigue? New York
Times Magazine.
Vohs, K., Baumeister, R., Schmeichel, B., Twenge, J., Nelson, N., & Tice, D.
(2008). Making Choices Impairs Subsequent Self-control: A Limited-resource Account Of Decision Making, Self-regulation, And Active Initiative. Journal of Personality and Social Psychology, 883-898.
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