SportsInsights Article on NBA Research: Betting Against the Public, Dogs & Point Spreads
NBA Data from 2003-2008 (Past five seasons) – December 2008
Some of our Members asked us to revisit an NBA article we wrote several years ago for the NBA that focused on:
In particular, that article looked at home underdogs that the Public hated. In this update, we’ll look at these factors — as well as visiting underdogs. 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.
NBA Data
The research for this article is based on five seasons’ worth of NBA data that SportsInsights collected, starting with the 2003-2004 season:
Betting Against the Public
Recently, we updated our annual NBA “Betting Against the Public” article. We saw that “betting against the public” — especially around the 25% level — can give sports bettors a slight edge against the sportsbooks. What if we bet on home underdogs that get a certain number of points? What about visiting dogs? Let’s take a look.
Betting Against the Public — Home Underdogs
Now, what if we look at home underdogs? We used “betting percentages” and took any team that opened as a home underdog (home team getting points). “Betting against the Public” continues to show a profitable bias over the past five seasons as follows:
Table 1: NBA and Betting Against the Public (Home Team Opening as Underdog) (2003-2008, Five Seasons)
Betting % on Home Team | Opening Home Spread >= 0.1Win % (Units) |
35% | 49.2% (-39 units) |
30% | 49.9% (-17 units) |
25% | 49.7% (-12 units) |
20% | 52.6% (+6 units) |
We can see that using “betting percentages” gives us an edge — although at the 20% level, there aren’t many games generated. We’ll also take a look at home underdogs that are getting more points (3 or more points, 5 or more points, and 7 or more points).
Table 2: NBA and Betting Against the Public (Home Team Opening as Underdog) (2003-2008, Five Seasons)
Betting % on Home Team | Opening Home Spread >= 0.1Win % (Units) | Opening Home Spread >= 2.9Win % (Units) | Opening Home Spread >= 4.9Win % (Units) | Opening Home Spread >= 6.9Win % (Units) |
35% | 49.2% (-39 units) | 49.7% (-22 units) | 48.6% (-23 units) | 49.3% (-7 units) |
30% | 49.9% (-17 units) | 50.2% (-10 units) | 48.9% (-15 units) | 50.6% (-1 units) |
25% | 49.7% (-12 units) | 49.6% (-10 units) | 48.4% (-11 units) | 50.5% (-1 units) |
20% | 52.6% (+6 units) | 50.0% (-3 units) | 50.0% (-2 units) | 52.6% (+1 units) |
Again, we can see that “Betting against the Public” marginally improves results. Now, let’s take a look at visiting underdogs.
Betting Against the Public — Visiting Underdogs
The Table below shows the results for “Betting Against the Public” and selecting Visiting Dogs getting at least 1 point, 3 points, 5 points and 7 points.
Table 3: NBA and Betting Against the Public (Visiting Team Opening as Underdog) (2003-2008, Five Seasons)
Betting % on Visiting Team | Opening Visiting Spread >= 0.1Win % (Units) | Opening Visiting Spread >= 2.9Win % (Units) | Opening Visiting Spread >= 4.9Win % (Units) | Opening Visiting Spread >= 6.9Win % (Units) |
35% | 52.7% (+29 units) | 52.4% (+23 units) | 51.3% (+4 units) | 49.9% (-11 units) |
30% | 55.4% (+32 units) | 54.5% (+25 units) | 53.2% (+14 units) | 53.3% (+11 units) |
25% | 53.1% (+6 units) | 52.3% (+4 units) | 51.8% (+2 units) | 52.2% (+2 units) |
20% | 54.5% (+2 units) | 54.5% (+2 units) | 56.7% (+3 units) | 55.6% (+3 units) |
Interestingly, the results for Visiting Underdogs are better than the results for Home dogs. In Table 3, we highlighted the 30% level for taking visiting dogs. Taking any visiting dog that has less than 30% of the bets would have resulted in a 55.4% winning percentage over the past five seasons. What other conclusions can we make?
Conclusions
Disclaimer
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 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.