Throwing Injuries In Children

children baseball throwing injury Little Leaguer Youth Pitcher Elbow

What’s up ? This is THE stephane ANDRE. With my training, I’m interested in biomechanics to avoid injuries. I read « Sport Medicine Media Guide » and I learned some good stuff.

In baseball, especially at the beginning of the season, there is an increase in elbow problems amoung young players. The most common elbow problem is the medial apophysitis named « Little Leaguer or Youth Pitcher Elbow ».

The elbow joint is composed of 3 bones : upper arm bone (humerus) and 2 bones in the forearms (radius and ulna). Muscles, ligaments and tendons keep the elbow joints together.

Little Leaguer Elbow

little leaguer Youth Pitcher Elbow humerus ulna radius medial apophysis epicondyle

This injury occurs when repetitive throwing creates an extremely strong pull on the tendons and ligaments of the elbow. The pain felt to prominence inside the elbow.

« Pitcher’s elbow » can become serious if the case gets worse. Repeated pull can tear ligaments and tendons of the bones. The tear can take tiny pieces of bone like when a plant takes piece of the soil when it uprooted. This can destabilize bone growth, which can create a deformity.

Symptoms

« Pitcher’s elbow » can cause pain in the elbow. If any of these symptoms occur, it’s recommended to stop the throws :

  • Elbow pain
  • Decreased movement amplitude
  • Locking or snagging in the elbow joint

Treatment

Elbow injuries by lanching movements can become complicated cases, if they’aren’t treated.

Non-surgical treatment

Younger children respond better to non-surgical treatment :

  • Stop throwing because continuing to do this can create major complications and may reduce a child’s ability to remain active in a throwing sport.
  • Use an ice bag to decrease swelling
  • If the pain continues after a few days of complete rest in the affected area or if the pain reoccurs when the throwing starts, stop the activity again until the child is treated.
  • Improve the technique of launched

Surgical treatment

Surgery is sometimes necessary for serious injuries, mainly for girls older than 12 years old and boys older than 14 years old.

Depending on the child’s injury, surgery may includes bone fragment removal, bone grafting or reattaching a ligament back to the bone.

Recovery time

The recovery time depends on the age of the athlete and the severity of the injury. If the injury detected early and the modification of the activity begins, there will be little time required for the athlete to start the sport again.

However, if the athlete continues to play despite the pain and other symptoms, it will take several months to heal the injury. Or it’s possible that the injury becomes permanent.

Prevent

The recommendation for a child to be safe is 15 for 8-10 years old, 100 for 11-12 years old and 125 for 13-14 years old. This involves training and competitions. To avoid pitching injury, young pitchers should play 3-4 inning each game.

Subscribe to my newsletter and share this article if you think it can help someone you know. Thank you.

-Steph

P.S. If you’re in Miami and you like Caribbean food, go to my cousin’s bistro to eat Haitian food, click here .

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Create Bins and View Distributions

tableau, bins, bar, chart, distribution, age, data, science

I have just enrolled in a Data Science course on Udemy  and I learned good stuff.

It’s cool, you finished the 1st part. Now we’re going to do more deep Data Mining analysis with this bank’s dataset.

tableau, bins, bar, chart, distribution, age, data, science

To make these analyzes more deep, we’ll create a more statistical approach.

To do that we will create a new tab.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

For this new tab, we want to understand how client distributed according to their age. Is there a majority of young or old people ?

tableau, bins, bar, chart, distribution, age, data, science

Move the variable « Age » in « Columns ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

As we want to see the distribution of client ages, we need to use the variable « Number of Records » to see the number of observations. Move the variable « Number of Record » to « Rows ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

Boom, we have a chart but there is only one point on the top right. What happened is that Tableau took the sum of the ages of all the bank’s clients and the sum of all the « Number of Records », it means the total number of clients, 10 000 clients.

We’ll find a solution but before we’ll change the format to better see the chart. Right-click in the middle of the chart and select « Format ».

tableau, bins, bar, chart, distribution, age, data, science

For the font’s size, select « 12 ».

tableau, bins, bar, chart, distribution, age, data, science

Here you can see that the total age is 39 218 but that’s not what we’re looking for. What we want to see is the number of clients for each age.

I’ll explain what’s going on. We took the aggregated sums of our variables. Aggregate means that we took the total sum of the variable for each category. We added the ages but in fact we want to see the total number of observations for each age separately.

To have that, just click on the arrow in « SUM(Age) » in « Columns ».

tableau, bins, bar, chart, distribution, age, data, science

Then select « Dimensions »

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

You see, Tableau doesn’t take the aggregated sum of ages but it takes ages separately. We have a curve that shows us the continuous distribution of our clients ages. That is to say, for each age, the curve gives is the number of clients of this age.

We’ll look at the dataset. Right-click on « Churn Modelling » and select « View Data… ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

There is window that appears that shows us the data in detail. If you scroll to the right, you will find the column « Age ».

tableau, bins, bar, chart, distribution, age, data, science

We see that the ages rounded. As all ages rounded, Tableau is able to group clients by age. By positioning the mouse on the curve, we can see that there are 200 clients who are 26 years old.

tableau, bins, bar, chart, distribution, age, data, science

If in the dataset, ages weren’t rounded, you would have seen clients with 26.5 or 26.3 years. It would create a lot of irregularity, there would be plenty of spikes with lots of variations.

Oooooh look, there is a variation that isn’t normal.

tableau, bins, bar, chart, distribution, age, data, science

Let’s analyze it in detail. Around this peak, we see that there are 348 clients who are 29 years old.

tableau, bins, bar, chart, distribution, age, data, science

Here, 404 clients who are 31 years old.

tableau, bins, bar, chart, distribution, age, data, science

And this peak down that shows us that there are 327 clients who are 30 years old.

tableau, bins, bar, chart, distribution, age, data, science

How to explain this irregularity ? It’s possible that many people of 29 years old are about to turn 30 years old and many people of 31 years old who just had 31 years old. It’s chance that make us have inaccuracies. You may have other inaccuracies if you data isn’t precise and rounded. In our case, the ages are rounded but we want to get rid of our small irregularity that we see on our curve.

There is way to see our distribution without our irregularities, it’s « bins ». « Bins » consists of grouping the information into different categories. That is we’re going to regroup our clients in different age groups.

Right-click on « Age » in « Measures ». Select « Create » and select « Bins… ».

tableau, bins, bar, chart, distribution, age, data, science

A window appears. We’ll group our clients in 5-years increments. In « Size of bins », write « 5 » and click on the « OK » button.

tableau, bins, bar, chart, distribution, age, data, science

As you can see, the variable « Age » has remained in « Measures » but there is a new variable in « Dimensions ».This is the variable we created « Age(bins) ».

tableau, bins, bar, chart, distribution, age, data, science

Our « Age(bins) » variable was correctly placed in « Dimensions » because it is a category variable because each category corresponds to a 5-year age group.

For example, one category is 20 to 24 age group. Now we’ll create a new distribution based on « bins ».

To do that, we’ll remove the variable « Age » from « Columns » with a click and drag outside.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

You move the variable « Age(bins) » from « Dimensions » to « Columns ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

Note

In this case, it’s not possible to directly replace « Age » by « Age(bins) » over « Age » on « Columns ». This is because « Age » is a measure and « Age(bins) is a dimension.

That’s nice distribution, it’s usually the type of distribution (chart) we see in economics or mathematics. The difference with the old chart is that this chart is discrete. This chart is discrete because the clients grouped by age group while the previous chart was continuous.

On this distribution (chart), each bar corresponds to an age range. For example, this bar corresponds to the 25-29 age group.

tableau, bins, bar, chart, distribution, age, data, science

Now, we’ll change the colors.

In « Row », move « SUM(Number of Record) » while holding down the « Ctrl » or « Command » key on your keyboard to « Colors ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

We get our distribution in blue but we’ll change the color to red. Click on « Colors » and click on « Edit Colors »

tableau, bins, bar, chart, distribution, age, data, science

In the window that appears, click on the blue square on the right to display the color pallet.

tableau, bins, bar, chart, distribution, age, data, science

Select the red color and click on the « OK » button.

tableau, bins, bar, chart, distribution, age, data, science

Click on the « OK » button of the « Edit Colors » window.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

To facilitate the reading of the bar chart, we’ll add the number of clients in each age group. In « Row », move « SUM (Number of Record) » while holding the « Ctrl » or « Command » key on your keyboard to « Label ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

That’s it, we can see how many clients there are in each age group.

We see that the dominant bar is the 35-39 age bracket and the second dominant bar is the 30-34 age bracket. Overall, we can see that most clients are between 25 and 40 years old, which seems consistent.

On our bar chart, we have absolute values. We’ll replace that with percentages. Click in the little arrow in « SUM(Number of Records) » in « Label » and you select « Add Table Calculation… » but I’ll show you another way to do it.

tableau, bins, bar, chart, distribution, age, data, science

Instead of clicking « Add Table Calculation… », click on « Quick Table Calculation » and select « Percent of total ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

It’s cool, we have the exact percentage of people in each age bracket. Now, we can see that in the 25 to 40 age group, we have 20 + 23 +17= 60% of clients.

I’ll show you one last thing.You can change the size of the slices easily, just click on « Age(bins) » and select « Edit ».

tableau, bins, bar, chart, distribution, age, data, science

In the windows, you can change the size of the slices (bins). Put « 10 » instead of « 5 » to get 10-years slices. Click on the « OK » button.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

Now, we have a distibution with fewer slices and the dominant slice is 30 to 39 years old.

Well, it was just to show you how to change the size of bins. To go back to the old distribution with the 5-years slices, click on « Back » button.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

As you can see, the values on bars are in percentages but the values on the axis are in absolutes values. Here is an exercise that I ask you to do : « Put the values of the axis in percentage ». I’ll give you the answer the next article.

Share this article if you think if can help someone you know.Thank you.

-Steph

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Boost Your Marketing Based On Science (Part 1)

brain

I watched an Olivier Roland’s video and I learned good stuff.

Let’s see what neuroscience found on things that influence people to buy.

The book of Michel Badoc and Anne-Sophie Bayle-Touroulou « Le neuro-consommateur » (in french)  helps us better to understand this.

It’s a book that has been written for other researchers and academics. This is why this book is very interesting for entrepreneurs and consumers.

Here are the elements from this book to boost your marketing.

Until now, marketing and communication are based on the rational purchasing decisions and perceptions of advertising messages by the consumer. But neuroscience shows us that a huge part of our actions come from the subconscious part of our brain.

For A.K Pradeep  and Martin Lindstrom , only 15% of purchasing decision are rational. Current marketing studies limited in the accuracy of customer behavior. What customers say doesn’t always match what they do. Responses collected during a market study can be influenced by context, which disturbs responses. With neuroscience, we can directly communicate with the brain to try to improve marketing.

Here the elements found in neuroscience on the unconscious behavior of consumers.

  • Age et gender

  • Memory

  • Emotions and desire in the decision

  • 5 sens

  • Cognitive ergonomics, pricing, distribution and sales.

  • Subliminals relationships

  • Community and social networks.

Let’s go, we’ll see that in detail. We’ll start with age and gender because these 2 create behaviors and attitudes, sometimes, difficult to understand by a person who doesn’t belong to the same category.

Age

reptilian limbic neocortex brain

Reptilian brain

It’s the center of instincts and the satisfaction of primary needs. This mainly affects young children. They respect the leader who is the mother or the father but also the strongest person who can protect them in case of external danger.

Limbic brain

It’s the center of stress emotions, instinctive behavior and memory. This mainly influences teenagers. They are mainly attracted by new brands / products and original fashions that can distinguish or oppose them to adult fashions.

Teenagers are often interested in causes or subjects with a lot of emotions : social, humanitarian, ecological, fair trade, etc. They prefer emotional communication over rational information.

neocortex,

It’s the center of anticipation and decisions. This mainly affects adults.

With internet, we can see several big differences in the generational behavior of consumers. There are Digital Native and Digital Immigrants and these 2 categories require different approaches.

digital native immigrant

Digital Natives

These are the people who grew up with computers, smartphone and internet. They prefer to have jerky information without verb and without object complement. They can read in parallel information on several different media. They don’t need to structure their thoughts and they can have a random read mode. They feel emotions much more with colors and designs rather than structured text. They want things to go fast.

Digital Immigrants

They prefer a linear processing of information. They like the text’s logic. They wish to receive the information in a slow way with consistency in the structure. They want to keep their privacy and are wary of the information’s distribution on internet. They sometimes want to work alone.

Gender

gender male female

There is a distinct difference between the behavior of female and male consumers.

Female

The left hemisphere of the brain is more developed in women and they’re subject to the hormones influence. We can see more of this phenomenon when a woman becomes a mother. A woman like to communicate more that a man, she likes to talk and be listened to. She needs shares her ideas, feelings and emotions.

She’s very well oriented in time. A woman is less emotional than a ma but she is more sensitive because she has the sens of smell, hearing and touch more developed than a man.

Male

The right hemisphere of the brain is more developed in man and they’re subject to the influence of testosterone. A man is more emotional than a woman, but he expresses less his emotions. He likes action and competition. He’s very well oriented in space, which allows him to find shortcuts. The man’s view is very developed and is eroticized. This explains why the man is attracted by the nude, jewelry, makeup and clothes.

For these reasons, it’s easier to mee a man’s expectations compared to a woman’s expectations.

Differences

difference

Male

As you can see, man primarily uses his view to select a product or service that he can use to show his strength and seductive power. He likes offers that give short-term profits. He prefers simple and direct communication. He prefers images rather than text. Price is more important for the man than for the woman.

Female

A woman is more complex in her expectations. She processes information in a way that is both rational and emotional. A woman is not attracted by nudity. She is attracted by a neat person with harmonious clothes and neat hands. In the case of a salesman, a woman has no preference for a man of a woman. This is influenced by several elements : voice, smell, facial expression, capacity to listen and quality of answers of the salesman.

A women prefers written and documented communication. She likes social media because she can express her ideas and meet people who share her points of view. She filters rational messages through her emotions. She likes positive communications. Before selecting a product/service, she will compare it with competitors and get information with her friends, co-workers and other people with experience.

A woman is less impulsive than a man even if a purchase can serve as an antistress. For a woman, the touch’s quality and the smell can influence a purchase like clothes.

This is the end of the 1st part.

Share this article if you think it can help someone you know. Thank you.

-Steph

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Know What We Want In Life

what you want

I watched an Olivier Roland’s video  and there is good stuff.

A lot of young and less young (30-50 years old) still don’t know what they want in life. It’s not something essential to succeed in life and be happy. But read this Seneca’s quote: « If one does not know to which port one is sailing, no wind is favorable ». Life can be more interesting when we know what we want to accomplish. When you take your car, before to go in your car, you know your destination. Do you already used your car without knowing the destination ?

I think it’s important that people know what they want accompish in life, what they want leave as inheritance or legacy. To do this, we need to find our passion, a passion that drive you to be better than yesterday.

I know people used different exercices to find their passion but they found nothing, it’s a failure and they’re frustrated. In my opinion, these people have just an exploration problem.

Exporation

exploration

Exlpore several activities is a great way to find a passion. It’s simple, how do you know you like an activity, if you have never tried this. May be you are an archery olympic champion but how do you know if you have never tried archery ?

I encourage you to do new activites, meet people, discuss with them and pratices to decrease the number of activites you don’t know. The truth is that your passion will not come to seek you.

Exlpore new activies, it’s good but don’t become addicted to exporation’s phase.

In a passion, there is 3 steps :

  • Exploration phase

    It’a like when we fall in love, everything is awesome, everything is beautiful.

  • Dry period phase

    For most people, it’s in this phase that they abandon. The enthusiasm of the beginning diminishes enormously. We spend a lot of energy for little result compared to a person who has done the same thing for 3-5 years.

    And it’s also in this phase where we must be careful to not be addicted to the exploration phase. For people who don’t like the dry period phase, they will find several excuses to change activity instead of holding on until to have good results.

  • Consecration phase

    It’s at this moment that we harvest the seeds that we sowed and generally success always exceeds us.

Project

project

Once we found a passion, have a project around this passion allow us to become a better version or ourselves. This project will allow us to get out of our comfort zone, to give the better or ourselves because we really want to succeed. The ideal is to combine a passion, skill and economic potential if you want to become an entrepreneur.

To test your project, I advise you to use « Lean startup » by experimenting in the field using little time, energy and money.

What is your last activity that you did and that you liked ? Do you plan a project with ?

-Steph

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The Right Time To Start Your Own Company

too old

Really there is no age to create your own company ! You can do it when you’re young, middle, old and even if you’re retired. No age.

What is important is to have an idea and really want to do it, execute it. There is a lot of people who create their company at 50 years old and it’s cool.

If you think you have less chance to have success with your company because you start it at 50 years old, you’re wrong. It’s a limiting belief or an excuse.

This envy may be caused by the bitterness of not realizing a dream or the loss of a job or people who are retired who are bored and want to have an activity.

Gary Vaynerchuk has an amazing video about it. Watch it and have fun.

-Steph

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