SAP Uses Own Big Data Analytics to Project Super Bowl Winner

By Chris Preimesberger  |  Posted 2014-02-01 Print this article Print

As of the afternoon of Jan. 31, Smith said, Seattle had the edge when it came to fans tweeting and blogging about the team and how much better they think the Seahawks are than the Broncos. But pregame chatter does not a final score make.

Smith said that special-teams data can turn out to be the most important when it comes to determining the final result. Denver clearly came out ahead there. For example, how many times has a field goal, onside kick or muffed punt figured prominently in the final outcome of a game? The analytics say "more often than you might think."

Key Takeaways From the Analysis

Key takeaways from the analysis, according to Smith:

--The Seahawks have a slight advantage on rushing yards, but the Broncos' passing yards blow the Seahawks away, giving the Broncos the advantage when looking at total yards.

--Analyzing opponents' scores, the Seahawks have the advantage with the best defense in the league, keeping opponents to much lower scores than the Broncos throughout the regular season.

--A head-to-head look at value-added by special teams throughout the season gives the Broncos the advantage.

--Using predictive algorithms, the most weighted characteristic of a winning team, showed special teams as the most contributory factor.

--Based on the variables of rushing yards, passing yards, total yards, defense and special teams, SAP's Predictive Analysis gave the winning edge to the Denver Broncos.

When all the available data was compiled, the social networks were scanned and the data illustrations were completed, Smith said, SAP came up with a projected final score for the game: Denver 26, Seattle 23.

Lessons Can Be Learned by This Use Case

If this actually turns out to be the final score, then we might be seeing Smith as a special guest Monday morning on the network talk shows.

Even though this is all in great fun, there are some good lessons here about the value of analytics for many use cases.

Despite all of the above analytics, the qualifier "might" is always going to be the key factor in any sports use case. After all, in football it often takes only one key fumble, interception, tip-toe pass catch or missed tackle to decide who wins and who loses. The analytics all go out the window when something like that happens.

Still, it's interesting to see how a case for a winner (or loser) is built by factoring in as many data bits as possible from the two teams before they butt helmets on the field Sunday afternoon in front of tens of millions of television and Web viewers.


Chris Preimesberger

Chris Preimesberger is Editor of Features & Analysis at eWEEK. Twitter: @editingwhiz


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