For weeks, I’ve been working hard to optimize all my betting algorithms in preparation for the new year. Yeah, I know it’s silly — January 1 is just a day — but, somehow, it seemed fitting. Besides, I had paid vacation days for the first time in years, so I had plenty of time to study and tinker without worrying that I would wind up eating my Christmas dinner from a dumpster at a nearby Holiday Inn. 

While most of my research was as exciting as watching grass grow in a blizzard, I think the money management system I came up with might be of interest to other sports bettors and/or investors, so I thought I would share the fruits of my labor.

Let’s start with a basic but undeniably true statement: To be successful in gambling or investing, one must have an advantage. No amount of money management will erase a negative expectation. Sure, one’s cute progression system might work for a while but, eventually, it will yield to the immutable laws of math and statistics. 

Thus, the first thing you must do is find your advantage, and the best way to do this is by utilizing the Kelly Criterion (click HERE to find out how).

Named after its inventor, John L. Kelly, the Kelly Criterion is a formula designed to optimize betting profits by determining the ideal percentage of capital to be staked on each wager. This is crucial because those who bet more than their advantage invariably wind up at that dumpster near the Holiday Inn grousing about their “bad luck” as they dust off a partially eaten chicken wing.

Although I have no statistics to back it up, I suspect a great many gamblers lose not because they are bad handicappers, but because they bet more than they should. For example, you will often hear that multi-race bets offer great value because the takeout applies just once. Yet, this is shortsighted thinking, as it ignores an important component of one’s betting advantage — the win rate. 

Consider: If you bet the favorite in every leg of a pick-3, you have a 5% chance of cashing (based on a 37% success rate for each favorite), which means that the winning pick-3 payoff would need to average over $40 (on a $2 bet) to offer even the slimmest of advantages.

Not only is such a payoff unlikely for winning pick-3 bets comprised of post-time favorites, but it’s also not how most people play the pick-3. Instead, they throw in a mix of favorites and longshots with the hopes of getting a “good price.” Thus, even the most skilled players who bet this way are combining what is likely a small advantage — the Kelly Criterion dictates that one’s betting advantage can never exceed one’s win rate — with extreme price volatility (in most cases).

Please don’t misunderstand me: I’m not saying that one should bet their perceived Kelly advantage in every race — it is, after all, merely an estimate based on past results. Rather, I advocate that one wager just a fraction of their Kelly advantage in each race. And because I think it is so important, I believe the expected win rate is the perfect fraction to use.

To keep it simple, I suggest utilizing a grading system similar to the one I devised:

 A (bet 4% of capital)= Kelly advantage x win rate ≥ 4%.
 B (3%)= Kelly advantage x win rate ≥ 3%.
 C (2%)= Kelly advantage x win rate ≥ 2%.
 D (1%)= Kelly advantage x win rate ≥ 1%.

For example, in the fourth race at Aqueduct today, Early Edition was given a grade of “BA,” meaning she offered a greater advantage to place than she did to win. As a result, I bet 1.5% to win and 2.5% to place (4% total) and received a great return on a filly that was beaten handily (though she easily held on to second place).

I also added a “+” designation to those algorithm plays that maintained their advantage even when heavily bet (for those that did not, I insisted on even odds at post time). Obviously, such a method is not foolproof — conditional wagering is notoriously unreliable — however, it adds at least a small layer of protection.

Lastly, for my algorithms that generate fair odds, I graded the overlays and, once again, will rely on the conditional wagering feature to determine whether the bet is placed or not. The minimum odds are obtained by rounding the fair odds up to the nearest tote price, e.g. fair odds of 5-2 become 3-1, 8-5 fair odds become 9-5 or 2-1, etc.

In the second race at Delta Downs today, Wild Mallory was a “B” win bet at fair odds of 5-2. Hence, my money was still in my pocket when she straggled home a well-beaten third at odds of 1-2.

Try something similar yourself and see if it helps your betting bottom line. I have a feeling it will.