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
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
    car expense data analytics
    Data Analytics for Smarter Vehicle Expense Management
    10 Min Read
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 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

How Is Knowing the Business Important to Data Science?
Mission: To convert the power in high altitude winds into clean…
Next Gen Market Research Analytics 2010 and Beyond
Top 10 mistakes on data mining – on YouTube!
Text Mining and Regular Expressions

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

intersection of data and patient care
How Healthcare Careers Are Expanding at the Intersection of Data and Patient Care
Big Data Exclusive
dedicated servers for ai businesses
5 Reasons AI-Driven Business Need Dedicated Servers
Artificial Intelligence Exclusive News
data analytics for pharmacy trends
How Data Analytics Is Tracking Trends in the Pharmacy Industry
Analytics Big Data Exclusive
ai call centers
Using Generative AI Call Center Solutions to Improve Agent Productivity
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Julia Language
Big Data

Could the Julia Language Fill an Untapped Void for Big Data Programmers?

6 Min Read

Votamatic Predicted the Presidential Election Results with R

4 Min Read
data science online education
R Programming Language

Data Science Education Gets Personal

5 Min Read

Geographic maps in R

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.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?