Barry uses Machine Learning and a dataset of all previous NFL matchups to predict the outcome of any two teams.

You can compare teams from different years or the same team over different years.

When a team wins in an actual NFL matchup, the winning team isn't necessarily the better team, it was just the better team that day. This model simulates a matchup 100 times, providing a better understanding of which team is better.

It does so by first generating what the team is expected to score - considering the strength of their offense and the strength of the opponent's defense. Then a score is randomly generated around that mean based on how much scores typically vary across real historical matchups.

NOTE: Barry reserves the first 34 games of a team's existence for model training, so those initial games are not suitable for use in the model.

Email joelday.business@gmail.com with any questions, issues, or fun ideas!

- Joel Raymond Day