Tempo, manipulating relationships.

Time for a quick recap: we have raw physical energy being turned into information that we use to make decisions. Most of these decisions involve other people so we engage still more people in the solution or exploitation of them. But just as soon as we have dealt with one decision we find another so we need to attend to and engage with a new mix of people. This cycle goes on with everyone on the field, there’s no blueprint or schedule for who deals with who or when.  

Rao’s concept of tempo gives us some valuable insight into how we move through this process. “Tempo has three elements: rhythm, emotion and energy” and manipulating tempo is largely a matter of timing. Here he uses driving in traffic as a metaphor to explain this idea. “Driving graphically illustrates the four main skilled behaviors that constitute the overall skill of timing: merging, going with the flow, pacesetting and disrupting.”

Merging is entering a new transitory relationship. You slide into traffic so as not to disturb the pace of others. But it does change everyone’s relationship. This creates the three or more systems problem and has to be resolved. But before you can enter a new relationship you have to leave the one you’re currently in, “every new beginning comes from some other beginning's end.” This also means that, at least for a brief moment, you’ll be caught between two worlds. Finally merging may or may not require a change of tempo from the player who is looking to ‘move into the new relationship.’ This is common when players move from one so called level to another.

Going with the flow is being in a harmonized state with the surrounding elements of the system. It’s the “orderly (and pleasant) state” that Boyd refers to in D&C. But in every group this state won’t last long. (Long is a relative term.) The tempo cannot be ‘perfect’ for every member and as they look around they begin to notice. At some point it will become too fast or too slow and they will have to decide if they should stay put or look for another group. In essence the ‘group’ will begin to dissolve as a cohesive unit. 

Pacesetting is the “art of harmoniously driving the natural tempo of your environment away from its current state towards your preferred state – slower or faster – in non-disruptive ways.” It’s a mutually agreed on change in tempo. Another way to say this is a local entity alters the global tempo to a new state. You can see this when a key player picks up the pace of ball circulation and other players pick up this cue.

Dissonance “is what will turn a potentially dangerous and stupid sort of behavior into a productive one.” This has “the potential to create irreversible structural changes.” The birth of “Total Football” is an example of dissonance that morphed into pacesetting. Ajax was playing against an East European team and couldn’t get the ball off of their midfield. Velibor Vasovic, the Ajax sweeper became frustrated and pushed deep into midfield. The chaos he created for the opponents was enough to get Ajax two goals, the win and show Michels what was needed for Total Football. What was a moment of improvisation and risk became the framework for the playmaking style of soccer.

The art of creating transitory, dynamic and complex systems that can actually do something is the aim of Teambuilding. “During a ninety-minute match every player constantly has to anticipate the ever-changing situations and make split second decisions about what option to take. They are created by the actions of teammates and opponents. The true top-notch players all possess the quality to continuously and quickly oversee all the possible options… The solutions will express directly or indirectly the aim of the match: to win or at least not to lose. The complexity and unpredictability of the ever-changing situations prevent the perfect match from ever being played.” Rinus Michels.

Certainly one of the qualities that all top-notch players possess is the ability to get the most out of other players. Not only can they adjust their own tempo but they can also influence those around them. Knowing when and who to merge with, when to go with the flow, when and how to change others gears and finally when to throw caution to the wind are the tools these players use in order to dictate the pace, i.e. tempo of the game. 

“You win battles by knowing the enemy's timing”

Now I’ll reintroduce the element of timescales. As Smith & Thelen pointed out, “we must be concerned with how different timescales interact.” The difference in timescales has two components, duration and relationship. A difference in duration is simple to grasp. A thinks, grows, acts faster, i.e. has a shorter timescale in a specific domain than B. It’s safe to assume that you will find a difference between even so-called identical systems, i.e. players on the same team.

The relationship between systems is something else. Venkatesh Rao, echoing Marianne Paget’s “acts of deciding” explains;

“popular decision-making models rely on what you might call point logic: the idea that a decision is a point, a fork in a temporal road… Fortunately, a better scheme, which organizes understanding of time around intervals rather than points, was worked out by planning researcher James Allen in the early 1980’s. This scheme, called interval logic, is a way of thinking about time… The idea of interval logic is simple… given two intervals of time… how many qualitatively distinct relations can there be between them? The answer is thirteen (six pairs of symmetrical relationships, and one special case).” The relationships are pictured above.

In a real world setting two systems will operate in one of the twelve symmetrical relationships. (Number 7, being equal is highly unlikely in soccer so we’ll discount it.) A starts before B: A starts after B; A starts B: A is started by B and so on. As long as you view the relationship retroactively, or, proactively with only two systems in a static environment you can use this model. (This is how the ‘freeze method’ of coaching works. It either recreates a situation for linear explanation or creates a scripted situation where the coach walks players through a series of relationships. It’s pure either/or – cause/effect reasoning in a static environment. Consider the language in Rao’s chart as a coaches instructive ‘ideas’ and you’ll get the picture.)

Retroactively life’s a done deal, a closed system and these relationships simply explain what happened. The principles of Taylor’s scientific management work very well. Two systems in a static environment also work for the same reason. So here’s the rub, it’s scientific managements inability to predict, let alone control the future where the trouble starts. Two cases illustrate this point, the three or more and uncooperative systems problems.

Looking back at the chart, imagine a relationship, 1-6 and then insert another system, “C” into it. You can’t tack it onto the beginning or end, it’s included in the moment of interaction between A&B. C reintroduces the six ‘W’ questions for A&B. In soccer systems are a relationship between individuals, groups or an individual and a group. Example, you can have a relationship to the left back or the two central defenders as an individual or as a part of another group, i.e. twin strikers. Now, insert another player or group into your relationship. This will be an anomaly that enters your attention. Once that happens the original relationship will altered in time if not meaning. You will be too early, too late in the original plan or in a whole new environment altogether. (In soccer the number of possible groups is staggering. The transitory nature of complex systems keeps the every player in a state of flux as to which system they are in and which one to attend.)

The later problem addresses the models weakness in a competitive situation. It assumes cooperation between the systems. (A necessary condition for the freeze coaching method.) In the case of an active and alert opponent this isn’t likely. It’s the old “they know that I know that they know that I know” game and one they don’t want to play, at least on your terms. You may want to ‘meet’ a system, say the ball so you aim to start ahead of them. They are determined not to let that happen so they start ahead of you instead. This situation is captured by Miyamoto Musashi’s line, “You win battles by knowing the enemy's timing, and using a timing which the enemy does not expect” and timing is all about timescales.

The six ‘W’s’ relentless cascade and feedback.

(Or how we get hopelessly lost in brain lock.)

Establishing harmonized transitory complex systems is easy when everyone starts from the same place (Orientation), answers the six ‘W’ questions and their follow-ups within the same timescale and the environment doesn’t change. Good luck with that.

Basically the six ‘W’ questions are:

  

1.       What is my job?

2.       Where should I be?

3.       Who is my concern?

4.       When do I act?

5.       How do I go about it?

       6.       Why does this matter?

Lists like this are useful for understanding complicated systems and multiple-choice tests. Alone they are useless in addressing complex problems. First off, every question is dependent on an answer to one of the other questions. For example, your job depends on where you are. Where you are constrains when you should act and so on. Which question comes first is itself an open question.

(Note, all of these questions are from the point of view of the individual. This POV will conflict with the POV of the group, the collective POV. That POV is based on the transitory complex system the individual is in at the moment in question and that moment can only be viewed in retrospect. If that’s confusing consider what’s going on during a game.)

Venkatesh Rao writes about the underlying ideas for each of these questions. “What gives you the study of options. Why gives you the study of causation, motivation, reward and punishment. How leads you to the classic problems of means-end reasoning, such as planning and scheduling.” Questions of “when, where and who” are “about timing, framing, background and context.” This perspective reinforces the notion that this isn’t a set list but a grab bag of interrelated questions that has to be answered in a time competitive dynamic environment. To stay too long on any one question can take you down a rabbit hole of indecision.

In the diagram above consider the change for each player when the ball moves from $1 to $2. On the field this ‘difference that makes a difference’ is three feet. But, in a cascading sense the answer to each question will be modified for every player. For a and d “what is my job” shifts and that change cascades throughout the field. Now consider the influence that the open independent movement of every player and the ball has on how each individual deals with the six questions. You soon find yourself skipping the follow-up questions and focusing on a smaller and smaller slice of the big picture. The ultimate small slice is ball watching where all six questions are rolled up into one overriding concern, the ball.

The need to get to the important questions first, and the knowledge that you’ll be short changing others is important. In a time competitive environment like soccer optimal is rarely an option and 20-20 hindsight is only good after the fact. Good enough decisions based on incomplete information and understanding will have to do. It clears the way for the next action and helps to avoid brain lock.

Transitory complex systems.

In the last post the complex systems exhibited a permanent nature. You can count on them. But there is another type of complex system that deserves attention. These are the transitory ones that people form in spontaneous and unpredictable manner.

Here’s a simple diagram of a 4v4 scenario. The attackers are numbered 1-4, the defenders are a-d and the ball is $. At any moment each player has a wide number of options to consider. The options can be mixed between members of both teams and the ball. For example, 1 may have $, a, b and 4 under observation while c has 1, $, d and 3 in mind. As long as no one moves independently you can connect the dots in a straightforward fashion. If-then scenarios are easy. This is what the freeze technique does in practice. It removes the element of complexity, i.e. independent movement and reduces the game to being simply complicated. At this level soccer can be understood in linear cause and effect terms. Even the permanent complex systems can be manipulated, at least on paper, to this level.

But on the field it’s different. No two players have the same ‘geographic view’ of the game, neither the same temporal sense nor starting point. Everybody is making sense of the game from entirely different points of view, perspectives and timescales. Sometimes it’s a wonder that anyone is on the same page at all.

This is a problem for communication. Harmonized action depends on at least an implicit level of understanding and agreement between players. If players are unaware of each other this is impossible. If they are aware of each other, but can’t agree on a course of action it’s difficult at best. When you add the dynamic nature of the game in the mix, i.e. every player independently moving where and when they choose while the ball is also in motion the opportunities to create and maintain transitory complex systems is very difficult. Players need to know who, when and where to connect with and share why they are connected. This way they can pool their resources for what they need to get done how they’ll do it. The time to carry out all of this may only be milliseconds and then they have to start all over.

While this is in another post it's worth repeating Boyd's point from D&C;

“The degree to which we cooperate, or compete, with others is driven by the need to satisfy this basic goal. If we believe that it is not possible to satisfy it alone, without help from others, history shows us that we will agree to constraints upon our independent action—in order to collectively pool skills and talents in the form of nations, corporations, labor unions, mafias, etc. —so that obstacles standing in the way of the basic goal can either be removed or overcome. On the other hand, if the group cannot or does not attempt to overcome obstacles deemed important to many (or possibly any) of its individual members, the group must risk losing these alienated members. Under these circumstances, the alienated members may dissolve their relationship and remain independent, form a group of their own, or join another collective body in order to improve their capacity for independent action.”

“In the study of development, we must be concerned with how different timescales interact.”

In the complexity-action post I defined a complex system as a model that includes action. I’ll expand on this idea by using Nina Degele’s description of complex systems;

“The systems I will therefore term complex are those characterized by irreversibility, non-linearity, emergence and interconnectedness under dynamic conditions… A multitude of elements, hierarchies and interdependencies do not yet turn a system complex, but merely complicated. In order for it to be complex, it takes state modifications, at high speed… In this sense, time is the complexity-generating factor, able to transform a complicated system into a complex one.”

 

In the same post I mentioned that there are many different systems in soccer and that they are usually organized as parts or functions, (actions/responsibilities). From Degele’s description we can see how many of these models fail to capture the complex nature of the game. They lack state modifications at high speed. However there are some models that do a better job than others. So what happens when these different complex systems interact? Logically the game takes on even greater complexity.

Let’s consider three complex systems models that can be used to understand the game.

First, OODA loops. This doesn’t need any explanation.

Second, the four main moments. These are; in possession, losing possession; opponents in possession; regaining possession. Each team occupies the moment opposite their opponent. From kick-off to final whistle this relationship doesn’t vary, only the length of time that a team is ‘in one of the moments’ is a variable.

Third, the KNVB’s TIC model. TIC stands for technique, insight and communication, but not as isolated entities, they are an integrated whole. It’s ‘explicit and implicit communication’ that makes the Dutch system complex; from Coaching Soccer, “Communication in this context refers to the interaction between the players and all the elements involved in the game… TIC covers all the attributes needed to play and to influence the game. An additional complicating and influencing factor is the continual flux of these ingredients. Situations change continuously as the game progresses, and the players must repeatedly reorient themselves and make new decisions.” That is pure Boyd.

The game can be understood using any one of these models. Scouts will note what teams do in, and how fast they transition between the moments. A coach will note a player’s technical execution and tactical understanding. A player will get inside an opponents OODA loop for an advantage. Each model catches the game from a different perspective and includes the element of time. All three meet Degele’s description above.

But in each one of these models time means something different. With Barcelona, possession maybe measured in minutes. A tackle may take seconds to frame and execute. Getting an idea may happen in a microsecond. The answer to these irreversible non-linearities of time difference is not to separate out each one as a disconnected process, but to embrace them collectively. Linda B. Smith & Esther Thelen make a great point that is too often ignored when trying to put the pieces together on the field;

“The second key assumption of the dynamics systems approach is that behavioral change occurs over different timescales...  Thus, in the study of development, we must be concerned with how different timescales interact.” The successful interaction between timescales is what makes good theory. It’s the inevitable mismatches in reality that too often spell disaster.

“Feedback must come from the specific to the general.”

From Destruction and Creation;

There are two ways in which we can develop and manipulate mental concepts to represent observed reality: we can start from a comprehensive whole and break it down to its particulars or we can start with the particulars and build towards a comprehensive whole. Saying it another way, but in a related sense, we can go from the general-to-specific or from the specific-to-general. A little reflection here reveals that deduction is related to proceeding from the general-to-specific while induction is related to proceeding from the specific-to-general. In following this line of thought, can we think of other activities that are related to these two opposing ideas? Is not analysis related to proceeding from the general-to-specific? Is not synthesis, the opposite of analysis, related to proceeding from the specific-to-general? Putting all this together: Can we not say that general-to-specific is related to both deduction and analysis, while specific-to-general is related to induction and synthesis? Now, can we think of some examples to fit with these two opposing ideas?

In the simple systems diagram the obvious answer is the direction of the signals flow. So what does that mean?

If your aim is to reach a goal deduction, general-to-specific seems to be the process you’ll employ. A goal is a desired specific end state. To get there from here you’ll need to ignore anything that’s extraneous to the journey. You don’t need redundancies, alternatives, options, just the bare bones. Analysis, focus, concentration, coordination, attention and insight are the tools of goal directed action. These are all reductionist terms.

But how do you know what you want when all of the end states are changing? In a match deductive analysis must have a pretty short shelf life. You’ll be chasing a non-existent end state before you know it or, as pilots call it ‘flying behind the airplane.’

The other side of the coin must lie in feedback. As Melanie Mitchell writes, “feedback must come from the specific to the general” and that is supported by experience. Feedback is the way that you reassemble a moment, examine it, it’s consequences and causes in order to learn from it. Feedback is based on reflection of experience. It broadens your understanding of what happened. The tools of feedback are making connections. It’s analogous, metaphorical, synthetic thinking that can expand your options as well as appreciation.

Marianne Paget shows why there’s a need to find a balance between feed forward and feedback;

“The unfolding act is sometimes ambiguous because its trajectory is unknown. It intends and aims at an appropriate response and presses into the unknown in order to achieve it… An inquiry uses the prism of the wrong result to peer back in time. Inquirers reason with knowledge of that result. But reasoning with knowledge of what is now knowable is very different from reasoning with knowledge of what was then known… Yet an asymmetry in understanding remains, for a retrospective inquiry cannot capture the subjects own experience of acting in the stream of time. This asymmetry is inherent in the retrieval of all subjective experience.”

‘Complexity includes the presence of action.’

Whenever the term systems is used in soccer the ideas of numbering, i.e. 1-4-3-3, 1-4-4-2 or a form of some principles of play, i.e. pressure, cover, balance; first, second, third attacker; high or low pressure comes to mind. In the former we have some type of organization of parts and the later actions/responsibilities. However, this way of thinking misses some vital elements in the use of the word 'systems' and this causes a big problem when theory hits the field.

Bertalanffy defines systems this way; “A system can be defined as a set of elements standing in interrelations. Interrelation means that elements, p, stand in relations, R, so that the behavior of an element p in R is different from its behavior in another relation, R.”

What Bertalanffy brings to the definition is a level of uncertainty based on the interactions caused by communication. The flow of signals from one entity to another makes for unpredictable results. What he discredits is the notion of “classical science,” the straightforward cause-and-effect, linear school of thought. This is the method that many coaching articles and sessions employ, “if you run there, your teammate can pass you the ball and you’ll take the shot.”

But such thinking is only possible under two conditions. “The first is that interactions between ‘parts’ be nonexistent or weak enough to be neglected…” and “the relation describing the parts be linear…” However, “These conditions are not fulfilled in entities called systems, i.e. consisting of parts ‘in interaction’.”

In the difference that makes a difference post I wrote about entity and process models. Now I’ll expand their meaning; entity models are complicated while process, i.e. system models are complex. Science is at odds at what the difference is so I’ll define it as ‘complexity includes the presence of action.’

Soccer is a complex sport, not a complicated one.

Feedback, control for feed forward.

Once you accept that feed forward and feedback are opposing concepts, and that the flow of information can be defined as a signal you have to deal with the question of how they’re related. In what order, forward or back, and in what amounts do these signals move? How does too much, too little or the wrong direction affect taking action?

Refer back to the bumper-sticker model in the Point of Departure post. In it there was no feedback, just feed forward from Observation to Action and repeat. In the extreme this model represents an allopoietic system. These systems are designed for rapidly completing a task, i.e. Henry Ford’s assembly line. At their best they embody principles of efficiency, predictability, calculability and control, what George Ritzer calls McDonaldization. Allopoietic systems are great for getting things done so long as nothing consequential changes.

But in soccer things do change. The quality, type and amount of signals entering the system is always in flux, that’s new information. Our previous experience is being constantly updated by it, which can alter cultural traditions. Our genetic heritage is being worn down and stressed through physical effort. What worked on the information processing assembly line just minutes ago may not work now. What is required is a level of self-awareness, an appreciation that change is about to, or has happened, to avoid having the line of actions shut down.

This self-awareness is what feedback brings to the system. It slows the processing down long enough to consider the smallest anomalies that invariably crop up. It can direct the process back to reconsider things that just don’t add up. When allopoietic systems work well, and they can, we can be lulled into the trap of habit, an outdated comfort zone. This from Destruction and Creation; “When this orderly (and pleasant) state is reached the concept becomes a coherent pattern of ideas and interactions that can be used to describe some aspect of observed reality. As a consequence, there is little or no further appeal to alternative ideas and interactions in an effort to either expand, complete, or modify the concept.” In short, don’t fix what ain’t broke.

While it may not be broken, what works now needs updating because it’s in a state of constant change. As you gain in experience you gain a more refined appreciation of differences. That is expertise. In essence, you reduce the amount and quality of signals needed in order to find the “difference that makes a difference.” Better and bigger ideas come from smaller and smaller input. Again from D&C; “Such a repeated and inward-oriented effort to explain increasingly more subtle aspects of reality suggests the disturbing idea that perhaps, at some point, ambiguities, uncertainties, anomalies, or apparent inconsistencies may emerge to stifle a more general and precise match-up of concept with observed reality… Clearly, any anticipated difference, or differences, suggests we should expect a mismatch between the new observations and the anticipated concept description of these observations.” Doing this rapidly is what Malcolm Gladwell calls Thin-slicing. It “refers to the ability of our unconscious to find patterns in situations and behavior based on very narrow slices of experience.”

So feedback is used within the system as a means to control the pace of and influences the direction of feed forward. It pushes back against the headlong Route 1 rush. This makes the system more responsive to change by broadening the field of view so to speak. But like every other antagonistic pair the key is to get the right balance. Too little feedback and you can miss those smaller bits in the environment that mean a great deal. You get a brutal audit. Too much feedback and you’re watching the game without being able to initiate any action at all. You might as well sit in the stands.

Feed forward & feedback, direction counts.

Taken as isolated individual elements Observe, Orient, Decide and Act is a simple entity model. It’s the addition of feed forward and feedback channels between and within them that moves it into being something else. These channels of communication allow for the exchange of energy information in every direction throughout the loop.

The explicit difference between feed forward and feedback is a simple one, direction-that’s it. What’s implied is where we’ll find things getting complex. I’ll start with a simple question. What is being fed forward and fed back? As we have seen so far it has to be energy information. We have to account for a flow of E/I in either direction.

I’ll use the definition of signal as the feed forward and feedback flow of E/I; “a detectable physical quantity or impulse (as a voltage, current, or magnetic field strength) by which messages or information can be transmitted.” In short we have communication. At the most basic level a signal requires a source-(origin), an idea-(a bit of information) for transmission-(flow) and a subject-(receiver) that understands it-(can make sense of the bit). It’s a meaningful interaction between two entities.

So how can you differentiate between a signal that’s being fed forward from one being fed back? The answer is the signals point of origin and destination. Feed forward is a signal being transmitted from the source to the subject. This is seen as normal communication, someone said something to someone that was understood. On the other hand feedback is a signal from the source that loops back to the source, it returns to the point of origin. If the signal went somewhere else, say third parties, it would be a relay. With feedback the entity or subsystem is essentially ‘talking to itself.’ This notion provides tension between co-operating antagonistic ideas, forward or backward. Does the signal pass onto the next entity or do we have to reconsider it? Do we carry on blindly or get stuck in endless navel gazing? Alone neither of these bode well for survival, together they are essential.

“Survival on our own terms.”

Action (Test) appears as the last element in the OODA loop. But to consider any action as just an ‘end product’ would be to miss the point. This happens when you rigidly use the input, throughput, output model. Such an interpretation makes the OODA loop an allopoietic system, the bumper-sticker model. A system where energy information enters, is manipulated and exits as a disconnected object from the system itself. OODA loops are not assembly lines.

Now we’ll revisit the “All models are wrong, but some are useful” post. In terms of movement, the physical part of action, I’ll use Bernstein’s models of the degree’s of freedom and the shifting focus heuristic. In those models you find antagonistic forces, coordination and exploration that combine to reach some future state. Those forces set up a binary choice, pick one or the other action in order to move towards a goal. The goal is asymmetrical that is, you cannot go back to a previous state.

So where do the goals originate? How does ‘why’ in the goal selection come into play? An answer can be found in Destruction and Creation;

“Studies of human behavior reveal that the actions we undertake as individuals are closely related to survival, more importantly, survival on our own terms… In viewing the instinct for survival in this manner we imply that a basic aim or goal, as individuals, is to improve our capacity for independent action…

Against such a background, actions and decisions become critically important. Actions must be taken over and over again and in many different ways. Decisions must be rendered to monitor and determine the precise nature of the actions needed that will be compatible with the goal. To make these timely decisions implies that we must be able to form mental concepts of observed reality, as we perceive it, and be able to change these concepts as reality itself appears to change. The concepts can then be used as decisionmodels for improving our capacity for independent action…”

But in any social system, and soccer is a social system, there is always tension between two antagonistic forces, the need for individual freedom and the constraints of cooperative action. It’s the old ‘me or the team’ argument. Boyd addresses this tension and the need for finding a balance;

“The degree to which we cooperate, or compete, with others is driven by the need to satisfy this basic goal. If we believe that it is not possible to satisfy it alone, without help from others, history shows us that we will agree to constraints upon our independent action—in order to collectively pool skills and talents in the form of nations, corporations, labor unions, mafias, etc. —so that obstacles standing in the way of the basic goal can either be removed or overcome. On the other hand, if the group cannot or does not attempt to overcome obstacles deemed important to many (or possibly any) of its individual members, the group must risk losing these alienated members. Under these circumstances, the alienated members may dissolve their relationship and remain independent, form a group of their own, or join another collective body in order to improve their capacity for independent action.”

The Hollywood, i.e. popular view of this conflict is the ‘who’ll step up and take charge in the moment of crisis’ picture. It’s the “win one for the gipper” moment. This assumes that one, you can predict when these moments will occur and two that you have time to do anything about it. It’s likely you can’t and you won’t. That’s back to Paget’s point about these ‘big’ moments seeming to be a singular, isolated event. They aren’t. The tension between finding your own solution or coordinating with others for survival is ongoing, never-ending and occurs over a rapidly changing landscape of possible options. The ideas that people find and create must compete with the ideas of others for survival. It’s a bloody and brutal process and one that is necessary for action that insures “survival on our own terms.”

Decisions are binary and dynamic.

So what is a decision? How long are they good for? How often do you have to make or refresh them? If you advocate that players should be decision-makers I believe, that at the least, you should consider these questions. So here are some answers.

A decision, in an energy information context, is an explicit selection of an idea. An example is in the game show where a contestant has to choose door number 1, 2 or 3. The host asks, “have you decided?” The contestant answers “yes” but that isn’t true. He or she can still change their mind, have a different idea and select one of the other doors. It’s only when they have made it known to others that have they ‘made their decision.’

Elaboration, decisions are binary. Back to the free auto story. When you chose your car you eliminated all other possibilities. It was yes to one and no to all others, a yes/no process. Decisions rest in the process of selection, not in the number of options or what was selected. Even if there was only one car left you still could decide as long as you had the option to turn it down. You have the option to not select.

Decisions are dynamic. This from Marianne Paget, “Action is seen, as it were, through the prism of “a decision”… It is not a decision but a sequence of acts of deciding being described as though it were a single decision.” (Consider coaching that sees a player making a 40 yard run as executing a single decision, that’s absurd.) This implies that decisions have a very short shelf life. The instant that you have made one, with or without acting on it you need to make another. It never ends.

Decisions are value free, there are no good or bad decisions at the moment of selection. Again from Paget, “mistakes are known always after they are made… A mistake follows an act. It identifies an act in its completion. It names it.” which applies to success also. At the moment of selection the result has yet to unfold.
 

So what is being selected? We have clues in the earlier quotes from Szilard and Bateson. In the former we had the “notion of a bit of information-the information obtained from the answer to a yes/no question.” For the later, this bit is “a difference that makes a difference and a difference that makes a difference is an idea.” What we are selecting are ideas. Decision-making is simply choosing ‘the difference that makes a difference.’ It’s a meaningful idea that is observed in the present moment. That idea, that difference, that bit will be found in the flow of visual, tactile or auditory energy information.

The most important energy information source is other people, especially their actions. That’s the second example in the auto story. Remember when you were too late and had to restart your selection process? You never act in isolation from other people’s decisions and actions. When someone got the keys to your first choice you had to go to ‘plan B.’ You may have done the same to someone else then. These events cascaded through everyone who was still ‘in the hunt.’

Other people includes teammates as well as opponents. It’s all mutually influential, a ‘cognitive furball.’ In a game you lead or follow others while they lead or follow you in a dance where the difference in who leads is a microsecond. But that’s getting ahead of the story.

“A good plan violently executed now is better than a perfect plan executed next week.”

The OODA loop has two paths from Orientation to Action.

One big difference between the paths is the speed of the energy information flow. Implicit guidance and control implies a direct connection from Orientation to Action, it’s a learned reflex. Decision (hypothesis) implies an intermediary step between the two. This position is supported by the definition of hypothesis as “a tentative assumption made in order to draw out and test its logical or empirical consequences.” Note that the name Boyd chose for the end state is Action (Test).

Now focus on the word tentative and its synonym uncertain in the realm of decision-making literature. In some of the popular decision-making models you are taught to go through a series of steps in order to reduce the degree of uncertainty. In specific situations this does help you to make a better decision, particularly in complicated matters. You can test the tentative assumptions to reach a more optimal result.

For example, suppose you are given the chance to choose a new car from a selection of twenty different and various models, everything from SUV’s to sports cars, a complicated problem. You have all the time and resources you need to make your decision. You can research, test-drive and question others in order to gather as much information as necessary. You can weigh your wants and needs against each other in different combinations. In this model you gather information, compare, contrast and test in order to remove uncertainty. This works until you get into a time competitive contest with an active opponent.

For example, take the same scenario but now you have 24 other people involved with the same goal. That means twenty people will leave with a new car; five will be empty handed. Of the twenty few will have an optimal match of a vehicle to their wants and needs. This is because, faced with the knowledge that you can be one of the five left out the tendency will be to rush the decision. You will have to go with your first best choice. If you deliberate too long you’ll lose. This is Klein’s Recognition-primed decision model. Running through a number of steps, getting feedback, working up comparison contrasts to wants and needs leaves you on the bus going home empty handed.

Furthermore, you have to connect the decision to the action. You have to do something, raise your hand, get the keys, sit in the car, something to indicate that you have made your decision. So what happens when someone else beats you to the action first? You lost that battle and have to choose another car. That means you engage in another OODA loop because whoever beat you to your choice got inside yours.

In the first scenario, when times on your side you can take a very academic approach to problem solving. You can use the higher functioning parts of the brain, i.e academic to reason your way to what maybe a good decision. You can work with rules and logic. When time isn’t available, this model is a sure way to lose. You’ll need to function with the constraints of limited information and time. Your existing genetic heritage, cultural traditions and previous experience will be driving your decision process. It’s what you brought with you to the table at that moment. Your trump card will be your Dialectical Engine. If you can analyze, synthesize and act faster then the others you should be driving home in something better than the last car on the lot. (Should is an important caveat. It represents among other models, Taleb’s Black Swans, Clausewitz’s chance, Heisenberg’s Uncertainty Principle and Paget’s definition of mistake as well as the presence of what are commonly called ‘levels.’)

In the time competitive world of soccer deliberate thinking is often the road to ruin. Intuitive thinking, while filled with problems such as biases, is the way to win. George Patton may have summed up this post best when he said, “A good plan violently executed now is better than a perfect plan executed next week.”

Orient, disorient, reorient, repeat or move on.

A look at Orientation sans input and output.

To grasp Orientation you need to be familiar with Boyd’s Destruction and Creation paper. (You can download a pdf file here, http://www.goalsys.com/books/documents/DESTRUCTION_AND_CREATION.pdf)

In it he states, “To comprehend and cope with our environment we develop mental patterns or concepts of meaning.” This post will look at Orientation in this context.

In the last post I used cultural traditions, genetic heritage and previous experience as observation filters. Tools to help control the amount of raw data that assaults Orientation. Now I’ll expand their use to represent parts of a systemic growth model; initial state, constraints for change and sustainable end state.

Systems models begin with an arbitrary initial state, for example the growth of a redwood tree. A seed requires sunlight, water and fertile soil to activate the growth process; energy, new information that provides the spark. There is a predictable pace and direction of change. The result is a maturing redwood over years, not something else in days. Finally there’s a sustainable end state, the tree can get so big given its total constraints.

This description applies to developing “mental patterns and concepts of meaning” as well. People have an initial starting point, constraints on how fast and in what direction they can change and a limit to how far they can go. This begins with the individual’s cultural traditions, genetic heritage and previous experience.

What happens is that an on-going assault of new information cascades through their “observing window” and hits these three facets. It’s the energy that provides the spark for action. The world is intruding on their perceived reality and they have just three options. Their initial starting point can handle the new information; they fail to recognize and deal with a difference between what they knew and what they observed or they can create a novel solution to match said difference. In Destruction and Creation Boyd clearly points out that in the real world the third state is the most common because “at some point, ambiguities, uncertainties, anomalies, or apparent inconsistencies may emerge to stifle a more general and precise match-up of concept with observed reality.” Here’s why;

The first option, finding a ‘perfect’ match cannot happen. Previous experience ‘never matches up perfectly’ with new, i.e. novel information. Here Ashby’s Law of Requisite Variety supports Boyd. It states, “If a system is to be stable the number of states of its control mechanism must be greater than or equal to the number of states in the system being controlled.” In this case the ‘previous experience’ in Orientation would have already had to experienced the ‘new information’. Problem is this can’t happen. It implies that there is nothing really new, everything has been seen before. This is the state of idealists, demagogues and fanatics at worst, stuckness at best.

The second option, failing to recognize and deal with some difference is a self-solving problem. Darwin’s theory of Natural Selection will take care of you very quickly. At it’s crudest you’re either beaten on the field or cut from the team. In the short, anecdotal run you can get lucky, even win on occasion. But in the long run this Las Vegas approach leaves more losers than winners because hope is not a method.

Our initial starting point is never a match for the new information that is being continually thrust upon us. By definition it is always at least one step behind those unfolding events. Because of this the status quo, the initial starting point, has to be immediately abandoned in the search for a new point. That is done through the interplay of analysis and synthesis. In Boyd’s words, “I believe we have uncovered a Dialectic Engine that permits the construction of decision models needed by individuals and societies for determining and monitoring actions in an effort to improve their capacity for independent action.”

“You see what you want to see, hear what you want to hear.”

Observations, the subsystem for data collection and selection.

 

In the large scheme of things observation is concerned with two antagonistic processes, sensitization and habituation. The former is a process of selection and answers the question what’s important while the later is one of elimination and answers the question what isn’t. Both skills are important in reaching a decision.

Just what is being selected is the ‘first best idea’ out of the overwhelming amount of raw energy, i.e. potential ideas, that cascades through our senses. What is being ignored is everything else. In soccer the three big energy sources are visual, auditory and tactile. Without the ability to limit the amount of raw sensory energy, i.e. data or potential ideas, decision-making would bog down with the overwhelming number of choices. For that we use habituation. We learn to ignore what’s not important. On the other hand without the ability to make a selection we won’t be able to approach our goal. Keeping your options open is not an option when you have a specific task. To get ‘there’ you have to take specific actions.

To help with sensitization and habituation there are three sets of filters in Orientation, the Implicit Guidance and Control. Genetic heritage, cultural traditions and previous experience together create a set of expectations that guide a filtering process. They determine what data gets through, what’s important and what gets ignored.

Observation also has to deal with the feedback from our own decisions and actions. We experience feedback from decisions when we have second thoughts. Players experience this moment when they ‘think’ they see something, hesitate and reorient to an evolved situation. Feedback from actions is more explicit, “Having acted, we have changed the situation, and so the cycle begins again.”

Observations stream through “the observing window” into Orientation driven by the Arrow of Time. Data deemed unnecessary has been discarded or ignored. Data that’s interesting is retained and fed forward. This is front-end decision-making. It’s also where the computer adage GIGO, garbage in, garbage out crops up. Poor selections here feed bad information into Orientation virtually killing the process going forward. 

Sensory energy is being continually fed to everyone on the field. Whoever finds ‘the difference that makes a difference’ and acts on it first can gain a time advantage they can build on. When it’s done between teammates it’s a powerful tool and is the hallmark of players who anticipate each others actions.

“The entire “loop” is an on-going many sided implicit cross-referencing process”

Now we’ll meet the adult OODA loop.

This model contrasts sharply with the earlier ‘bumper-sticker’ model. You still have the four parts, Observe, Orient, Decide and Act but they are now fleshed out with greater detail. This is particularly true in Orientation or, as Boyd called it “the big ‘O’.”

Some details about this model based on the earlier posts.

It’s a process model made up of process models. Put another way, it’s system of subsystems. All four parts, Observe, Orient, Decide and Act are themselves processes playing the part of entities. That is, each contains its own internal interactions between different parts best illustrated by Orientation.
 

Within Orientation we find the antagonistic pair of analysis and synthesis. Note that they can act on and are acted on by, genetic heritage, cultural traditions, new information and previous experience.

There is an energy source that runs through the entire loop. It begins as energy, raw data or information entering through observation. This becomes energy-information as the data gains meaning in Orientation. Some of this E/I is fed forward for a Decision or Action.

The biggest difference between the first model and this one is the inclusion of feedback. In the former model feedback didn’t happen at all. Stuff went through from start to finish and nothing was sent back. It was a poster child for allopoietic systems. In this model feedback plays as much of a role as feed forward. Its inclusion moves the model from an assembly line to potentially recreating itself. Feedback is a bridge between allopoietic and autopoietic systems. It’s the key to reflection and reflection is the key to growth and learning.

Finally in all cases when the loop is completed, whether at Orientation, Decision or Action you return to Observations through feedback and the cycle starts again making “The entire “loop” an on-going many sided implicit cross-referencing process.”

“A difference that makes a difference is an idea.”

Models can be categorized in different ways. For the physical sciences they are either entity or process models. Entity models are static; they contain no motion or interaction between the parts. A city map is a good example. You can see distances and directions between objects, their usage, addresses, public or private land and so on. All of the parts are laid out and there is ‘no order’ that you must use the different parts in.

Process models are built to explain motion, action, change; they are systems models. The OODA loop and well-conceived allopoietic and autopoietic models do that. They use entity models as bookends to establish communication boundaries and channels. In this sense process models borrow entity models to help explain change. When we use a city map as a part of the process of locating our position or destination it is one part of our search process.

The difference between the two types of models is that process models must account for change or movement, entity models don’t. In physics change or movement is work and requires energy. Process models have to include some type of energy source in order to produce this work.

In soccer the predominant energy source is information. In order to play the game information has to be shared which requires communication. Someone sends a signal that is received and understood by someone else, the bookends above. In order to play well communication has to be at a high level. The information flow needs to be clear, accurate, concise and timely. Which brings up some new voices on information theory.

I’ll combine Leo Szilard and Gregory Bateson to set the stage. “Szilard was perhaps the first to define the notion of a bit of information-the information obtained from the answer to a yes/no question.” For Bateson, this bit is “a difference that makes a difference and a difference that makes a difference is an idea.” At this level a bit of information is all that’s needed to create an idea. (This notion has tremendous implications for learning, decision-making and action.)

These bits have to get to us somehow and that is in the form of energy. In soccer we’re concerned with several forms of E/I. These forms can work together to create clear understanding or conflict and create ambiguity and confusion. The important E/I forms are visual, hearing, touch, vestibular, kinesthetic and the Second Law of Thermodynamics. The first three should be familiar and how they come together or fall apart shouldn’t need explanation. The next two provide us with information about where all of the Degrees of Freedom are, how fast and where they’re going even though we can’t ‘explicitly know’ all of those details. The Second Law is a part of the E/I package because it supplies the Arrow of Time. We can ‘feel time pass’ and the inability to control it. The Second Law is like having a hand in your back constantly pushing you forward whether you’re ready or not. It’s also a great equalizer on the field. While everyone has different levels of the first five E/I forms no one has an advantage in real time. Just because someone can see, hear or sense faster their advantage can be easily lost if the necessary action isn’t taken ‘in time.’

For players to make a proactive action they have to make decisions. To make a decision they need information. Information comes to them as a form of energy. Energy is subject to the laws of physics. Therefore we can say that there is a connection between energy flow and information. Since there is a connection between the two it will need to be explained through process models. If “a difference that makes a difference is an idea” is true this appears to be the way to go.

POINT OF DEPARTURE: THE OODA LOOP

Since the OODA loop plays such a prominent role in these articles I’ll use a primary source introduce it, the U.S. Marine Corps.

“The OODA loop applies to any two-sided conflict, whether the antagonists are individuals in hand-to-hand combat or large military formations. OODA is an acronym for observation-orientation-decision-action… When engaged in conflict, we first observe the situation—that is, we take in information about our own status, our surroundings, and our enemy… Having observed the situation, we next orient to it—we make certain estimates, assumptions, analyses, and judgments about the situation in order to create a cohesive mental image. In other words, we try to figure out what the situation means to us. Based on our orientation, we decide what to do… Then we put the decision into action… Having acted, we have changed the situation, and so the cycle begins again.” MCDP 6.

This brief explanation paints a picture that looks like this;

On the surface this looks fine but on closer inspection it fails as a learning model. (I’ll call this the bumper-sticker model. It gets the point across for mass consumption. Boyd’s last model is richer and succeeds as a learning model. We’ll get to it later, for now this works.) This model represents an allopoietic system. These systems comprise “the process whereby an organization produces something other than the organization itself. An assembly line is an example of an allopoietic system.” Think of Henry Ford’s mass production methods or the people who are a part of the fast food process. Rigid allopoietic systems simply pass something through, from point-to-point, without any concern for what comes after. The parts can’t change what they do; they merely follow orders, policies and procedures. This can work for well-defined actions but fall short in dealing with novel situations.

In contrast to allopoietic systems are autopoietic systems. The difference is that the former exists to create ‘something else’ while the later exists to ‘recreate itself.’ Biological cells are an example of autopoietic systems. The knock on autopoietic systems is that, in the extreme, they become isolated as the degree of self-referentiality increases to self-absorbtion. In these cases they are a positive feedback loop like cancer or big business. They survive at others expense and in the end will kill the host body.

These two systems set up the tension I wrote about earlier. In soccer a pure assembly line system produces robots while a self-centered system produces prima donnas. It takes a blend of “soldiers and artists” within the system to maintain the proper balance between bottom-up emergent behavior and top-down intent. This is part of the individual player development vs. team focus debate. Players are not developed in a vacuum and teams cannot improve except through individual growth. Getting the right balance is hard.

So what is ‘flowing’ through the OODA loop, allopoietic and autopoietic systems? At its most basic level it’s energy/information. It’s what keeps things going, the raw material for creation. Stop the flow of E/I and they cease to function as a system or as a process. They become an entity and that's a different type of model.

An energy/information flow implies that someone communicated with someone else through a medium and that the meaning was understood. In a personal sense, you made an observation, it altered your orientation in some way, you had to decide what to make of it and took some action. In short your point of departure was an OODA loop.

“All models are wrong, but some are useful”

Since we’ll be working with models we’ll start with a straightforward definition;

“A model, in the context of science, is a simplified representation of some “real” phenomenon. Scientists supposedly study nature, but in reality much of what they do is construct and study models of nature.” Melanie Mitchell.

In the first post I introduced three important models and now will expand on two of them.

Here are basic pictures of Bernstein’s shifting focus heuristic and Boyd’s Destruction and Creation argument. Both models contain a dynamic asymmetrical goal; a method for approaching the goal, restricting a search, Bernstein’s coordination / Boyd’s analysis and a method for adapting to the inevitable changes that dynamic goals demand, expanding a search, exploration and synthesis respectively.

The goal provides the context for determining the balance between coordination/exploration and analysis/synthesis. It is in constant flux, a state of continual change. Imagine crossing a chasm on an undulating rope. For Bernstein the goal was movement, physical activity. For Boyd it was learning, growth and survival on your own terms.

Bernstein developed his model in response to his degrees of freedom problem. In short, how does the body control movement? With so many nerves, muscles, joints, the DoF, how do we move without getting stuck in a rut or ending in uncontrolled spasms? His answer, by alternating between freezing, (coordinating) and freeing, (exploration) certain DoF we are able to move through a wide variety of environments and manage to reach our goal most of the time.

 

Boyd developed his model in response to the question of how do we learn? How do we construct new concepts to deal with the novelty that the world continually presents to us? By breaking down existing concepts into smaller parts and than reassembling them into new impressions we can create novel ideas. These antagonistic processes combine to help us make sense of a continually evolving environment. We’re able to find “the linear thread swimming in a non-linear sea.”

Both models embody the dynamic interaction between opposed positions that are framed by an underlying goal. Balancing the tension that rises between polar opposites contesting an evolving environment is necessary in order to ‘reach your goal.’ Neither model can exist without these three elements and movement, including thought would be impossible.

So what does this have to do with youth soccer? Listen to the debates, problems, commentaries about the game and they usually seem to revolve around a static or undefined problem and offer single, either-or solutions. For example, “the problem is a lack of technique or it’s the parents.” For solutions “we’ll support development over winning, the individual over the team, dribbling over passing.” With the former you think the future is certain, the problem is clear. With the later you take a position that you have to defend. You get locked into a defensive posture. Both paths lead to stuckness. If there is only one way, one point of view there’s no tension so there’s no need to look beyond the status quo. What worked yesterday, last week, last year will work tomorrow.

But the future is never clear, solutions are never one-dimensional and time waits for no one.

Since we’re dealing with models consider what George Box has to say, “All models are wrong, but some are useful; the practical question is how wrong do they have to be to not be useful.” The models above will prove to be pretty useful and Boyd’s OODA loop even more so.