The Draft Board Dashboard: Visualize Your Fantasy Football Draft

It’s August and Football is Back!

Like the real world, the world of sports has seasons.  College basketball season ran through March with Virginia winning its first NCAA tournament. The NBA wrapped up in early June with the Raptors winning their first NBA championship.  We’re now currently in the middle of baseball season (Let’s Go Yankees!). 

For many Americans and some international fans, the month of August means the NFL is coming back.  Preseason games have already begun and the regular season is set to kick off on Thursday September 5th.  

I’ve been a huge New York Giants fan my whole life.  More than being a Giants fan though, what makes the NFL even more interesting for me is playing fantasy football.  Since 2007, I’ve been in at least one fantasy football league each year.

If you’re unfamiliar with fantasy football, the traditional type of league is a season long competition where each individual drafts a team made up of real NFL players.  Each fantasy team is awarded points based on the performance of the NFL players. Fantasy teams with more points than their competitors each week are awarded a win. At the end of the season, playoff seeding is determined by number of wins during the season.  A championship match determines the league winner.

Vizpiration

Before the season begins though, all of the news, strategy, and speculation that has been studied by each fantasy football player throughout the offseason culminates in the fantasy football draft.  This is the event that kicks off the fantasy season for every league and where each team picks their players to start the year. A typical fantasy football draft is conducted snake style where each team picks one player in the first round and then the order is reversed so that the last player in round one gets the first pick in round two.  The draft continues in this back and forth manner until each team’s roster is full.

This year, I have the good fortune of joining two of my favorite activities together by playing in a 16 team fantasy football league with several other Tableau enthusiasts.  Shout out to my fellow #DataFamtasy leaguemates! 

  • Jesse McConnell @mcconnellj
  • Brian Moore @BMooreWasTaken
  • Jacqui Moore @jaxx084
  • Sean Miller @HipsterVizNinja
  • Alex @databiscuits
  • Tim Cady @tiivn
  • Katy Sandlin @the_worldforgot
  • Vince Baumel @quantum_relic
  • @dataNOTdoctrine
  • Bo McCready @boknowsdata
  • Mark Bradbourne @MarkBradbourne
  • Vinodh kumar V R @VinodhDataArt

Throughout the season, we’re going to be vizzing our fantasy football data.  As soon as I signed up for this fantasy league, I knew that I wanted to viz the draft.  The standard snake style draft board lends itself so well to being visualized in Tableau.  While my league hasn’t drafted yet, I’ve created the following Draft Board Dashboard as a template for anyone to use to visualize your own fantasy football draft!

Draft Board Dashboard Template

Utilizing the top rated fantasy football players from the Fantasy Pros website (link), I created a dataset in excel to build my draft board.  Here is a look at the fields in the dataset:

Draft Template Data Headers.png

At the very least this viz requires the following fields:

  • Round Number: Draft round number.  Dictated by the number of roster positions that each team has available.
  • Round Pick: Determined by the number of teams.  If you have 12 teams, there will be picks from 1 through 12 in each round
  • Fantasy Team Number: The numerical position that the team will be drafting in the odd numbered rounds.  Used to order the teams on the board
  • Player Name: Name of the NFL player.

To capture more detail in the viz, I’ve also included the following fields in the template:

  • Fantasy Team Name – Name of the teams in the fantasy league.  This is pulling from the “Team Names” tab in the excel datasource so you only have to enter the team names once
  • Player Position: Position of the player for their team e.g. QB, RB, WR
  • Player Team: Current team of the NFL player
  • Overall Pick: Overall pick number that a player was selected in the draft

Note that I created this template for a 16 team league.  If you have less teams in your league you can delete the extra teams from the dataset.  For example, if you only have 10 teams, filter the Fantasy Team Number column in the spreadsheet for teams 11 through 16 and delete those rows.   As your draft will have its own set of picks and teams, be sure to update the player data as well as the pick numbers.

Here is a copy of the dataset: Fantasy Football Draft Template

To create the Draft Board Dashboard in Tableau, I put the Fantasy Team Number and Fantasy Team Name on the columns shelf.  I hid the header on the Team Number but left it in the viz because it keeps the team names in order. On the rows shelf I put the Round Number.  By changing the viz to use Square mark types and adjusting the size of the squares, the main grid for the draft board was ready.

Draft Board Grid.png

Player Name and Position were then added to each square.  A custom tooltip is also included that details the Players Team and which number they were picked, both in the round and overall in the draft.  Here is the final version:

Draft Board.png
Draft Board Dashboard

Tableau Public Link

The Player Position field is used on the color shelf.  After a real fantasy football draft, the colors can be used to see how various Player Positions were drafted throughout.  The Draft Board can be analyzed to answer questions like “was a kicker drafted too early?”, “which fantasy team started the run on quarterbacks in Round 7”, and “which position was drafted the most overall?”.

Draft Board Dashboard In Action

The most fun I had in creating this viz was animating the whole fantasy draft to see what it looks like as each pick is put on the board.  I placed the Overall Pick field on the Pages shelf in Tableau to create the Fantasy Football Draft animation. Unfortunately, Tableau Public doesn’t support animation for published vizzes.  However if you download the viz into Tableau Desktop, you too can create your own fantasy draft gif just like this!  

Draft In Action2.gif

The #DataFamtasy league draft will happen within the next month.  Once it does, I’ll create an updated viz and gif of our actual draft.  Good luck to all my fellow fantasy football players out there on your upcoming season!  If you create your own Draft Board Dashboard, be sure to tag me so I can check it out.

Are You Up To The Challenge? My Creative Process for Data Viz Challenges

Have you heard of #MakeoverMonday or #WorkoutWednesday?  I’m sure many of you have, but if not, they are two of the many free and publicly available challenges offered by the Data Visualization community.

Some challenges are offered weekly while others are monthly.  Some focus on creation of new visualizations while others focus on challenging you to recreate existing ones – with the goal of teaching new visualization techniques.

For me, there are three main reasons why I have become a regular participant in these challenges over the last year and a half:

1. Practice

As with any art form, to get better at data visualization you need to practice. The more that you create, the more scenarios that you encounter, the more functionality that you’ll be able to understand and use, and the better your skills will become.  You can never stop learning or get enough practice with data visualization.  Even Tableau Zen Masters are constantly learning and working to expand their knowledge.

2. Accountability

While it’s easy for me to set goals for myself, if I don’t have a means of staying accountable to those goals, I have a much harder time of staying on track. Creating these challenge visualizations, publishing them to Tableau Public, and then posting them on social media has been a great way for me to stay accountable to my progress.

3. Building a Portfolio

Along with accountability, as I continue to publish my work on Tableau Public, I’ve amassed a nice portfolio of non-job related data visualizations. This has been especially useful when I’ve applied for new positions in the past.  You usually cannot show potential employers visualizations you have done at work, but if you have worked on things on your own time, and have them published on Tableau Public, you have a portfolio of your work in reverse chronological order.

My Creative Process

I just recently participated in #ProjectHealthViz, a monthly challenge by Lindsay Betzendahl focused on publicly available health data.  Health data is fun to visualize as there are many different stories to be found within the data and many different ways of presenting them.

This month’s dataset was from the CDC and focused on disease outbreaks across the US.  The data was in an excel file with over 400 thousand rows.  Each row contained information on a single outbreak.

https://data.world/zendoll27/projecthealthviz-m7november-2018-cdc-national-outbreaks

Let’s walk through how I got from the raw data to my final viz.

 

Norovirus Outbreaks

https://public.tableau.com/profile/paul.wachtler#!/vizhome/ProjectHealthVizNovemberNorovirus/NorovirusOutbreaks

Process, Not Rules

While each challenge is different, when I’m creating something new there is a general process I follow.  By no means are any of the following points meant to be seen as rules (very few of those exist in data visualization).  Rather my intent in sharing these guidelines is to provide a spark to those who are just getting started with these data viz challenges and provide a possible structure for doing so.

Reviewing Data Structure

The first thing I do when presented with a new dataset is to look at which data fields are available.  In this data from the CDC, there were:

  • date fields for when an outbreak occurred
  • state location information
  • an Etiology field that listed the name of the disease
  • some descriptor fields (like mode of transmission and outbreak setting)
  • several measures including the number of illnesses, hospitalizations, and deaths.

When reviewing the structure of the data, you want to get a general understanding of what your main dimensions and measures will be for your visualization.

Exploration and Choosing a Topic

This CDC dataset is a little on the heavier side as far as content goes but it’s rich with stories to be told.  To decide which story I wanted to tell, I needed to explore the data.  While I could have done this in Excel, I like to bring the data into Tableau to start exploring.  I start by reviewing overall statistics with the goal of finding a topic that stands out in the data.

For this dataset, that included the following:

Number of Outbreaks Per Year

Outbreaks per Year

 

Total Outbreaks by Location

Outbreaks by Location

 

Outbreaks by Location 2

 

Number of Outbreaks by Disease Type

Outbreaks by Type

It was clear from my exploration that Norovirus had the most outbreaks of all the diseases in the dataset.  I decided at this point to use Norovirus as the focus for my viz.  While I don’t always create visualizations based on the highest or lowest numbers in a dataset, once I have found a good topic I like to start creating my viz in Tableau.

Although you can and should take as long as you’d like when creating your own visualizations, I try to keep some structure around the amount of time I spend on any single viz.  Some take longer than others, but I have a family and friends that I like to spend time with so I make sure my viz time does not take away too much from my personal time.

Telling a Story

Sometimes you have a dataset and you know exactly the story you want to tell right away.  In those cases, you may start by creating the overall design of your dashboard and filling it in with your data later.

I tend to start with the data before I create a dashboard.  I create several different charts, and iterations on those charts, before I put them all together.  For the #ProjectHealthViz challenge, I created several different views.  However, not all of them made the final version of my dashboard.

It’s up to you how many charts you want to create before combining them into a dashboard, but don’t feel like everything you create needs to be included.  Sometimes your best ideas don’t come till after several iterations or a few times stepping away from your computer and coming back to it.  More importantly, even if you really like one of the several charts that you have created, if it doesn’t fit with your overall story, you do not need to include it in your final viz.

Putting It All Together

Once I have a few different views to choose from, I start putting them together.  My dashboards usually are not the same shape or size, and I often resize my dashboards as I’m working on them.

The one actual rule I stick to though is using fixed dashboards.  You never know what size screen your viewers will have and if you do not fix the size of your dashboard, it may stretch or shrink in ways that make it unreadable.

Alignment and Chart Selection

There are many different ways to layout your dashboard.  I often like to make a rough sketch with a pencil and paper of what I want my dashboard to look like.  This helps me visualize what I want to do before I start creating in Tableau.

For my ProjectHealthViz I decided that I wanted to make it look like a long and narrow infographic – something where the story builds as you go from top to bottom.  While I had several charts to choose from, I decided on these three to present the data:

  • Bar Chart
  • Hex Map
  • BANs (Big Ass Numbers)

I’ve used bar charts and BANs many times in the past.  They’re both great ways to highlight simple information.  The bar chart I created clearly shows that Norovirus is the top cause of outbreaks in the US.  The BANs at the bottom deliver raw numbers for how many have been affected by Norovirus.

As for the hex map, while I could have used a traditional map instead, there are two reasons I chose the hexagon style.

  1. It makes it easier to see the number of outbreaks per state when each state is the same size.
  2. I’ve always wanted to create a hexagon map and hadn’t done so before.

While some charts are more effective than others for different scenarios, sometimes stretching your ability by trying something new is fun too.  And data viz should be fun!

Font and Color

I’m no expert on fonts.  However, Tableau Public has a limited number of fonts it can render.  Since the options are limited, it’s not too difficult to choose a font.

Jennifer VonHagel put together this great resource on which fonts are supported by Tableau Public and how they look:

https://community.tableau.com/docs/DOC-18254

I personally like the look of the Georgia font but sometimes stick with Tableau Regular (and use Tableau Bold or Tableau Semibold for bold characters).  For my ProjectHealthViz, I stuck with Tableau Regular and Tableau Semibold.  The bold function does not work well with Tableau Regular so I used Tableau Semibold for making certain text and numbers stand out.

When it comes to color selection, I try not to be too flashy.  You don’t want extra color taking away from what you are presenting with your data.  You also don’t want to use color that doesn’t have meaning.  Color can be a great asset in your viz, but it is also very easy to overuse.  My recommendation is that less color (and a fewer number of overall colors) tends to work better for visualizing data. In my viz, I used red to highlight the outbreaks while keeping everything else black or white.

Custom Fonts in Tableau

For my title at the top, to give it a little something more than the standard font look, I turned to PowerPoint.  You can create a title in PowerPoint using any font available, save it as an image, and import it into your viz as an image.  This way it looks like you’re using custom fonts, even though they’re actually image files.

At the end of last year, Zen Master Ken Flerlage tweeted about a tool called wordmark.it that lets you type in a word or phrase and see how it looks in all of the fonts installed on your machine.

I’ve used wordmark.it on several of my visualizations. It’s an easy way to find a font for a custom title, especially if you do not want to go through each font in PowerPoint one at a time.

Footer

The footer is where I place information to tag my viz as my own.  I put the name of the challenge I’m participating in and my Twitter handle.

This is also where two very important pieces of information should go:

  1. Link To Your Datasource:  If the data is publicly available, make sure to cite where it came from.
  2. Attribution: If you were inspired by someone else, or took a similar approach to a visualization as someone else, make sure to note that in the footer. Attribution in data visualization is as important as attribution in a book or research paper.

Be Deliberate About Difference

Once your viz is done, make sure to review it.  Check for consistency in both your font usage and your colors.  If you decide to make something a different font or color or shape than other items in your viz, do it intentionally and know that you did it. Do not do it because you overlooked it.  Be deliberate about difference in your viz.

Check your tooltips too!  They’re often overlooked and can be a useful feature for including additional information.

Pro tip: It never hurts to have someone else review your viz.  The Data Viz community can be a great resource for this, but sometimes it helps to have someone from outside the field review it as well.  If they have trouble interpreting your viz or understanding your data, you may need to make it clearer.

Get Started!

Sometimes getting started can be the hardest part.  Regardless of the process you use, the most important part of getting started with these challenges is to create something.  Import your data into Tableau and start making charts.

I’d say the second most important part is sharing your finished viz online.  For me, sharing my work online has been the best way to stay accountable to my progress and to elicit feedback from the community.

Here’s a list of challenges that I have had the pleasure of participating in (in no particular order):

 I challenge you all to participate in more challenges.  And if you ever would like any feedback on your visualizations, I’m more than happy to help!