WiseStats db – Packers vs. Bears, Part 1

Today is the first of a four-part series where we will examine this coming weekend’s NFL Conference Championship games using WiseStats db, a new product that allows you to use statistics and historical outcomes to better predict the winners of upcoming games. WiseStats db is a must-have weapon in your arsenal to make you a more intelligent bettor!

The first matchup this weekend is a classic showdown between NFC North rivals when wildcard winner Green Bay Packers march into Soldier Field to take on division winner Chicago Bears. These two teams have met twice this season, splitting the season series at 1 win apiece. The game has big implications, with the winner representing the NFC at Super Bowl XLV on February 6 at Cowboys Stadium in Arlington, Texas. It is expected to be the largest attended Superbowl in history, and President Obama has even declared his attendance should his favorite team – the Bears – get past the Packers this weekend.

So how do these teams match up, and what can we glean from historical outcomes to pick the winner of this game?

When the Green Bay Packers play as a 3.5 to 6.5 point favorite after a road win against a conference opponent, their record is 10-1, a 90.9% win rate.

Here is the breakdown to show you what makes this situation “in play” on Sunday:

• Most sportsbooks have Green Bay listed as 3.5-point favorites against the Bears (what is a point spread?)
• They won their last game 48-21, which was on the road
• Green Bay’s opponent in their last game was Atlanta, a fellow NFC Conference team

When Green Bay has found themselves in this situation in the past, they have won significantly more times than they’ve lost with a 90.5% winning percentage, making them a comfortable favorite to win on Sunday in Chicago.

So far, we’ve used WiseStats db exclusively to better predict who will win or lose games outright. Tomorrow, we’ll turn our attention to the concept of point spreads, and look yet again at the upcoming Packers/Bears matchup to see which team is likely to cover the spread using historical statistics to help reach a conclusion.