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SmartData Collective > Big Data > Data Quality > The Data Analytics of the NFL Playoffs
AnalyticsData QualityPredictive Analytics

The Data Analytics of the NFL Playoffs

Brett Stupakevich
Brett Stupakevich
5 Min Read
The Data Analytics of the NFL Playoffs
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Saints fans are sad. Everyone is pondering Tim Tebow’s 2012 fate after he defied the odds of making it to the playoffs. The Packers and Aaron Rogers did not make it to back-to-back Super Bowls.

Tom Brady is obviously a machine, but his 55.9 completion percentage against the Ravens in five career games is his lowest against any other team, writes Jeff Reynolds of The Sports Xchange in a USA Today article. Will this matter this weekend?

Eli Manning’s elite standing as a quarterback is still making waves in the sports gossip circles. San Francisco’s offense, led by quarterback Alex Smith, got hot in the postseason. The Giant’s defense also came alive.

As we move into the conference championships, we can note that the statistics may be used to determine polls, odds and the Pro Bowl contenders, but they can’t always predict the games. Especially in the playoffs.

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Before we move into more of the data analytics of the NFL playoffs, I have to issue a little disclosure and give you a fun stat about this NFL postseason.

I went to college with New York Giants quarterback Eli Manning (we weren’t close friends, but we did graduate at the same time). Now for the fun stat. Manning and four other former University of Mississippi players are starters on the four teams playing in this weekend’s conference championships. Six other colleges nationwide can also claim between three and five players on each of the championship teams. Now, on to why this postseason is an anomaly in more ways than one.

Do Stats Really Matter in the NFL Outcomes?

According to Sam Farmer, a sports writer for the Los Angeles Times, this year is different because stats don’t tell the whole story. He writes: “In an unusual twist, these playoffs follow a noteworthy pattern: Most of the NFC participants have top offenses; most of the AFC teams are more defense-minded.”

And he says this year’s Super Bowl may give us the answer to the burning question: “What’s better – a great offense or defense?”

Jeff MacGregor, a senior writer for ESPN.com, made a good point this past week: “If stats, science, and analysts really predicted the outcome, would we watch?” His piece centered on quarterbacks and the fact that no one who  predicted the “Year of the Quarterback” would have Eli Manning beating Aaron Rodgers.

He brings us back to an observation we’ve made before on the Spotfire blog – the human element. Without that, analytics can’t tell the whole story. And would we really want them to? To this point, MacGregor writes:

“The propositional knowledge of 21st century football is now so incredibly complex it’s impossible to predict the outcome of any single game using only statistics. The numbers just don’t mean much. Too many people and too much rage and too much chaos to account for. The sample size is too small and the stage is too big and the ball is too pointed and too much depends upon momentum and bad chance.”

This begs the question – should we just leave the analytics to our fantasy football teams?

The Business of America’s Obsession with Football

While this postseason shows how hard it is to predict game outcomes and who will make it to the final game, no one can deny the impact of the game on the economy. This infographic from IBM shows the data analytics of the impact a lack of the 2012 season would have had if there had been a NFL lockout in 2011.

Next Steps: Tweet us your predictions for the conference champions this weekend.

Amanda Brandon
Spotfire Blogging Team

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