“I
write entirely to find out what I'm thinking, what I'm looking at, what I see
and what it means. What I want and what I fear.”
Joan Didion
Human decision-making during uncertain times have been shown
to be unreliable at best and the results tend to work to the detriment of the
decision maker. This proclivity for making dodgy decisions in the uncertain times
have been well studied in the recent years.
Our minds default to what author David Epstein
It is not that procedural thinking-based solutions are never
applicable to all situations because there are times where the speed of
decision is more important than the effectiveness and accuracy of the solution,
and conceptual thinking process would be too slow in reacting to a dire
situation.
I think of the decision-making environment as generally a
system, which has a technical meaning from engineering and sciences. Epstein
calls them environments; he describes them as being either kind or wicked.
Simple system can be thought of as being the kind environments and
complex systems can be thought of as being the wicked environments.
For the sake of explanation, an environment (system) is broadly
characterized by two different categories or variables. The first is the internal
variables or state variables in system-ese. Internal (state) variables
can be observable from the outside, but not necessarily measurable. In the
volleyball context, the set score can be thought of as an internal (state) variable;
as can each athlete’s level of play, physical exertion, and mental state. The
game flow of a team, the players’ responses to the opponent’s actions, the
atmospheric conditions of the playing gym and court can be broadly described as
an internal (state) variable. In short, internal (state) variable is everything
that characterizes all the actions in the game which comes from actually playing
volleyball and affects the result of the game.
The second category or variables are the control
variables. These are what we do as players and coaches to affect the
results. They are the levers that we can pull in our effort to change the
outcome, or more accurately change the internal (state) variables which changes
the result. In the case of the player, the control variables can be how they
perform their skills, whether individually or in conjunction with their
teammates; the choices they make; and the decisions they make while setting,
hitting, serving, blocking, and playing defense. In short, everything that the athlete
can directly control which contributes to their team’s scoring, or to keep the
other team from scoring.
For the coaches, the control variables are more subtle and
indirect. On the tactical front: the choices of the lineup, the rotation choice
to take advantage of matchups, the choice and timing of substitutions, the
tactical adjustments on offense and defense during play, and their emphasis on
the strategy and tactics used for that set, ad infinitum. On the communication front they include: the
coach’s choices of what to communicate; their communication styles; and what to
emphasize before, during, and after each set. On the psychological front: their
choice of how to address the team before, during, and after each set or match.
Kind environments (simple systems) can generally be
characterized by two features: linearity and non-interaction of the internal (state)
variables. Linearity refers to the system characteristic that the predicted result
is known when using a proportional tweak
to the known control variable and the predicted result is also proportional.
This is based on prior knowledge of the kind environment (simple system).
Because many complex systems behave linearly if the
perturbations to the internal or control variable are small, the known small
perturbation results can mislead the decision makers to think that their
assumption of a kind environment (simple system) is correct, and the familiar procedural thinking
will serve their purposes. Human decision makers like this mode because it allows us to be comfortable with using the
known solutions. The non-interaction of internal
(state) variable is implied by the term “linear”.
The wicked environment (complex systems) is the opposite of
simple systems: any lever that we push, the control variables that we can
access, will not usually result in what we expect. A big reason is that the system is opaque; either because we do not
have a good model of the complex system, nor can we accurately predict the
complex system response. It is all a black box. The second condition of the
complex system comes into play because all the internal (state) variables and
the control variables are intricately coupled. Sometimes the coupling is direct
and measurable: a missed serve means a point; sometimes it is indirectly
coupled: a tough serve makes the passer pass a slightly off pass which moves
the setter to a slightly less optimal setting position, making her less likely
to set the middle, which causes the opposing blockers to focus on blocking the
left side hitter, giving the left side hitter a greater challenge to score. One
can use the Butterfly effect to describe the indirectly coupled effect inherent
in the complex system.
Butterfly effect:
A phenomenon in which
a small perturbation in the initial condition of a system results in large
changes in later conditions. Such phenomena are common in complex dynamical
systems and are studied in chaos theory.
Complex systems can react dynamically,
with high volatility to unexpected perturbations.
The complexity of a wicked environment (complex system) also
means that its uncertainty, unpredictability, and nonlinearity will also react
unpredictably to a solution that is based on the kind system (simple system).
Humans
generally rely on our knowledge of simple systems as reference for any
decisions we need to make in any unfamiliar or unknown scenario, we like having
a stake in the ground. We pivot around
our own trusted knowledge of the simple system behavior, nibble around it to feel
safe even as we are making decisions in a wicked environment (complex system), because
are optimistic creatures, we usually assume that we are in a kind environment
(simple system) even when we suspect that we are not. We do this because we do not want to
overthink, to deal with the unknown, the uncertain, and the random. This is not
an indictment of our decision-making ability; it is just the way our rational
mind works.
The word Antifragile comes from the author Nassim
Nicholas Taleb as he describes in the book of the same title.
The definitions of fragile, robust, and antifragile
below are definitions that I cobbled together from Taleb’s work and my own
understanding of the concepts.
Definitions
Fragile: Something
fragile does not like volatility, randomness, uncertainty, disorder, errors,
and stressors. Fragile systems crumbles under high magnitude shock
(perturbations). Fragile systems prefer the deterministic, the known, and the
familiar. Fragile systems prefer to operate in a rut and will suffer because of
extrapolating solutions based on simple system assumptions.
Robust: Something
robust is neutral to volatility, randomness, uncertainty, disorder, errors, and
stressors. Robust systems can
successfully survive and resist the high magnitude shock (perturbation);
although they will only maintain the status quo at best, they will not get
better or gain from the situation.
Antifragile: Something
antifragile thrives on volatility, randomness, uncertainty, disorder, errors,
and stressors. Antifragile systems will
not only survive but will benefit from the high magnitude perturbation. In this
case, the gains and benefits from the perturbation will be nonlinear, i.e., the
benefits stemming from the perturbation increases exponentially.
A volleyball match is a wicked environment, a highly
nonlinear and complex system. Indeed, because most sports are highly causal:
one action affecting the succeeding action which affects the action after that,
ad infinitum, we must model sports actions with Markov chains. https://polymathtobe.blogspot.com/2021/03/stats-for-spikes-markov-chains.html
It is this complexity that drew my attention towards examine
the volleyball match as a theoretical application of Taleb’s ideas.
Specifically, how does a coach avoid building a coaching framework which forces
the team to always play a fragile game? How does a coach prepare a team to play
in an antifragile way?
I delved into Taleb’s tome while also thinking about hypothetical
situations within the volleyball context to try to imagine ways of applying
Taleb’s thinking. The examples in Taleb’s book are mostly about the financial
markets and the decision making thereof, he did not write about sports and how
to apply his antifragile methods specifically to sports, playing sports, and
coaching sports. I wanted to translate his ideas about what creates
antifragility in decision making, in training ourselves to be antifragile, and
how to create antifragile players.
One specific example that I thought of right away and read
from Mike Hebert’s book
This should be fun. And painful. And challenging.
Stay tuned.
Works Cited
Butterfly effect. (2022). Retrieved from American Heritage Dictionary:
https://www.ahdictionary.com/word/search.html?q=butterfly+effect
Dukes, A. (2018). Thinking in Bets. New York:
Penguin.
Epstein, D. (2019). Range, Why Generalists Triumph
in a Specialized World. New York : Riverhead Books.
Hebert, M. R. (1995). Insights & Strategies
for Winning Volleyball. Champaign IL: Leisure Press.
Kahneman, D. (2013). Thinking Fast and Slow.
NYC: Farrar, Straus and Giroux.
Konnikova, M. (2020). The Biggest Bluff: How I
learned to Pay Attnetion, Master Myself, and Win. London: 4th Estate.
Taleb, N. N. (2007). The Black Swan: The Impact of
the Highly Improbable. NYC: Random House.
Taleb, N. N. (2012). Antifragile: Things That Gain
From Disorder . NYC: Random House.