What is data analysis?

Data analysis involves using code to process and examine data for valuable insights and patterns. These insights can be used to improve business operations, create new features and products, better connect with users, and more.

How is data analysis used in the sports industry?

Data analysis is revolutionizing the sports industry as various teams and coaches use it to find new opportunities in advantages. For example, NFL coaches use data analysis to evaluate the effectiveness and frequency of different plays — and even predict games.

What kind of jobs in sports use data analysis?

You can find Sports Data Analysts in every major league (including the MLB, NBA, and NFL) processing team and player performance data to find potential improvements and optimizations.

What else should I study if I am learning about sports data analysis?

If you’re thinking about pursuing a career in sports data analysis, you’ll want to learn how to use SQL, along with other Python libraries like Scikit-learn and TensorFlow.

Free

Course

Analyze NFL Stats with Python Case Study

Use NFL team statistics to model game winners and discover the most important team-level stats

This course includes

5,651 learners enrolled

This course includes

Skill level
Beginner
Time to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary

1 hour
Projects
1
Prerequisites
None

About this course

If you’re looking to put your machine learning skills to use answering interesting questions about the NFL, try this case study! We will provide you with the context, data, and instructions that you need to build a machine learning model to predict the winners of NFL games and guide you in making that model better. Finally, use feature importance to identify the most important stats for winning a game.

Syllabus

NFL Stats Case Study
Build a machine learning model using NFL statistics to predict who will win a game!

article Analyze NFL Stats with Python
project Analyze NFL Stats with Python
informational Analyze NFL Stats with Python: Next Steps
Certificate of completion available with Plus or Pro
Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.

The platform

Hands-on learning

Animated GIF of an AI provided error explanation within Codecademy's learning environment

An AI-generated hint within the instructions of a Codecademy project

Animated GIF of Codecademy's Job Readiness Checker tool generating a compatibility report for a senior software engineer role

Animated GIF of building a phone screen interview using Codecademy's Interview Simulator

A fill-in-the-blank JavaScript question in a Codecademy assessment

Explore features

Projects in this course

practice Project
Analyze NFL Stats with Python
Predict winning NFL games from game stats using logistic regression. Then find out which game stats are most important to your model.

Meet the creator of the course

Meet the full team

Andrea Hassler

Andrea has a Master's in Applied Statistics from NYU and a Bachelor's in Psychology from SUNY New Paltz. She has worked with students individually as a tutor for many years. She has also contributed to research projects in the health sciences as a statistical consultant and research assistant.

Meet the full team

Earn a certificate of completion

Show your network you've done the work by earning a certificate of completion for each course or path you finish.

Show proofReceive a certificate that demonstrates you've completed a course or path.
Build a collectionThe more courses and paths you complete, the more certificates you collect.
Share with your networkEasily add certificates of completion to your LinkedIn profile to share your accomplishments.