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How to understand probability | What is implied probability in odds

Implied probability oddsThe further you delve into the principles of sports betting, the likelier it is you'll bump into the terms implied probability, odds probability and odds percentage. Intimidating as they might appear, these terms are probably the most important when it comes to finding valued odds and a key aspect into figuring how to earn long term profits. What they practically describe, are the confirmation chances of each outcome according to the bookie. Before you start puzzling yourself with head-scratching percentages and calculations, perhaps its best we take everything from the start.

What is implied probability?

Let's say you're rolling a dice. Do you know what chances each number has to appear? Of course you do, as all that's required is to divide 100% by each possible outcome, in this case being six. This means that each die roll has a 100% ÷ 6 = 16.66% implied probability of appearing. Fairly easy right?

The same applies to football betting. Each match has three possible results (home win, draw, away win) with each one having 33.33% probability. In Asian Handicaps or over/under bets, the probability rises to 50% as there are only two possible outcomes.

Of course this percentage should be taken with a pinch of salt. Contrary to math probabilities you must have noticed that betting sites rarely offer identical odds, as there are many factors in play behind each match's result. To put it plainly, sports results are not as math-tied as the roll of a dice or the spin of a roulette ball, where the implied probability is always fixed. Every football odds set comes with its own implied probability that is carefully calculated from the bookie's odds compilers and influenced from the money staked on each outcome.

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How are sports betting odds calculated?

Before we go into further detail on what odds compilers actually do, we should understand how betting odds work. Let's take it from the top. Odds are nothing more than a different way of portraying the winning/confirming chance of each outcome. For the sake of the argument, let's say that Bayern Munich are playing at home against Real Madrid for the Champions League Semi Final. The fairest possible odds set might appear like 1 (2.00) X (4.00) 2 (4.00). Now the calculation is somewhat different from our dice example, but also fairly easy. You just have to think one step ahead.

Divide each odd into 100% to find its implied probability

This means that the implied probability of Bayern winning stands at 50% (100% ÷ 2.00 = 50%), with the Draw and a Real Madrid win having 25% probability each. Remember how we mentioned the "fairest possible odds set" right above? This is because there's no way you'll find such odds, unless your wagering on a betting exchange. A typical odds set would look like 1 (1.90) X (3.60) 2 (3.80). If you wondering why the odds have been so shortened, then you are completely forgetting about the bookie's commission.

This commission is basically the house's edge, the money a bookie takes for setting up the platform where you and other punters can place your bets. More on that on our bookmaker vig article. Now let's get back to the odds compilers, the people behind the numbers, so to speak. They are responsible for analyzing all the data surrounding a match and translating them into odds. From absent players and new signings, to team form and previous meetings. Practically every stat you can think of, plays a part in setting the odds. You can think of odds compilers as really acute predictors who have their hands untied from the information a bookie's collective stats offer.

How come some bookies offer higher odds?

odds implied probability odds volatitlityThis is an observation you can't miss when comparing odds between two or possibly more operators. It all comes down to the vig, with longer odds having lower commission levels and vice versa. In order to better understand this, let's analyze a complete set of football odds.

Let's say we found 1 (1.90) - X (3.60) - 2 (3.80) we mentioned above on Beteast. The first thing you should do, is calculate the implied probability of the odds.

100% ÷ 1.90 = 52.63% | 100% ÷ 3.60 = 27.77% | 100% ÷ 3.80 = 26.31%

The next thing is to sum them up. This gives us a total of 106.71%, marking a commission of 6.71%.

Now let's say Bet365 has the following odds: 1 (1.95) - X (3.75) - 2 (3.80). Once again we make our calculation.

100% ÷ 1.95 = 51.28% | 100% ÷ 3.75 = 26.66% | 100% ÷ 3.80 = 26.31%

A sum of Bet365 odds probability offers 104.25% for a 4.25% commission. This is significantly lower compared to Beteast, meaning that even if we didn't have access to the odds to begin with, the vig alone would mark a clear path into picking Bet365.

How to convert moneyline to probability

There's no difference in converting moneyline odds from 3-way football odds, as all you have to do is once again divide 100% from each outcome's price. To better visualize this, let's say the Houston Rockets are hosting the Golden State Warriors. The home win odds stand at 1.90, while the visitors are priced at 1.80. This means that a Rockets' win has a 52.63% implied probability with the Warriors having 55.55%. The 8.18% commission might seem high, however, it's the added drawback of betting on 2-way markets.

Is implied probability the same as odds volatility?

These two terms should not be confused as they bear no resemblance whatsoever. Implied probability is the basis for creating an odds set or calculating the chances of a possible outcome. Odds volatility, on the other hand, represents how susceptible a specific set of odds is to price changes. Odds with high volatility will become shorter or longer with relative ease if they are suddenly backed by large stakes. Volatility is mainly found in exchange markets from betting exchanges like Betfair to Forex, stock exchanges and spread betting. The only way you can take advantage of volatile odds is by predicting odds movements in low staked markets in order to place sure bets or cash out your profits.

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