GameDayStats: A Winning Strategy for NFL Football Betting

GameDayStats.com (GDS), a new website that provides remarkably accurate predictions of the outcomes of NFL football games launches today, just in time for the beginning of the new season. Founded by two long-time fans, Shannon McKenna and Steve Borron of San Diego, the site features a predictive model that is unmatched for reliability. Based on an algorithm developed especially for the site by Yang Gu, a Carnegie Mellon University-trained computer scientist, GDS offers picks that average 67% accuracy over the course of a season. Stats, injuries, weather--any number of variables can affect a team's performance and the GDS model includes these factors in determining its picks. As the season progresses and more data is analyzed, the accuracy rate will continually improve.

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We want people to have a chance to beat the odds by combining our data with their own likely choices

San Diego, CA (PRWEB) September 8, 2009

GameDayStats.com (GDS), a new website that provides remarkably accurate predictions of the outcomes of NFL football games launches today, just in time for the beginning of the new season. Founded by two long-time fans, Shannon McKenna and Steve Borron of San Diego, the site features a predictive model that is unmatched for reliability. Based on an algorithm developed especially for the site by Yang Gu, a Carnegie Mellon University-trained computer scientist, GDS offers picks that average 67% accuracy over the course of a season. Stats, injuries, weather--any number of variables can affect a team's performance and the GDS model includes these factors in determining its picks. As the season progresses and more data is analyzed, the accuracy rate will continuously improve.

Both McKenna and Borron work for an engineering firm where talk of statistics, machine learning, artificial intelligence and Bayesian networks opened their eyes to the predictive possibilities these methods presented. As entrepreneurs, they saw an opportunity. The two realized that many fans prefer to bet against the Las Vegas point spread rather than participate in football pools.

As a result, GDS has developed a model that not only provides a level of confidence for predicting straight-up wins but also provides a higher level of confidence for betting against the point spread. GDS uses a Bayesian statistical method, which allows for the input of new information and can even account for uncertainty factors prior to each week's games. This is different from a typical linear regression model used by most systems. Although no model will ever be 100 percent accurate, GDS always strives for the objective consistency that the Bayesian model provides.

According to McKenna, GDS was launched as a way of giving subscribers access to predictions based on objective criteria, not the speculations of handicappers or fan sentiment. "We want people to have a chance to beat the odds by combining our data with their own likely choices," says McKenna. "Winning bets will happen more often for the savvy bettor who learns how to use computer-generated probabilities in making their picks."

Borron adds, "This is a step up from the office football pool and can be more satisfying than fantasy football. It is more exciting, we think, to look at real world data as it relates to real teams. Fantasy football can be fun, but betting on a real game armed with facts, stats, probabilities based on computer analysis is something more."

Some may think that placing winning bets on NFL football games is like trying to pick a winning number in the lottery, shooting craps, or flipping a coin. But GameDayStat.com's founders believe that with the right data and the right system for analyzing it, experienced bettors, fans, and even casual players can win more bets than they lose.

"Our model will predict the level of confidence for betting against the Las Vegas point spread and straight up wins for every game during the NFL season," says Borron. "Using Bayesian statistics and machine learning methods developed especially for us, we have developed a predictive model that is objective, consistent and flexible."

"We know most of you are looking for an edge--a way to make more money--and our goal is to help you accomplish that," says McKenna. "To get an advantage you've never had before, review the results of our predictions and we think you'll be ready to subscribe to our new service."

About GameDayStats

GameDayStats provides highly accurate statistical predictions on the outcomes of NFL football games using computer modeling based on the Bayesian statistics and machine-learning theory. Subscribers gain access to the predictive results for upcoming games, and current and historical statistics for teams and individual players. The GDS system provides a much higher chance of making profitable bets on a consistent basis. Founded by Shannon McKenna and Steven Borron, two long-time fans and students of the game, the site relies on the expertise of one of the nation's leading computer theorists to provide predictive outcomes based on a specific level of confidence. As a result, GameDayStats.com produces consistent, unbiased, and accurate predictions of the outcomes of NFL games.

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