Methodology
The basic methodology of how I come up with the strongest pick for the day is fairly simple.
1.) I look at what the collection of handicappers I track are saying.
I compile information from handicappers who have been in the industry for several years, as well as handicappers who post their picks on legitimate, subscription-based websites. (During the college football season, I will look at as many as 50 different opinions for the games being played on Saturday.)
2.) Then I look more closely at who exactly is making a certain prediction and how strong THEY THINK their prediction is.
I have subscriptions to various handicapping websites, and I look at both the “premium picks” as well as the free analysis. And though I do look at the individual handicappers’ rating of his pick, I completely disregard any mention of “the pick of the month,” “the Atlantic Coast Conference play of the year,” etc.
3.) Then I ASSIGN weightings based on “who is saying what,” and what the handicappers’ track record really is (based on the ongoing data I have collected since 2004).
Not only do I look at the handicappers’ overall historical performance, but also I dissect it by sport. I have found some pretty interesting trends over the years. For example, one handicapper I track does relatively well in men’s college basketball, yet his results in the NBA are only mediocre. When I first started tracking handicappers I thought that in such an instance there would be a positive correlation; but as I have learned, this isn’t always the case.
After following these three steps above, I then look at what my calculations show as the strongest pick, which in summary is essentially based on the “majority vote,” the “strength rating” of the pick, AND the historical performance of the handicapper himself.
It could be my bias towards numbers, but one aspect of this industry that I really like is that it’s not ambiguous whether a handicapper is good. It’s certainly important to understand what’s realistic in this industry, and in the end the results (i.e., the numbers) speak for themselves, which is one of the reasons why I post all my historical results.