What a year 2020 has been, but thank goodness for football. As a diehard fan of football and analytics, I decided to visually explore some data from the NFL Draft Combine of 2020.
Could I provide a fun and useful way to identify players who performed well in various categories related to speed, strength, and agility? Could I use the data to identify players who are making a big splash with their current teams in the NFL?
Where to start? Well, first it has to be said that I am a visual person through and through. Prior to and throughout my career, I have always had a passion for the fields of art, design, communication, and technology. In the world of business intelligence (BI), it has never been more important to effectively utilize all of these disciplines when crafting visual analytics and storytelling to convey actionable insights.
After downloading the data, I started by simply exploring it. I gave it a quick look in its original tabular format to answer basic questions such as:
- What kinds of fields am I dealing with?
- How many sort or dimension fields do I have? How many metrics or measures are there?
- Is there a good variety of both so that I can create a compelling, fun, and useful form of visual analytics?
Now it was time for the real fun to begin. I uploaded the data, recalled the importance of visualization best practices, and began visually exploring. Remember my goal: provide a visual analytics dashboard that would enable someone to identify players who performed well in the NFL Draft Combine. This, in turn, could be used to identify players who are making a big impact for their respective teams in the current NFL season.
The analytics of agility
Let’s start with agility. I chose to focus on the player’s position and visualize the average broad jump distance via a ranked bar graph. This enabled me to easily see and compare, at a glance, which positions recorded, on average, the highest broad jump distance.
Next (and one of my favorite visualizations) is the 40-yard-dash scatter plot. The scatter plot was perfect in that it enabled me to easily visualize all of the players with respect to their weight and 40-yard dash times.
Power in the data
Through the use of color, I was able to easily see if certain positions landed in similar areas of the scatter plot and identify any anomalies. Thanks to the size attribute, I was also able to incorporate strength into the visualization, which could help with identifying the quicker players that were also able to complete a significant number of bench press repetitions.
I really wanted to do justice to the strength metric. In this word cloud, the player’s name is sized according to the number of 225-lb. bench press repetitions each player completes, so I can easily see who the leaders are.
After I added a detailed grid report that included the player’s draft status, the dashboard was complete. The resulting dashboard provides access to surface-level observations, including a detailed data grid, but also crucial interactivity with broadcasted filtering to uncover answers to deeper questions.
Why it matters
Noodling around with NFL draft data was fun, but there was a lot more to this exercise than that. It was a reminder that humans are hardwired to process visual content much more easily than written content.
Visualizations can help us identify patterns, trends, and anomalies and will ultimately help us to make better, more informed decisions. I think you will also find that your consumers will enjoy and more easily remember their visual analytics, the resulting insights, and the storytelling that comes from this approach.
As a data and analytics software company, ibi can help you embed intelligence into everything, from fun projects related to the NFL to your most pressing business challenges.
Request a free trial and start working with your data today and, until next time, thank you for reading!