How to De-Vig Odds: Find the No-Vig Fair Odds Behind a Line

Posted odds are not fair odds. Every sportsbook bakes a margin — the vig, the juice — into its prices, which is exactly why the two sides of a market add up to more than 100%. Learning how to de-vig odds means learning to strip that margin back out, so a line finally tells you the true probability underneath it.

The vig, and why odds don’t add up to 100%

Convert any two-way moneyline to implied probabilities and add the sides together. On a truly fair market they’d sum to exactly — 100%. They never do. A normal two-way line lands somewhere near to . That excess is the overround, and it’s the book’s cut: the vig.

This is why beating the closing number matters more than winning any single bet. To find real value you first have to remove the vig and recover the no-vig fair odds the line is hiding.

Step 1: convert the odds to implied probability

American odds map straight to a probability. A favorite priced at −152 implies . An underdog at +138 implies . The general rule:

Add the two sides and you get the overround — the number you have to remove:

Step 2: remove the vig to get no-vig fair odds

The simplest method — proportional (or multiplicative) de-vigging — just rescales both sides so they sum to 100%: divide each implied probability by the overround. Fast, transparent, and the right first tool.

But proportional makes a quiet assumption: that the margin is spread evenly across both sides. Books don’t work that way. They shade favorites and longshots differently — the favorite-longshot bias — and two sharper methods correct for it. The power method raises probabilities to a fitted exponent; Shin’s method treats part of the margin as insider money. On lopsided lines they can move the no-vig fair odds by a full point or more.

Which de-vig method should you use?

For a quick read on a roughly even market, proportional is fine. For heavy favorites, long underdogs, or any time you’re comparing a soft book against a sharp one to hunt for value, reach for the power or Shin method — the bias correction is exactly where the edge hides. The calculator below runs all three side by side so you can see how much the method choice actually moves the answer.

The de-vig, on one page

The same three moves, written out: turn each price into the probability it implies, add them to expose the fee, then rescale so the pair sums back to 100%. The power method removes more of the margin from the longshot, matching the favorite–longshot bias.

Advanced: the power and Shin methods

Proportional de-vigging pads both sides by the same factor, spreading the margin in proportion to each side’s size. Real prices don’t behave that way. Books shade longshots harder than favorites, so more of the overround hides in the underdog’s price than in the favorite’s. The power and Shin methods each remove the vig unevenly, and each has a precise rule for how.

The power method raises each implied probability to a single exponent , then solves for the one that makes the two sides sum to exactly 1:

Why does this shade longshots harder? Every implied probability sits below 1, so raising it to a power above 1 shrinks it — but it shrinks a small probability by a larger fraction of itself than a big one. The correction lands hardest exactly where the book’s shading lands hardest, which is why the power method is the right upgrade whenever a line is lopsided.

Shin’s method reaches a similar place from an actual model of why the vig exists. Suppose a fraction of the money the book faces comes from insiders who already know the result. The book pads its prices to protect itself, and the padding falls heaviest on longshots, where insider money hurts most. Solving that model gives a closed form for the fair probabilities:

Put side by side, the three methods disagree by a few tenths of a point on this mild favorite — and by more as lines get more lopsided. That gap is not noise: which method you choose is an input to every fair-probability calculation, so it should be a visible one. The De-Vig calculator runs all three on the same prices so you can see the spread for yourself.

One posted price isn’t the last word, either. Pool the de-vigged numbers across books and you get a sturdier benchmark — the idea behind building a sharp-consensus fair line from many de-vigged prices at once.

Every formula here lives on the Formula Sheet for quick reference.