The original viz for this week was so good that I struggled to come up with something different. In the end, I wanted to learn by recreating the original. Check out #WatchMeViz and interact with the viz below.

• The years are listed in order from most recent to oldest.
• Table can be sorted
• Including separate columns for each medal
• Including links to each athlete

What works well?

What could be improved?

My Goals

What works well?

What could be improved?

My Goals

What works well?

What could be improved?

• Final dashboard is 700x700
• Everything must be a single sheet except for the footer
• Match the title, summary below the title, colors, and tooltips
• Each circle represents a score
• Circles are sized by the type of basket (FT, 2Pt, 3pt)
• Score must be cumulative across the game; note that time counts down in basketball
• Tooltips should shows the score at that moment in time and a description of what happened
• UNC color is #6490C6 while the Gonzaga color is #00143F
• Gridlines should be displayed every 5 minutes and every 10 points
• Last basket for each team should be labeled with the cumulative score

Definitely my quickest Makeover Monday ever. Forgive me, I’m busy at the bar at the beach.

This week we looked at a rather funny dataset from FiveThirtyEight about how the media tries to avoid saying “groin” when someone in a sporting event gets hits where it hurts. They presented their work in this table:

There’s nothing particularly terrible about this other than a table of numbers makes comparisons more difficult than necessary. The summary on the right helps it make a bit more sense.

For my viz, I wanted to create a chart that I’ve never built - a treemap bar chart. Basically this is a way to view the distribution of the words by each media outlet but also summarize them in bar chart form so that you can see which media outlet ranks the highest.

This week's Makeover Monday looks at this simple stacked bar chart from Sports Chart of the Day:

What works well:

1. Nice labelling on the axes; this makes it clear what we data is displayed
2. Nice annotation of the point of the chart

What could be done better:

1. Needs a better title
2. Needs to incorporate shooting % so that I can better understand the relationship between shots taken and shooting %
3. Group together all shots over 30 feet
4. Find a better way to compare the number of shots taken on each range. I find the stacked bars hard to compare within in a shot distance.
5. Make the different shot ranges more clear, e.g., what defines a long 2?
6. Provide a summary
7. How are Curry's shot selections changing over time?

With these considerations in mind, here is my my makeover of the chart:

Note: If you'd like to participate in Makeover Monday, check this link for the details.

Business Insider published this vertical bar chart of beer prices in the NBA.  The data is incredibly simple, yet they made the chart unnecessarily hard to read.

Some of the problems I see with this chart include:

1. The vertical bars should be horizontal, which would make them easier to read and compare.
2. The bars are sorted backwards.  The topic is high beer prices, so the highest prices should be first.
3. This chart requires you to turn your head sideways to read it.  When you mentally turn your head, suddenly the chart goes from right to left, instead of left to right.  Bars are easier to compare when left aligned vs. right aligned because that’s how we read. 

I previously had some data from Forbes about franchise values (and other financials).  I added the beer price to the data set.  My goals for this viz were:

1. Redesign the chart, factoring in the problems I’ve noted
2. Make the chart a bit more fun
3. Determine if there’s a relationship between what teams charge and their revenue, franchise value, etc.

Earlier this week, my wife was having a conversation on Facebook about our move to California when she suddenly said “he has gained weight from the cafeteria.”

She’s was being funny.  If you ever meet her, you’ll know what an angel she is quite quickly, especially for putting up with me.

Unfortunately she’s not exactly wrong.  I pretended to be offended of course.

Many of us are familiar with the “freshman 15” from college.  At Facebook, there’s the “Facebook 15”.  Same idea.  I can use the unbelievably tasty, free food and unlimited snacks as an excuse (moderation is a challenge), but I really haven’t gained much weight, maybe five pounds.

I exercise, not often enough however.  I decided that I needed some help, so I build this viz to help me find the right activities for me.

Cork Gaines wrote about the HR trend in baseball since testing started for performance enhancing drugs.  He presented a chart of the trend (surprising effective given his past charts), but he never answered his own question….is testing working? 

One way to determine the answer is through comparisons to other statistics.

I downloaded the season averages across both leagues and MLB in total from baseball-reference and built this interactive analysis.  The stats are order by batting stats then pitching stats.

This viz allows you to compare home runs to many other statistics through the selectors at the top right.  In addition you can:

1. View any two statistics to look for trends by choosing a primary measure and a comparison
2. Filter the time frame to all years, the pre-testing era, and the testing era (1993+)
3. Filter the leagues to focus your analysis
4. Click on a league at the bottom to highlight that league

In this initial view of HR vs. ERA, I see a couple of things:

1. HR are on a slow descent in the testing era, especially since 2000
2. ERA is in a similar decline, possibly indicating that improved pitches has had as much of an impact as testing
3. Batting Average has remained flat.  This means that the reduction in HR has not impacted BA.
4. Teams are simply scoring fewer runs, likely due to the reduction in long balls
5. The trend in complete games is despicable

What do you see?  Play around with the different stats and see if you can draw any conclusions.

The commentary included with the pie chart below is fantastic, but the pie chart is absolutely horrible.

A simple bar char is much more effective.  With the bar chart, it’s so much easier to see just how favored Ohio State is to win the tournament.  Also, there’s no color legend, therefore you’re not tempted to assume the colors mean something.

With the bar chart, I can clearly see that Florida and UNC are way overrated and Texas is way underrated (the seeds are in parentheses).