Intro Note: Football is a matchup and idiosyncratic game where teams change their behavior over the course of a season, players improve, and random results and injuries can skew outcomes that don’t necessarily reflect underlying value.
I personally find that so much of my success betting at this point in the season relies on sifting through the data to understand the sample sizes that are the most relevant/predictive going forward. With 4-5 weeks of data, off-season priors are not yet fully shed, and we are already starting to see teams change their methods of attack.
By taking an intensive look at our data and understanding the context in which it lives we can (hopefully) stay a bit ahead of the market. This column, then, an experiment for now, feedback appreciated, will look at some of the stats and angles I’m monitoring as I parse through the data and try to stay ahead of the market.
I won’t capture everything (there will prob be typos) and the structure and style is all in flux, but it’s a start nonetheless and something to think about midweek.
