Shading Sports Betting Lines

How to Bet On Sports > Shading Sports Betting Lines

Economists often study supply and demand, or analyze other themes, related to global economies and financial markets. In this article, Sports Insights’ economists will take a break from studying interest rates and global currencies to take a micro look at shading sports betting lines. What is going on inside the sports betting world? How do sportsbooks maximize their profit margin? What does this mean to other sports marketplace participants such as sports bettors?

The goal of this article is to study the market structure of the sports marketplace and determine if we can match theoretical ideas with real world results. The information on this site is for entertainment and educational purposes only. Use of this information in violation of any federal, state, or local laws is prohibited.

Sportsbook Profit Margins: Simple Centered Example

For the purpose of this article, we will use the standard –110 line for vigorish and other computations. You must lay $110 to win $100. If you win the bet, you receive $210 (your original $110 plus the $100 winnings). If you lose the bet, you lose $110.

The sportsbook, in this example, would receive $10, or 4.5%, of the combined $220 betting action. A bettor would need to win 52-53% of their bets to break even. This study used both moneylines and spreads, and a wide range of examples, to verify results and computations.

In our simple “centered” example, the moneylines and point spreads are centered exactly on the expected probabilities of the games’ outcomes. For example, a game priced at 180/-220 is centered at 200, so the favorite is expected to win two-thirds (66.7%) of the time. We studied the micro-structure of this simple sports marketplace, as well as other variations, to study how sportsbooks might behave.

In this example, no matter what the public does does, the sportsbook will maintain a 4.5% profit margin. Individual games will lead to profits and losses for market participants (bettors, the betting public in general, and the sportsbooks), but the long-term will result in a 4.5% profit margin for the sportsbooks.

Sportsbook Margins: Shading Example

Now, what happens to these results if sportsbooks shade their lines to exploit human tendencies? A simple example that we’ve discussed in the past is the fact that most people like to bet on favorites and overs. Sportsbooks pad their pockets by shading the lines to overprice favorites and overs, on average.

There have been several articles and sources that suggest that this shading takes place. Levitt’s academic article states that sportsbooks could potentially improve their profit margins 20-30% by shading their lines. Here, we study the market structure of the sports betting world and see if this makes sense. Instead of centering the line (or probability) of a game, what if sportsbooks shaded their lines to make certain teams more expensive?

First, we studied a sportsbook’s profit margin if they shaded their lines so that the probability distribution was shifted 1%. In our example above, the game priced at 180/-220 is centered at 200, so that the favorite might be expected to win two-thirds (66.7%) of the time. Since the sportsbooks know that most people will want to bet on the favorite, they might shift the probability distribution, or pricing, of the event so that this favorite might win only 65.7% of the time.

We computed a sportsbook’s expected profit margin based on results over a wide range of events (small favorites, heavy favorites, etc.). Note that the percentage of public money (on the overpriced side) impacts results and expected profit margin. For the purposes of the table below, we assume that each bet is the same size.

Table 1: Sportsbook Profit Margins

A Function of Probability Distribution “Shading” and Public Money

Public % on Overpriced Side Profit Margin (Prob Dist Shaded 1%) Profit Margin (Prob Dist Shaded 2%) Profit Margin (Prob Dist Shaded 3%)
100% 6.3% 8.2% 10.2%
80% 5.6% 6.7% 8.0%
60% 4.9% 5.3% 5.7%
50% 4.5% 4.5% 4.5%
40% 4.2% 3.8% 3.4%
20% 3.5% 2.3% 1.2%
0% 2.8% 0.9% -1.1%

Conclusions: What does this mean?

Based on the results in Table 1, we see that there is, indeed, a strong incentive for sportsbooks to shade their lines, on average. Below are some notes and conclusions:

If sportsbooks shade their probability distributions just 2-3%, their expected profit margins do, in fact, increase 20-30% (from 4.5% to 5.3%-5.7%, at the Public 60% level). Profit margins are even higher at higher Public % and higher shading levels.

If sportsbooks shade their lines 3% or more, they are starting to leave money on the table for sports investors with good information. Note the highlighted –1.1% at the bottom-right of Table 1.

With many sports bettors paying reduced vig (or shopping around for softer lines), sportsbook profit margins are being pressured all the time. Lower margins give sportsbooks even more incentive to shade their lines and improve their profits.

These results agree with our (and most people’s) philosophy that it pays to be a contrarian investor and Bet Against the Public.

Based on Sports Insights’ results (that have been profitable over the years, across various major sports), it seems like sportsbooks could be shading their probability distributions as much as 3-4%.

We believe that serious sports investors can earn a profit in the sports marketplace. In this article, we used some theoretical tools to analyze the real-world sports betting world. We showed how and why sportsbooks might price sporting events the way they do.

These are just some of the reasons why Sports Insights’ tools and statistics are effective and can help you succeed in sports investing. Note, however, that the sportsbooks have a nice cushion (the vig) to work with so it takes a lot of hard work.


We do not guarantee that the trends and biases we’ve found will continue to exist. It is impossible to predict the future. Any serious academic research in the field of “market efficiencies” recognizes that inefficiencies may disappear or fade over time. Once inefficiencies are discovered, it is only a matter of time before the market corrects itself. We do not guarantee our data is error-free. However, we’ve tried our best to make sure every score and percentage is correct.