What are they keys to making a winning Bet Labs system?

Jason Awad
Jason Awad
  • Updated

Bet Labs, part of the SI UNLIMITED package, can be an invaluable tool in creating historically profitable betting systems. With dozens of filters to choose from and thousands of games included in our database, there is no shortage of information. Here are a few things to keep in mind when creating profitable systems of your own.

1. Sample Size

When dealing with statistics and betting trends, it is essential that your betting system has a significant sample size which accurately represents the data as choosing a sample size that is too small may not give an accurate representation. Large sample sizes allow you to more accurately observe advantages that you may hold over the sportsbooks.

2. Consistent Year to Year Results

With Bet Labs, users are able to easily create winning betting systems with significant returns i.e. a large number of units won and a high return on investment. However, some systems will have one or two highly profitable seasons which frequently occurred many years prior. When we see this type of downwards regression, it is typically an indication that bookmakers have adjusted their lines to account for this previously held advantage. That means the edge sports bettors used to hold no longer exists.

Instead of looking for an inconsistent system with one or two huge seasons, you would prefer to find a system with consistent year-to-year gains. 

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These systems will have graphs that steadily rise year after year, going from the bottom left to the top right. Inconsistent systems, which may still be profitable, are more unpredictable and have graphs that look more like an EKG.

3. Don’t Custom Fit Your Data

Frequently, we come across betting systems in which a customer has custom-fitted their data to produce a betting system with a high number of units won. Oftentimes, users will create systems that focus on very specific data points that have been profitable as opposed to looking at a full range.

For example, knowing that teams receiving less than 30% of public bets is valuable information, however, if you only examined the specific data points (i.e. 17%) with the highest units won, you could create a system with a greater ROI but you wouldn’t have learned anything particularly valuable – especially considering that the public betting percentage could move a single point after placing your bet, thus falling out of your system.

These type of systems are generally poor indicators of future success and perform much worse than their previous records indicate after they are created. 

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