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April 19, 2016

What is open source coaching?

Many people are in conflict about the nature of talent. Some believe that talent is made. These people believe in the 10,000 hour rule – that 10,000 hours of deliberate practice leads to talent. Others believe it is innate – you are born with it. Still others believe that talent requires master coaching to be developed.

I’ll tell you right away where I stand.

I believe that talent is made. I also believe that your talent is largely determined by how you use critical periods in your development. So if you miss a window to develop body awareness as a youngster, you may be shit out of luck for being athletic. Then I believe that deliberate practice is a foundation, but not the only thing you can rely on. You must have a force guiding your deliberate practice. Otherwise, you may spend all that precious practice time on the wrong things, in the wrong way. Effort gets you in the door. Intelligent work keeps you there. I’ll suggest that you don’t need to be an intelligent person to do intelligent work. Sometimes a pathway to intelligent work lands in front of a player. Sometimes that pathway is a master coach, Sometimes it’s an ideal competitive environment.

A lack of fairness in this process stands out. A player may be willing to put 10,000 hours of deliberate practice into an activity – but they may not happen to be coached by a master coach. If they are lucky, they develop just fine. If they’re not, despite all their hard work, they may not develop at the same rate as others.

If anyone who is reading this knows me, you may recognize that I am 100% talking about my own plight. I do not think it was fair that I put in way more time than other players, but had less success. Knowing what I know now, I know it was because I spent some time learning the wrong things in the wrong way. I compounded this by practicing my poor patterns EVEN MORE to compensate for my lack of success. I’ve already talked about learning how to shoot the wrong way because a non-expert coach gave me a pointer on shooting that was wrong. Is it fair that an 8 year old screws himself over by practicing too much? I don’t think so.

I see this all the time with other players. It upsets me. It also drives my passion to help the player who wants to put in the time and effort. But as it stands, the player that wants to put in the time and effort does not always get rewarded. The best player gets rewarded regardless of their effort they put in. That’s the way it works.

But what if there was a system that provided master coaching to anyone, anywhere? A system that didn’t require you to roll the bones on your development. That if you wanted to put in the time, you were carefully guided down the right path.

By automating a skill development system using principles of operant conditioning, we could do that. The technology is right there. It just needs to be put together.

We’re putting it together.

If this isn’t crazy enough for you, you may want to learn more about what we’re doing here. If you want to get involved, start here.

April 19, 2016

Your Questions Answered – The Next Step

We know that coaching doesn’t quite work the way it should. We also know that there’s a lot of technology out there. Today, we discuss how technology could actually help hockey players and solve the coaching problem.

Ben Schmidt is an old teammate of mine, an engineer who has one of his design patents in use by the Bill & Melinda Gates foundation, and is an ex-professional hockey player. He is here to get you up to speed on the technology available for hockey players right now.

Enter Ben:

Statistics in hockey are advancing. Have you noticed? For years people complained that goals, assists, plus/minus, didn’t show the whole picture of a hockey players value. Now we can look deeper with statistics like Corsi (shots attempts %), Fenwick, zone starts, etc. The statistically inclined fan may be using these fancy new metrics to evaluate their favourite NHL players or fantasy hockey teams. NHL teams are using them to scout, evaluate, and make roster decisions with big payroll/cap implications. If you have never seen them before visit NHL.com/stats/enhanced

In hockey, analytics has uncovered some great insights, notably that puck possession is a significant contributing factor to wins. The Los Angeles Kings and Chicago Blackhawks in recent years have been analytics darlings for their possession numbers. Here is their rank in terms of 5 on 5 Corsi in the regular season when they went on to win the Stanley Cup:

  • Chicago Blackhawks, 2010            1st
  • Los Angeles Kings, 2012                2nd
  • Chicago Blackhawks, 2013            4th
  • Los Angeles Kings, 2014                1st
  • Chicago Blackhawks, 2015            2nd

Now this is not absolute relationship. However, if we think rationally about Corsi it is effectively measuring shot attempt % at even strength. The best teams at generating shots at even strength in the regular season are good ones to bet on in the postseason. Side note: The top two teams this season were the Kings followed by the Penguins, just don’t bet the house;)

** For our more statistically inclined readers check out: http://www.eightleaves.com/nhl-stanley-cup-champions

Now I am not here to tell you about how great these are. To be completely honest in terms of player evaluation I am not impressed. As a hockey player I know there is a large evaluation gap between what’s happening on the ice and the statistics that are describing hockey. I am sure we have all had that game where you played great; you contributed to generating offense, you were sound defensively and you had the puck on a string, but didn’t register anything on the scoresheet. Maybe these new stats will show your worth. In my opinion they may expose an outlier in a particular game, or an undervalued player on a bad team, but they are not revolutionary. Connor McDavid wasn’t discovered from the 4th line of the Erie Otters because he had great underlying peripherals. He was a prolific goal scorer.

To me these new ‘enhanced stats’ only describe 10% more of the game. Call me ignorant but as a baseball fan the statistics in hockey to evaluate, predict, and explain pale in comparison. This is no fault of hockey. Hockey is a complex game with no deliberate and repeatable mechanic. It is a free flowing team sport without the discrete variables that allow us to isolate those statistics in baseball. To put it simply a hockey game is a complex system that requires complex analysis.

Enter computer vision. From the footage that you or I will be watching the Stanley Cup playoffs there is a company gathering millions of data points. This company is SportlogiQ. They are based out of Montreal. The first time you as a hockey player/fan visit sportlogiq.com your heart rate will spike. There it is! Instead of fishing together a new statistic why not collect all the data. Time stamped x-y coordinates of every player and the puck.

Mark Cuban the flashy owner of the Dallas Mavericks funds SportlogiQ. But it is led by some very smart computer science and hockey minds. Their CEO, Craig Buntin, is a former Olympian. Recently, I spoke with Craig over a WebEx meeting. Craig explained to me that they are gathering time stamped data points at 30 times per second and using these to tag events in a hockey game. They employ machine-learning algorithms, which basically recognize patterns of events in a hockey game and group them . From this new wealth of data they can create metrics for hockey that are only limited by our own creative hockey minds. Here is a screen shot of their recent evaluation of Nazem Kadri:

Sport logiq

What do you gather from this information? What sticks out to me is that the Leafs are a bad hockey team. They are recovering pucks in the OZ and making OZ defensive plays, but not generating many chances versus the league AVG. What this means is they are chasing the puck and forechecking, but they are not able to hold onto the puck and make offensive plays, except Kadri, he’s clearly playing well on a bad team. Further evidence is the Leafs inability to make passes on the rush. This requires passing skill (saucer pass), hockey IQ (predicting how rush will develop) or deception (making defender think you are shooting when you are passing). The Leafs are below league average, thus Kadri excelled this season with players of inferior skill level…… and I would say that analysis passes the eye test.

Computer vision is so clearly the most effective way to describe the complex game of hockey. Now what can we do with all this data. It’s a hockey game on a spreadsheet. Do we evaluate players, use it to scout the next Connor McDavid, or predict the next Stanley Cup champion. I have an idea and I’ll share that with you next.


If you like what we’re saying, you may want to learn more here. If that’s not enough, you may want to get involved by starting here.

April 19, 2016

The Problems You Pointed Out with the System

Yesterday you may have noticed a number of problems with my solution. Today, we discuss mitigation strategies.

  • Problem 1) Don’t you need a lot of coaches?
  • Problem 2) Isn’t this a little subjective?
  • Problem 3) How do you know if it works?

The solution to all three problems is automation. We discuss exactly how we are already creating that system. Let’s explore how automating this system solves the three problems that I brought up.

Problem 1) Don’t you need a lot of coaches?

If it’s an automated system, you just need a wide enough camera to capture all the players. Now, you no longer need one coach per player. You only need one system per game so long as each player has a wearable device to signal the positive reinforcement.

Problem 2) Isn’t this a little subjective?

Yes. Right now it is completely subjective. But so is coaching. Automating the system reduces that by nature. With automation, we can systematically split test what the best habits to reinforce are, what timing we should use, how many habits to reinforce, etc..

Problem 3) How do you know if it works?

We have tons of anecdotes suggesting that it works great. But as any good scientist knows, the plural of anecdotes is not data. We know we need data in order to fully validate the method. What we know for sure is that the players enjoy using the system, they believe it helps them, and they ask to use the system more. We also know that they don’t feel reliant on the system and report improved play after using the system even when they are not currently using the system.

Like I said, the plural of anecdotes is not data. By automating the system, it allows us to gather more data points to tweak our methodology and make a bigger difference.

We are creating the automated system. While this might not be available to players right now, the opportunity to get involved with what we’re doing…is.

If this interests you, you may want to learn more.

April 19, 2016

Solving the Coaching Problem (It’s worse than you think)

Today we solve two common problems for hockey coaches. We recognize that games and practices are far away from an optimal learning structure. So we seek to use Flow Theory and Operant Conditioning to come up with a way to move hockey games and practices towards an optimal learning structure.

I think I’ve come up with an elegant solution to this problem. Here is what I came up with.

Here is the problem:

  • There’s a physical distance from coaches to players in game
  • Psychological processing capabilities of a player is limited
    • Ability to conceptually understand feedback and then apply it is limited depending on intelligence level and age
    • Ability to process auditory feedback quickly and unconsciously is limited
  • Distribution of coach and players (coach to player ratio) is low
  • Time lapsed between skill and feedback is large

Here is what I cam up with for a solution:

Do a video analysis or game analysis on a player to determine 3-4 key areas that need to improve. Those key areas should be specific and measurable. They should also be attainable based on the players skill level. 3 or 4 things seems to be about the right amount based on some basic testing I did.

The key areas to improve should be “translatable” or “keystone” habits. This means that by fixing one habit, it increases the odds of success in a game. One example of a “keystone” or “translatable” habit is shoulder checks. By creating a shoulder check habit, many other good habits follow. For example, players “see” the ice better. They can also make plays quicker. I suggest that Darryl Belfry is the best in the world at determining which habits lead to the biggest differences.

Once you have determined the 3-4 key habits to improve, you get a remote vibration device. Also known as a remote vibration dog collar. This is where most of you start laughing uproariously. You can get these things at any pet store. (You’re not buying a shock collar – it is a vibration trainer). Then you attach the dog collar to a player’s leg.

You can then watch the practice or game and provide a vibration when the player executes one of the 3-4 key habits. The vibration serves as POSITIVE REINFORCEMENT – not a punishment. Players already know when they mess up. That’s why I don’t think that a punishment needs to be executed. I think that it is often less clear when a player has done something well. So by identifying it and reinforcing it, you help to make it clear to the player.

That’s it. That’s the solution.

This solves a number of things:

  • Immediate feedback: check.
  • Clear goals: check.
  • Match challenge to skill: check.
  • A little “out there”? Check that too

Here are some other solutions. I’ll explain why they don’t work as well as my solution.

Video Analysis

I believe that Darryl Belfry is the best in the world at this. He has tons of experience and distills the key “translatable” habits that players should adopt to improve their odds of success. What makes him unique is his ability to isolate the “translatable” habits. Whereas other coaches might just huck stock advice at players after looking at video, Belfry seems to be very precise and data-driven in his approach. I don’t know these things for sure, but that’s the impression I get from watching his stuff.

The video analysis still leaves one loop open – live feedback. I believe part of Darryl’s process is to show video prior to an ice session, then practice it in a drill. This is very close to the optimal learning structure. However, it also takes a lot of time and energy to implement. Only the top players can get this type of video-instruction situation.

I suggest that video analysis to isolate “translatable” habits can be supplemented with real-time in practice and in-game feedback using the wearable device. This is the exact same as getting feedback from a coach in a 1on1 training session, but now you get it in the dynamic practice or game environment.

1on1 Coaching (On-Ice Habits)

I think that 1on1 coaching is great for skill training. It is the best ratio. But what happens when a player doesn’t need to learn skill – but needs to learn habits? You can run simulations in the 1on1 session, but without the dynamic real-game environment, the player simply can’t learn in the same way.

This methodology arose because I was kept trying to communicate in-game cues to a player in a 1on1 environment. It wasn’t working. So I innovated this new approach to signal to him his appropriate habits in a game situation.

1on1 Coach (Consultant)

Sometimes parents will get an experienced coach to come and watch their kid play. They’ll want feedback from that experienced coach. This is great. It’s another eye in the sky. But what is missing is…you guessed it! Immediate feedback. The coach may provide the best analysis in the world, but without immediate feedback, the player misses the opportunity for a neural connection to learn new habits.

Small Group Sessions

I love small group sessions. But during them I still need to divide my attention. I try to structure drills so that I can coach each athlete enough, but I still miss things. I’d guess that I miss 40-50% of teachable moments per player. If I were to try and reduce that number, the practice would move at a snails pace. I tradeoff pace of the practice for missing out on teachable moments. With my above solution, there is no tradeoff.

Normal Coaching

As I write this, I’m in the middle of coaching a team in a tournament. I leave the rink exhausted because I’m so mentally engaged while coaching. I’m trying to pay attention to the right things, instruct the players in the right way, catch them doing things right, and catch teachable moments. Meanwhile I’m running the lines, and paying attention to the game situations.

This is nothing special. This is what any coach does. My point is that as a coach, I’m trying to pay attention to many, many things. I simply cannot pay attention to each player and reinforce their every skill. I estimate that I provide teachable information to players 10-30% of the time that they need it.

As a coach, I found myself wishing I had backup. I wish I had someone there to catch every teachable moment for each player. Every mistake, every success was a teachable moment to players who were completely lost – who had not learned translatable habits. And I missed so many of them. If I had backup, each player would have gotten more feedback. More feedback means an optimal learning structure, which means accelerated learning.

No other coach is going broadcast that they’re not doing a good enough job. That they’re constantly failing to teach your kids. I’m a pretty good coach, and I’m telling you that I am definitely failing. Imagine how bad the average and below average coaches are doing… How much development and potential is being left on the table?

If you liked this article because it was different than most Drone Coach advice, and you’d like to get to work on becoming a Hockey Wizard, then click here to check out the benefits of becoming a Train 2.0 Member.

April 19, 2016

How to Train Skills & Habits in Hockey

The funny thing about animals, is that we often treat them the same way we treat humans. We personify them by giving them human names, attributing their behaviour to human-like desires, and giving them human emotions.

We all know people who have ill-behaved pets. Those humans make the assumption that their pet understands their language and emotions. Their pets don’t understand language or emotions. Pets may recognize language and emotions but they don’t understand them. Pets understand cues and reinforcement.

Some may say that humans are different. The Moist Robot Hypothesis disagrees.

When you break down the world to into cues and reinforcement – you may first discover yourself feeling a little uneasy. Then, many of the mysteries of the world, while still mysterious, become mysteries that are solvable using c(l)ues. (See what I did there?)

For example, if we know that humans react to cues and reinforcement, the mystery is in figuring out what cues to give, and how to reinforce behaviours.

Most humans reinforce the wrong behaviours in the wrong way. For example, my new dog gets very excited after a walk. We put her in her kennel to calm down. Except, when she’s in the kennel she starts whining. Many people would take the dog out of the kennel to reduce the whining. However, that legitimately makes the problem worse. Because the dog gets the outcome she wants, and she gets it by whining: we let her out of the kennel. If we let her out of the kennel, we would accidentally reinforce whining. Most people don’t look past the immediate reduction in whining to what type of behaviour pattern this sets up. Neither do most coaches.

You might see now that it is difficult to respect the laws that govern our behaviour. The logic is non-intuitive to most people.

Remember discussing how to make hockey players more aggressive on the ice? One coach suggested boxing as a solution.

While boxing may have some sort of carryover effects – like increased confidence, decreased fear of confrontation, etc., it doesn’t do anything to help a player recognize cues. Nor does it do anything to reinforce a player’s appropriate aggressive behaviour in a game situation.

I find there are coaches who coach with using a stream of consciousness style. Whatever pops into their head (frustration, anger, happiness) just comes spewing out to the player. Regardless if the emotion reinforces the right thing or not, they spew it out. They do not tactically decide what emotions to let out in order to properly reinforce behaviour.

There are other coaches, the top ones, who tactically determine which behaviours to reinforce. They see a situation and provide a calculated response. Those coaches are few and far between. Most of the coaches who do this well are not conscious of it. I really appreciate them.

Then there are quite a few coaches who think they know what I’m talking about, but don’t. They usually reinforce the wrong stuff, the wrong way. I’d say that 90-95% of coaches are like this. So, there’s a good chance that if you are a coach reading this, you’re one of the coaches who think they know but don’t. Sorry for being blunt, but that’s just the way the statistics line up. But maybe you’re the 5-10%. We can’t rule that out.  (On that note, I usually assume that I’m one of the idiots, and see what I can learn. But that’s just me.)

Anyway, by this point, you might be buying what I’m saying about proper cueing, and proper reinforcement. If you haven’t bought yet, you will buy it soon.

Let’s take it to the next level. Let’s talk about Flow State.

We all know that the Flow state is the psychological state of peak performance. It is also known as being “in the zone”, or “dialled in”, or whatever you want to call it.

Funnily enough, the research for Flow State lines up with the research for cues and reinforcement (operant conditioning). For example, we know that if you want to get in a peak psychological state of Flow, you need three things:

  • The challenge must be hard enough so that it’s challenging, but not too hard that is causes anxiety. Proper challenge to skill balance.
  • There must be clear goals.
  • You must have immediate feedback in your task.

Hmm. What does that sound like?

It sounds like operant conditioning doesn’t it? Let’s see how they match up.

  • The fastest mode of behaviour shaping is with positive reinforcement. In order to properly do positive reinforcement, you must have a clear target behaviour. Sounds like clear goals are needed for both, doesn’t it? Flow Theory and Operant Conditioning in synch? Check.
  • For operant conditioning to work well, the skill to be shaped is a skill that the performer can complete. But the performer is not completing consistently yet. This sounds like finding an appropriate challenge to skill balance like in flow theory, right? Flow Theory and Operant Conditioning in synch? Check Two.
  • Positive reinforcement requires that a reward stimulus be presented shortly after the target behaviour has occurred. Flow Theory predicts that you need immediate feedback to get into Flow. Flow Theory and Operant Conditioning in synch? Check Three.

It looks like the ideas of operant conditioning matches up with research in Flow Theory. Could it be that both theories describe the same thing? An optimal learning structure? And when we have an optimal learning structure, don’t we get Accelerated Learning?

Now here’s a problem for you. I think I’ve come up with a solution for it. I will share in a later post. But meditate on this:

How do you get a player to have an optimal learning structure in a game situation? There are a number of problems. Negative feedback is often immediate in the form of a mistake. Positive feedback is only sometimes obvious. Sometimes it isn’t. Mostly, eedback from a coach occurs on the bench after the shift is over. There is a time gap between skill execution and feedback. In this situation, if a player is unclear on what behaviours deserve positive reinforcement, what happens? Is there any learning at all? Moreover, what if a player is unclear on their objectives for every shift?

Here’s a second problem:

How do you get a player to have an optimal learning structure in a practice situation? There are way more players than coaches. The coach has limited attentional resources – so they can only pay attention to about 7 things at a time. Meanwhile they are supposed to monitor the drill, individual players, and themselves. How do players get immediate feedback? They might get it some of the time, but not all the time. How do players have challenges matched for their skill level? There’s too many players on the ice for the coach to give individual goals to each one. And finally, are the goals for each player always clearly identified? No, because the coach doesn’t have enough time. A player could get 1on1 coaching, but then you lose the interactivity component of the practice.

You might see how these are common problems for hockey coaches. You might also see that it is very far from the optimal learning structure. Can you solve this problem using what we know from Flow Theory and Operant Conditioning? I think I might have come up with one solution. Check it out here.

P.S. If you liked this article because it was different than most Drone Coach advice, and you’d like to get to work on becoming a Hockey Wizard, then click here to check out the benefits of becoming a Train 2.0 Member.

April 19, 2016

The Weirdest Perspective On Hockey You’ve Come Across

Not long ago, I talked about treating your players like dogs. There was a funny part and an interesting part to this little piece. The funny part is that treating your players like dogs (properly) works. The interesting part, is that not many people understood it.
One reason that few understood this article is because most people don’t understand the Moist Robot Hypothesis.
Scott Adams thinks that humans are like Moist Robots. The Moist Robot has a set of instructions (a program), and it responds to commands based on their programming.
Now, Scott Adams is a “trained hypnotist” and a cartoonist. He often suggests that his readers should “not take advice from a cartoonist”. He might be right. But we might be able to take advice from a Ph.D in psychology: Robert Cialdini. Cialdini suggests that there is a “click, whirr” response in the brain. Where a request framed in a certain way leads to a pre-programmed response. He found that persuasion professionals (salespeople, dealmakers) are adept at invoking this “click, whirr” response to get more “yeses”. Cialdini’s work shows that we might have less free will than we think. From the flower-giving Hare Krishna devotees, to establishing rapport, we can influence behaviour of another, without them knowing, based on what actions we take.
On top of this, in “The Power of Habit”, Charless Duhigg suggests over 40% of our actions are habits – automatic reactions to external events (cues).
Work by Kahneman and Tversky also shows that humans are known as “cognitive misers”. This means that we don’t engage in effortful thinking all the time. In fact, our brains prefer the simple shortcut/approximation most of the time. Effortful thinking has a huge energy cost. So our brain systematically takes mental shortcuts to save energy and processing power. As a result, humans often have predictable (programmed) reactions to certain problems. These mental shortcuts/programs lead to faster processing, but can also sometimes lead to systematic errors in judgment. We call these programmed reactions biases.
You might be getting a little freaked out now that the data seems to confirm this Moist Robot Hypothesis. And that might be helpful.
You see, when you accept that we are indeed Moist Robots, you start looking at your learning and development in a different way.
I used to think that if I “worked harder” I would automatically get better. But then I realized two things: 1) My environment matters a lot 2) How I’m programmed to react to my environment matters even more.
Here’s an example:
As a young player, I was extremely determined to succeed. I would listen to any advice that coaches offered me. I remember that one time, a well meaning coach told me I should take a slapshot with a straight left arm (I’m right handed). While it’s generally true that you make contact with the puck with a straight arm, your wind up should usually be with a bent arm. But I didn’t know this. Neither did this well meaning coach. But since I was so determined to get a harder shot, I practiced this (faulty) technique again and again and again and again.
Eventually, I figured it out and stopped taking slapshots like that. But the amount of years where I had a crappy shot was…a lot. My shot is still the weakest part of my game.
Why did this happen?
1) The advice the coach gave me was shitty. Environment.
2) I was programmed to be coachable rather than trust my instincts.
Fixing the first part is easy. Well maybe not that easy for some coaches. But it should be the easier part: get better information.
The second part is challenge. How do you hack into a player’s program and figure out how they respond to certain inputs?
Remember that in my example, I wanted to listen to a volunteer minor hockey coach more than I trusted my own body feel. Most people do. For me, I derived more pleasure from being coachable than from trusting myself while ignoring a coach. Ignoring a coach was painful to me. There’s nothing inherently wrong with this setup so long as your coach gives you better information than your body does. In my case, I was unlucky and my coach didn’t.
One way to adjust the programming in a player’s mind is to show them what to pay attention to. Particularly, what things they should associate pleasure to and what things they should associate pain with.
Even famed life coach Tony Robbins jumps in on the Moist Robot hypothesis. He says that everything we do comes down to the pleasure-pain principle. You do something to get more pleasure or to avoid pain. Often, problems occur in our lives are when we misacossiate pleasure and pain to the wrong things. For example, someone who is overweight associates more pleasure to food than to being skinny. Or the pain of eating healthy is larger than the pain of being skinny. Either way, their pain-pleasure principle is all out of whack. They need to mentally associate pain and pleasure to the right things in the right way in to get what they actually want. He calls this alignment of the pain-pleasure principle with your goals Neuro Associative Conditioning.
The other day, a mom told me that her son’s coach recommended boxing lessons. The coach felt the player wasn’t aggressive enough on the ice and that boxing would solve this. While this seems to make sense, it often doesn’t work that well. By the same logic, I should tell my athletes to play poker to learn to be more deceptive on the ice. I’ve seen the boxing thing happen, and it rarely works for players that don’t have the correct programming for aggression.
The problem is not that the player doesn’t know how to hit a punching back or throw a left hook. The problem is that the player does not recognize the cues for initiating aggression. It might also be true that the player is scared. This means that he associates more pain to initiating aggression than to not initiating aggression. Think about this for a second.
To train someone to be aggressive you cannot teach someone boxing and expect them to become aggressive on the ice. I believe that they need to be taught the cues to demonstrating aggression, and then associate more pleasure to initiating it. Then they need to be rewarded for this. This isn’t a simple or quick process, but it can be done.
So how do you go through this process?
Another Moist Robot supporter, Karen Pryor, wrote an entire book on this type of thing….for animals.
Pryor notes that it is often easier and more obvious to correct (negatively reinforce) bad behaviour than to creatively reinforce a positive behaviour. However, she also notes that positive reinforcement leads to faster adoption of behaviours. Positive reinforcement is different than a reward. Positive reinforcement is INSTANTANEOUS and leads to a neural connection between behaviour and reward. In other words – pleasure. You might see how this ties into the Pain-Pleasure principle. A reward comes later. There is a time gap between behaviour and reward. As a result, there is no neural connection. That is one reason why money (year end bonuses) is not as motivating as people think.
Putting all of this together, can you figure out how you might shape aggressive behaviour in a hockey player? How about other behaviour? (I keep intermixing behaviour and skill. They are the same thing).
Next article we discuss this question a bit more.
If you’re finding this topic bizarre, you may enjoy the rest of the series.

P.S. If you liked this article because it was different than most Drone Coach advice, and you’d like to get to work on becoming a Hockey Wizard, then click here to check out the benefits of becoming a Train 2.0 Member.