This module will introduce our Super Bowl Winning Index (SBWI), which is one way to profile championship NFL teams.
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Learning Objectives
By the end of this module, you will be able to:
- Locate, clean and transform NFL data to evaluate Super Bowl championship teams.
- Create a composite metric to characterize the profile of winning football teams.
- Identify offensive, defensive and situational strengths and weaknesses in Super Bowl champions.
- Translate your analysis into an infographic that tells a fun and compelling story.
Module Map
This module contains the following progressive lessons.
- Lesson 1: The Big Question
- Introduces the 'big question' that this module will analyze.
- Lesson 2: Show Me the Data
- Learn where the NFL Super Bowl data was sourced from and how we cleaned and transformed it.
- Lesson 3: Stats and Methodology (Releasing 01/20/26)
- Understand the stats that matter and how to use them in an analysis.
- Lesson 4: Data Analysis and Visualizations (Releasing 01/27/26)
- Compare 20 years worth of Super Bowl winning teams.
- Lesson 5: Discovering the Storyline (Releasing 02/07/26)
- Create a story flow that can be represented through an infographic.
Module Resources
Below are key resources you can use to follow along with this module.
- 20 Years of NFL Data for SBWI Calculation
- Python Code to Extract and Clean the 20 Years of NFL Data
- R Code to Analyze the Data and Create Visualizations
All module resources can be found at our Data Punk Media GitHub repo folder.
Published Story
Coming 02/07/26
Check out our Stories page for more deep dives on different data stories.
Key Takeaways
Coming 02/07/26
Additional Resources
Coming 02/07/26