And it's time for week two! Last week my home town Kansas City Chiefs won despite my pre-season model picking them to lose. This week my model chose the Chiefs to beat the Denver Broncos, though I think that might be a crazy pick.
LAST WEEK'S RESULTS
Last week, I went 10-6, and was correct on both of my "high certainty" picks. But how good is 10-6 (62.5% correct)? Here's how it performs against other "null" statistical models:
- It's better than a null model where we pick random teams (50% correct).
- It's better than a "home" model where we pick the home team (55% correct).
- It's better than choosing the team who won more games last year (59% correct).
It's great that it outperforms other naive models, but how does it do against professional Football analysts. For this analysis, I checked against the site NFLPickWatch, which aggregates and compares the game picks made by experts and sportswriters. I've included data below, but in essence, for the first week, my model performed as well as the median pundit (10 correct predictions). I will continue to track this comparison metric in future weeks.
Stay tuned for this next week, the in-season model is not significantly better than the pre-season model for week two, because we don't have enough new data for this season.
And for this week, our pre-season model predictions for week two. I generally agree with these predictions, based on my not-so-exhaustive knowledge of football, but have some concerns:
- The team my model finds most certain to lose is the New York Jets, despite the team having a coach with the last name Bowles (no relation).
- I don't have faith that the Chiefs will beat the Broncos, based on recent history, and the existence of Peyton Manning.