The following betting concept was posted by me over at Sportsforumworld at the beginning of college football (it's one of my "thinking outside the box" plays).
First of all I'm not a professional gambler, in fact I'd rather be fishing for tarpon off the coast of Costa Rica (which I just got back from) than trying to beat the sports books. With that said, there's entirely too much hand-wringing about not being able to beat the WA closing lines. I'm saying that they can be beat and it isn't even that hard to do. I do no handicapping whatsoever, all my bets are the result of data analysis. Also, I seldom make straight bets (exceptions below), the majority of my bets involve teasers or other forms of parlays.
Below is an actual example of one of the methodologies I use. This particular database reflects the closing lines depicted by Don Best for college football 2000-2009 (6338 games). The subset is for full game lines that are less than 2 to 1 LTR, e.g., USC-28 with a total of 55 or a LTR of 1.96. But the bets themselves are all first half bets, the USC 1h line would be about -14.5 with a total of 27.5. And the sample size for this subset is 461 or 7.3% of the database. Just to be perfectly clear, the best bets by far would be correlated parlays, but none of the respectable books will allow them with an LTR of 2 or less, so we're going to skin this cat another way! First, the results of the 461 games for the first half as they actually turned out from a correlated parlay perspective:
Fav/O 163 for 35.4%
Fav/U 43 for 9.3%
Dog/O 89 for 19.3%
Dog/U 153 for 33.2%
F/P 5 for 1.1%
D/P 5 for 1.1%
P/O 1 for .2%
P/U 2 for .4%
Obviously the correlated parlays of Fav/O or (and) Dog/U would be nice, but of course, they won't let you bet these. So what I do is bet two STRAIGHT bets on the Dog and the Over. At first glance these bets appear to be anti-correlated, but let's do the math.
If you were to bet $110 on the Dog and $110 on the Over for all of the 461 games you would have $101420 invested.
You would collect 89x$420=$37380 for when the Dog and Over came in and 316x$210=$66360 when the Fav/O or Dog/U came in (win one, lose one, lose $10 juice). $37380+$66360=$103740-$101420=$2320 profit. This appears to be only a 2.3% +EV ROI. But if you look at it from a ROR perspective all you are really risking is the $10 juice on the 316 times the F/O or D/U came in ($3160) and the $220 lost when the F/U came in (43x$220=$9460). So the way I figure it the real risk is $9460+$3160=$12620 or +EV of 18.4%. Simply stated, 70% of the time you're going to lose $10, 10% of the time you're going to lose $220 and 20% of the time you're going to win $200.
Also, I know all about the "in sample" and "out of sample" paradigm as it relates to data analysis, But honestly, I'm not inclined to sit on what I consider a profitable subset for 3 or 4 years to see if it withstands the test of time. Some may say that a sample size of 461 is not enough to extrapolate from when making these types of bets, but it's enough for me!
My first full year betting this subset (2009), SS 46, 1 F/U, 9 D/O and 36 F/O D/U.
So far this year, SS 27, 1 F/U, 7.5 D/O and 18 F/O D/U