What is the Helices Posit?

Posted by deck104 on October 1, 2008

Very simply, Mr.F spends most of his time calculating the power rankings. After, the numeric rating each team is given is then adjusted based on certain factors and then compared against the opponent. Eventually (and this is when it gets tricky and secretive), Mr. Formula will give a range of pointspreads that we want to target and bet on.

Now since point spreads move, we try to keep an eye on which ones are in, or close to, our range. If any spread is really close to the edge of our range we will take it. If it’s right in the middle we might wait to see where it moves to try and get a better line than the one originally presented to us and take it. If a line moves into our range from outside of it, we’ll take it. And we bet on every game Mr. Formula tells us to. Except favorites giving up more than 10 points. Based on the formula, favorites giving up more than 10 points are a serious liability whence removed increases our success rate greatly.

Mr. Formula started outputting games last year in a CBS Sportsline Office pool and did pretty well. It was then run for the previous three years using the CBS Sportsline spreads and still did fine. Going back a few more years we used spreads from  Using this data, Mr. Formula continued to tweak what he was doing and eventually we found that in the first four weeks of the season the spreadmakers are erratic because the teams have yet to establish themselves for the given season.  But more importantly, our data on the season is still fledgling and our success rates were at the point where we’d be losing money on those weeks. Also, the last two weeks of the season many teams rest their star players once clinching a playoff spot. This isn’t necessarily reflected in the spreads, but we found that eliminating weeks 16 and 17 from the formula increased our success rate even more.

So over the past five seasons (2003 – 2007), betting on every game Mr. Formula tells us to (not taking into account weeks 1-4 or 16 & 17), yielded the following results.

2003 – 35 games, 20 wins, 1 tie (58.8% predicted correctly)
2004 – 35 games, 25 wins (71.4% predicted correctly)
2005 – 31 games, 21 wins (64.5% predicted correctly)
2006 – 43 games, 26 wins (60.5% predicted correctly)
2007 – 42 games, 27 wins (64.3% predicted correctly)

Now most betting tomes say that once you achieve 58% winning percentage you can start to make money consistently at anything. As evidenced, over these five years if we’d wagered $110 to win $100 (the normal vig in sportsbooks) we’d have won $4,350. While that may not seem like a lot of money, each game has an expected return of 21.8%, meaning each bet of $110 has an expected return of $134 (which you don’t need a finance degree to tell you is pretty significant).  Bet on a much larger scale you can obviously win a lot more money.

One thing about these results is, as previously stated, they’ve been run against CBS Sportsline office pool spreads. If any of you have ever been in a league at that site, you know that all the spreads end in a .5. Meaning there are no opportunities for pushes in the 3 years we used their data, but statistically that should only affect the amount of money we’d lose on the vig, and shouldn’t skew our data in any way since we are only “betting” on games that fit within our spread-range.  This can be seen by our high winning percentages in the other 2 years where we didn’t use cbssportsline spreads.

This year though, it’s the real deal. We’re running this campaign against “real” spreads and putting our own “real” money down on the games. We’re using a site that will remain nameless and betting to win $50 dollars per game, no matter the vig. And on this site we’ll be blogging about it all. We’ll be posting our weekly power rankings, posting which spreads we’re betting on (and more importantly, which spreads YOU should be betting on) as well as the spread ranges so you can track lines yourself and bet at will. You can use the information to gauge your own picks in your office pool, or share info with your friends to try to identify “sucker” spreads. Whatever you do with the information, we’d love to hear about it so feel free to comment or send us emails as often as you like.


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