Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
    cybersecurity efforts
    How Behavioral Analytics and AI Are Redefining Cybersecurity for Boca Raton Businesses
    14 Min Read
    data driven risk management in heatlhcare
    How Data Analytics Is Changing Healthcare Risk Management
    17 Min Read
    big data and customer service outsourcing
    How Data Analytics Improves Customer Service Outsourcing
    18 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: NCAA Data Visualizer for March Madness Face-Offs
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > NCAA Data Visualizer for March Madness Face-Offs
AnalyticsData MiningData VisualizationModelingPredictive AnalyticsR Programming LanguageStatistics

NCAA Data Visualizer for March Madness Face-Offs

DavidMSmith
DavidMSmith
2 Min Read
SHARE

If you’re laying down a friendly bet on the March Madness games or just tweaking your fantasy roster, this NCAA Data Visualizer by Rodrigo Zamith will be a boon. Just choose two teams to compare head-to-head, choose an attribute to compare them on. You can look at more than a dozen invividual player attributes (e.g. points scored, assists, 3-point shots made) or over 20 team attributes (e.g.

If you’re laying down a friendly bet on the March Madness games or just tweaking your fantasy roster, this NCAA Data Visualizer by Rodrigo Zamith will be a boon. Just choose two teams to compare head-to-head, choose an attribute to compare them on. You can look at more than a dozen invividual player attributes (e.g. points scored, assists, 3-point shots made) or over 20 team attributes (e.g. fouls, wins, and turnovers), and compare against other top players or NCAA team averages.

For example, here’s how the top players match up for individual points scored for tomorrow’s Oregon/Saint Louis game:

NCAA data visualizer
All of the data used was scraped from the NCAA website for the 2012-2103 season. Rodrigo created the visualizations using the R programming language, which means he can used some advanced techniques like the boxplots above. Rather than just showing the median or highest/lowest scores for each player, he can show all of each player’s games, and highlight the bulk (the middle 50%) of their games using the box. But you can still see, for example, that Saint Louis’s Kwamain Mitchell had a couple of hot streaks last season and was in fact their highest scorer last season — a fact that you might miss just looking at averages.

More Read

Image
Statisticians Push Back Against the “End of Theory” Problem
Is Big Data Causing Insurance Actuaries to Move Away from Using Credit Scores?
How to Be a Text Analytics Rock Star in your Organization
When Do You need All the Data for Big Analytics?
The R Ecosystem: a Presentation

You can play with the NCAA data visualizer and choose your own teams and stats to compare at the link below.

Rodrigo Zamith: Visualizing Season Performance by NCAA Tournament Teams (via Myles Harrison)

TAGGED:r language
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

smarter cybersecurity threats
As Vehicles Get Smarter, Cybersecurity Threats Intensify
Exclusive IT Security
chatgpt image jul 18, 2026, 05 09 14 pm
When Data-Driven Businesses Must Recover Data from USB Drives
Big Data Exclusive
chatgpt image jul 15, 2026, 03 28 38 pm
How Cloud Technology Helps IT Asset Recovery Services
Cloud Computing Exclusive IT Security
chatgpt image jul 13, 2026, 04 23 45 pm
How Data Analytics Helps Companies Improve User Engagement
Analytics Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

A Data Scientist Investigates the Belgian Municipal Elections

13 Min Read

Geographic maps in R

3 Min Read

NYT: SAS facing stiff competition

4 Min Read

Open Data App for the Paris Métro

3 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai chatbot
How AI Website Chatbots Improve Customer Support and Lead Generation
Chatbots Exclusive
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?