Friday, October 30, 2015

Golfers who have reached #1 in the Official World Golf Rankings

The Official World Golf Rankings were established in 1986 to measure performance of professional golfers.  These rankings change weekly and are based on tournament results from the previous 2 years.  Certain tournaments such as the Major championships (Masters, US Open, Open Championship, and PGA Championship) and the four World Golf Championships use the rankings to determine which players are automatically qualified to enter the events.

For the first 10 years of the OWGR, there were only 7 different golfers who held the title of World #1.  The next 15 years brought forth the age of Tiger Woods.  During a 12 year period from 1998 to 2010, Tiger was the world #1 90% of the time.

Since 2010, there have been 8 different golfers (including Tiger for a 7 week span).  This season there have been 7 changes in the #1 spot and the mantle has been passed to the new "Big 3" golfers in the sport - Rory McIlroy, Jordan Spieth, and Jason Day - all under the age of 30.

Monday, October 26, 2015

What can a dog teach you about data?

I just got back from last week's Tableau Conference after spending a few extra days in Las Vegas.  What an amazing week!  This was my second conference and I can't wait until next year when the conference will be coming to Austin, Texas.

As I met people at conference, I shared my Tableau journey over the last year.  How I went to conference in Seattle without ever using the tool, taking 2 days of training, and starting this blog the day I came home.  It has been an exciting year, and I have come a learned so much, but hands down the most rewarding experience was when I was asked to present about data at my son's school

Sharing this with people over the last week, many of them commented on my example of using a dog to teach 10 year kids about the different types of data.  I was even mentioned by Tableau Zen Master Peter Gilks on his blog post of thoughts from conference.  Some people thought that this analogy was a great tool to explain to their own children what they do everyday while others mentioned that it was a great way to educate their management on data types.

So how can we use a dog to learn about data?  Well as most of you know, data can be classified as either qualitative or quantitative. Since my audience was a group of elementary students, I looked for a way to keep the definitions simple and easy to remember. 
  • Qualitative - data that is descriptive, and does not measure things
  • Quantitative - data that is used to measure and can be written down in numbers
To help them remember it, I pointed out at the "Quantitative is about Quantity."  These definitions are also useful when describing the difference between Dimensions and Measures to a new Tableau user.

Taking it one step further, there are two types of quantitative data - discrete and continuous.  I will admit that when I first started using Tableau, I struggled with this until I started thinking about it in the following terms:
  • Discrete - whole numbers or items that can be counted
  • Continuous - numbers within a range or can be measured
Once the students had a general understanding of the definition, I introduced them to Data the Dog and began asking questions. 
  • What is something qualitative about Data?
    • He is brown and white
    • He has a red collar
    • He has lots of energy
    • He is friendly
  • How about something quantitative that is discrete?
    • He has 4 legs
    • He has 2 eyes
  • Or something continuous?
    • He weighs 14.5 pounds
    • He is 3 years old
  • Can you combine qualitative and quantitative to describe him?
    • He has 2 (discrete) brown ears (qualitative)
Going in, I wasn't sure how well they would grasp the concept.  I gave 5 different presentations that day to different classes.  I thought there would be 1-2 students in each class that would provide answers, but I was wrong.  In every session, multiple kids raised their hands and gave correct answers.  One of the sessions was for my daughter's 1st grade class.  I didn't want her to feel left out since I was at her school all day.  Even they understood after a few examples!

It was so fulfilling to see these kids get excited about data!  One of the teachers even sent me an email the next day to tell me that the students had Chromebooks in class and they all wanted to build visualizations.  Future Data Rockstars!

Tuesday, July 21, 2015

2015 Open Championship

I really enjoyed watching the Open Championship this year at the birthplace of golf - The Old Course at St. Andrews.  By the final day there were 20 players within 2-3 shots of the lead at any given time.

I quickly threw together a visualization of the leaderboard and tried to model it after the style of the iconic yellow scoreboards at the tournament.

Tuesday, June 9, 2015

Junior Golf Tournament Results

One year ago today, my son entered his first golf tournament.  He had decided to give up baseball and pursue a new sport - golf.  I love both golf and baseball, and enjoyed coaching him and many other kids in baseball over the years.  I have to admit though, this past year has been so much fun for the two of us.  He has participated in 24 tournaments and made huge improvements.  I am so proud of his hard work, drive, and passion for the game.

To show him how much he has improved over the last year, I decided to create a Tableau viz.  He started out playing in 5 hole tournaments and progressed to 9 holes as his scored improved.  To adjust for the different scores, I extrapolated the 5 hole scores to 9 holes and added 3 strokes to adjust for the added length of the course.

Friday, May 15, 2015

4th Grade Survey

I was asked to do a presentation at my son's school for Career Week on analytics and data visualization.  As part of the presentation, I asked the kids to complete a survey with their favorite color, movie, TV show, book, etc.  I then created the following dashboard in Tableau for us to visualize the results.

For the kids in the presentation here is the link I promised to the Pokemon visualization created by Jewel Loree

Saturday, March 7, 2015

How Good is Mike Trout?

As a baseball fan and a data guy, I have followed some of the blogs on Fangraphs, but I didn't realize that there was a query tool for statistics.  Wow.  What an awesome resource.

I started downloading some data and thought I would take a look at how good Mike Trout has been in his young career.

Monday, February 23, 2015

Which MLB Teams Have the Most Luck?

The Pythagorean Expectation was developed in the 1980s by legendary baseball statistician Bill James.  The formula is used to determine the number of games a team "should" have won based upon the number of runs scored and allowed.  He originally used an exponent of 2, which has been revised over the years to the current 1.83.

Teams who outperform their Pythagorean expectation are generally perceived as "lucky" and those who under perform are considered "unlucky."  This viz allows you to take a look at which teams are lucky or unlucky over the years.

Tuesday, February 17, 2015

MLB Franchise Performance

I always look forward to this time of year waiting to hear the phrase "Pitchers and catchers are  reporting to Spring Training this week."

I love baseball and especially baseball history, so I wanted to focus a visualization on the past performance of MLB franchise performance.  I have also wanted to try a "small multiples" visualization.  I love the look of the NBA BALLCODE visualization by Peter Gilks over at Paint By Numbers, so I thought I would try something similar.

The viz below shows the performance of MLB franchises using games above/below .500.  You can use the sliders to go back to the 1870's, but I decided to focus primarily on the Expansion Era beginning in 1961.  I felt this was a good starting point since 4 teams were added over 2 years: Angels, Astros, Mets, and the new Senators (after the previous Senators became the Minnesota Twins).  The league also expanded the number of games from 154 to the current 162.

I also wanted to add another dimension to the data, so I decided to change the team color to gold in seasons when the team won the World Series.  This adds a good perspective to teams like the Yankees (especially if you move the slider back to the 1920s) and the Marlins (only 6 winning season, but 2 World Series titles).

Wednesday, February 11, 2015

2014 PGA Tour Average Proximity

I was inspired to tackle this chart after stumbling across a radial bar chart on the InterWorks Tableau blog.  I figured proximity to the hole was the perfect application for this type of chart.

I had to complete the custom SQL from a full version of Tableau, then extract the results into a spreadsheet to upload them to Tableau Public.  Other than that the rest was fairly straightforward using the calculations in the InterWorks blog