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“It is only with the heart that one can see rightly; what is essential is invisible to the eye.”
—Antoine de Saint-Exupéry
Since we share the car in my family, it’s normal that every time I get in I have to readjust the seat and mirrors because they are adapted to the measurements of my father, my mother or my brother. It must have happened to you, too. If you don’t have a car, you’ve probably had to adjust your bikeseat, desk chair... or any other invention.
So now imagine that, the next time you go to sit in the car or in the invention you have chosen, you find measurements that are not yours... but that you cannot adjust either. This is what made the US air force pilots could not keep control of their planes in late 1940. At its worst point, 17 pilots crashed in a single day.
It wasn’t a problem of engineers, mechanics or piloting styles... but about our devotion for numbers. The cockpits were designed according to the average measurements of the male pilots of 1926. They wondered if the measurements of the pilots had changed much and was the main cause of the insecurity.
They hired the anthropologist Gilbert S. Daniels to carry out a similar process. The same guy than with his thesis came to the conclusion that “if you want to design something for a human being, the average is completely useless.” He quickly forgot it, and went to design airplane cabins —without ever having set foot in one— measuring the bodies of male pilots, obtaining the average and creating the cabin “useful” for everyone. Taking the average, he could calculate the “perfect” cabin... he thought.
The reality was that none of the 4063 pilots he measured fit within the average range on all 10 body dimensions measured. Pilots were doing life-or-death moves in an environment that played against them.
“There are three kinds of lies: lies, damned lies, and statistics.”
—Mark Twain
Airplane cockpits were the bed of Procrustes of the 20th century. Procrustes —which meant “the stretcher”— was the cruel owner of a small estate and had a peculiar sense of hospitality: he abducted travelers, provided them with a generous dinner, then invited them to spend the night in a rather special bed. He wanted the bed to fit the traveler to perfection. Those who were too tall had their legs chopped off; those who were too short were stretched.
Procrustes —like many coaches, doctors...— changed the wrong variable: the person rather the bed. As if a tailor boasted of making the best suits in the world altering the limbs of their customers. Like the medication we give schoolchildren to make them adjust to the curriculum, rather than the reverse.
Unless you’re in a hurry for the inheritance, don’t leave your grandparents on vacation for two weeks at an average 21ºC resort. Half at -18ºC and the other at 60ºC won’t suit them too much. This is what we do with many scientific studies. We take many players or patients, we apply a program, we take the average... and we forget that the results talk about the characteristics of the population but say little about each person. For 3 weeks we do “nordic hamstrings”. All players —the population— on average improve by 10%. But it tells us little about the dynamic process experienced by the player and the team: two players have gotten 10% worse, two have stayed the same, one has improved 30% and the last one 50%.
There was no such a thing as an average pilot. There wasn’t an average cockpit. The average is the Santa Claus of adults, it doesn’t exist. It is an artificial ideal of normality. The average, the ideal... is just a widespread myth that creates the illusion of knowledge.
We have to fit the system to the individual, not the opposite. The car, the bike, the desk seat or the cabin... at the service of the pilot, not the opposite. The “technique” has to fit the player, not the “average” created from what most or successful players do.
The Barcelona highway —to give an example— collapses when more than 95,000 cars are driving —to say a random amount. Between 7 and 9 in the morning, around 100.000 vehicles circulate there on average. If you leave your home around 7 when 80.000 cars circulate, you won’t encounter any traffic jams. But from 8 o’clock, with 120.000 cars on the asphalt... you’ll have a problem.
The numbers provide us with a small static picture... of a large process that varies over time —that is, dynamic—... and, often, much more complex. At the other extreme of dynamism, there is staticity. This is statistics: the mathematics of static values in a world of complex —so, dynamic— systems.
If we want to be a little more specific, we could also say non-linear. If you multiply ten times the number of cars on the Barcelona highway, you don’t preserve the same properties than before the increase. There is a transformation. Therefore, hypotheses and predictable laws are impossible in a world of living and changing phenomena. People and complex phenomena are not predictable and mechanical entities. We don’t know which characteristics matter more than others, we don’t know if each factor contributes equally in each person, or how it is combined.
We coaches control the stimuli, but not the adaptation to them. Just as adding a car to a freeway can cause effects that no previous car had caused, adding a lane to the freeway —as Alexandria knows well— can cause the opposite of what was intended. The Katy Freeway of Houston is the widest freeway in the world. It has 26 lanes. You would think that because it’s so wide, there isn’t as much congestion as other less huge highways. But it was the second-worst bottleneck in the country in 2004. More lanes, more drivers that might not have used the highway before… and much more congestion.
When we perturbate a complex system —such as our players or the traffic of a city—, with a task, a physical load, a strength exercise, a lane addition… we don’t know how they will respond as we know with physical objects as happened to Newton with the apple and the gravity.
Even though we have never had more data than we have now to improve performance and health… yet have less predicability than ever. There exist no laws that exactly predict the outcomes of interventions. What we have are many associations and predictions… that don’t describe causations. We lose the individuality. One characteristic (independent) not always can describe a second one (dependent). Married people are not happier. They are happy, that’s why they get married. More data —such as paying attention to the eye colors of the people around when crossing the street— can make you miss the big truck that can kill you.
What’s more, the fact that a correlation exists does not mean that causation must also exist —third-cause fallacy. The correlation between ice cream sales and heatstrokes is high... but there is no causation. The cause, of both, is the hot weather. The levels of CO2 in the atmosphere and the levels of obesity are increasing considerably. Which cause which? Won’t it be the fucking capitalist system and the wealthy countries lifestyle?
“He uses statistics as a drunken man uses lamp-posts —for support rather than illumination.”
—Andrew Lang
We all fall into the trap, however. We all love how the numbers that make our lives so much easier. We look at a simplistic statistic —the average in cockpits—, and we settle. But it’s not our fault. We have evolved from contexts in which not a single calorie was free. To survive, every calorie counted and spending one had to be justified. That’s why we tend to rest. To not spend more energy than necessary to satisfy a task. If I think that a number represents a whole group... why should I make an effort to study each individual separately? Why spend so much time and energy analyzing, studying differences... if I can stick with just one number? Because the context has changed and our beliefs need an update.
Our amygdala and its hatred of uncertainty also play against us. Between static metrics or subjective parameters that are not easily quantified... it does not hesitate to choose the former.
“Maturity is the capacity to endure uncertainty.”
—John Huston Finley
We cling to numbers and certainties —even if they are wrong— to put the amygdala to sleep, live a little more calmly and, unconsciously, be a little bit more “monkeys”. We assume that measurability reflects importance. We create the myth “what gets measured, gets managed.” We start looking at the clock to take into account the heart rate but it doesn’t tell us anything about psycho-emotional factors or the state of confidence. Julio Cortázar wondered —Pablo Vázquez explains— if when somebody gives you a watch, you weren’t the one given since you begin to develop some dependencies on it. We open the laptop to look at the graphs of accelerations and decelerations but nowhere are the different styles of play between the side and the wing quantified. Looking at the screen —paraphrasing Kike Lacasa— we forget about the game.
We end up paying attention to what we can measure instead of what matters.
As humans we may be scared about what will happen in the future. Uncertainty is an inevitable part of living, and nothing —a specific behaviour, test or task— will overcome it. If we are not conscious about it, this fear may destroy our ability to make rational decisions. In front of the fear of what is going to happen, we prefer to take the drug —also called medicine— expecting a desired results —even it may be counterproductive— than wait dealing with the uncertainty. For our body, in some cases, it might be better… but not for our monkey mind.
We may end up exhausting our team because in order to be fit we need 5 sets of a specific exercise. If we do 4 sets, the work is useless. We may end up without considering the exhausted face of our players because in order to develop the aerobic pathway and arrive “well” to the race we need to run 15’, not anything less. It does not matter what the player feels because what is truly important are the graphs of the Excel. Just kidding, it’s the opposite. The numbers help us if, first, we are sensitive to all the unquantifiable information that the player provides us.
How do we deal with uncertainties? Don’t try to create false certainties —as doctors do. Decide what is important and what is not in the context of your team or player. The same meters run in the weekend game —recorded by the WIMU state-of-the-art device— can feel like a marathon or like a 100 meter race if the match was lost or won. A win or a loss completely alters the context. The sensations are completely different and, therefore, so must be the training.
“Not everything that counts can be counted, and not everything that can be counted counts.”
—Albert Einstein
If it can’t be measured... can’t we improve it? What do we do with everything subjective that we can’t quantify?
If we just stick with numbers, we risk ending up playing Russian roulette or believing that New Zealand has become the most dangerous country in the world. They interviewed 100 people who had played Russian roulette. The conclusion was that Russian roulette was a safe game. In New Zealand they had an increase in murder rates of 251.35%. They had gone from killing 0’74 people a year to 2’60.
The more cherries you pick, the more you will be able to choose the best ones. Take as many people, variables… as possible, collect a lot of data. It would be impossible not to find in it a high correlation of some kind… and choose the one you prefer —“cherry picking”. You will obtain a correlation —which does not mean causation— and false positives —you also call errors in the result. Then you can draw the conclusion you prefer.
“Statistics: the only science that enables different experts using the same figures to draw different conclusions.”
—Evan Esar
Like, for example, that masks are useless. That sauna only provides benefits if you used it 9 to 12 times a month at more than 100ºC. If you were using it 7 or 15 times a month at 90ºC... You will become a crazy person. You will be able to choose your diet anti-cancer too. Because every food in your fridge has been listed by isolated studies to both cause and prevent cancer. Sorry if you love bacon, it has only negative effects for cancer —according to data.. but it hasn’t been quantified if it is also bad for your mental health.
Actually data is not reality and transforming it into insight is hard. If the decisions are biased —which is human— the result will be too. The researcher can select the experiment that fits better what he was looking for in order to stay relevant and successful within the academic community... and help make the status quo a little stronger.
“The world cannot be understood without numbers. But the world cannot be understood with numbers alone.”
—Hans Rosling
In order to deal with uncertainties and make rational decisions, we cannot stay with just one number. A single number doesn’t allow us to focus on individuality. Like when we design cockpits, we can only undestand our team focusing on the subjective information with the help of all the objective one. Creating a cockpit —or a car seat— that allows us to adapt as much as we need. And please contradict me but don’t do it with the Moneyball example if you don’t mention what Isiah Thomas did to the New York Knicks on 2003. He brought to the Knicks the players with the highest combined scoring average. They lost 66% of their games.
“We make our best decisions when we are uncomfortably aware of the novelty inherent in every complex situation.”
—John Kiely
How do we measure the sensations, the impenetrable psycho-emotional considerations such as levels of trust, the quality of player interactions, the coordinative fluctuations of the team...? The best 3-point shooter in basketball in a context where the numbers square up but that doesn’t give him confidence, that doesn’t generate shooting opportunities... he may no longer be.
No Excel or big data model will quantify the trust the players place in the coach, nor the quality of your communication with the team. No artificial intelligence will predict the state of your team after a specific physical intervention, nor will it quantify the loyalty of your technical staff, nor your honesty in the management style. You won’t find any algorithm that summarizes the team’s alignment to a single number —if you are united by the same goals—, if all the players and coaches have the same interests, they row in the same direction.
“An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.”
—John Tuk
Accept the uncertainty of all interactions in the training process, the ones that we can see and the ones we cannot. Develop our athletes’ awareness, such as quality of attention, depth of understanding and the athletes’ perception of the utility and value of subjective monitoring processes. There is no better tool to detect burn-out, stress, over-training or the risk of injury.
The coach as prescriber and the player as executor generates dependence. Instead, we can encourage self-sufficiency, self-consciousness and autonomy to be aware of everything that the heart rate monitor doesn’t tell us or the coach doesn’t see. Manu Arjona tells us that we must pay attention to “the Garmin we all have inside”. Educate your players so they are aware of it.
Seirul·lo explains that a lot of coaches get anxious if an exercise is missing two series… but nothing happen! The players may have a bit more of muscular power… but the coach may lose the confidence of the team. They will have made all the series the coach wanted... and the price has been their trust in him. No formula or algorithm tells you this, so you have to look up and see your players.
We have to satisfy the goal that the player feels prepared for the efforts of the competition, not to have the spreadsheet values where we as coaches feel more confident. Sometimes the strongest and most wonderful things are those we cannot see.
Martí Cañellas | Fosbury Flop
If you liked the post, I encourage you to consult the following resources:
Antifragile: Things That Gain from Disorder | Nassim Nicholas Taleb
Periodization Theory: Confronting an Inconvenient Truth | John Kiely
For every complex problem, there is an answer that is clear, simple and wrong | Jochim Sturmberg & Stefan Topolski
The End of Average: How We Succeed in a World That Values Sameness | Todd Rose
Integrative Proposals of Sports Monitoring: Subjective Outperforms Objective Monitoring | Lluc Montull, Agne Slapšinskaitė-Dackevičienė, John Kiely, Robert Hristovski & Natàlia Balagué
Do masks work? | Tomas Pueyo
Everything in Your Fridge Causes and Prevents Cancer | David Epstein
This is how easy it is to lie with statistics | Zach Star
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