March, long known for the Big Dance, is now getting
recognized for Big Data.
The 2014 NCAA basketball tournament kicked off last week and with it, so did millions of hopeful brackets, dreams of $1 billion and – wait – data analysis? I bet you thought I was going to say hot dogs and pretzels, but this year more than ever, Big Data is getting in on the March Madness action. Kaggle, an online predictive modeling platform and major Big Data player, launched a competition this January to see how we can predict the outcome of the tournament by analyzing data we already have. Bloomberg Business recently posted an article about Kaggle, data and the games:
“Kaggle’s competition isn’t about winning an office pool but rather about developing a predictive model that can analyze a lot of data in a variety of scenarios. That’s why the online platform has asked its competitors to submit predictions across an entire matrix of possible games. Theoretically, any one of the 64 teams could play any other team at some point in the tournament, so Kaggle wants predictions for every possible matchup—2,016 predictions in all (64 times 63 divided by 2).”
[Read the full Bloomberg Business article here]
Intel, the sponsor of Kaggle’s competition, even chimed in on the action on Twitter.
These guys believe in Big Data too.
A formula that we already have for looking at how Big Data can help predict tournament winners is the “Dance Card” created by Jay Coleman, Mike DuMond and Allen Lynch. This formula predicts the at-large bids that will go on to play in the NCAA tournament. In the last 3 years it has a combined 98% accuracy; this year it predicted 35 of 36 bids and last year it got a perfect 100%. The formula uses the same analytics businesses use to predict what customers will buy and can also be leveraged to prevent credit card fraud, making it highly valuable for retail companies.
Another example of March Madness Big Data analysis comes from the Huffington Post’s “Predict-o-Tron.” The Atlantic walks us through the app:
“Take the Huffington Post’s remarkable achievement: The Predict-o-Tron. Users set a series of parameters like a school’s graduate rate or (more probably) the school’s defensive efficiency or pre-season AP rating. Those parameters are then fed through software that adds up your choices and makes your picks for you. The whole thing is sitting on a vast pool of data assembled by HuffPo’s deputy data editor, Jay Boice, and his team. “I’m not a huge basketball fan,” Boice told me. “I’m a data fan.”
[Read the full Atlantic article here]
Seems the Cinderella story this year might turn out to be Big Data and we at Integra aren’t the least bit surprised. Earlier this month we told you how you can get Big Gains from Big Data and taking our outlined approach to the sports industry is no different. Using trends found in data and analyzing and applying those trends is always to your advantage, on and off the court.