Baseball is a game of figures. America's pastime is enshrined in numbers, records and statistics. In the current era, there are thirty teams and 2,430 contests scheduled during the regular season. With this massive sample size of games, baseball presents more opportunities for the gambler than any other major sport. But to fully exploit these opportunities, one needs to have a proper understanding of the relationship between money lines (the odds format for baseball) and winning percentages implied for every money line price point (e.g. -110, +110, -120, +120, etc.).
This concept might best be understood by sharing an email one of our handicapping associates recently received. It was a long time friend of his and it came on opening day of the MLB Season. To put this email in its proper context, let us quickly set the stage. Toronto kicked off the season hosting Detroit. The Blue Jays opening day starter was Roy Halladay, considered by most baseball “experts”as one of the best handful of pitchers in the Major Leagues. The Tigers countered with Jason Johnson, who subsequently had led Baltimore (his previous team) to a 2-12 lifetime record vs. the Jays behind a towering 6.92 career ERA in those fourteen respective starts. By all accounts, this looked to be a helpless cause for Detroit. After all, the toothless Tigers lost more games than any other team last season. On paper, the chances of Detroit winning seemed less likely than Jessica Simpson becoming a Rhodes Scholar. Oddsmakers priced the Toronto at -250, meaning you had to lay a whopping $250 on the Blue Jays in order to win $100. If Toronto lost, you would be out $250. Now back to the friend's email.
"Can I ask why you are not betting on the Blue Jays? The Tigers'bats are as thin as your hair and the Halladay vs. Johnson match up is an utter mismatch. The Blue Jays are brimming with confidence right now and this is a big first game. Seems totally illogical to miss out on this gimme'bet."
Final Score: Detroit 7 Toronto 0
Our anonymous friend, like so many before him, thought there is no way a stud like Halladay will ever lose to a team like the paper Tigers. Well, as you can see, this couldn't be further from the truth as Detroit not only won, but won handily. In fact, there were a number of other large favorites who crashed and burned in just the first few days of the regular season. Mike Mussina twice (-250, -210), Barry Zito (-240), Randy Johnson twice (-220, -190), Matt Morris (-220), Roy Oswalt (-200), Andy Pettitte (-190), Miguel Batista twice (-190, -195) and Pedro Martinez (-180) all failed to grab the cash as heavy chalk in the opening days of the season.
In hopes that you can avoid making the same mistake as our Harvard-bound friend, let us quickly illustrate the relationship between a particular price point (e.g. -250) and the winning percentage needed to show a long term profit at that price point. This concept sounds like a mouthful, but it is actually a fairly easy one to understand. We will look to explain this concept in full by using the example of a large favorite. But this model really applies regardless of price. And once you fully understand it, you should use it to gauge each of your baseball wagers no matter what the price. The first question we ask ourselves before releasing any pick is whether or not it looks like a long term winning proposition at the posted price.
As far as the example above goes, the Blue Jays at -250 would have to win this particular match up 72% of the time over the long term in order to be profitable. This percentage is derived from the following equation:
$100W –$250L = 0, where W=Blue Jays long term winning percentage in this match up, and L=Blue Jays long term losing percentage in this match up. $100 represents what the amount you will win if the Blue Jays win; while -$250 represents the amount you will lose if the Blue Jays lose (both numbers assume you are a $100 player). Assume the Blue Jays win this match up 72% of the time over the long term. This would imply that the Blue Jays lose 28% of the time (1-.72) or if you prefer the Tigers win 28% of the time over the long term. When W=72% and L=28%, the above equation equals zero (it's slightly off due to rounding errors).
To recap, Toronto must win this match up at least 72% over the long term or else you are going to lose money. This is a formidable challenge for the Blue Jays. And one crucial point here is that when you risk 2.5 times your money (i.e. -250); you are really risking it on the team and not the pitcher. Halladay can throw a gem and still lose a 1-0 game, as is so often the case. To put it another way, the Blue Jays would have to win 117 times over a 162-game season in order to win at a 72% clip. Even if the Blue Jays had 5 Halladay clones in their starting rotation, it is highly unlikely they could win at this rate. There are simply too many “other”factors that Halladay (or his hypothetical clones) cannot control (hitting, defense, umpiring, etc.).
Of course, our staff member did not suggest to his anonymous Harvard-bound friend to bet on Detroit either. Here in the office, we felt like everyone else about the game. The clawless Tigers did not stand a snowballs chance in hell of winning. That said; the risk-reward ratio (the price) did not seem to justify a wager on the Blue Birds.
On the other side of this equation, Detroit sat at +220 (depending on the sportsbook). This simply means for every $100 wagered, you receive $220 in net return if the Tigers won. Again, there is long term winning percentage implied at this price point. As we noted above, the Tigers would “only”have to win at a 32% clip to be profitable over the long haul. Imagine for a moment that Detroit won this match up 29%-31% of the time over the long term. This would fall below the 32% break even threshold. But it also implies that Toronto won this match up between 69%-71% of the time. Notice that this also falls below the 72% break even threshold for the Blue Jays. In such an instance, the player would be wise to lay off because it would be impossible for him or her to win money on either side over the long term! By the way, there is a “can't win range”for the player at most every price point (including your standard -110 wagers).
Handicapping is really just a process of comparing posted odds set by linesmakers to the “true odds”of that particular team winning. By “posted odds,”we mean the odds that the linesmakers are implicitly assigning to a particular team given the particular price. In our above example, the posted odds for Toronto winning at -250 are 72%. The posted odds for Detroit winning at +220 are 32%. “True odds”on the other hand, are the actual odds of a particular team winning. Handicapping is really an exercise in identifying situations in which the true odds are greater or less than the posted odds. This concept applies across all sports for any given line. Of course, this is far easier said than done because while we can always calculate the posted odds for a given line, it is impossible to say with 100% accuracy what the true odds actually are. Trying to find a variance between posted odds and true odds with enough regularity to earn a profit over the long term is the very definition of handicapping.
Calculating posted odds is easy. We have shown you how to do this above with Toronto and Detroit. Here are a few more money lines and their implied posted odds:
Money Line Implied Posted Odds -110 - 52.38% -150 - 60.00% -200 - 66.67% +110 - 47.62% +150 - 40.00% +200 - 33.33%
For each price point in the left hand column there is a corresponding implied posted odds percentage. This is simply what percentage a team would need to win at for it to be profitable over the long term. If the Yankees are -150 over the Red Sox, New York would need to win better than 60% of the time to turn a profit. Notice that the posted odds increase as the price of the favorite increases (i.e. from -110 to -200). Notice too that the posted odds decrease as the size of the underdog increases (i.e. from +110 to +200). In other words, you must win a larger percentage of games as the money line price rises and a lower percentage of games as the money line price decreases. This is why playing underdogs in baseball is so appealing! And notice that even with a small underdog like +110, you can win actually win less than 50% of your wagers and still come out ahead! And finally, we should point out that the implied posted odds for -110 (52.38%) and +110 (47.62%) add up to 100%. This is also the case for the pairs -150 (60%) and +150 (40%); as well as -200 (66.67%) and +200 (33.33%).
The key question to ask each time a money line wager is placed on Team X at Money Line Y is: Are the true odds for Team X winning (based on your handicapping) greater than the posted odds at Money Line Y. If the Cubs for example are priced at -150, simply ask yourself: “Will Chicago win this game more than 60% of the time over the long term”? If the answer is “yes”then it makes sense to bet on Chicago. Conversely, if the answer is “no”then you should lay off or consider the Cubs opponents in this game as an option. The key phrase here is “long term.”Anything can and will happen over the short term. But if the Cubs really are better than their opponent 60% of the time in this particular match up, then over the long term you can make money by wagering on them. Again, this concept applies for any team at any given price across all sports. Using basic math, you can quickly calculate the implied posted odds for any money line price point. Understanding and utilizing this concept should take you one giant step closer to a profitable baseball season.
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