Which NHL players benefit from more shifts?: Official Entry for Tableau Sports Data Viz Contest (2 of 2)

Tableau allows us to enter up to two visualizations in their contest.  So after building the monster Explore NHL Player Stats I took some time to figure out what a more manageable data visualization would look like based off the results I was getting from exploring the player stats.

I have always been a fan of the plus/minus stat.  I always thought it was a good way to measure how well players play together on the ice.  A player's plus/minus increases by +1 when their team scores while that player is on the ice.  However, it also decreases -1 whenever the opponent scores while that player is on the ice.  I compare that against the average number of shifts a player has during a game and we can start to see which players benefit from having more shifts. 

It is another scatter plot, but with the filters, you can narrow your view and compare conferences and divisions and teams.  I also added a box based off of the min and max values for shifts and plus/minus.  This allows you to compare how groups of players (divisions, conferences, teams) compare against one another.  However, before you get that far, just take a look at the visualization as is.  Which conference's players seems to have a better plus/minus the more shifts they have?

Let me know what you think!

Explore NHL Player Stats from 2010-11 Season: Official Entry for Tableau Sports Data Viz Contest (1 of 2)

When I was younger, I loved choose your own adventure books.  However, I always got peeved when I wanted to choose an option that the book did not make available to me.  Or that several of the paths in the book seemed to have the same ending.  Well, now that I am older and am in control of the "story" I will let you choose which path to take in order to determine your own ending.  Choose your stats to mash-up. Choose how you want to view the players in the chart.  Highlight teams, players, or positions.  Or drill down to look at specific divisions or teams.

This visualization might seem intense, but if you take some time and choose your path wisely, you'll find that there are a wide variety of endings to choose from.  I had a lot of fun making it and even more fun playing with it.  Let me know what sorts of interesting tidbits you get as a result.

Energy Generation Viz: My first published data visualization

A former colleague of mine, Walter Frick, works up in Boston for the New England Clean Energy Council.  As a follow up to a conversation we had, he shared this EIA graph with me. As you can see it is an area chart. I've never been able to understand or read stacked area charts.  (Perhaps because they are often used incorrectly?) So, I downloaded the data for the EIA chart and reworked it. Walter liked it and used it for a blog post for his organization. My first public data visualization!

I know that stacked bar charts are not always the best way to see changes in amounts across the x axis for a particular band. However, I think visually it turned out rather nicely.

Precinct Results for Anne Arundel County Executive Race

I am involved in local politics in the Annapolis area and in 2010 I was a volunteer for a County Executive candidate.  He lost.  But it was a fun campaign nonetheless.

I was able to put together the results by precinct and throw it together in Tableau.  The results are what we would expect from taking a look at just the data itself.  However, I found it interesting that there were a few precincts with very low turnout but major support for a candidate.  I think both the Republican and Democratic candidate each had a precinct like that.  Take a look below and let me know what you think about the results.