This is an exercise in building a simple blind predictive model based on a team’s historical stats in 4 areas: pass and rush efficiency, and avg EPA for special teams and penalties. The season-long experiment will track how well future games are determined by past statistical performance and compare that record against Vegas betting lines.
Last weekend, the model went 2 for 4 straight up and 2 for 4 against the spread. That’s not good, but with only 4 games the variance was high and so I’ll live with it.
Vegas hit on 3 of 4 straight up, so the model falls back to 3 games behind on the season with an overall 66.4% prediction rate. Against the spread, I’ve gone 56.3%, which is much, much higher than I had hoped for.
The model agrees with Vegas on a Green Bay victory, but it continues to throw shade at Kansas City, favoring Buffalo. I don’t agree with that pick, but I’m not the boss.