Contemporary Analysis

Data Science

Nate Watson

2018 NCAA bracket picks using Machine Learning.

Contemporary Analysis (CAN) and Cabri Group and have teamed up again to use Machine Learning to predict the 2018 NCAA Men’s Basketball Tournament. This is different than last year as we are picking the entire 2018 bracket instead of just upsets.

Historically, only 26% of tournament's games end in an upset (this includes games from all rounds). That's 17 out of 64 games. Last year we did really good. Only failing to predict 3 upsets and getting 50% of our predictions right. We are going to need to improve a bunch to win that 1M/year for life from Berkshire Hathaway--including that wee bit about having to work for Berkshire Hathaway to be eligible. This year we added far more variables and used an ensemble model. Will we be perfect? Probably not. Here is the problem with using Machine Learning to try and predict a perfect bracket:

Nate Watson

Game of Throne Meets Data Science

Sometimes obsession breads genius. Fans of Game of Thrones have dedicated much time to tracking the deaths, births, twists, and turns of the previous seasons. Now that season 7 has arrived, there are some amazing maps of the story out there. We found one we particularly liked on Tableau Public.

For More Information

From the archives "Why Become a Data Scientist?"

Did you know CAN's blog is full of sound data science related advice dating back to the beginning of CAN? In case you didn't, we make it a habit to regularly re-post our favorites. What follows are reasons why you should consider becoming a data scientist. If it grabs you - check out the Omaha Data Science Academy. It might be the first step in your data science career.

 

Why Become a Data Scientist?

Bridget Lillethorup

Bloggers Writing About Tableau

Tableau is a data visualization software that CAN uses daily with our customers. We even have our own Tableau expert on staff: Matt Hoover.

Bridget Lillethorup

From the CAN Vault: History of Predictive Analytics Since 1689

History is a fascination for us at CAN for two reasons. The first is that we find our own history pretty fascinating. Did you know that CAN has been around for 9 years? Pretty cool.

Bridget Lillethorup

Where in the world CAN you find us?

In the next few years, CAN is predicted to be among the nation’s leaders in data science. We have an impressive resume to back this up. We’ve worked with multiple Fortune 500 hundred companies, and many more Fortune 1000 companies all over the globe and have built a solid reputation among local Omahans for producing experts in data science and IT.

Nate Watson

Machine Learning Upset Prediction Project Proves its Value

At the beginning of the project, we set out to show how the 2017 NCAA College Basketball Tournament could be a proving ground for Machine Learning analysis. There are very few places in the world where we can use the same model to predict multiple outcomes in a short period of time, have a ready-made scorecard (Vegas), have the general public understand what we are trying to do, and have a chance to "beat" the algorithm with their own knowledge.

Gordon Summers

2017 NCAA Tournament Machine Learning Prediction Results

After the first weekend of basketball, our Machine Learning Prediction tool has good results.

Gordon Summers

2017 NCAA Tournament Round of 64 Upset Predictions

The Cabri Group / CAN Machine Learning Lower Seed Win Prediction tool has made its first round forecast! Without further ado:

Nate Watson

March Machine Learning Mayhem

Machine Learning and the NCAA Men’s Basketball Tournament Methodology

 <<This article is meant to be the technical document following the above article. Please read the following article before continuing.>>

“The past may not be the best predictor of the future, but it is really the only tool we have”

 

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