Tableau Public Revizited | Feb 4 , 2020

For the third installation of Tableau Public Revizited, we’re looking back at a powerful viz created by Kaleigh Piscioneri just over a year ago, on January 30, 2019. In her viz Kaleigh does an exceptional job breaking down the gender gap in sports. Let’s look at a few elements of this visualization that make it so effective.

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What makes this great data viz?

  • Use of Color – I absolutely love the colors Kaleigh uses in this viz and the faded gray is a perfect compliment to let that red really pop, grabbing the reader’s attention. The red is a powerful color to use here and is simple to understand. Anytime we see red in the viz, we know that color is associated with women, as Kaleigh ties it into the quote at the top of the page, as well as in a couple of other places. I can’t imagine a better use of color to tell this story. In my opinion, Kaleigh nails it!
  • Chart Selection – The stacked horizontal bar charts at the top of the viz are nice as they do two things, aiding in the telling of the story while also separating the title from the rest of the visualization.
    • Unit Charts – The main focal point of the viz, Kaleigh’s use of the side-by-side unit charts is brilliant. The charts help drive home the disparity in earnings of professional male and female athletes better than any other chart Kaleigh could have placed here. We can quickly see that in 2017, of the Top 100 highest paid professional athletes in the world, just one was a woman. And in 2018, zero were women.
    • Donuts – Below the unit charts, Kaleigh looks more in depth at the difference in male to female average salary in three sports; basketball, soccer and tennis. The difference in basketball, where the average female salary is 1.3% that of the average male salary, is staggering to see visually. While soccer is not much better, tennis has far and away the smallest gap of the three sports. I like the use of donuts here, as it allows Kaleigh to add the KPIs in the center, while also including the background image to help the reader understand which sport is which.
  • Tooltips Upon first seeing the side-by-side unit charts, your initial thought is likely that you’re interested in knowing which athletes represent each of the dots. It’s a perfect use case for tooltips and Kaleigh does a great job of including more detail, as the reader hovers over a mark. While hovering on a mark, we can see that the female athlete who shows up in the 2017 Top 100 is Serena Williams. Name, rank, gender, sport, country and salary are all included in a very clean, compact layout. Nicely done! 


Exploring the viz – I was particularly interested to see which NBA players would show up each year. The reason being is that in 2015 the NBA salary cap was around $63 million, meaning each team could spend that amount of money on their roster, before being hit with penalties/taxes, if they exceeded that amount. By 2017, in large part to new TV deals, the cap had jumped to just north of $94 million, an increase of $31 million dollars from where it was in 2015. This led to teams over-spending on mid-level (average in terms of talent) free agents in 2017 and 2018, as they had the cap space to burn. Knowing this, I wanted to see how many of those mid-level players made the Top 100. After exploring the viz, I found five players who fit this description; Harrison Barnes, Chandler Parsons, Nic Batum, Steven Adams and Otto Porter Jr. were all among the Top 100, despite none of them ever being selected to an NBA All-Star game. While Batum and Parsons were making eight figures even before their new, free agent deals, the average salary of Barnes, Adams and Porter Jr. jumped from $4.3 million to an astonishing $23.1 million. Nothing like getting a near 600% raise for being just ok at your job!

Overall, I feel Kaleigh does a wonderful job of combining the elements we covered, to bring attention to this glaring gender gap in the earnings of professional athletes. Great viz, Kaleigh!


Tableau Public Revizited | Jan 20, 2020

With 2020 Australian Open underway, this week we’ll be reviziting a beautiful viz from Kate Schaub, published on May 5, 2019. The viz, which has a really cool poster-like feel to it, is titled ‘Serena – The Greatest of All Time’ and it covers the amazing career of tennis superstar, Serena Williams. Let’s get started!Serena _ G.O.A.T. v2First off, just take a step back and zoom out a bit to get a nice full shot of the viz. I really appreciate how well Kate thought through the design and layout of the visualization, as it flows together so well. Alright, let’s see what makes this a great data visualization.

What makes this great data viz?

  • Design/Layout – As we just touched on, the visualization is laid out really well, in an order that makes it easy for the reader to follow.
    • Top section – this section features the title in an absolutely awesome font, while also including Serena’s personal information, ranking by year and some KPIs centered around her titles won and career earnings. Serena’s personal info in the upper left-hand corner is a nice touch, providing us with a little background on Serena Williams the person, before getting into Serena Williams, the tennis superstar. Next, we move onto year end ranking. Kate nails the chart choice here, given the theme, as the circles resemble tennis balls and the line chart gives the effect of the path of the ball. It’s amazing to see how many years Serena was ranked in the Top 7 (15 out of 22 years) and I also love how her 2006 ranking of 95th makes it look as though the ball is bouncing; very cool! Lastly, Kate includes some nice and clean KPIs that provide three key metrics; Grand Slam Titles, WTA Titles and Prize Money.
    • Middle section – After reading the KPI section, my first thought is what Grand Slams has Serena won and how many of each. I like the use of icons here displayed as unit charts, as seeing the actual trophy/medal Serena won adds a little something that we wouldn’t get had Kate gone with a plain circle or square in her unit chart. This also adds to the poster feel, I like it a lot. We can easily see that Serena’s won the Australian Open and Wimbledon seven times apiece, as well as the U.S. Open six times.
    • Bottom section – In this section, Kate provides more detail around Serena’s seventy-two WTA titles. The lollipop charts again give us the tennis ball feel and we can see that Williams started her career with a bang, winning twenty-five titles by the age of 23. However, her career appears to regress from age 24-29, which makes me wonder what happened? A quick Wikipedia search and it looks like Williams battled several injuries during this stage of her career. We then see her reaching peak dominance in her early to mid-thirties, before regressing again in her late thirties. This regression can be attributed to Serena’s pregnancy, which saw her miss almost the entire 2017 season. Lastly, I feel the image of Serena fits well in between the lollipops and the radial chart, which shows Serena’s titles won by playing surface.
  • White Space – Kate does a really nice job of packing a ton of information into the viz, while not making it feel cluttered. She leverages white space to give each section of the visualization plenty of breathing room.
  • Excellent Use of Color – Whether you see yellow or green, let’s just agree that the way the tennis ball color pops against the black background is a thing of beauty! Kate nailed it with this combination and another thing she did very well is to not overuse the large attention grabbing font. She placed it only where she wanted to guide the readers attention; beginning with the title and then the names of the Grand Slams, sticking with a smaller, more basic font for the other headers. She also uses the popping tennis ball color for the two main charts, very well done.
  • Tooltips Provide Context Tooltips are a powerful Tableau feature and particularly viz in tooltips, when used effectively. If we think back to Kate’s use of white space, we can see in the image below that her use of viz in tooltips helps prevent the viz itself from being cluttered. However, the tooltips pack even more insightful information into the viz. When I saw the viz for the first time, I remember thinking, “I wonder how many Grand Slams and how much Prize Money Serena has won compared to everyone else?” Well, wouldn’t you know, Kate included that very information through her use of viz in tooltips. The reader can also see who Serena defeated for each of her Grand Slams, as well as the score.


At the end of the day, this is a really cool visualization that should be framed and hanging on a wall somewhere. It’s pleasing to look at, designed very well and tells the story of one of the greatest athletes of all time. Great work, Kate!

Tableau Public Revizited | Jan 7, 2020

With over 750,000 Tableau Public authors and thousands of visualizations published daily, great visualizations are becoming more and more likely to fly under the radar. We’re most likely to remember the one that garnered thousands of views, a bunch of favorites and perhaps, even, a Viz of the Day. However, there are so many more visualizations on the Tableau Public platform that exhibit great data visualization skills. It’s for this reason that I’d like to introduce Tableau Public Revizited; a project dedicated to celebrating examples of excellent data visualization, which happened to fly a little under the radar, from a Tableau Public number of views standpoint. The only requirement to be considered for selection is that a visualization must have had fewer than 500 views on Tableau Public, at the time of selection. Ok, time to get started with our first visualization of 2020!

We’ll get Tableau Public Revizited underway with this fantastic viz from Justin Davis.NCAA Football SalariesJustin published this viz on October 23, 2019 and with the College Football National Championship game scheduled for Monday, January 13, what better time than now to highlight his viz? You may remember a visualization Justin created back in March, called ‘NCAA Basketball Salaries.’ That viz was recognized as not only March 28th Tableau Public Viz of the Day (#VOTD), but also as Tableau Public Viz of the Week for the week of March 25-29th. NCAA Football Salaries has the same layout, so I like the fact that we’re already familiar with the look and feel. Several elements make this a great Tableau Public visualization. Let’s take a look at the viz.

Justin’s visualization features the salaries of coaches from what are referred to as the ‘Power 5’ conferences of Division I-A college football; these conferences are the Atlantic Coast Conference (ACC), the Big 12, the Big Ten, the Pacific-12 (Pac-12) and the Southeastern Conference (SEC). The bottom right section also includes the Top 10 highest paid coaches from schools outside of the Power 5, including independent, Notre Dame.

What makes this great data viz?

  • Simple layout – Grouping the bar charts by conference allows the user to quickly and easily compare salaries not only within each conference, but also across the different conferences. For instance, we can quickly see that Clemson’s Dabo Swinney and Alabama’s Nick Saban are the highest paid coaches in college football…and rightfully so, as these teams have combined to win the last four college football national championships, with two apiece. And furthermore, the only other team to even make an appearance in any of those title games was Georgia in 2017. Two other things grabbed my attention right away;
    • The fact that the highest paid coaches in the Pac-12 are paid quite a bit less than the highest paid coaches within the other Power 5 conferences.
    • Notre Dame’s Brian Kelly earns a salary of just $1.67 million. As a lifelong Irish fan, I’m aware of the fact that NBC has held Notre Dame football TV rights since 1991. And with the latest deal being worth $15 million annually, I assumed Kelly’s contract would be larger, so seeing it highlighted when I opened the viz, captured my attention.
  • Clean formatting – You’ll notice the viz includes no grid lines and no axes. Why? Because, with the way Justin designed the viz, they are unnecessary. He includes a bar chart for each school and labels the value on the inside of the bar, which I love as well in this scenario. Not only does labeling the inside of the bar save some room, but it also allows the user to more easily scan down and read the salaries. It’s a much cleaner look than if he had labeled the ends of the bars. He also stuck with easy to read Tableau fonts which I’m a big fan of. Ok, now to my favorite part and the part that really makes this viz special, in my opinion.
  • Effective Use of Color – Under the title, Justin includes a parameter driven slider, where the user can select a winning percentage of their choice. This then updates the visualization by highlighting coaches who have won at least that percentage of their games. The default is set to 85%, which is a great place to start. When I opened the viz, the first thing I did was slide it down to 50%, as I wanted to see which highly paid coaches failed to win 50% of their games. See the result below. We can see that Purdue’s Jeff Brohm and Florida State’s Willie Taggart were both paid at least $5MM and won fewer than 50% of their games. Taggart was actually fired by FSU earlier this season, after getting out to a 4-5 start, while Brohm is still hanging on as coach at Purdue, but had another disappointing year, finishing 4-8 this season.NCAA Football Salaries (1)
    • One last really cool detail Justin added to the slider is dropping a calculation onto size that makes the 0%, 25%, 50%, 75% and 100% bands wider than the others. This helps make them much easier for the user to find. He also leverages a hover parameter action to drive the interactivity on viz itself. param%s

All in all, I think this is a great example of a clean, effective visualization. Easy to understand, as we’re dealing with bar charts, not cluttered at all with any unnecessary text or labeling and powerful in its use of color. Great work, Justin!