How the De-Vig Calculator Works
Every sportsbook builds a margin — called the vig, juice, or overround — into their odds. A standard -110/-110 NFL spread line implies a combined probability of 104.76%, not 100%. That extra 4.76% is the book's cut.
De-vigging removes that margin to find the fair odds: what the line would be in a perfectly competitive, zero-margin market. These fair probabilities are the foundation of serious betting models — they tell you how the sharpest money is actually pricing each outcome.
Step 1: Convert odds to implied probability
# American odds → implied probability negative odds (-110): 110 / (110 + 100) = 52.38% positive odds (+150): 100 / (150 + 100) = 40.00% # Two-side spread at -110 / -110 total implied: 52.38% + 52.38% = 104.76% ← vig is 4.76%
Step 2: Remove the margin (three methods)
Multiplicative: Divide each implied probability by the total. For the -110/-110 example: 52.38% ÷ 104.76% = 50.0%. Both sides become a coin flip, as you'd expect from a balanced market. This is the most common method and works well when the book applies margin proportionally.
Additive: Subtract an equal share of the margin from each side. On a 4.76% hold with two sides: subtract 2.38% from each. Produces the same result on balanced lines but diverges on lopsided markets — it tends to overestimate the underdog's true probability.
Shin: The Shin (1993) model treats the margin as the book's protection against a fraction of informed bettors in the market. It solves numerically for the "insider trading fraction" parameter z, then adjusts each probability accordingly. Most researchers consider Shin the most accurate method for sharp market data.
Why this matters for betting models
Fair implied probabilities are the input to Closing Line Value (CLV) analysis — the practice of comparing the odds you bet at to the no-vig closing line. If your models consistently beat the closing fair price, that's strong evidence of a real edge.
De-vigged odds are also used to calibrate model output. If your model assigns 55% probability to a team covering, but the de-vigged market says 50%, you have a potential value bet. If the market says 57%, you should pass — the sharp money sees something your model doesn't.
Frequently Asked Questions
What's the difference between the three de-vig methods?
Multiplicative scales all implied probabilities proportionally — it's the industry default and works well for most markets. Additive removes a flat amount from each side; it underestimates underdog edges on lopsided lines. Shin is the most mathematically rigorous: it models the vig as the book's protection against informed bettors, giving the best estimate of true probabilities on sharp markets.
Why do sportsbooks charge vig?
Vig (vigorish, or 'juice') is the commission a sportsbook charges to guarantee a profit regardless of outcome. By pricing -110 on both sides of a spread instead of even money (+100), the book collects ~4.76% on every dollar wagered. Sharp bettors try to find markets where the fair price is better than the vig-adjusted line — that's positive expected value.
What is a 'no-vig' line used for?
No-vig lines represent what the odds would be in a zero-margin market. They're used as a benchmark: if you can bet a market at better than the no-vig price (e.g. at closing line), you have positive closing line value (CLV). Over large samples, positive CLV strongly correlates with long-term profitability.
How do I use this for arbitrage detection?
Paste the best available odds from two different books for the same market. If the fair probabilities from de-vig add up to less than 100%, and you can bet both sides at those prices simultaneously, you've found an arbitrage opportunity. In practice, books limit arb bettors quickly, so this tool is more useful for finding soft lines than pure arb.