Simulating the 2020 NFL Season 100,000 Times

Simulating the 2020 NFL Season 100,000 Times

Simulating the 2020 NFL Season 100,000 Times. Predicting the outcomes of the entire 2020 NFL season by tracking how often each simulated universe yields a given result for each team

It’s official! On Thursday night, the NFL returns with the defending champions Kansas City Chiefs taking on the Houston Texans. It is the beginning of a season that many thought we would not see given how this year has played out. But nevertheless, football is back, and we are going to attempt to simulate and predict the outcomes of the entire 2020 NFL season.

Elo Model

If you’re familiar with how players are ranked in chess then you're familiar with Elo ratings. Elo rating is a simple system that judges teams or players based on head-to-head results, and is the model we used to simulate NFL games for the 2020 season. These Elo ratings are able to forecast the outcome of every game, and generate win probabilities for each team.

How the Elo model works is that it assigns every team a power rating. Those ratings are used to generate win probabilities based on the difference between the two team’s Elo ratings. Teams increase their Elo rating by winning games and decrease by losing, but by how much depends on the expected result of the game.

For example, let's take two teams and give them each an Elo rating. Let's say the Dallas Cowboys are versing the New York Giants. The Dallas Cowboys have an Elo rating of 1650 and the New York Giants have a rating of 1400. Since Dallas’s rating is higher we know they have won more games than New York and should be favored in this game. In fact, I can tell you, the Elo model gives them a win probability of 80%.

sports data-science sports-analytics nfl football

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