This topic comes up every quadrennial, or in this case, five
years, when we are treated to the spectacle of volleyball in the Olympics, the
showcase event for our sport. Why are these top-level athletes missing so many
serves? They are the best of the best, why can’t they serve a ball over?
The philosophy is this: at the
highest level of our game, a controlled serve does not put enough pressure on
the passer to make them pass into an Out-of-System play; in order to put
pressure on the passer, the serve must be as difficult to handle as possible, the
intent is not necessarily to ace out the passer, but to get an Out-of-System pass.
As the coach, you
have to give the passers the green light to rip it because human nature is such
that the players respond intrinsically to the rewards/consequence cues that the
coaches feed back to their play, i.e. if you want them to rip it at full speed,
you have to be willing to take off all the constraints and learn to live with service
errors. Coach Speraw's philosophy is that if the team does not make a certain
number of service errors every set, the team is not serving aggressively which automatically
translates to points for the opponent.
There have been a
number of responses to this idea on Volleyball Coaches and Trainers. Some
sampling:
· It is
aesthetically unpleasing to see all the missed serves at this level, especially
those serves into the middle of the net. Or it is shameful how our best players
can’t serve a ball over the net. I don’t think the players,
or the coaches care about the aesthetics. They want to win, and to win, they must
score points, to score points, they must serve tough, all the time. The
aesthetically pleasing mindset also reveals a latent vein of thought: failure
is undesirable and must be avoided. Even as coaches are beginning to come
around to the mindset that errors are the natural way of testing the player’s
skills in the competitive environment, the best way to learn, and the only feedback mode that matters; we,
in our weakest decision-making moments reach back to the safest and most certain
decision-making bias because we are afraid of the unknown and we will
inevitably reach for the known and safe. The other part of this reaction is that many
responders are assuming that the level of volleyball as we teach it to our
players are played at the same speed, force and intensity as the volleyball
that is played in the highest level of the game; that is definitely not the
case. Most of us understand that the speed and athleticism displayed in every
level of play is tightly coupled to the athletic and cognitive abilities of the
players. As the players and games evolve, the strategies and tactics must also
evolve to resolve the challenges presented at each level. We also forget that
the speed, force, and intensity at each
level rises exponentially as the level of the game being played progresses.
· Situational: when the score is close or
you are approaching that end of set mark, you should just make sure that the
serve is in. Or, we need to know when to throw in a changeup in our service to
catch the other team unaware. This statement will be addressed after I
introduce some probabilistic definitions.
Probability and Volleyball
Statistics
From Wikipedia: https://en.wikipedia.org/wiki/Probability
Probability is the branch of mathematics concerning
numerical descriptions of how likely an event is to occur, or how likely it is
that a proposition is true. The probability of an event is a number between 0 and 1,
where, roughly speaking, 0 indicates impossibility of the event and 1 indicates
certainty.
How do we
come up with the probabilities? In most cases, we use descriptive statistics,
i.e. game statistics that are taken regularly in volleyball. This definition
comes from (Spiegelhalter
2019).
To be clear,
probability is usually associated with being a measure of uncertainty, whereas
statistics are presented without including any measure of uncertainty.
There are
numerous kinds of probability, the ones we usually employed are as follows,
this is not a complete list:
·
Classical probability: The ratio of
the number of outcomes favoring the event divided by the total number of
possible outcomes, assuming the outcomes are all equally likely.
It is easy to see that we can readily use
this when we are doing counting statistics in volleyball. Hitting percentage,
kill percentage, Service efficiency etc.
·
Long run frequency probability: based
on the proportion of times an event occurs in an infinite sequence of identical
experiments.
This kind of probability is the kind that we
tend to lock into as the THE objective probability, i.e. this is the foundation
of our beliefs when it comes to making our decisions. There are problems with
this kind of probability, they are hard to compile because their robustness
depends on the law of large number: big numbers in the denominator means that
the probability is more likely to be true universally, but the statistics we
take in sports have infinite numbers of correlation and factors which affects
the statistics. If we chose to ignore the different factors, we are also
choosing to include the effects of those factors without recognizing their
effects while we are accumulating that large denominator.
·
Propensity or chance: idea that there is some
objective tendency of the situation to produce an event.
This is what we choose to believe, this is
the basis of our faith in the numbers.
·
Subjective or personal probability: specific persons
judgment about a specific occasion, based on their current knowledge, and it's
roughly interpreted in terms of the betting odds.
This is the probability that we employ when
we go by gut feel or by our intuition. This has generally been dismissed as a decision-making
tool because of the amount of bias that can be subconsciously included in the
internal calculation of the personal probability. Yet we ignore this kind of
probability at our own peril because experienced coaches and scouts have their
personal probabilities which are not only valid, calibrated, but also rich in
insights, which are not measurable nor consciously identifiable.
While professional sports have embraced the
Moneyball religion, many professional teams are working with the greybeards in
the sport to create a way to integrate the statistics driven approach with the
personal probabilities of the experienced coaches because they are finding that
just Moneyball is not enough to help them make decisions, that those intangible
and unexplained gut feels might be valuable and they need to take advantage of
both, in close coordination.
The most common
way to generate probabilities is to take the game statistics and turn them into
classical probability. The next step is to take as many of the same type
of statistics and then combining them to create a long run frequency
probability. The belief is that this is the Propensity or chance or
the underlying objective probability of process. For example, if I took my
teams hitting percentage over the course of a season, then I have the
probability by which I could use as the reference by which I can compare to each
match. The problem is that the playing parameters of each match is different:
easy serving team versus tough serving team, big blocking team versus a smaller
team, teams that runs fast versus teams that sets high and slow, ad infinitum.
Now for the
interpretation of the probability. Most people look at a probability to mean
that given the same conditions, the results would mirror the probability, but
the optimistic bias that we all have subconsciously makes us think that a 99%
probability of success means that the action being performed successfully is a
foregone conclusion, that is, we can predict that we are going to be successful
99% of the time, but we always neglect that 1% where we are not going to be
successful. We would usually take that gamble because the odds are pretty good,
but we also blame bad luck when we are not successful. Luck had nothing to do
with it, the probability told us it was going to happen. The other part of the
consideration is the assumption that the long run frequency probability is
not as representative as we think it is because we are ignoring all the other
factors.
Let ‘er rip
Back to the original discussion.
There are essentially two probabilities that comes into play
in this decision.
The first probability is the success rate of a particular
server. The second probability is the success rate of the opposing
offense in siding out based on the kind of serves that they are served.
The probability of success of a particular server can be rewritten,
if there were enough data into a probability distribution function: the classic
bell curve, we are assuming a bell curve, normal or Gaussian distribution, because
it is mostly true, and the bell curve allows us to use the classical
probability data to extrapolate the results, to allow us to draw inference.
Of course, as any good coach knows, the human factors play a large role in
affecting the server success probability. A ten-year-old serving in a game for the first
time or a player serving when their team
is behind in the Olympics apply different psychological pressures to the
server, even though the results may be the same, blow the serve and you suffer
immense embarrassment. There are factors that play into the calculations as
well: serving in a large gym that has bad background contrast for server depth perception;
strange air flow patterns in an unknown gym, amongst many other things.
In the case of our national team, the coaches have been
effusive in their praise of the statistical team, so I am sure that the coaches
have good data on each server and their probabilities of success under many
different conditions. I am also sure that the coaches make their own
adjustments to those probabilities based on what they know of the psychological
makeup of their players. I know that both teams employ sports psychologists. But
that is just the side of equation that everyone seems to focus on directly.
The criticism is that they err too often. Many will bring up
the fact that if they require their players to get the ball in no matter what,
why can’t the national team do the same? The difference is that the jump
topspin is a high risk, high reward serves, it is a chance that the national
team coaches see as an acceptable risk, even if the high risk of the serve translates
to higher error rates. The national team coaches understand this fact and are
willing to take this chance because when compared with the probabilities from other
side of the equation — the sideout rate of the other team when faced with
different serves— the payoff outweighs the risks.
It is curious to me why this part of the decision-making
equation is so often ignored. If there is a serve there needs to be a pass,
they are continuous actions. They are, in essence, one event. We tend to split
it into serve and pass components so that we can understand the action in terms
of the skills, which sometimes leads us to erroneously view them as being
independent actions. Serving statistics should always be spoken of as a
conditional probability: we have this
kind probability of success given that we are serving this specific serve against
a team that passes that specific serve with a given probability of success. Passing should also always
be spoken of as a conditional probability: we have this probability of success given
that we are passing this specific serve against a team that serves the specific
serve with a given probability of success.
It is at the confluence of the two conditional probabilities that we can
make good decisions.
In this instance, the sideout rate of almost all the teams
when served a less than full speed jump topspin has been assigned to be 100%;
that is, anything that is less than full aggression will essentially give the
opponent a free ball. Indeed, as we watch the Olympic teams, the sideout rate for
serves delivered with full aggression are still high, but not 100%.
The question is: how realistic is this assumption? Are the
coaches being intellectually lazy by just assuming that the opponents are that proficient
at siding out under these circumstances? I don’t have access to the data. I
would assume that all the national teams in the Olympic tournament would have extensive
statistics about the top teams, at the minimum. What does the real sideout rate
have to be in order for the national team coaches to back off of the Let ‘er
Rip standard? I am not sure, but seeing
the serving game in Tokyo, I am going to go with the coaches.
Which brings us back to the serving abilities of all the
servers. First, given the steadfast belief that the coaches have on the sideout
proficiencies of the opponents and the high-risk nature of the jump topspin, no
player with a horrible probability of success with a jump topspin would be allowed
on the court, or they have been trained to improve their probability of success
for a jump topspin. The determining
factor has to do with the execution of
the serve, how the players react to each situation, whether they hurry their
serving ritual, whether they get distracted by the situation, or whether they
are able to adjust to the environmental conditions. This then makes the
decision not of strategy and tactic but of execution.
Someone suggested that perhaps the team can employ a surgical
approach: go full out until the score gets close or when the score is close to
being 25, then just get the ball in, whether by serving short or go to a jump
float. One problem is that if the teams show
this kind of tendency, the opponents will undoubtedly know it, and it is
difficult to trick your opponents at this level. The other problem is that
since the players are human, and mostly risk averse by human nature, it is a mental
struggle to actually go 100% on a swing because they will subconsciously pull
back a little bit when executing, just to be safe, if they were told to pull
back consciously, the edict would contradict the team philosophy of being
actively aggressive, chances are that the serve that would result might be not
effective, or that the opponent handles the obfuscation easily. This is not to
say that it is a bad strategy, but making that decision requires that the
player and coach know and understand how well the opponent knows the team and
whether the opponents can be caught by surprise. More variables which contribute
to the decision and complicates the calculation.
As I had said in the beginning, this discussion pops up all
the time, mostly during the men’s college season and during the Olympics. It is
a healthy discussion to have and I doubt this essay will change too many minds
one way or the other, although I hope that this essay does introduce some probabilistic
concepts as well as provide some other points of view to the coaches who have
so passionately debated this particular topic.
Works Cited
Spiegelhalter, David. The Art of Statistics:
Learning from Data. London: Pelican Books, 2019.
