College
Football

There are 130 Division 1 football teams and over the course of a season each team plays a minimum of 6 home games which equates to 822 potential opportunities to wager. Roughly 65%  of these home teams are favored to win (N=492).  In 2019 there were 488 teams favored in 2018  542, and in 2017 a total of 530 were favored. Currently there are 25 teams in the NCAA with over 90% win percentage when favored at home. Additionally, roughly 96% of all home teams when favored by 17 pts or more have won their games since 2014.

Watching The Money Line Trend

With over 60 games to wager on every College Football Saturday, clients are provided with every edge to winning. SW&G researches the splits of money and ticket percentages on the each week’s games, this allows us to can get a sense of where the public is wagering. SW&G also provides the trends on each week’s games for FREE

Point Spread = Losing  / Money Line = Winning

Sports betting systems are sets of events that when combined for a particular game for a particular sport represent a profitable betting scenario. Since sports betting involves humans, there is no deterministic edge to the house or the person wagering when using point spread. However, when it comes to money line wagering the advantage go to the sports wager IF statistical analysis by regression analysis is used!

No Need to Reinvent the Wheel - Just Build a Better Mouse trap

Regression analysis is a type of statistical technique used to determine the important factors that affect the outcome of the event. In the case of sports betting this is usually done with multivariate linear regression.

Betting systems based on statistical analysis have been around for a while, however they have not always been well known. One group that was known for their accurate predictions was called The Computer Group. They formed in Las Vegas in 1980 and successfully wagered on college football and basketball games for years making millions. Michael Kent, co-founder and one of the lesser-known individuals of the group, would use his computer software to run through massive amounts of data, which then provided the group's network of bettors with useful information. The network of bettors would then bet on games in which they had a statistical advantage (as determined by the software).