Click here to download this week's dataset as a CSV from Data.World

Click here to download this week's dataset as a Hyper Extract from Data.World

Dataviz Approach

I struggled a bit with coming up with deciding exactly what I wanted to do with my viz for this dataset. However, looking at the raw data, I noticed a few things right off the bat. In particular the large amount of injuries in the preseason. It is conceivable that players are coming back from the offseason in less than optimal condition and are therefore more prone to injury. Additionally, with the pressure to perform at a high enough level to make the team, some players may take unnecessary risks that lead to injury.

This may also explain the larger numbers of injuries in preseason practice versus practice injuries during the regular and post season. Despite the fact that the regular and post season are about 5 times as long as the preseason, players may require less physical practices as they recuperate from games. Unfortunately, the reasons aren't in the dataset, BUT the trends are, and I decided to focus on this for my viz.

I wanted to approach two different metrics with two different vizzes. For the first, I chose to use a waterfall chart to show the number of total number of injuries, while also being able to show the breakout of injuries by season and whether those injuries occurred in game or practice scenarios. The viz draws attention to the disparity in injuries occurring in practices versus games by season type, while also showing the overall injury trend for the past 5 years.

My second viz focused on the number of injuries per game, excluding injuries sustained during practice. The number of games in a season is set, but the amount of practice across a season could be variable. The viz is a side by side bar, showing the difference in injuries per game by season type, clearly showing the difference between the preseason and regular + postseason. I used a parameter to allow the user to select an injury type to filter the vizzes, while also driving intelligent labels and tooltips.

I chose to use separate dashboards to keep the look simple, and used the new dashboard buttons feature in Tableau 2018.3 to drive the navigation between the sheets. After initially struggling with what to do, I'm pretty happy with the outcome.

Not had a chance to get your viz out? There's still time! Download the data and see what you can do. Create your viz and post your work to Tableau Public and Twitter with the hashtag #ThrowbackDataThursday, tagging @TThrowbackThurs. We're really looking forward to seeing what the Tableau Community can come up with!

Data Source

This week's dataset comes from the NFL Play Smart, Play Safe, an initiative focused on player health and safety. Please be sure to cite the source on your viz.